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Medicare Program; Inpatient Rehabilitation Facility Prospective Payment System for FY 2006

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Start Preamble Start Printed Page 47880

AGENCY:

Centers for Medicare & Medicaid Services (CMS), HHS.

ACTION:

Final rule.

SUMMARY:

This final rule will update the prospective payment rates for inpatient rehabilitation facilities for Federal fiscal year 2006 as required under section 1886(j)(3)(C) of the Social Security Act (the Act). Section 1886(j)(5) of the Act requires the Secretary to publish the classification and weighting factors for the inpatient rehabilitation facilities case-mix groups and a description of the methodology and data used in computing the prospective payment rates for that fiscal year.

In addition, we are implementing new policies and are changing existing policies regarding the prospective payment system within the authority granted under section 1886(j) of the Act.

DATES:

These regulations are effective October 1, 2005. The updated IRF prospective payment rates are applicable for discharges on or after October 1, 2005 and on or before September 30, 2006 (FY 2006).

Start Further Info

FOR FURTHER INFORMATION CONTACT:

Pete Diaz, (410) 786-1235. Susanne Seagrave, (410) 786-0044. Mollie Knight, (410) 786-7948 for information regarding the market basket and labor-related share. August Nemec, (410) 786-0612 for information regarding the tier comorbidities. Zinnia Ng, (410) 786-4587 for information regarding the wage index and Core-Based Statistical Areas (CBSAs).

End Further Info End Preamble Start Supplemental Information

SUPPLEMENTARY INFORMATION:

Table of Contents

I. Background

A. General Overview of the Current Inpatient Rehabilitation Facility Prospective Payment System (IRF PPS)

B. Requirements for Updating the Prospective Payment Rates for IRFs

C. Operational Overview of the Current IRF PPS

D. Summary of the FY 2006 Proposed Update to the IRF PPS

II. Provisions of the Proposed Regulations

III. Analysis of and Responses to Public Comments

IV. Research to Support Refinements of the Current IRF PPS

V. Refinements to the Patient Classification System

A. Changes to the IRF Classification System

1. Development of the IRF Classification System

2. Description and Methodology Used To Develop the IRF Classification System in the August 7, 2001 Final Rule

a. Rehabilitation Impairment Categories

b. Functional Status Measures and Age

c. Comorbidities

d. Development of CMG Relative Weights

e. Overview of Development of the CMG Relative Weights

B. Changes to the Existing List of Tier Comorbidities

1. Changes to Remove Codes That Are Not Positively Related to Treatment Costs

2. Changes to Move Dialysis to Tier One

3. Changes to Move Comorbidity Codes Based on Their Marginal Cost

C. Changes to the CMGs

1. Changes for Updating the CMGs

2. Use of a Weighted Motor Score Index and Correction to the Treatment of Unobserved Transfer to Toilet Values

3. Changes for Updating the Relative Weights

VI. FY 2006 Federal Prospective Payment Rates

A. Reduction of the Standard Payment Amount to Account for Coding Changes

B. Adjustments to Determine the FY 2006 Standard Payment Conversion Factor

1. Market Basket Used for IRF Market Basket Index

a. Overview of the RPL Market Basket

b. Methodology for Operating Portion of the RPL Market Basket

c. Methodology for Capital Proportion of the RPL Market Basket

d. Labor-Related Share

2. Area Wage Adjustment

a. Revisions of the IRF PPS Geographic Classification

b. Current IRF PPS Labor Market Areas Based on MSAs

c. Core-Based Statistical Areas (CBSAs)

d. Revisions of the IRF PPS Labor Market Areas

i. New England MSAs

ii. Metropolitan Divisions

iii. Micropolitan Areas

e. Implementation of the CBSA-Based Labor Market Areas

f. Wage Index Data

3. Teaching Status Adjustment

4. Adjustment for Rural Location

5. Adjustment for Disproportionate Share of Low-Income Patients

6. Update to the Outlier Threshold Amount

7. Budget Neutrality Factor Methodology for Fiscal Year 2006

8. Description of the Methodology Used to Implement the Changes in a Budget Neutral Manner

9. Description of the IRF Standard Payment Conversion Factor for Fiscal Year 2006

10. Example of the Methodology for Adjusting the Federal Prospective Payment Rates

VII. Quality of Care in IRFs

VIII. Miscellaneous Comments Within the Scope of the Proposed Rule

IX. Miscellaneous Comments Outside the Scope of the Proposed Rule

X. Provisions of the Final Regulations

XI. Collection of Information Requirements

XII. Regulatory Impact Analysis

Acronyms

Because of the many terms to which we refer by acronym in this final rule, we are listing the acronyms used and their corresponding terms in alphabetical order below.

ADC Average Daily Census

AHA American Hospital Association

AMI Acute Myocardial Infarction

BBA Balanced Budget Act of 1997 (BBA), Pub. L. 105-33

BBRA Medicare, Medicaid, and SCHIP [State Children's Health Insurance Program] Balanced Budget Refinement Act of 1999, Pub. L. 106-113

BIPA Medicare, Medicaid, and SCHIP [State Children's Health Insurance Program] Benefits Improvement and Protection Act of 2000, Pub. L. 106-554

BLS Bureau of Labor Statistics

CART Classification and Regression Trees

CBSA Core-Based Statistical Areas

CCR Cost-to-charge ratio

CMGs Case-Mix Groups

CMI Case Mix Index

CMSA Consolidated Metropolitan Statistical Area

CPI Consumer Price Index

DSH Disproportionate Share Hospital

ECI Employment Cost Index

FI Fiscal Intermediary

FIM Functional Independence Measure (FIMTM is a registered trademark of UDSMR)

FIM-FRGs Functional Independence Measures-Function Related Groups

FRG Function Related Group

FTE Full-time equivalent

FY Federal Fiscal Year

GME Graduate Medical Education

HCRIS Healthcare Cost Report Information System

HIPAA Health Insurance Portability and Accountability Act

HHA Home Health Agency

IME Indirect Medical Education

IFMC Iowa Foundation for Medical Care

IPF Inpatient Psychiatric Facility

IPPS Inpatient Prospective Payment System

IRF Inpatient Rehabilitation Facility

IRF-PAI Inpatient Rehabilitation Facility-Patient Assessment Instrument

IRF-PPS Inpatient Rehabilitation Facility-Prospective Payment System

IRVEN Inpatient Rehabilitation Validation and Entry

LIP Low-income percentage

MEDPAR Medicare Provider Analysis and Review

MSA Metropolitan Statistical Area

NECMA New England County Metropolitan Area

NOS Not Otherwise Specified

NTIS National Technical Information Service

OMB Office of Management and Budget

OSCAR Online Survey, Certification, and Reporting

PAI Patient Assessment Instrument

PLI Professional Liability Insurance Start Printed Page 47881

PMSA Primary Metropolitan Statistical Area

PPI Producer Price Index

PPS Prospective Payment System

RIC Rehabilitation Impairment Category

RPL Rehabilitation Hospital, Psychiatric Hospital, and Long-Term Care Hospital Market Basket

TEFRA Tax Equity and Fiscal Responsibility Act

TEP Technical Expert Panel

I. Background

We received approximately 55 timely items of correspondence on the Inpatient Rehabilitation Facility Prospective Payment System for FY 2006 proposed rule (70 FR 30188). Summaries of the public comments and our responses to those comments are set forth below under the appropriate section heading of this final rule.

A. General Overview of the Current Inpatient Rehabilitation Facility Prospective Payment System (IRF PPS)

Section 4421 of the Balanced Budget Act of 1997 (BBA) (Pub. L. 105-33), as amended by section 125 of the Medicare, Medicaid, and SCHIP [State Children's Health Insurance Program] Balanced Budget Refinement Act of 1999 (BBRA) (Pub. L. 106-113), and by section 305 of the Medicare, Medicaid, and SCHIP Benefits Improvement and Protection Act of 2000 (BIPA) (Pub. L. 106-554), provides for the implementation of a per discharge prospective payment system (PPS), through section 1886(j) of the Social Security Act (the Act), for inpatient rehabilitation hospitals and inpatient rehabilitation units of a hospital (hereinafter referred to as IRFs).

Payments under the IRF PPS encompass inpatient operating and capital costs of furnishing covered rehabilitation services (that is, routine, ancillary, and capital costs) but not costs of approved educational activities, bad debts, and other services or items outside the scope of the IRF PPS. Although a complete discussion of the IRF PPS provisions appears in the August 7, 2001 final rule, we are providing below a general description of the IRF PPS.

The IRF PPS, as described in the August 7, 2001 final rule, uses Federal prospective payment rates across 100 distinct case-mix groups (CMGs). Ninety-five CMGs were constructed using rehabilitation impairment categories, functional status (both motor and cognitive), and age (in some cases, cognitive status and age may not be a factor in defining a CMG). Five special CMGs were constructed to account for very short stays and for patients who expire in the IRF.

For each of the CMGs, we developed relative weighting factors to account for a patient's clinical characteristics and expected resource needs. Thus, the weighting factors account for the relative difference in resource use across all CMGs. Within each CMG, the weighting factors were “tiered” based on the estimated effects that certain comorbidities have on resource use.

The Federal PPS rates were established using a standardized payment amount (previously referred to as the budget-neutral conversion factor). The standardized payment amount was previously called the budget neutral conversion factor because it reflected a budget neutrality adjustment for FYs 2001 and 2002, as described in § 412.624(d)(2) of our regulations. However, the statute requires a budget neutrality adjustment only for FYs 2001 and 2002. Accordingly, for subsequent years we believe it is more consistent with the statute to refer to the standardized payment as the standardized payment conversion factor, rather than refer to it as a budget neutral conversion factor (see 68 FR 45674, 45684 and 45685). Therefore, we will refer to the standardized payment amount in this final rule as the standard payment conversion factor.

For each of the tiers within a CMG, the relative weighting factors were applied to the standard payment conversion factor to compute the unadjusted Federal prospective payment rates. Under the current system, adjustments that accounted for geographic variations in wages (wage index), the percentage of low-income patients, and location in a rural area were applied to the IRF's unadjusted Federal prospective payment rates. In addition, adjustments were made to account for the early transfer of a patient, interrupted stays, and high cost outliers.

Lastly, the IRF's final prospective payment amount was determined under the transition methodology prescribed in section 1886(j) of the Act. Specifically, for cost reporting periods that began on or after January 1, 2002 and before October 1, 2002, section 1886(j)(1) of the Act and as specified in § 412.626 provide that IRFs transitioning into the PPS would receive a “blended payment.” For cost reporting periods that began on or after January 1, 2002 and before October 1, 2002, these blended payments consisted of 662/3 percent of the Federal IRF PPS rate and 331/3 percent of the payment that the IRF would have been paid had the IRF PPS not been implemented. However, during the transition period, an IRF with a cost reporting period beginning on or after January 1, 2002 and before October 1, 2002 could have elected to bypass this blended payment and be paid 100 percent of the Federal IRF PPS rate. For cost reporting periods beginning on or after October 1, 2002 (FY 2003), the transition methodology expired, and payments for all IRFs consist of 100 percent of the Federal IRF PPS rate.

We established a CMS Web site that contains useful information regarding the IRF PPS. The Web site URL is http://www.cms.hhs.gov/​providers/​irfpps/​default.asp and may be accessed to download or view publications, software, and other information pertinent to the IRF PPS.

B. Requirements for Updating the Prospective Payment Rates for IRFs

On August 7, 2001, we published a final rule entitled “Medicare Program; Prospective Payment System for Inpatient Rehabilitation Facilities” in the Federal Register (66 FR at 41316), that established a PPS for IRFs as authorized under section 1886(j) of the Act and codified at subpart P of part 412 of the Medicare regulations. In the August 7, 2001 final rule, we set forth the per discharge Federal prospective payment rates for fiscal year (FY) 2002 that provided payment for inpatient operating and capital costs of furnishing covered rehabilitation services (that is, routine, ancillary, and capital costs) but not costs of approved educational activities, bad debts, and other services or items that are outside the scope of the IRF PPS. The provisions of the August 7, 2001 final rule were effective for cost reporting periods beginning on or after January 1, 2002. On July 1, 2002, we published a correcting amendment to the August 7, 2001 final rule in the Federal Register (67 FR at 44073). Any references to the August 7, 2001 final rule in this final rule include the provisions effective in the correcting amendment.

Section 1886(j)(5) of the Act and § 412.628 of the regulations require the Secretary to publish the classifications and weighting factors for the IRF CMGs and a description of the methodology and data used in computing the prospective payment rates for the upcoming FY. On August 1, 2002, we published a notice in the Federal Register (67 FR at 49928) to update the IRF Federal prospective payment rates from FY 2002 to FY 2003 using the methodology as described in § 412.624. As stated in the August 1, 2002 notice, we used the same classifications and weighting factors for the IRF CMGs that were set forth in the August 7, 2001 final rule to update the IRF Federal prospective payment rates from FY 2002 Start Printed Page 47882to FY 2003. We have continued to update the prospective payment rates each year in accordance with the methodology set forth in the August 7, 2001 final rule.

We published a proposed rule in the Federal Register (70 FR 30189) to update the IRF Federal prospective payment rates from FY 2005 to FY 2006, and we proposed revisions to the methodology described in § 412.624.

C. Operational Overview of the Current IRF PPS

As described in the August 7, 2001 final rule, upon the admission and discharge of a Medicare Part A fee-for-service patient, the IRF is required to complete the appropriate sections of a patient assessment instrument, the Inpatient Rehabilitation Facility-Patient Assessment Instrument (IRF-PAI). All required data must be electronically encoded into the IRF-PAI software product. Generally, the software product includes patient grouping programming called the GROUPER software. The GROUPER software uses specific Patient Assessment Instrument (PAI) data elements to classify (or group) the patient into a distinct CMG and account for the existence of any relevant comorbidities.

The GROUPER software produces a 5-digit CMG number. The first digit is an alpha-character that indicates the comorbidity tier. The last 4 digits represent the distinct CMG number. (Free downloads of the Inpatient Rehabilitation Validation and Entry (IRVEN) software product, including the GROUPER software, are available at the CMS Web site at http://www.cms.hhs.gov/​providers/​irfpps/​default.asp).

Once the patient is discharged, the IRF completes the Medicare claim (UB-92 or its equivalent) using an alphanumeric CMG code and sends it to the appropriate Medicare fiscal intermediary (FI). (Claims submitted to Medicare must comply with both the Administrative Simplification Compliance Act (ASCA), Pub. L. 107-105, and the Health Insurance Portability and Accountability Act of 1996 (HIPAA), Pub. L. 104-191. Section 3 of ASCA requires the Medicare Program, subject to subsection (H), to deny payment under Part A or Part B for any expenses for items or services “for which a claim is submitted other than in an electronic form specified by the Secretary.” Subsection (h) provides that the Secretary shall waive such denial in two types of cases and may also waive such denial “in such unusual cases as the Secretary finds appropriate.” See also, 68 FR 48805 (August 15, 2003). Section 3 of ASCA operates in the context of the Administrative Simplification provisions of HIPAA, which include, among others, the transactions and code sets standards requirements codified as 45 CFR part 160 and 162, subparts A and I through R (generally known as the Transactions Rule). The Transactions Rule requires covered entities, including covered providers, to conduct covered electronic transactions according to the applicable transaction standards. See the program claim memoranda issued and published by CMS at www.cms.hhs.gov/​providers/​edi/​default.asp (http://www.cms.hhs.gov/​provider/​edi/​default.asp) and listed in the addenda to the Medicare Intermediary Manual, Part 3, section 3600. Instructions for the limited number of claims submitted to Medicare on paper are located in section 3604 of Part 3 of the Medicare Intermediary Manual.

The Medicare Fiscal Intermediary (FI) processes the claim through its software system. This software system includes pricing programming called the PRICER software. The PRICER software uses the CMG code, along with other specific claim data elements and provider-specific data, to adjust the IRF's prospective payment for interrupted stays, transfers, short stays, and deaths and then applies the applicable adjustments to account for the IRF's wage index, percentage of low-income patients, rural location, and outlier payments.

D. Summary of the FY 2006 Proposed Update to the IRF PPS

In the FY 2006 proposed rule (70 FR 30188), we proposed a number of refinements to the IRF PPS case-mix classification system (the CMGs and the corresponding relative weights) and the case-level and facility-level adjustments. The refinements that we proposed were based on analyses by RAND using calendar year 2002 and FY 2003 data.

Several new developments warranted proposing these refinements, including—(1) The availability of more recent 2002 and 2003 data; (2) better coding of comorbidities and patient severity; (3) more complete data; (4) new data sources for imputing missing values; and (5) improved statistical approaches.

Our proposals included the following key changes:

The FY 2006 IRF PPS proposed rule (70 FR 30188, 30234 through 30241) included a proposal to adopt OMB's Core Based Statistical Area (CBSA) market area definitions in a budget neutral manner. This geographic adjustment is made using a 1-year lag of the pre-reclassification hospital wage index (FY 2001 hospital wage data).

The FY 2006 proposed rule (70 FR 30188, 30222) also included a proposal to implement a payment adjustment to account for changes in coding. We proposed to reduce the standard payment amount by 1.9 percent to account for changes in coding following implementation of the IRF PPS. The analysis conducted by CMS's contractor found that the real change in the case-mix was between negative 2.4 percent and positive 1.5 percent, with the rest of the change (between 1.9 percent and 5.8 percent) attributable to coding changes. CMS proposed to reduce the standard payment amount by the lowest of these estimates.

In addition, in the FY 2006 proposed rule (70 FR 30188), we proposed modifications to the case mix groups, tier comorbidities, and relative weights. The proposed rule included a number of adjustments to the IRF classification system that are designed to improve the system's ability to predict IRF costs. The new data indicate that moving or eliminating some comorbidity codes from the tiers, redefining the case mix groups, and other minor changes to the system could improve the ability of the classification system to ensure that Medicare payments to IRFs continue to be aligned with the costs of care.

In addition, the FY 2006 IRF PPS proposed rule (70 FR 30188, 30241) contained a proposal to implement a new teaching status adjustment for IRFs, similar to the one recently adopted for inpatient psychiatric facilities. We proposed to implement the teaching status adjustment in a budget neutral manner.

The FY 2006 IRF PPS proposed rule (70 FR 30188, 30222) also contained a proposal to revise the market basket. We proposed to use a new market basket reflecting the operating and capital cost structures for rehabilitation, psychiatric, and long term care hospitals to update IRF payment rates. The proposed new market basket excludes cancer hospitals and children's hospitals. For the FY 2006 proposed rule (70 FR 30188), we proposed a market basket increase for FY 2006 of 3.1 percent.

In the FY 2006 proposed rule (70 FR 30188, 30244 through 30246), we also proposed to update the rural adjustment (from 19.1 percent to 24.1 percent), the low-income patient adjustment (from an exponent of 0.484 to an exponent of 0.636), and the outlier threshold amount (from $11,211 to $4,911). We proposed to implement the changes to the rural and low-income percentage updates in a budget neutral manner. Start Printed Page 47883

Lastly, in the FY 2006 proposed rule (70 FR 30188), we estimated that the proposed changes would increase costs to the Medicare program for IRF services in FY 2006 by $180 million over FY 2005 levels. The estimated increased cost to the Medicare program was due to the estimated IRF market basket of 3.1 percent, the 1.9 percent reduction to the standard payment amount to account for changes in coding that affect total estimated aggregate payments, and the update to the outlier threshold amount. We proposed to make the changes to the IRF labor-related share and the wage indices, the case mix groups, tier comorbidities, and relative weights, the new IME adjustment, the updated rural adjustment, and the updated LIP adjustment in a budget neutral manner. Thus, these proposed changes would have no overall effect on estimated costs to the Medicare program.

II. Provisions of the Proposed Regulations

In the FY 2006 proposed update to the IRF PPS (70 FR 30188), hereinafter referred to as the FY 2006 proposed rule, we proposed to make revisions to the regulations to implement the proposed PPS for IRFs for FY 2006 and subsequent fiscal years. Specifically, we proposed to make conforming changes in 42 CFR part 412. These proposed revisions and others are discussed in detail below.

A. Section 412.602 Definitions

In § 412.602, we proposed to revise the definitions of “Rural area” and “Urban area” to read as follows:

Rural area means: For cost-reporting periods beginning on or after January 1, 2002, with respect to discharges occurring during the period covered by such cost reports but before October 1, 2005, an area as defined in § 412.62(f)(1)(iii). For discharges occurring on or after October 1, 2005, rural area means an area as defined in § 412.64(b)(1)(ii)(C).

Urban area means: For cost-reporting periods beginning on or after January 1, 2002, with respect to discharges occurring during the period covered by such cost reports but before October 1, 2005, an area as defined in § 412.62(f)(1)(ii). For discharges occurring on or after October 1, 2005, urban area means an area as defined in § 412.64(b)(1)(ii)(A) and § 412.64(b)(1)(ii)(B).

B. Section 412.622 Basis of Payment

In this section, we proposed to correct the cross references in paragraphs (b)(1) and (b)(2)(i). In paragraph (b)(1), we proposed to remove the cross references “§ 413.85 and § 413.86 of this chapter” and add in their place “§ 413.75 and § 413.85 of this chapter.” In paragraph (b)(2)(i), we proposed to remove the cross reference “§ 413.80 of this chapter” and add in its place “§ 413.89 of this chapter.”

C. Section 412.624 Methodology for Calculating the Federal Prospective Payment Rates

In this section, we proposed to make the following revisions:

  • In paragraph (d)(1), remove the cross reference to “paragraph (e)(4)” and add in its place “paragraph (e)(5).”
  • Add a new paragraph (d)(4).
  • Redesignate paragraphs (e)(4) and (e)(5) as paragraphs (e)(5) and (e)(6).
  • Add a new paragraph (e)(4).
  • Revise newly redesignated paragraph (e)(5).
  • Revise newly redesignated paragraph (e)(6).
  • Add a new paragraph (e)(7).
  • In paragraph (f)(2)(v), remove the cross references to “paragraphs (e)(1), (e)(2), and (e)(3) of this section” and add in their place “paragraphs (e)(2), (e)(3), (e)(4), and (e)(7) of this section.”

D. Additional Changes

We also proposed the following changes:

  • Reduce the standard payment amount by 1.9 percent to account for coding changes.
  • Revise the comorbidity tiers and CMGs.
  • Use a weighted motor score index in assigning patients to CMGs.
  • Update the relative weights.
  • Update payments for rehabilitation facilities using a market basket reflecting the operating and capital cost structures for the RPL market basket.
  • Provide the weights and proxies to use for the FY 2002-based RPL market basket.
  • Indicate the methodology for the capital portion of the RPL market basket.
  • Adopt the new geographic labor market area definitions as specified in § 412.64(b)(1)(ii)(A)-(C).
  • Use the New England MSAs as determined under the proposed new CBSA-based labor market area definitions.
  • Implement a budget neutral 3 year hold harmless policy for FY 2005 rural IRFs redesignated as urban in FY 2006.
  • Use FY 2001 acute care hospital wage data in computing the FY 2006 IRF PPS payment rates.
  • Implement a teaching status adjustment.
  • Update the formulas used to compute the rural and the LIP adjustments to IRF payments.
  • Update the outlier threshold amount to maintain total estimated outlier payments at 3 percent of total estimated payments.
  • Revise the methodology for computing the standard payment conversion factor (for FY 2006 only) to make the CMG and tier changes, the teaching status adjustment, and the updates to the rural and LIP adjustments in a budget neutral manner.

III. Analysis of and Responses to Public Comments

As stated above, we received approximately 55 timely items of correspondence containing multiple comments on the FY 2006 proposed rule (70 FR 30188) from providers, health industry organizations, the Medicare Payment Advisory Commission, and others. In general, commenters expressed some concerns about our proposals in light of other changes occurring in the IRF PPS at this time and suggested that we wait to implement the proposals until other recent IRF policy changes are fully implemented. However, many commenters supported the proposed changes to the facility-level adjustments. Summaries of the public comments received on the proposed provisions and our responses to those comments are provided in the appropriate sections of the preamble of this final rule.

IV. Research To Support Refinements of the Current IRF PPS

As described in the August 7, 2001 final rule, we contracted with the RAND Corporation to analyze IRF data to support our efforts in developing the CMG patient classification system and the IRF PPS. Since then, we have continued our contract with RAND to support us in developing potential refinements to the classification system and the PPS. RAND has also developed a system to monitor the effects of the IRF PPS on patients' access to IRF care and other post-acute care services.

1. History of RAND's Research on the IRF PPS

In 1995, RAND began extensive research, sponsored by us, on the development of a per-discharge based PPS using a patient classification system known as Functional Independence Measures—Function Related Groups (FIM-FRGs) for IRFs. The results of RAND's earliest research, using 1994 data, were released in September 1997 and are contained in two reports available through the National Technical Information Service (NTIS). The reports are: Classification System Start Printed Page 47884for Inpatient Rehabilitation Patients—A Review and Proposed Revisions to the Function Independence Measure—Function Related Groups, NTIS order number PB98-105992INZ, and Prospective Payment System for Inpatient Rehabilitation, NTIS order number PB98-106024INZ.

In July 1999, we contracted with RAND to update its earlier research. The update included an analysis of Functional Independence Measure (FIM) data, the Function Related Groups (FRGs), and the model rehabilitation PPS using 1996 and 1997 data. The purpose of updating the earlier research was to develop the underlying data necessary to support the Medicare IRF PPS based on CMGs for the November 3, 2000 proposed rule (65 FR at 66313). RAND expanded the scope of its earlier research to include the examination of several payment elements, such as comorbidities, facility-level adjustments, and implementation issues, including evaluation and monitoring. Then, to develop the provisions of the August 7, 2001 final rule (66 FR 41316, 41323), RAND did similar analysis on calendar year 1998 and 1999 Medicare Provider Analysis and Review (MedPAR) files and patient assessment data.

We have continued to contract with RAND to help us identify potential refinements to the IRF PPS. The refinements we proposed to make to the IRF PPS, and which we are finalizing in this final rule, are based on the analyses and recommendations from RAND. In addition, RAND sought advice from a technical expert panel (TEP), which reviewed their methodology and findings.

2. Data Files Used for Analysis of the Current IRF PPS

RAND conducted updated analyses of the patient classification system, case mix and coding changes, and facility-level adjustments for the IRF PPS using data from calendar year 2002 and FY 2003. This is the first time CMS or RAND has had data generated by IRFs after the implementation of the IRF PPS that are available for data analysis.

Public comments and our responses on RAND's research to support the proposed refinements are summarized below:

Comment: Several commenters expressed concerns about basing the refinements that we proposed in the FY 2006 proposed rule (70 FR 30188) on analyses of calendar year 2002 and FY 2003 data, which do not reflect IRF case mix changes currently taking place in response to our recent enforcement of the classification criterion, commonly known as the “75 percent rule.” These commenters suggested that we wait for analysis of future data (CY 2005 or beyond) to become available before implementing refinements to the IRF PPS.

Response: As discussed in the August 7, 2001 final rule (66 FR 41316), we used RAND's analysis of calendar year 1998 and 1999 Medicare Provider Analysis and Review (MedPAR) files and patient assessment data to develop the initial classification system and prospective payment amounts for the IRF PPS. These data were from a period of time before the IRF PPS when IRFs' reimbursement was based on costs, subject to certain limits, rather than on prospective payment amounts. Furthermore, we used the best available 1998 and 1999 data from a time period that also preceded enforcement of the 75 percent rule requirements. Today, we have 2002 and 2003 data that represents all Medicare-covered IRF cases in a post-PPS environment and, therefore, portrays a recent and complete picture of IRFs' patient populations. In addition, the IRF payment system has undergone a major transformation since the 1998 and 1999 data in the form of a change from a cost-based payment system to a PPS that became effective with the cost reporting periods beginning on or after January 1, 2002. Because of this transformation, we believe the data we have on which to base refinements to the IRF PPS will help ensure that IRF PPS payments accurately reflect the costs of care in an IRF.

This is because these data allow RAND to obtain precision in their analyses, and ensures that the data are not over- or under-representing particular types of facilities or patients. We believe it is appropriate and necessary to implement refinements to the IRF PPS at this time, based on the best available data we have from calendar year 2002 and FY 2003. Since analysis of this data indicates that we have an opportunity at this time, through the proposed refinements, to improve the alignment between IRF payments and the cost of care, we believe it is important to proceed with the refinements discussed in this final rule.

However, we agree with the commenters that we should continue to collect the best available data we can to monitor the IRF PPS and ensure that IRF payments are appropriately aligned with costs of care and that Medicare patients continue to have appropriate access to IRF services. We will, whenever necessary, use the best data available in the future to propose appropriate refinements that will further improve the alignment between IRF payments and the costs of care. Thus, to the extent changes in case mix occur due to enforcement of the 75 percent rule, these changes should appear in later data that we will use to propose refinements in the future.

Comment: Several commenters noted that 98 IRF providers in RAND's analysis data affiliated with HealthSouth decided to omit home office cost data from the 2002 and 2003 cost reports that were filed with us. The commenters questioned whether this omission might have affected the results of RAND's analysis and, therefore, our proposed policies.

Response: After publication of the FY 2006 proposed rule (70 FR 30188), we learned that 98 providers in our data file that were affiliated with HealthSouth omitted home office cost data from the 2002 and 2003 cost reports that were filed with us and that RAND used in the analysis of the FY 2006 proposed rule (70 FR 30188). These data were a voluntary omission on the part of these providers, but nevertheless affect some of the distributional policies (that is, the proposed teaching status adjustment, the proposed changes to the rural and LIP adjustments, and the proposed change to the outlier threshold) contained in the proposed rule. However, because RAND used the hospital-specific relative value method (that is, the methodology that effectively controls for inter-hospital variation while estimating the relative costs of different types of patients within each hospital) for all of the proposed changes to the classification system described in section V of this final rule (that is, the proposed changes to the tier comorbidities, the proposed changes to the CMG definitions, the proposed weighted motor score methodology, the proposed change to the coding of the transfer-to-toilet item, and the proposed update of the relative weights), these proposed changes would not have been affected by the omission of the home office cost data. In other words, RAND examined the relative costs of patients within each IRF, so the fact that the omission of HealthSouth's home office costs caused total costs to be understated in the cost report data would not have mattered for the proposed classification system changes described in section V of this final rule.

In addition, the omission of the home office cost data would have no effect on the proposed 1.9 percent reduction to the standard payment amount (discussed in section VI.A of this final rule) because cost report data were not Start Printed Page 47885used in the analysis that supports this proposed reduction.

Although the omission of the home office cost data, in theory, could have had some effect on the estimates of the proposed FY 2002-based RPL market basket (discussed in section VI.B.1 of this final rule), our Office of the Actuary conducted some preliminary analyses of the effects on the market basket calculation and, based on these analyses, determined that these effects would likely be small. Home office costs represent only one of many cost categories (including, but not limited to, salaries, benefits, professional liability insurance, and pharmacueticals) that are used to develop the cost category weights. We believe the absence of HealthSouth home office costs in this market basket has a minor impact on the distribution of these weights and, by extension, the final market basket update itself. Thus, we did not believe it was necessary to recalculate the market basket.

Finally, since the facility-level adjustments we proposed in the FY 2006 proposed rule (70 FR 30188) were calculated using regression analysis based on the relative total costs associated with care in different types of IRFs (that is, urban/rural, teaching/non-teaching, low DSH percentage/high DSH percentage), the omission of HealthSouth's home office costs had some effect on the results of these analyses. The largest example is for the cost differential between urban and rural facilities in our analysis. Since the providers that omitted the home office cost data were largely urban facilities, their lower reported total cost data caused the differential between urban and rural facilities to be larger in the initial analyses. The same was true, to a lesser extent, with the teaching status adjustment and the LIP adjustment.

Furthermore, the omission of the home office cost data caused overall reported costs to be lower in these facilities and, therefore, affected the cost-to-charge ratios computed for these facilities for FYs 2002 and 2003. We used these cost-to-charge ratios to determine the proposed update to the outlier threshold amount. Therefore, analysis of the data indicates that the outlier threshold amount we proposed in the FY 2006 proposed rule (70 FR 30188) was affected by the omission of the home office cost data.

Given that the facility-level adjustments, such as the rural, LIP, and teaching status adjustments, and the outlier threshold amount for all IRFs were likely affected by the decision of this one large for-profit chain provider to omit home office cost data from the FY 2002 and FY 2003 cost reports, we believe it is appropriate for us to recalculate the values for these adjustments and for the outlier threshold using data that accounts for the omitted home office costs. Thus, we obtained the FY 2004 HealthSouth home office cost statement and, from this cost report statement, compiled the home office cost data for each of the individual HealthSouth IRF providers listed. Of the 98 providers that omitted home office cost data for FYs 2002 and 2003, 92 of the providers have had home office cost data reported on the FY 2004 home office cost statement; and six providers did not have any home office cost information for FY 2004.

We considered several options with respect to incorporating the missing HealthSouth home office costs into the data RAND used to conduct the analyses for this final rule. First, we considered the option of removing all of the HealthSouth cost report data from the analysis and re-computing the facility-level adjustments (that is, the rural adjustment, the LIP adjustment, and the teaching status adjustment) and the outlier threshold without the HealthSouth cost report data. Dropping all of the cost report data for 98 of the 1,188 facilities in RAND's analysis file, especially when they are large urban facilities, would seem to skew the data even further because we would be leaving out a substantial amount of cost report data connected with one specific type of IRF provider (i.e., urban IRFs). Leaving out the data for these facilities would make other types of IRFs that are left in the data appear to have more of an effect on the regression analysis than they actually do. Since we were hoping to reduce the bias in the data, rather than increase the bias, we generally rejected this option.

The second option we considered was to update the analysis using FY 2004 data for all providers and re-compute the facility-level adjustments and the outlier threshold using the FY 2004 cost report data. Unfortunately, the FY 2004 data have only recently been submitted by all IRF providers, and it would have been impossible for RAND and CMS to have completed all the necessary re-analysis of all of the proposed policies with the FY 2004 cost report data for all IRF providers in time for the proposed policies to be implemented in FY 2006.

The third option we considered was to use the FY 2004 home office cost data that we were able to obtain from the HealthSouth home office cost statement for 92 of the 98 HealthSouth IRF providers, standardize all of the other cost report data from FY 2003 for the 98 HealthSouth providers and the other non-HealthSouth providers using the most recent market basket for FY 2004, and fill in the FY 2004 home office cost data for the 92 HealthSouth providers for which we had data. This option enabled us to meet the October 1 implementation date of our updates as well as to make those updates and payment adjustments as accurate as possible. Next, we considered two options for treating the six HealthSouth facilities for which we did not have FY 2004 home office cost data: We considered leaving those six IRFs' cost data as is, without adding any home office cost data since we had none from FY 2004 to add. The other option we considered for treating these six facilities was to take the average home office costs as a percentage of total costs for the 92 facilities (which came to approximately 13 percent) and use this as an estimate of home office costs for the 6 facilities. We chose the second of the two options, which meant that we inflated total costs for those six facilities by the average of about 13 percent, because it seemed inappropriate to ignore the fact that cost data was missing for these six facilities and 13 percent appeared to be a reasonable estimate of home office costs generally for IRFs (from the general analysis we were able to perform).

Because we believe the data file that results from the third option is more complete than the data RAND previously used to compute the proposed facility-level adjustments and the proposed outlier threshold amount for the FY 2006 proposed rule (70 FR 30188), we used the data from the third option described above to re-compute the values for the teaching status adjustment (described in more detail in section VI.B.3 of this final rule), the rural adjustment (described in more detail in section VI.B.4 of this final rule), the LIP adjustment (described in more detail in section VI.B.5 of this final rule), and the outlier threshold amount (described in more detail in section VI.B.6 of this final rule). Because the values of these adjustments have changed, we also re-computed the budget neutrality factors and, thus, the standard payment conversion factor.

Comment: Several commenters requested that we make IRF claims data, IRF-PAI data, patient-specific CMG data, and cost report files available to the public so that the public would have the opportunity to recreate the analyses used in developing the proposed refinements for the FY 2006 proposed rule (70 FR 30188).

Response: The data files mentioned by the commenters are generally available (and were generally available Start Printed Page 47886during the comment period for the FY 2006 proposed rule (70 FR 30188)) to the public through CMS's standard data distribution systems. More information on CMS's data distribution policies is available on CMS's website at http://www.cms.hhs.gov/​researchers/​statsdata.asp.

Comment: A few commenters requested that we make available RAND's research using FY 2003 data. They noted that 3 of the 4 reports published on RAND's website for public access are based on analysis of calendar year 2002 data. One of RAND's publicly available reports is based on analysis of FY 2003 data.

Response: We asked RAND to use the best available, most current data possible for the analyses contained in the FY 2006 proposed rule (70 FR 30188) and this final rule. This was generally FY 2003 data.

The updated analysis is generally not contained in RAND's reports, and RAND has indicated to CMS that they have no plans to publish the updated analyses (using the FY 2003 data) after publication of the final rule. However, RAND informed us that, in all of the FY 2003 analyses for the FY 2006 proposed rule (70 FR 30188) and for this final rule, they used the identical methodologies presented in the reports available on RAND's website and reviewed by RAND's technical expert panel. The only change was that RAND used updated data from FY 2003 (and FY 2004 HealthSouth home office cost data, as discussed above). Thus, interested parties should examine the reports available on RAND's website for the detailed methodology used to develop the proposed and final revisions. In addition, interested parties may contact RAND directly for more information regarding the analysis of FY 2003 data.

Comment: One commenter asked whether a large number of short period cost reports for periods ending in 2001 might have affected RAND's research findings and, if so, how RAND handled this issue in the data.

Response: We were unable to find any reasons for the unusually large number of short period cost reports the commenter is indicating for cost report periods ending in 2001. However, since some of RAND's analysis for this final rule was based on calendar year 2002 data, and the majority of RAND's analysis for this final rule was based on FY 2003 data, we do not believe that a spike in the number of short period cost reports in 2001 would have had an effect on RAND's analyses.

V. Refinements to the Patient Classification System

A. Changes to the IRF Classification System

1. Development of the IRF Classification System

Section 1886(j)(2)(A)(i) of the Act, as amended by section 125 of the Medicare, Medicaid, and SCHIP Balanced Budget Refinement Act of 1999 requires the Secretary to establish “classes of patient discharges of rehabilitation facilities by functional-related groups (each referred to as a case-mix group or CMG), based on impairment, age, comorbidities, and functional capability of the patients, and such other factors as the Secretary deems appropriate to improve the explanatory power of functional independence measure-function related groups.” In addition, the Secretary is required to establish a method of classifying specific patients in IRFs within these groups as specified in § 412.620.

In the August 7, 2001 final rule (66 FR at 41342), we implemented a methodology to establish a patient classification system using CMGs. The CMGs are based on the FIM-FRG methodology and reflect refinements to that methodology.

In general, a patient is first placed in a major group called a rehabilitation impairment category (RIC) based on the patient's primary reason for inpatient rehabilitation, (for example, a stroke). The patient is then placed into a CMG within the RIC, based on the patient's ability to perform specific activities of daily living, and sometimes the patient's cognitive ability and/or age. Other special circumstances, such as the occurrence of very short stays, or cases where the patient expired, are also considered in determining the appropriate CMG.

We explained in the August 7, 2001 final rule that further analysis of FIM and Medicare data may result in refinements to CMGs. In the August 7, 2001 final rule, we used the most recent FIM and Medicare data available at that time (that is 1998 and 1999 data). Developing the CMGs with the 1998 and 1999 data resulted in 95 CMGs based on the FIM-FRG methodology. The data also supported the establishment of five additional special CMGs that improved the explanatory power of the FIM-FRGs. We established one additional special CMG to account for very short stays and four additional special CMGs to account for cases where the patient expired. In addition, we established a payment of an additional amount for patients with at least one relevant comorbidity in certain CMGs.

2. Description and Methodology Used To Develop the IRF Classification System in the August 7, 2001 Final Rule

a. Rehabilitation Impairment Categories

In the first step to develop the CMGs, the FIM data from 1998 and 1999 were used to group patients into RICs. Specifically, the impairment code from the assessment instrument used by clients of UDSmr and Healthsouth indicates the primary reason for the inpatient rehabilitation admission. This impairment code is used to group the patient into a RIC. Currently, we use 21 RICs for the IRF PPS.

b. Functional Status Measures and Age

After using the RIC to define the first division among the inpatient rehabilitation groups, we used functional status measures and age to partition the cases further. In the August 7, 2001 final rule, we used 1998 and 1999 Medicare bills with corresponding FIM data to create the CMGs and more thoroughly examine each item of the motor and cognitive measures. Based on the data used for the August 7, 2001 final rule, we found that we could improve upon the CMGs by making a slight modification to the motor measure. We modified the motor measure by removing the transfer to tub/shower item because we found that an increase in a patient's ability to perform functional tasks with less assistance for this item was associated with an increase in cost, whereas an increase in other functional items decreased costs. We describe below the statistical methodology (Classification and Regression Trees (CART)) that we used to incorporate a patient's functional status measures (modified motor score and cognitive score) and age into the construction of the CMGs in the August 7, 2001 final rule.

We used the CART methodology to divide the rehabilitation cases further within each RIC. (Further information regarding the CART methodology can be found in the seminal literature on CART (Classification and Regression Trees, Leo Breiman, Jerome Friedman, Richard Olshen, Charles Stone, Wadsworth Inc., Belmont CA, 1984: pp. 78-80).) We chose to use the CART method because it is useful in identifying statistical relationships among data and, using these relationships, constructing a predictive model for organizing and separating a large set of data into smaller, similar groups. Further, in constructing the CMGs, we analyzed the extent to which the independent Start Printed Page 47887variables (motor score, cognitive score, and age) helped predict the value of the dependent variable (the log of the cost per case). The CART methodology creates the CMGs that classify patients with clinically distinct resource needs into groups. CART is an iterative process that creates initial groups of patients and then searches for ways to divide the initial groups to decrease the clinical and cost variances further and to increase the explanatory power of the CMGs. Our current CMGs are based on historical data. In order to develop a separate CMG, we need to have data on a sufficient number of cases to develop coherent groups. Therefore, we are removing these codes from the tiers that increase payment.

c. Comorbidities

Under the statutory authority of section 1886(j)(2)(C)(i) of the Act, we proposed to make several changes to the comorbidity tiers associated with the CMGs for comorbidities that are not positively related to treatment costs, or their excessive use is questionable, or their condition could not be differentiated from another condition. Specifically, section 1886(j)(2)(C)(i) of the Act provides the following: The Secretary shall from time to time adjust the classifications and weighting factors established under this paragraph as appropriate to reflect changes in treatment patterns, technology, case mix, number of payment units for which payment is made under this title and other factors that may affect the relative use of resources. The adjustments shall be made in a manner so that changes in aggregate payments under the classification system are a result of real changes and are not a result of changes in coding that are unrelated to real changes in case mix.

A comorbidity is a specific patient condition that is secondary to the patient's principal diagnosis or impairment that is used to place a patient into a RIC. A patient could have one or more comorbidities present during the inpatient rehabilitation stay. Our analysis for the August 7, 2001 final rule found that the presence of a comorbidity could have a major effect on the cost of furnishing inpatient rehabilitation care. We also stated that the effect of comorbidities varied across RICs, significantly increasing the costs of patients in some RICs, while having no effect in others. Therefore, for the August 7, 2001 final rule, we linked frequently occurring comorbidities to impairment categories in order to ensure that all of the chosen comorbidities were not an inherent part of the diagnosis that assigns the patient to the RIC.

Furthermore, in the August 7, 2001 final rule, we indicated that comorbidities can affect cost per case for some of the CMGs, but not all. When comorbidities substantially increased the average cost of the CMG and were determined to be clinically relevant (not inherent in the diagnosis in the RIC), we developed CMG relative weights adjusted for comorbidities (§ 412.620(b)).

d. Development of CMG Relative Weights

Section 1886(j)(2)(B) of the Act requires that an appropriate relative weight be assigned to each CMG. Relative weights account for the variance in cost per discharge and resource utilization among the payment groups and are a primary element of a case-mix adjusted PPS. The establishment of relative weights helps ensure that beneficiaries have access to care and receive the appropriate services that are commensurate to other beneficiaries that are classified in the same CMG. In addition, prospective payments that are based on relative weights encourage provider efficiency and, hence, help ensure a fair distribution of Medicare payments. Accordingly, as specified in § 412.620(b)(1), we calculate a relative weight for each CMG that is proportional to the resources needed by an average inpatient rehabilitation case in that CMG. For example, cases in a CMG with a relative weight of 2, on average, will cost twice as much as cases in a CMG with a relative weight of 1. We discuss the details of developing the relative weights below.

As indicated in the August 7, 2001 final rule, we believe that the RAND analysis has shown that CMGs based on function-related groups (adjusted for comorbidities) are effective predictors of resource use as measured by proxies such as length of stay and costs. The use of these proxies is necessary in developing the relative weights because data that measure actual nursing and therapy time spent on patient care, and other resource use data, are not available.

e. Overview of Development of the CMG Relative Weights

As indicated in the August 7, 2001 final rule, to calculate the relative weights, we estimate operating (routine and ancillary services) and capital costs of IRFs. For this final rule as we indicated in the FY 2006 proposed rule (70 FR 30188), we use the same method for calculating the cost of a case that we outlined in the August 7, 2001 final (66 FR at 41351 through 43153). We obtained cost-to-charge ratios for ancillary services and per diem costs for routine services from the most recent available cost report data. We then obtain charges from Medicare bill data and derived corresponding functional measures from the FIM data. We omit data from rehabilitation facilities that are classified as all-inclusive providers from the calculation of the relative weights, as well as from the parameters that we use to define transfer cases, because these facilities are paid a single, negotiated rate per discharge and therefore do not maintain a charge structure. For ancillary services, we calculate both operating and capital costs by converting charges from Medicare claims into costs using facility-specific, cost-center specific cost-to-charge ratios obtained from cost reports. Our data analysis for the August 7, 2001 final rule showed that some departmental cost-to-charge ratios were missing or found to be outside a range of statistically valid values. For anesthesiology, a value greater than 10, or less than 0.01, is found not to be statistically valid. For all other cost centers, values greater than 10 or less than 0.5 are found not to be statistically valid. In the August 7, 2001 final rule, we replaced individual cost-to-charge ratios outside of these thresholds. The replacement value that we used for these aberrant cost-to-charge ratios was the mean value of the cost-to-charge ratio for the cost-center within the same type of hospital (either freestanding or unit). For routine services, per diem operating and capital costs are used to develop the relative weights. In addition, per diem operating and capital costs for special care services are used to develop the relative weights. (Special care services are furnished in intensive care units. We note that less than 1 percent of rehabilitation days are spent in intensive care units.) Per diem costs are obtained from each facility's Medicare cost report data. We use per diem costs for routine and special care services because, unlike for ancillary services, we could not obtain cost-to-charge ratios for these services from the cost report data. To estimate the costs for routine and special care services included in developing the relative weights, we sum the product of routine cost per diem and Medicare inpatient days and the product of the special care per diem and the number of Medicare special care days.

In the August 7, 2001 final rule, we used a hospital specific relative value method to calculate relative weights. Start Printed Page 47888For the FY 2006 proposed rule (70 FR 30188) and this final rule, we used the following basic steps to calculate the relative weights as indicated in the August 7, 2001 final rule (at 66 FR 41316, 41351 through 41352).

The first step in calculating the CMG weights is to estimate the effect that comorbidities have on costs. The second step required us to adjust the cost of each Medicare discharge (case) to reflect the effects found in the first step. In the third step, the adjusted costs from the second step were used to calculate “relative adjusted weights” in each CMG using the hospital-specific relative value method. The final steps are to calculate the CMG relative weights by modifying the “relative adjusted weight” with the effects of the existence of the comorbidity tiers (explained below) and normalizing the weights to 1.

Our methodology for determining the IRF classification system remains unchanged from the August 7, 2001 final rule.

B. Changes to the Existing List of Tier Comorbidities

1. Changes To Remove Codes That Are Not Positively Related to Treatment Costs

While our methodology for this final rule for determining the tiers remains unchanged from the August 7, 2001 final rule, as we indicated in the FY 2006 proposed rule (70 FR 30188), RAND's analysis indicates that 1.6 percent of FY 2003 cases received a tier payment (often in tier one) that was not justified by any higher cost for the case. Therefore, under statutory authority section 1886(j)(2)(C)(i) of the Act, as we proposed in the FY 2006 proposed rule (70 FR 30188) we are implementing several technical changes to the comorbidity tiers associated with the CMGs. Specifically, the RAND analysis found that the first 17 diagnoses shown in Table 1 below are no longer positively related to treatment cost after controlling for CMG. The additional two codes were also problematic. According to RAND, code 410.91 (AMI, NOS, Initial) was not specific enough to be differentiated from other related codes and code 260, Kwashiorkor, was found to be unrealistically represented in the data according to the RAND technical expert panel.

With respect to the eighteenth code in Table One, (410.X1) Specific AMI, initial), we note that RAND found there is no clinical reason to believe that this code differs in a rehabilitation environment from all of the specific codes for initial AMI of the form 410.X1, where X is an numeric digit. In other words, this code is indistinguishable from the seventeenth code in Table One (410.91 AMI, NOS, initial). Following this observation, RAND tested the other initial AMI codes as a single group and found that they have no positive effect on case cost. Thus, as we indicated in the FY 2006 proposed rule (70 FR 30188), we proposed to remove “AMI, NOS, initial” from the tier list because it is not positively related to treatment cost after controlling for the CMG. In addition, for similar reasons, we proposed in the FY 2006 proposed rule (70 FR 30188) to remove “Specific AMI, initial from the tier list since it is indistinguishable from “AMI, NOS, initial.”

As we proposed in the FY 2006 proposed rule (70 FR 30188), with respect to the last code in Table One (Kwashiorkor), we are removing this code from the tier list as well. This comorbidity is positively related to cost in our data. However, RAND's technical expert panel (TEP) found the large number of cases coded with this rare disease to be unrealistic and recommended that it be removed from the tier list.

Table 1 contains two malnutrition codes, and as we proposed in the FY 2006 proposed rule (70 FR 30188), we are removing these two malnutrition codes. As we stated in the FY 2006 Proposed Rule (70 FR 30188), removal of these codes where use is concentrated in specific hospitals is particularly important because these hospitals are likely receiving unwarrantedly high payments due to the tier one assignment of these cases. Thus, because we believe the excess use of these two comorbid conditions is inappropriate based on the findings of RAND's TEP, they will be removed.

The data indicate large variation in the rate of increase from the 1999 data to the 2003 data across the conditions that make up the tiers. The greatest increases were for miscellaneous throat conditions and malnutrition, each of which were more than 10 times as frequent in 2003 as in 1999. The growth in these two conditions was far larger than for any other condition. Many conditions, however, more than doubled in frequency, including dialysis, cachexia, obesity, and the non-renal complications of diabetes. The condition with the least growth, renal complications of diabetes, may have been affected by improved coding of dialysis.

As we proposed in the FY 2006 proposed rule (70 FR 30188), we are finalizing changes to our initial list of diagnoses that deal with tracheostomy cases. These rare cases were excluded from the pulmonary RIC 15 in the August 7, 2001 final rule. The new data indicate that they are more expensive than other cases in the same CMG in RIC 15, as well as in other RICs. Therefore, we believe the data demonstrate that tracheostomy cases should be added to the tier list for RIC 15 in order to receive a higher payment. Finally, the new data indicate that DX V55.0, “attention to tracheostomy” should be part of this condition as these cases were and are as expensive as other tracheostomy cases. Thus, since “attention to tracheostomy” is as expensive as other tracheostomy cases, it is logical to group such similar cases together. Therefore, we are finalizing our proposal to remove the RIC 15 exclusion for code V55.0 (attention to tracheostomy) so that code V55.0 can receive appropriate payment for the additional costs it incurs.

As we stated in the FY 2006 proposed rule (70 FR 30188), we believe that the data provided by RAND support the removal of the codes in Table 1 below because they either have no impact on cost after controlling for their CMG or are indistinguishable from other codes or are unrealistically overrepresented. Therefore, we are finalizing our proposed policy to remove these codes from the tier list.

Table 1.—List of Codes To Be Removed From the Tier List

ICD-9-CM codeAbbreviated code titleCondition
235.1Unc behav neo oral/pharMiscellaneous throat conditions.
933.1Foreign body in larynxMiscellaneous throat conditions.
934.1Foreign body bronchusMiscellaneous throat conditions.
530.0Achalasia & cardiospasmEsophegeal conditions.
530.3Esophageal strictureEsophageal conditions.
530.6Acquired esophag diverticulumEsophageal conditions.
Start Printed Page 47889
V46.1 *Dependence on respiratorVentilator status.
799.4CachexiaCachexia.
V49.75Status amputation below kneeAmputation of LE.
V49.76Status amputation above kneeAmputation of LE.
V49.77Status amputation hipAmputation of LE.
356.4Idiopathic progressive polyneuropathyMeningitis and encephalitis.
250.90Diabetes II, w unspecified complications, not stated as uncontrolledNon-renal complications of diabetes.
250.93Diabetes I, w unspecified complications, uncontrolledNon-renal complications of diabetes.
261Nutritional MarasmusMalnutrition.
262Other severe protein calorie deficiencyMalnutrition.
410.91AMI, NOS, initialMajor comorbidities.
410.X1Specific AMI, initialMajor comorbidities.
260KwashiorkorMalnutrition.
* V46.11 and V46.12 were not in existence when the data used in the analysis was collected. Since these codes are subcategories of code V46.1 (the code we proposed to remove from the tiers that make additional payment), they will be removed from the comorbidity tiers as well.

We received numerous comments on the proposed changes to the existing list of tier comorbidities which are summarized below:

Comment: One commenter remarked that kwashiorkor should be omitted from the list of comorbidities to be deleted from the list of comorbidities that increase the payment rate of the CMG because some of the software packages used by the industry allow this code to be used for the coding of the inpatient's comorbidities.

Response: We disagree with the commenter. Kwashiorkor is a severe malnutrition of infants and young children, primarily in tropical and subtropical regions, caused by deficiency in the quality and quantity of protein in the diet. It is characterized by anemia, edema, potbelly, loss of pigment in the skin, hair loss or change in hair color, hypoalbuminemia, and bulky stools containing undigested food. In addition, an inpatient with this condition most likely would not be able to receive the three hours of intensive rehabilitation that is a qualifying guideline to be an inpatient within an IRF. While protein deficiencies may be noted in patients within an IRF, by definition, the incidence of Kwashiorkor could not be as high as reported. Also, as previously stated, RAND's TEP reported that the data indicate large variation in the rate of increase across conditions. However, coding of malnutrition increased by more than 10 times, and RAND found the large number of cases coded with this rare disease to be unrealistic and recommended that it be removed from the tier list. Consequently, kwashiorkor will be eliminated from the list of comorbidities that increase the payment rate of the CMG.

Comment: One commenter wrote that code V46.1 is listed in the proposed list of codes to be removed from the tier list. Since this code contains two other codes, the commenter wanted to know if it is our intention to remove both codes in this category, namely V46.11 (Dependence on respirator, status) and V46.12 (Encounter for respirator dependence during power failure) or just one of these codes.

Response: First, we want to explain how codes V46.11 and V46.12 became codes that are used to increase the CMG payment rate. In the August 7, 2001 final rule (66 FR 41316), we published Appendix C that listed the ICD-9-CM comorbid condition codes which are used to increase the CMG payment rate. The ICD-9-CM codes of the comorbid conditions are recorded by the IRF's staff on the IRF-PAI, and that data as well as some other data recorded on the IRF-PAI is used to classify an inpatient into a CMG payment rate. One of the codes we published as part of Appendix C was V46.1. Each year the codes used in the ICD-9-CM coding system undergo a review resulting in updates to some of the existing codes. In accordance with a review that updated the ICD-9-CM coding system V46.11 and V46.12 were added to the ICD-9-CM coding system as subcategories of V46.1. We believe that the comorbid condition represented by the code V46.11 or V46.12 is a derivative of the comorbid condition represented by the code V46.1. Therefore, in 2005 we updated the CMG grouper software which resulted in the CMG payment being increased by the same amount if the IRF-PAI data of an inpatient included codes V46.1, or V46.11, or V46.12.

The analysis that our data contractor performed, using certain data after the IRF PPS was implemented, shows that the comorbid condition represented by code V46.1 does not have an effect upon treatment cost after controlling for the CMG. Therefore, code V46.1 and its derivative codes that comprise it (V46.11 and V46.12) will be removed from the list of codes that are used by the IRF PPS to increase the CMG payment rate.

Comment: Several commenters urged us to consider not removing codes V49.75, V49.76, and V49.77 from the list of comorbidity codes that increase the CMG payment because of concerns with the complexity of a patient with an amputation.

Response: After controlling for the CMG, RAND found that these codes do not impact cost. Further, IRFs do not incur additional costs to treat these comorbidities after controlling for the CMG. This means that the CMG to which the inpatient is assigned, already accounts for the costs associated with the treatment of inpatients with an amputation and no additional payment is needed beyond the CMG amount to adequately reimburse for such a case. Therefore we are removing these codes from the list of comorbidities that increase the CMG payment.

Comment: Several commenters mentioned a concern with the code V497.7 in the table of codes to be removed. They believed it to be a typographical error where the actual code to be removed is V49.77.

Response: We agree with the commenters and have made the correction to the typographical error. The corrected code to be removed is V49.77.

Comment: Several commenters noted that there is a discrepancy with code 428.3 (vocal cord paralysis, not otherwise specified) in CMS' list of Start Printed Page 47890codes being reassigned based on their marginal cost in the Comorbidity Tier Reassignment Changes File found at http://www.cms.hhs.gov/​providers/​irfpps/​fy06nprm.asp. They stated that it should actually be code 478.30 (vocal cord paralysis, not otherwise specified).

Response: We agree with the commenters and shall make the appropriate corrections to the typographical error within the file.

Comment: Several commenters noted an error with the description of meningitis and encephalitis for code 356.4 in the Comorbidity Tier Reassignment Changes File found at http://www.cms.hhs.gov/​providers/​irfpps/​fy06nprm.asp.

Response: We agree with the commenters and the description will be amended to read idiopathic progressive polyneuropathy for code 356.4.

Comment: Commenters expressed concern for the removal of codes 530.0 (achalasia and cardiospasm), 530.3 (stricture and stenosis of esophagus) and 530.6 (diverticulum of esophagus) that are used to record esophageal conditions because of costs associated with these conditions and requested that they not be removed from the tier list which increases payment for these comorbidities.

Response: After controlling for the CMG, RAND found that these comorbidities do not positively impact costs, meaning that the CMG encompasses sufficient payment to compensate for these comorbidities. Therefore, we are removing codes 530.0, 530.3 and 530.6 from the list of comorbidities that increase CMG payment.

Comment: Several commenters agreed with CMS' proposed policy to remove malnutrition codes 261 (nutritional marasmus) and 262 (other severe protein-calorie malnutrition), while others opposed the proposed policy to remove these codes. In addition, several commenters suggested that CMS examine the impact of malnutrition on increasing the length of stay within an IRF.

Response: We acknowledge both opinions as expressed by the different commenters. The RAND TEP, and our Medical Officers, believes these codes are drastically overstated and inpatients with these levels of malnutrition would not be candidates for three hours of intensive therapy. In addition, after controlling for the CMG, both of these codes do not positively affect payment. Therefore we believe it is appropriate to remove malnutrition codes 261 and 262 from the list of comorbidity codes that are used to increase the CMG payment rate. Additionally, we will continue to examine the impact of comorbidities, including malnutrition, upon IRF Medicare-covered inpatients.

Comment: One commenter suggested adding codes 250.91 and 250.92 to the list of comorbidities to be removed from the list of codes used to increase payment because they believe those codes to be similar in description to codes 250.90 and 250.93.

Response: Only the first 17 codes within Table 1 were found to have no positive effect on cost after controlling for the CMG. The data analysis performed by RAND does not indicate that at this time 250.91 and 250.93 should be removed from the list of codes used to increase the CMG payment rate because they continue to positively affect costs. Therefore we believe it is inappropriate to remove them from the list of comorbidities that impact cost. Consequently, we are not removing any other codes from the list of codes used to increase the CMG payment rate.

Comment: One commenter recommended that several codes be added to our comorbidity tier system based upon suggestions from the RAND TEP, namely codes 428.0 (congestive heart failure), V43.3 (heart valve replacement), 250.1 (insulin dependent diabetes without mention of complications, not stated as controlled) and 438.2X (hemi-paresis due to an old stroke).

Response: After examining the RAND recommendations, our Medical Officers felt that codes V43.3 and 438.2X were too vague and non-descript to capture the necessary information needed for these codes to be added to the list of codes used to increase the CMG payment rate. However, in response to the comments our Medical Officers re-evaluated the effect on cost by the comorbid condition represented by code 250.1 (insulin dependent diabetes without mention of complications, not stated as controlled). They determined that code 250.1 should be added to the list of codes used to increase the CMG payment rate. They also determined that the code should be a tier 3 code because the other 250 series of codes related to diabetes are in tier 3. Therefore, this code will be added as a tier 3 code to the list of codes used to increase the CMG payment rate. There will be no excluded RICs with code 250.1. After examining the comments, our Medical Officers continue to believe that 428.9 (heart failure, unspecified), was too non-descript and should not be added to the list of codes that can increase payment. However, our Medical Officers agree with the commenter regarding other numerous congestive heart failure codes including Code 428.1—Left Heart Failure, Code 428.20—Systolic Heart Failure Unspecified, Code 428.21—Systolic Heart Failure Acute, Code 428.22—Systolic Heart Failure Chronic, Code 428.23—Systolic Hear Failure Acute on Chronic, Code 428.30—Diastolic Heart Failure Unspecified, Code 428.31—Diastolic Heart Failure Acute, Code 428.32—Diastolic Heart Failure Chronic, Code 428.33—Diastolic Heart Failure Acute on Chronic, Code 428.40—Combined Systolic and Diastolic Heart Failure Unspecified, Code 428.41—Combined Systolic and Diastolic Heart Failure Acute, Code 428.42—Combined Systolic and Diastolic Heart Failure Chronic, and Code 428.43—Combined Systolic and Diastolic Heart Failure Acute on Chronic, largely due to the increased costs associated with these codes. Therefore, these 428 cardiac codes will be added to the list of codes used to increase the CMG payment rate as tier 3 codes because of their similarity to certain cardiac codes with respect to resource utilization. However, these codes will not be used to increase the CMG payment rate if the CMG code is one of the CMG codes derived from RIC 14 (the cardiac RIC) because these cardiac codes costs have been accounted for in the CMGs associated with RIC 14.

Comment: A commenter believes that the CMG payment rate should include an adjustment for mental health problems, such as a depression. The commenter believes that a patient's mental health status has an effect on the patient treatment costs an IRF incurs.

Response: The significance and appropriateness of a patient's state of mental health in response to an impairment that requires a patient to undergo intensive inpatient rehabilitation is a subject that we believe requires further study. Additional study will help to determine the effect of the patient's state of mental health on treatment costs. An ICD-9-CM code may be used to show that a patient is exhibiting signs that a rehabilitation clinician believes indicate a mental disorder. However, quantifying by use of ICD-9-CM codes the association between a patient's state of mental health and how it affects a patient's response to rehabilitation treatment is at best limited. For example, we believe that in response to a stroke or hip fracture, or some other impairment, a situational depression may be a rational response. However, that does not mean that the IRF will incur additional costs that were not already taken into account when the CMG payment rates were developed. In addition, mental disorders vary greatly Start Printed Page 47891in severity as does how a patient's functioning is affected by a mental disorder.

There would have to be multiple factors taken into consideration before any type of mental disorder could be added to the list of comorbidities that would increase payment of the CMG. The data for a complete psychiatric evaluation must be made available to correctly code for these comorbidities. In addition, this is a budget neutral system, and no additional funding will be added to the system. Under our final rule, funds will not be added but simply be redistributed among the comorbidities among the tiers that increase payment. This is because the changes associated with the comorbidity tiers and CMGs are done in a budget neutral manner. On the assumption that there is an even distribution of these psychiatric patients among IRFs, and these patients may receive the redistributed payment, the addition of these codes may not contribute to an increased payment for inpatients with these comorbid conditions and may affectively lower payments for CMG's with other comorbid conditions because the same amount of funding is distributed across more comorbid conditions. Also, few IRFs have psychiatric personnel and rehabilitation doctors rarely have the time required to observe the patient to make a complete psychiatric evaluation and thus some codes may be assigned (or not assigned) in error. In addition, RAND's TEP believed that it would be inappropriate to use ICD-9-CM diagnoses to identify patients with affective disorders. Therefore, in this final rule, we are not adding codes for depression and mental disorders to the list of codes used to increase payment.

Comment: We received comments to both challenge and support the removal of certain comorbidity codes from the tier list including code 799.4 Cachexia, and code 933.1 (foreign body in larynx). Commenters stated that these conditions required more resources, and thus increased treatment costs. The other commenter stated that the CMG already covered these costs.

Response: The data analysis did not show that the comorbid conditions indicated by these codes increased the costs of treating an inpatient with these comobidities after controlling for the CMG because their CMG payment rate covers costs associated with their corresponding treatment. The more recent RAND analysis found that after controlling for the CMG, these comobidities do not impact cost. Therefore, we are removing them from the comorbidity tiers that would increase payment.

Comment: One commenter made a general statement stating that the list of comorbidities that comprise the tiers do not reflect the challenges that contribute to higher costs in the rehabilitation setting.

Response: We disagree with the commenter because the RAND regression analyses show that the comorbid conditions that comprise the tiers positively impact cost and provide additional payments for services not included in the payment associated with the CMG.

Final Decision: In this final rule, we are adopting the proposal to remove the comorbidity tier codes set forth in Table 1 of the FY 2006 proposed rule (70 FR 30188). We are also removing codes V46.11 and V46.12 because they are subcategories of code V46.1, which has been found to have no impact on cost after controlling for the CMG. We are adding several codes that the RAND analyses found to positively impact costs. We chose to add codes 250.1 (insulin dependent diabetes without mention of complications, not stated as controlled), as well as numerous congestive heart failure codes including Code 428.1—Left Heart Failure, Code 428.20—Systolic Heart Failure Unspecified, Code 428.21—Systolic Heart Failure Acute, Code 428.22—Systolic Heart Failure Chronic, Code 428.23—Systolic Heart Failure Acute on Chronic, Code 428.30—Diastolic Heart Failure Unspecified, Code 428.31—Diastolic Heart Failure Acute, Code 428.32—Diastolic Heart Failure Chronic, Code 428.33—Diastolic Heart Failure Acute on Chronic, Code 428.40—Combined Systolic and Diastolic Heart Failure Unspecified, Code 428.41—Combined Systolic and Diastolic Heart Failure Acute, Code 428.42—Combined Systolic and Diastolic Heart Failure Chronic, and Code 428.43—Combined Systolic and Diastolic Heart Failure Acute on Chronic, which our Medical Officers believe were specific enough to be used in our list of codes that are used to increase the CMG payment amount.

2. Changes To Move Dialysis to Tier One

As we proposed in the FY 2006 proposed rule (70 FR 30188), we are finalizing the movement of dialysis from comorbidity tier two to comorbidity tier one, which is the tier associated with the highest payment. The data from the RAND analysis show that patients on dialysis cost more than the tier payment to which dialysis is currently assigned, and should be moved into the highest paid tier because this tier would more closely align payment with the cost of a case. Based on RAND's analysis using 2003 data, a patient with dialysis costs 31 percent more than a non-dialysis patient in the same CMG and with the same other accompanying comorbidities.

Overall, the largest increase in the cost of a condition occurs among patients on dialysis, where the coefficient in the cost regression increases by 93 percent, from 0.1400 to 0.2697. Part of the explanation for the increased coefficient could be that some IRFs had not borne all dialysis costs for their patients in the pre-PPS period, which was the previous data analysis time period(because providers were previously permitted to bill for dialysis separately). It is likely that, in the 1999 data, some IRFs had not borne all dialysis costs for their patients. Because the fraction of cases coded with dialysis increased by 170 percent, it is also likely that improved coding was part of the explanation for the increased coefficient. We believe a 170 percent increase is such a dramatic increase that it would be highly unlikely that in the time periods used for the data analysis, 170 percent more patients needed dialysis when compared to the time period before the implementation of the IRF PPS. We also believe that the improved coding is likely due to the fact that higher costs are associated with dialysis patients, and therefore IRFs, in an effort to ensure that their payments cover these higher expenses better and more carefully coded comorbidities whose presence resulted in higher PPS payments.

Therefore we are moving dialysis patients to comorbidity tier one will more adequately compensate IRFs for the extra cost of those patients and thereby maintain or increase access to these services.

Comment: A number of commenters supported our decision to move dialysis patients to tier one due to the increase cost of dialysis patients.

Response: We agree with these commenters. The data analyses performed by RAND found evidence that suggested that a dialysis patient cost 31 percent more than a non-dialysis patient in the same CMG. Therefore, as proposed in the FY 2006 proposed rule (70 FR 30188), we are moving dialysis to tier 1 because the additional payment associated with tier 1 more closely approximate the additional costs associated with the treatment of an inpatient with this condition.

Final Decision: As proposed in the FY 2006 proposed rule (70 FR 30188), we are adopting the decision to move dialysis patients to comorbidity tier one. Start Printed Page 47892

3. Changes To Move Comorbidity Codes Based on Their Marginal Cost

Under section 1886(j)(2)(C)(i) of the Act, as was proposed in the FY 2006 proposed rule (70 FR 30188), we are refining how we pay for a comorbidity based on marginal cost. A commonly understood definition of marginal cost is the increase or decrease in costs as a result of one higher or lower unit of a good or service. In this situation, we are reassigning comorbidities to tiers based on their marginal costs, and by this we mean the increase or decrease in costs as a result of one higher or lower comorbidity tier. Payment for several comorbidities would be more accurate if their tier assignments were changed, and after examining RAND's data, we believe that of the FY 2003 cases, a full 4 percent of cases should be associated with comorbidity tiers that have a lower payment than the comorbidity tiers to which they were assigned. Therefore, comorbidities would be more accurate if their tier assignments were more appropriately based on their marginal costs.

As we proposed in the FY 2006 proposed rule (70 FR 30188), comorbidity tier assignments in this final rule are based on the results of statistical analyses RAND has performed under contract with CMS, using as independent variables only the CMGs and conditions for tiers. As we proposed in the FY 2006 proposed rule (70 FR 30188), tier assignments of each of these conditions for the final rule are determined based on the magnitude of their coefficients in RAND's statistical analysis.

We believe the IRF PPS led to substantial changes in coding of comorbidities between 1999 (pre-implementation of the IRF PPS) and 2003 (post-implementation of the IRF PPS). The percentage of cases with one or more comorbidities increased from 16.79 percent according to the data used to define the comorbidity tiers (1998 through 1999) to 25.51 percent in FY 2003. This is an increase of 52 percent in tier incidence (52 = 100 × (25.51-16.79)/16.79). The recording of a tier one comorbidity, the highest paid of the tiers, almost quadrupled during this same time period. Although, improved coding likely increased the recording of comorbidities, those coding the comorbidities may have been motivated by the objective to use coding changes as a means to increase the CMG payment.

The 2003 data provides an excellent comprehensive picture of the costs that are associated with each of the comorbidities. We believe this because CMS has data for 100 percent of the Medicare-covered IRF cases. Therefore, as we indicated in the FY 2006 proposed rule, we believe that using the 2003 data to assign the comorbidities to a payment tier ensures heightened accuracy with respect to the matching of payments to relative costs of a case.

We received several comments on the proposed changes to the existing list identifying which tier is associated with a particular comorbidity. The public comments are summarized below.

Comment: One commenter suggested that we postpone reassigning comorbidity tiers based on their marginal costs, and again instead perform the data analysis used to reassign the comorbidity codes based on marginal costs using more current data.

Response: This final rule reflects the most recent analysis of data. In the future, we will continue to perform data analyses and, as necessary, adjust the payment rates to achieve the most accurate payment. In this final rule, we are adopting the policy we proposed in the FY 2006 proposed rule (70 FR 30188), and reassigning comorbidities to tiers based on their marginal cost because we believe that this reassignment is based on the best comprehensive post-PPS implementation data that are available at this time.

Comment: One commenter recommended that we not reassign any comorbidity codes based on their marginal costs under the premise that there is no concrete evidence of upcoding.

Response: Taking into consideration that we believe that there has been improved coding due to prospective payment based system, the recommendations of RAND's technical expert panel, and the guidance of our Medical Officers, we believe that the comorbidity codes should be assigned based on their marginal costs in order to increase the association between costs and payment.

Final Decision: In summary, we are adopting all of the proposals set forth in the FY 2006 proposed rule (70 FR 30188), with regard to the removal of the list of codes from comorbidity tiers that increase payment, the movement of dialysis patients to tier one, the code V55.0 will no longer be excluded from RIC 15, and comorbidity codes will now be reassigned based on their marginal costs.

C. Changes to the CMGs

Section 1886(j)(2)(C)(i) of the Act requires the Secretary from time to time to adjust the classifications and weighting factors of patients under the IRF PPS to reflect changes in treatment patterns, technology, case mix, number of payment units for which payment is made, and other factors that may affect the relative use of resources. These adjustments shall be made in a manner so that changes in aggregate payments under the classification system are the result of real changes and not the result of changes in coding that are unrelated to real changes in case mix.

In the FY 2006 proposed rule (70 FR 30188, 30196), in accordance with section 1886(j)(2)(C)(i) of the Act and as specified in § 412.620(c) and based on the research conducted by RAND, we proposed to update the CMGs used to classify IRF patients for purposes of establishing payment amounts. We also proposed to update the relative weights associated with the payment groups based on FY 2003 Medicare bill and patient assessment data. We proposed replacing the current unweighted motor score index used to assign patients to CMGs with a weighted motor score index that would improve our ability to accurately predict the costs of caring for IRF patients, as described in detail below. However, we proposed not to change the methodology for computing the cognitive score index.

As described in the August 7, 2001 final rule, we contracted with RAND to analyze IRF data to support our efforts in developing our patient classification system and the IRF PPS. We continued our contract with RAND to support us in developing potential refinements to the classification system and the PPS. As part of this research, we asked RAND to examine possible refinements to the CMGs to identify potential improvements in the alignment between Medicare payments and actual IRF costs. In conducting its research, RAND used a technical expert panel (TEP) made up of experts from industry groups, other government entities, academia, and other interested parties. The technical expert panel reviewed RAND's methodologies and advised RAND on many technical issues.

Several recent developments make significant improvements in the alignment between Medicare payments and actual IRF costs possible. First, when the IRF PPS was implemented in 2002, a new assessment instrument was used to collect patient data, the IRF Patient Assessment Instrument (IRF-PAI). The new instrument contained items that improved the quality of the patient-level information available to researchers.

Second, more recent data are available on a larger patient population. Until now, the design of the IRF PPS was based entirely on 1999 data on Medicare Start Printed Page 47893rehabilitation patients from just a sample of hospitals (the best available data at the time). Now, we have post-PPS data from 2002 and 2003 that describe the entire universe of Medicare-covered rehabilitation patients.

Finally, we believe that improvements in the algorithms that produced the initial CMGs, as described below, should lead to new CMGs that better predict treatment costs in the IRF PPS.

Using the inpatient rehabilitation facility assessment instrument before the PPS, which is commonly referred to as the FIM, and Medicare data from 1998 and 1999, RAND helped us develop the original structure of the IRF PPS. IRFs became subject to the PPS beginning with cost reporting periods starting on or after January 1, 2002. The PPS is based on assigning patients to particular CMGs that are designed to predict the costs of treating particular Medicare patients according to how well they function in four general categories: Transfers, sphincter control, self-care (for example, grooming, eating), and locomotion. Patient functioning is measured according to 18 categories of activity: 13 motor tasks, such as putting on clothing, and 5 cognitive tasks, such as memory. The PPS is intended to align payments to IRFs as closely as possible with the actual costs of treating patients. If the PPS “underpays” for some kinds of care, IRFs have incentives to limit access for patients requiring that kind of care because payments for a particular case would be less than the costs of providing care, so an IRF may try to limit its financial “losses”; conversely, if the PPS overpays, resources are wasted because IRFs' payments exceed the costs of providing care for a particular case.

The fiscal year 2003 data file currently available for refining the CMGs contains many more IRF cases and represents the universe of Medicare-covered IRF cases, rather than a sample. The best available data that CMS and RAND had for analysis in 1999 contained 390,048 IRF cases, representing 64 percent of all Medicare-covered patients in participating IRFs. The more recent data contain 523,338 IRF cases (fiscal year 2003), representing all Medicare-covered patients in participating IRFs. The larger file enables RAND to obtain greater precision in the analysis and portrays a more recent and complete picture of patients under the IRF PPS.

Also, the fiscal year 2003 data include more detailed information about patients' level of functioning. For example, new variables are included in the more recent data that provide further details on patient functioning. Standard bowel and bladder scores on the FIM instrument (used to assess patients before the IRF PPS), for example, measured some combination of the level of assistance required and the frequency of accidents (that is, soiling of clothes and surroundings). New variables on the IRF-PAI instrument measure the level and the frequency separately. Since measures of the level of assistance required and the frequency of accidents contain slightly different information about the expected costliness of an IRF patient, having measures for these two variables separately provides additional information to researchers.

Furthermore, additional optional information is recorded on the health status of patients in the more recent data (for example, shortness of breath, presence of ulcers, inability to balance).

1. Changes for Updating the CMGs

In the FY 2006 proposed rule (70 FR 30188), we proposed to revise the definitions of the CMGs based on regression analysis by RAND of the FY 2003 data. As described in the August 7, 2001 final rule, RAND developed the original list of CMGs using FIM data from 1998 and 1999 (see the FY 2006 proposed rule (70 FR 30188, 30198 through 30202) for a table of the original CMG listing).

Given the availability of more recent, post-PPS data, we asked RAND to examine possible refinements to the CMGs to identify potential improvements in the alignment between Medicare payments and actual IRF costs. In addition to analyzing fiscal year 2003 data, RAND also convened a TEP, made up of researchers from industry, provider organizations, government, and academia, to provide support and guidance through the process of developing possible refinements to the PPS. Members of the TEP reviewed drafts of RAND's reports, offered suggestions for additional analyses, and provided clinicians' views of the importance and significance of various findings.

As we explained in the FY 2006 proposed rule (70 FR 30188), RAND's analysis of the FY 2003 data, along with the support and guidance of the TEP, strongly suggested the need to update the CMGs to better align payments with costs under the IRF PPS. The other option we considered before proposing to update the CMGs with the fiscal year 2003 data was to maintain the same CMG structure but recalculate the relative weights for the current CMGs using the 2003 data. After carefully reviewing the results of RAND's regression analysis, which compared the predictive ability of the CMGs under 3 scenarios (not updating the CMGs or the relative weights, updating only the relative weights and not the CMGs, and updating both the relative weights and the CMGs), as we stated in the FY 2006 proposed rule (70 FR 30188), we believed and continue to believe (based on RAND's analysis) that updating both the relative weights and the CMGs will allow the classification system to do a better job of reflecting changes in treatment patterns, technology, case mix, and other factors which may affect the relative use of resources.

We continue to believe it is appropriate to update both the CMGs and the relative weights at this time because the 2003 data we now have represent a more recent and broader set of data elements. The more recent data include all Medicare-covered IRF cases rather than a subset, allowing us to base the CMG changes on a complete picture of the types of patients in IRFs. In designing the IRF PPS, we used the best available data, but those data may not have contained a complete picture of the types of patients in IRFs. Also, the improved clinical coding of patient conditions in IRFs is better reflected in the more recent data than it was in the best available data we had to design the IRF PPS. In addition, changes in treatment patterns, technology, case mix, and other factors affecting the relative use of resources in IRFs since the IRF PPS was implemented likely require an update to the classification system.

Prior to the finalization of the proposed changes contained in this final rule, we paid IRFs based on 95 CMGs and 5 special CMGs developed using the CART algorithm applied to 1999 data. The CART algorithm that was used in designing the IRF PPS assigned patients to RICs according to their age and their motor and cognitive FIM scores. CART produced the partitions so that the reported wage-adjusted rehabilitation cost of the patients was relatively constant within partitions. Then, a subjective decision-making process was used to decrease the number of CMGs (to ensure that the payment system did not become unduly complicated), to enforce certain constraints on the CMGs (to ensure that, for instance, IRFs were not paid more for patients who had fewer comorbidities than for patients with more comorbidities), and to fit the comorbidity tiers. Although the use of a subjective decision-making process (rather than a computer algorithm) was very useful, there were limitations. For example, it made it difficult to explore Start Printed Page 47894the implications of variations to the CART models because an individual person is not able to examine as many variations of a model in as short a period of time as a computer program. Furthermore, the computer is more efficient at accounting for all of the possible combinations and interactions between important variables that affect patient costs.

In analyzing potential refinements to the IRF PPS, RAND created a new algorithm that would be very useful in constructing the CMGs (the new algorithm would be based on the CART methodology described in detail in section V.A.2.b of this final rule). RAND applied the new algorithm to the fiscal year 2003 IRF data. In the FY 2006 proposed rule (70 FR 30188), we proposed to use RAND's new algorithm for refinements to the CMGs. The algorithm is based entirely on an iterative computerized process to decrease the number of CMGs, enforce constraints on the CMGs, and assign the comorbidity tiers. At each step in the process, the new CART algorithm produces all of the possible combinations of CMGs using all available variables. It then selects the variables and the CMG constructions that offer the best predictive ability, as measured by the greatest decrease in the mean-squared error. We proposed to place the following constraints on the algorithm, based on RAND's analysis: (1) Neighboring CMGs would have to differ by at least $1,500, unless eliminating the CMG would change the estimated costs of patients in that CMG by more than $1,000; (2) estimated costs for patients with lower motor or cognitive index scores (more functionally dependent) would always have to be higher than estimated costs for patients with higher motor or cognitive index scores (less functionally dependent). We believe that the PPS should not pay more for a patient who is less functionally dependent than for one who is more functionally dependent; and (3) each CMG must contain at least 50 observations (for statistical validity).

RAND's technical expert panel, which included representatives from industry groups, other government entities, academia, and other researchers, reviewed and commented on these constraints and the rest of RAND's proposed methodology (developed based on RAND's analysis of the data) for updating the CMGs as RAND developed the improvements to the CART methodology.

The following are the most substantial differences between the CMGs used prior to October 1, 2005 and the proposed new CMGs for FY 2006:

  • Fewer CMGs than before (87 now compared with 95 in the prior system). The 5 special CMGs for very short stay cases and cases in which the patient expires would remain unchanged.
  • The number of CMGs under the RIC for stroke patients (RIC 1) would decrease from 14 to 10.
  • The cognitive index score would affect patient classification in two of the RICs (RICs 1 and 2), whereas it previously affected RICs 1, 2, 5, 8, 12, and 18.
  • A patient's age would now affect assignment for CMGs in RICs 1, 4, and 8, whereas it previously affected assignment for CMGs in RICs 1 and 4.

The primary objective in updating the CMGs is to better align IRF payments with the costs of caring for IRF patients, given more recent information. This requires that we improve the ability of the system to predict patient costs. RAND's analysis suggests that the proposed new CMGs clearly improve the ability of the payment system to predict patient costs. The proposed new CMGs would greatly improve the explanation of variance in the system.

Public comments and our responses on the proposed changes for updating the CMGs are summarized below.

Comment: Several commenters raised concerns that the FY 2003 data used to update the CMGs did not reflect the full enforcement of the 75 percent rule and that CMS should, therefore, wait until the data reflect full enforcement before making any changes to the CMGs.

Response: We agree that additional changes to the CMGs may potentially be necessary in the future if enforcement of the 75 percent rule results in substantial changes to IRFs' patient populations. However, we believe it is now appropriate to begin refining the system because several recent developments make significant improvements in the alignment between Medicare payments and actual IRF costs possible. First, when the IRF PPS was implemented for cost reporting periods beginning on or after January 1, 2002, a new recording instrument called the IRF-PAI was used to collect patient data. The new instrument contained questions that improved the quality of the patient-level information available to researchers. The 2003 data used in the proposed refinements reflects this data.

Second, more recent data are available on a larger patient population. Until now, the design of the IRF PPS was based entirely on 1999 data on Medicare rehabilitation patients from just a sample of hospitals. Even though this was the best available data at the time, we now have post-PPS data from 2002 and 2003 that describe the entire universe of Medicare-covered rehabilitation patients.

Finally, we believe that proposed improvements in the algorithms that produced the initial CMGs, as described above, lead to new CMGs that better predict treatment costs in the IRF PPS.

We further note that making refinements to the IRF patient classification system now, based on post-PPS data, does not preclude us from making future refinements to the system if IRFs' case mix and care practices change over time. We will continue to monitor the IRF PPS, and make refinements as needed, to ensure that IRF payments are aligned as closely as possible with the costs of providing care.

Comment: One commenter believed that the proposed changes to the CMGs would make IRF quality measurement more difficult over time because the proposed changes to the CMG definitions would mean that a case classified into a particular CMG (such as CMG 0107) before October 1, 2005 (when the proposed changes would be implemented) would not necessarily be classified into CMG 0107 after October 1, 2005. Thus, people attempting to create a one-for-one crosswalk between the CMGs before October 1, 2005 and the proposed CMGs after October 1, 2005 would be unable to do so. The commenter noted that many quality measurement tools currently being used by IRFs require such a one-for-one crosswalk.

Response: We recognize the importance of monitoring IRF quality of care over time. However, we do not believe that the proposed changes to the CMGs inhibit the ability to monitor quality in IRFs over time. Quality of care is not measured by a payment rate, but by data reflecting various indicators of the treatment patients receive. In the FY 2006 proposed rule (70 FR 30188), we did not propose changes to the patient assessment form itself or changes to the coding of the underlying data that is used to classify patients into CMGs. Therefore, comparisons of the underlying patient classification data could still be used to monitor quality in these facilities over time.

Comment: One commenter expressed concerns that the cognitive scores are not used as often in the definitions of the proposed revisions to the CMGs as they were in the original CMGs defined in the August 7, 2001 final rule. This commenter stated that the cognitive scores are important predictors of how costly patients are likely to be in the IRF setting. The commenter also stated that, Start Printed Page 47895if cognitive scores are not used as often as motor scores for assigning patients to CMGs, the reason may be that measures of patients' cognitive abilities may not currently be as well developed as measures of patients' motor abilities. Therefore, this commenter recommended that we develop more sensitive measures that have better predictive qualities.

Response: As we noted previously, the cognitive score used to classify IRF patients into CMGs is made up of cognitive items from the IRF-PAI. These cognitive items are generally indications of the patient's mental functioning level, and are related to the patient's ability to process and respond to empirical factual information, use judgment, and accurately perceive what is happening. Patients' cognitive functioning clearly affects their expected costliness in an IRF. However, RAND's regression analysis, in which they explored the relationship of the FIM motor and cognitive scores to cost, showed that patients' cognitive scores generally did not predict patients' expected costliness above and beyond what patients' motor scores already were able to predict. Thus, we see no reason to use cognitive scores in CMG definitions for which they do not add predictive ability. When the cognitive scores add information that increases the predictive ability of the classification system, we make use of this information in the CMG assignment.

We agree with one of the commenter's points that the cognitive score may not predict costs as well as the motor score because the cognitive items may not be as sensitive to patients' cognitive status as the motor items are to patients' physical functioning. We further agree with the commenter that more work could be done to better identify measures of cognitive functioning. Along these lines, CMS has awarded a contract to the Research Triangle Institute (RTI) to perform research and data analysis to support possible changes to the IRF-PAI instrument that would better capture physical and cognitive functioning information on IRF patients. CMS remains open to examining well-constructed peer-reviewed studies by other types of providers, researchers, and other interested parties in order to improve upon the cognitive assessment functioning measures for the Medicare population. Until then, we will use the best cognitive functioning information available for IRF patients to classify patients into the most appropriate CMGs so IRF payments align as closely as possible with the costs of care in IRFs.

Final Decision: After carefully considering all the comments we received on the proposed changes to the CMG definitions, we are finalizing our decision to adopt the CMG definitions presented below in Table 2. Based on RAND's regression analysis of FY 2003 data, the best data available for analysis, we believe these changes will increase the accuracy of IRF PPS payments.

Table 2.—Case Mix Groups (CMGs), With the Associated Rehabilitation Impairment Categories (RICs)

[Beginning with discharges on or after October 1, 2005]

RICCMG No.CMG description
01 Stroke (Stroke)0101Motor >51.05.
0102Motor >44.45 & Motor <51.05 & Cognitive >18.5.
0103Motor >44.45 & Motor <51.05 & Cognitive <18.5.
01 Stroke (Stroke)0104Motor >38.85 & Motor <44.45.
0105Motor >34.25 & Motor <38.85.
0106Motor >30.05 & Motor <34.25.
0107Motor >26.15 & Motor <30.05.
0108Motor <26.15 & Age >84.5.
0109Motor >22.35 & Motor <26.15 & Age <84.5.
0110Motor <22.35 & Age <84.5.
02 Traumatic brain injury (TBI)0201Motor >53.35 & Cognitive >23.5.
0202Motor >44.25 & Motor <53.35 & Cognitive >23.5.
0203Motor >44.25 & Cognitive <23.5.
0204Motor >40.65 & Motor <44.25.
0205Motor >28.75 & Motor <40.65.
0206Motor >22.05 & Motor <28.75.
0207Motor <22.05.
03 Nontraumatic brain injury (NTBI)0301Motor >41.05.
0302Motor >35.05 & Motor <41.05.
0303Motor >26.15 & Motor <35.05.
0304Motor <26.15.
04 Traumatic spinal cord injury (TSCI)0401Motor >48.45.
0402Motor >30.35 & Motor <48.45.
0403Motor >16.05 & Motor <30.35.
0404Motor <16.05 & Age >63.5.
0405Motor <16.05 & Age <63.5.
05 Nontraumatic spinal cord injury (NTSCI)0501Motor >51.35.
05 Nontraumatic spinal cord injury (NTSCI)0502Motor >40.15 & Motor <51.35.
0503Motor >31.25 & Motor <40.15.
0504Motor >29.25 & Motor <31.25.
0505Motor >23.75 & Motor <29.25.
0506Motor <23.75.
06 Neurological (Neuro)0601Motor >47.75.
0602Motor >37.35 & Motor <47.75.
0603Motor >25.85 & Motor <37.35.
0604Motor <25.85.
07 Fracture of LE (FracLE)0701Motor >42.15.
0702Motor >34.15 & Motor <42.15.
0703Motor >28.15 & Motor <34.15.
0704Motor <28.15.
08 Replacement of LE joint (RepLE)0801Motor >49.55.
Start Printed Page 47896
0802Motor >37.05 & Motor <49.55.
0803Motor >28.65 & Motor <37.05 & Age >83.5.
0804Motor >28.65 & Motor <37.05 & Age <83.5.
0805Motor >22.05 & Motor <28.65.
0806Motor <22.05.
09 Other orthopedic(Ortho)0901Motor >44.75.
0902Motor >34.35 & Motor <44.75.
0903Motor >24.15 & Motor <34.35.
0904Motor <24.15.
10 Amputation, lower extremity (AMPLE)1001Motor >47.65.
1002Motor >36.25 & Motor <47.65.
1003Motor <36.25.
11 Amputation, other (AMP-NLE)1101Motor >36.35.
11 Amputation, other (AMP-NLE)1102Motor <36.35.
12 Osteoarthritis (OsteoA)1201Motor >37.65.
1202Motor >30.75 & Motor <37.65.
1203Motor <30.75.
13 Rheumatoid, other arthritis (RheumA)1301Motor >36.35.
1302Motor >26.15 & Motor <36.35.
1303Motor <26.15.
14 Cardiac (Cardiac)1401Motor >48.85.
1402Motor >38.55 & Motor <48.85.
1403Motor >31.15 & Motor <38.55.
1404Motor <31.15.
15 Pulmonary (Pulmonary)1501Motor >49.25.
1502Motor >39.05 & Motor <49.25.
1503Motor >29.15 & Motor <39.05.
1504Motor <29.15.
16 Pain Syndrome (Pain)1601Motor >37.15.
1602Motor >26.75 & Motor <37.15.
1603Motor <26.75.
17 Major multiple trauma, no brain injury or spinal cord injury (MMT-NBSCI)1701Motor >39.25.
1702Motor >31.05 & Motor <39.25.
1703Motor >25.55 & Motor <31.05.
1704Motor <25.55.
18 Major multiple trauma, with brain or spinal cord injury (MMT-BSCI)1801Motor >40.85.
1802Motor >23.05 & Motor <40.85.
1803Motor <23.05.
19 Guillian Barre (GB)1901Motor >35.95.
19 Guillian Barre (GB1902Motor >18.05 & Motor <35.95
1903Motor <18.05.
20 Miscellaneous (Misc)2001Motor >49.15.
2002Motor >38.75 & Motor <49.15.
2003Motor >27.85 & Motor <38.75.
2004Motor <27.85.
21 Burns (Burns)2101Motor >0.
Special CMGs5001Short-stay cases, length of stay is 3 days or fewer.
5101Expired, orthopedic, length of stay is 13 days or fewer.
5102Expired, orthopedic, length of stay is 14 days or more.
5103Expired, not orthopedic, length of stay is 15 days or fewer.
5104Expired, not orthopedic, length of stay is 16 days or more.
Note: CMG definitions use weighted motor scores, as defined below.

2. Use of a Weighted Motor Score Index and Change to the Treatment of Unobserved Transfer to Toilet Values

In the FY 2006 proposed rule (70 FR 30188, 30210), we proposed to use a weighted motor score index in assigning patients to CMGs, instead of the motor score index previously used that treated all components equally. We also proposed to change how the IRF PPS GROUPER software would assign a value for the transfer-to-toilet item when it is coded by the provider with a 0. We proposed that the software would assign this item a value of 2 instead of a 1 when the activity is coded by the provider with a 0. However, we proposed not to change the cognitive score index. As described in detail below, we continue to believe that a weighted motor score index, with the change to the scoring of the transfer to toilet item when the provider records a 0 value for the activity on the IRF-PAI, will improve the classification of patients into CMGs, which in turn will improve the accuracy of payments to IRFs.

To classify a patient into a CMG, IRFs use the admission assessment data from the IRF-PAI to score a patient's functional independence measures. The Start Printed Page 47897functional independence measures consist of what are termed “motor” items and “cognitive” items. In addition to the functional independence measures, the patient's age may also influence the patient's CMG classification. The motor items are generally indications of the patient's physical functioning level. The cognitive items are generally indications of the patient's mental functioning level, and are related to the patient's ability to process and respond to empirical factual information, use judgment, and accurately perceive what is happening. The motor items are eating, grooming, bathing, dressing upper body, dressing lower body, toileting, bladder management, bowel management, transfer to bed/chair/wheelchair, transfer to toilet, transfer to tub or shower, walking or wheelchair use, and stair climbing. The cognitive items are comprehension, expression, social interaction, problem solving, and memory. (The CMS IRF-PAI manual includes more information on these items.) Each item is generally recorded on the IRF-PAI and scored on a scale of 0 to 7, with a 7 indicating complete independence in this area of functioning, a 1 indicating that a patient is very impaired in this area of functioning, and a 0 indicating that the activity did not occur.

As explained in the August 7, 2001 final rule (66 FR 41349), the instructions for the IRF-PAI required that providers record an 8 for an item to indicate that the activity did not occur, as opposed to a 1 through 7 indicating that the activity occurred and the estimated level of function connected with that activity. However, when the IRF-PAI form was finalized, the code 8 had been removed and was replaced with the code 0. Therefore, facilities now record a 0 when an activity does not occur.

To determine the appropriate payment for patients for whom an activity is coded as 0 (that is, the activity did not occur), we needed to decide an appropriate way of changing the 0 to another code for which payment could be assigned. As discussed in the August 7, 2001 final rule (66 FR at 41349), for purposes of classifying patients into CMGs, we decided to assign a code of 1 (indicating that the patient needed “total assistance”) whenever a code of 0 appeared for one of the items on the IRF-PAI used to determine payment. This was the most conservative approach we could have taken based on the best available data at the time because a value of 1 indicates that the patient needed total assistance performing the task. The result of recoding a 0 as a 1 and using that value to classify a patient into a CMG is that the provider might receive a higher payment for that item (although it might not be the highest payment overall, depending on the patient's other functional abilities and/or comorbidities).

In the FY 2006 proposed rule (70 FR 30188), we proposed to change the way we treat a code of 0 on the IRF-PAI for the transfer to toilet item. This is the only item that we proposed to change at this time because RAND's regression analysis demonstrated that, of all the motor score values, the evidence supporting a change in the motor score values was the strongest with respect to this item. We proposed to assign a code of 2, instead of a code of 1, to patients for whom a 0 is recorded on the IRF-PAI for the transfer to toilet item (as discussed below) because RAND's analysis of calendar year 2002 and FY 2003 data indicates that patients for whom a 0 is recorded are more similar in terms of their characteristics and costliness to patients with a recorded score of 2 than to patients with a recorded score of 1. We proposed to make this change to provide the most accurate payment for each patient.

Using regression analysis on the calendar year 2002 and FY 2003 data, which is more complete and provides more detailed information on patients' functional abilities than the FY 1999 data used to construct the IRF PPS (even though the 1999 data were the best available data at the time), RAND analyzed whether the assignment of 1 to items for which a 0 is recorded on the IRF-PAI continues to correctly assign payments based on patients' expected costliness. RAND examined all of the items in the motor score index, focusing on how often a code of 0 appears for the item, how similar patients with a code of 0 are to other patients with the same characteristics that have a score of 1 though 7, and how much a change in the item's score affects the prediction of a patient's expected costliness. Based on RAND's regression analysis, we believed and continue to believe it is appropriate to change the assignment of 0 on the transfer to toilet item from a 1 to a 2 for the purposes of determining IRF payments.

Until now, the IRF PPS has used standard motor and cognitive scores, the sum of either 12 or 13 motor items and the sum of 5 cognitive items, to assign patients to CMGs. This summing equally weights the components of the indices. These indices have been accepted and used for many years. Although the weighted motor score is an option that has been considered before, most experts believed that the data were not complete and accurate enough before the IRF PPS (although they were the most complete and accurate data available at the time). Now, it is believed that the data are complete and accurate enough to support using a weighted motor score index.

In developing candidate indices that would weight the items in the score, RAND had the following competing goals: developing indices that would increase the predictive power of the system while at the same time maintaining simplicity and transparency in the payment system. For example, RAND found that an “optimal” weighting methodology from the standpoint of predictive power would require computing 378 different weights (18 different weights for the motor and cognitive indices that could all differ across 21 RICs). Rather than introduce this level of complexity to the system, RAND decided to explore simpler weighting methodologies that would still increase the predictive power of the system.

RAND used regression analysis to explore the relationship of the FIM motor and cognitive scores to cost. The idea of these models was to determine the impact of each of the FIM items on cost and then weight each item in the index according to its relative impact on cost. Based on the regression analysis, RAND was able to design a weighting methodology for the motor score that could potentially be applied uniformly across all RICs.

RAND assessed different weighting methodologies for both the motor score index and the cognitive score index. They discovered that weighting the motor score index improved the predictive ability of the system, whereas weighting the cognitive score index did not. Furthermore, the cognitive score index has never had much of an effect (in some RICs, it has no effect) on the assignment of patients to CMGs because the motor score tends to be much stronger at predicting a patient's expected costs in an IRF than the cognitive score.

For these reasons, we proposed a weighting methodology for the motor score index. We proposed to continue using the same methodology we have been using since the IRF PPS was first implemented to compute the cognitive score index (that is, summing the components of the index) because, among other things, a change in methodology for calculating this component of the system failed to improve the accuracy of the IRF PPS payments. Therefore, it would be futile to expend resources on changing this Start Printed Page 47898method when it would not benefit the program.

Table 3 below shows the optimal weights from the regression analysis for the components of the motor score, averaged across all RICs and normalized to sum to 100.0, obtained through the regression analysis. The weights relate to the FIM items' relative ability to predict treatment costs. Table 3 indicates that dressing lower, toilet, bathing, and eating are the most effective self-care items for predicting costs; bowel and bladder control may not be effective at predicting costs; and that the items grouped in the transfer and locomotion categories might be somewhat more effective at predicting costs than the other categories.

We are making no changes to Table 3, which was Table 5 in the FY 2006 proposed rule (70 FR 30188, 30211).

Table 3.-Optimal Weights, Averaged Across Rehabilitation Impairment Categories (RICs)

[Motor Items]

Item typeFunctional independence itemAverage optimal weight
SelfDressing lower1.4
SelfToilet1.2
SelfBathing0.9
SelfEating0.6
SelfDressing upper0.2
SelfGrooming0.2
SphincterBladder0.5
SphincterBowel0.2
TransferTransfer to bed2.2
TransferTransfer to toilet1.4
TransferTransfer to tub(1)
LocomotionWalking1.6
LocomotionStairs1.6
1 Not included.

Based on RAND's analysis, we considered a number of different candidate indices before we proposed using a weighted index. We considered defining some simple combinations of the four item types that make up the motor score index and assigning weights to the groups of items instead of to the individual items. For example, we considered summing the three transfer items together to form a group with a weight of two, since they contributed about twice as much in the cost regression as the self-care items. We also considered assigning the self-care items a weight of one and the bladder and bowel items as a group a weight close to zero, since they contributed little to predicting cost in the regression analysis. We tried a number of variations and combinations of this, but RAND's TEP generally rejected these weighting schemes. They believed that introducing elements of subjectivity into the development of the weighting scheme may invite controversy, and that it is better to use an objective algorithm to derive the appropriate weights. We agree that an objective weighting scheme is best because it is based on regression analysis of the amount that various components of the motor score index contribute to predicting patient costs, using the best available data we have. Therefore, we proposed to use a weighting scheme that applies the average optimal weights. To develop the weighting scheme, RAND used regression analysis to estimate the relative contribution of each item to the prediction of costs. Based on this analysis, we proposed the weighting scheme indicated in Table 3 above and in the following simple equation:

Motor score index = 1.4*dressing lower + 1.2*toilet + 0.9*bathing + 0.6*eating + 0.2*dressing upper + 0.2*grooming + 0.5*bladder + 0.2*bowel + 2.2*transfer to bed + 1.4*transfer to toilet + 1.6*walking + 1.6*stairs.

Another reason we proposed to use a weighted motor score index to assign patients to CMGs is that RAND's regression analysis showed that it predicts costs better than the current unweighted motor score index. Across all 21 RICs, the proposed weighted motor score index improves the explanation of variance within each RIC by 9.5 percent, on average.

Public comments and our responses on the proposal to use a weighted motor score index and to change the treatment of unobserved transfer to toilet values are summarized below.

Comment: One commenter suggested that the optimal weights for the bladder and bowel items may be too low because incontinence is the most cited reason patients receive inpatient post-acute care.

Response: We believe that the weights for the bladder and bowel items are appropriate since they were determined based on regression analysis of the effects of these items on the prediction of IRF costs. The purpose of the optimal weights for the proposed weighted motor score index is not to indicate the reasons patients receive inpatient post-acute care but rather to estimate the influence of various motor score items on the expected costs of treating patients in the IRF setting. While we do not disagree that incontinence may be a significant reason that many patients receive post-acute care in an inpatient setting, the optimal weights described above were obtained from RAND's regression analysis of the functional items on patient costs using FY 2003 data.

Comment: Several commenters were concerned that the proposed weighted motor score is complex, creates added costs for providers, will require retraining of staff, is not sensitive to differences among RICs, and that RAND's technical expert panel did not support the weighting methodology.

Response: We proposed a weighted motor score index because RAND's analysis indicates that a weighted motor score index will improve the classification of patients into CMGs, which in turn will improve the accuracy of payments to IRFs.

As we stated earlier, in developing candidate indices that would weight the items in the score, RAND had competing goals: To develop indices that would increase the predictive power of the system while at the same Start Printed Page 47899time maintaining simplicity and transparency in the payment system. For example, they found that an “optimal” weighting methodology from the standpoint of predictive power would require computing 378 different weights (18 different weights for the motor and cognitive indices that could all differ across 21 RICs). Although this would have made the score more sensitive to differences among RICs, as the commenter requested, it would have made the score substantially more complex and less transparent. Thus, we proposed a weighting methodology that balances these two competing goals.

With regard to the commenter's statement regarding the lack of support for the weighting methodology, RAND's technical expert panel generally endorsed the particular weighting methodology we proposed to implement. Furthermore, in the technical expert panel's discussions, participants told RAND that the weighting methodology would not be difficult for providers to implement. They stated that providers typically have software that computes the motor score, and that software would only require slight modifications to accommodate the new weighting methodology. Staff members in IRFs that complete the patient assessments would continue to input the same information they currently do into the software and therefore, in general, staff should not need to be retrained. We are not proposing any changes to how providers code items on the IRF-PAI, only how the information is used to classify patients into CMGs for determining the payment rate. We wish to point out that the weighted motor score for classifying patients into CMGs will be computed automatically by the GROUPER software, not by a clinician. CMS will issue the new GROUPER software at no cost to providers, and the new GROUPER software can be used in the same manner as the old GROUPER software. Thus, the proposed change to the weighted motor score index would not be expected to add to providers' costs. However, CMS will assist providers in any training efforts that may be required to implement the proposed new weighting methodology.

Comment: Two commenters raised concerns regarding the proposed change in assignment of the transfer-to-toilet item. They indicated that this change could artificially elevate the motor score, reduce payments, and have a negative impact on severely ill patients, specifically spinal cord injury patients.

Response: We proposed to assign the transfer-to-toilet item on the IRF-PAI a value of 2, instead of 1, when the provider has recorded a value of 0 (meaning the activity did not occur) because RAND's regression analysis of calendar year 2002 and FY 2003 data indicates that patients for whom a 0 is recorded are more similar in terms of their characteristics and costliness to patients with a recorded score of 2 than to patients with a recorded score of 1. We proposed to make this change in order to provide the most accurate payment for each patient.

We do not believe this proposed change will have a significant effect on payment or on access to care for patients for the following reasons: (1) The transfer-to-toilet item is only 1 of 12 items that make up the motor score index, (2) we are only proposing to change the score on this item by 1 point (which results in a 1.4 increase to the weighted motor score index), and (3) this change will only affect those patients for whom a 0 is recorded for this item (only about 2.8 percent of all IRF cases RAND examined).

Furthermore, the payment for a particular patient with a 0 value for this item would only change if the proposed 1.4 point increase in the motor score index changes the patient's CMG classification. For this to happen, the patient's motor score would have to be within 1.4 points of a CMG boundary. In particular, as the commenter noted the example of spinal cord injury patients, we will use RIC 04 (traumatic spinal cord injury) as an example. The difference in motor scores values that would qualify a patient for CMG 0402 versus CMG 0401 is 18.1 points, and the difference in motor scores values that would qualify a patient for CMG 0403 versus CMG 0402 is 14.3 points. Because these ranges are relatively large, we believe patients will rarely change CMGs as a result of a 1.4 point increase in the motor score index.

We proposed this change in coding of the transfer-to-toilet item because, based on RAND's analysis, we believe this proposed change will improve the accuracy of payments in the IRF PPS. As always, we are concerned that all patients have appropriate access to IRF services. Accordingly, we will monitor the impact of this proposed change and the other proposed changes to the IRF classification system finalized in this final rule to ensure that patients continue to have adequate access to IRF care.

Comment: One commenter was concerned that the weighted motor score might disproportionately affect IRF payments for certain types of patients with certain conditions, such as cognitively impaired patients with significant lower body impairments or with significant dysfunctions in upper body and bladder/bowel problems.

Response: We do not believe the weighted motor score methodology will have a disproportionate affect on any particular groups of patients. RAND's data analysis and RAND's technical expert panel did not raise any concerns regarding any particular groups of patients that would be unduly affected by these changes. We believe that the types of patients the commenter mentioned were included in the data RAND used to determine the optimal weights for the weighted motor score and to calibrate the appropriate payments. The purpose of the proposed weighted motor score, as with all of the proposed changes discussed in this final rule, is to align payments more appropriately with the costs of caring for all types of patients in IRFs. CMS will continue to closely monitor the data to ensure that no groups of patients are disproportionately affected by the change to a weighted motor score index.

Comment: One commenter indicated that CMS, in proposing to implement the weighted motor score, did not seek enough review from experts who developed and researched the FIM items.

Response: As discussed in this final rule under section IV, we contracted with RAND to examine potential refinements to the IRF PPS. RAND sought advice from a technical expert panel, which reviewed their methodology and findings regarding the proposed weighted motor score methodology and generally endorsed the methodology we proposed in the FY 2006 proposed rule (70 FR 30188). RAND's technical expert panel included representatives from industry groups, other government entities, academia, and other researchers, including members with expertise in the FIM items. Thus, we believe RAND sought sufficient review from experts in the field in developing the proposed weighted motor score methodology.

Comment: One commenter requested that CMS remove the transfer to tub item from the IRF-PAI, to reduce the length of the form, because the transfer-to-tub item is not used in classifying patients into CMGs for payment purposes.

Response: We did not propose any changes to the IRF-PAI. However, we will take this comment into consideration in future reviews of the IRF-PAI. We would need to more fully consider the benefits and costs of removing this item from the IRF-PAI form to determine if this change is appropriate. Start Printed Page 47900

Final Decision: After carefully considering all of the comments we received on the proposed weighted motor score methodology, we are finalizing our decision to adopt the methodology as described above. Specifically, the weighted motor score index will be computed using the following equation:

Motor score index = 1.4*dressing lower + 1.2*toilet + 0.9*bathing + 0.6*eating + 0.2*dressing upper + 0.2*grooming + 0.5*bladder + 0.2*bowel + 2.2*transfer to bed + 1.4*transfer to toilet + 1.6*walking + 1.6*stairs.

In addition, we are finalizing our decision to reassign a value of 2 instead of 1 when providers code a 0 for the transfer-to-toilet item on a patient's IRF-PAI. Based on RAND's regression analysis of FY 2003 data, the best data available for analysis, we believe these changes will increase the accuracy of IRF PPS payments.

3. Changes to the Relative Weights

In the FY 2006 proposed rule (70 FR 30188), we proposed to update the relative weights assigned to each CMG. Section 1886(j)(2)(B) of the Act requires that an appropriate relative weight be assigned to each CMG. Relative weights that account for the variance in cost per discharge and resource utilization among payment groups are a primary element of a case-mix adjusted prospective payment system. The accuracy of the relative weights helps to ensure that payments reflect as much as possible the relative costs of IRF patients and, therefore, that beneficiaries have access to care and receive the appropriate services.

Section 1886(j)(2)(C)(i) of the Act requires the Secretary from time to time to adjust the classifications and weighting factors to reflect changes in treatment patterns, technology, case mix, number of payment units for which payment to IRFs is made, and other factors which may affect the relative use of resources. In accordance with this section of the Act, we proposed to recalculate a relative weight for each CMG that is proportional to the resources needed by an average inpatient rehabilitation case in that CMG. For example, cases in a CMG with a relative weight of 2, on average, would cost twice as much as cases in a CMG with a relative weight of 1. We did not propose to change the methodology for calculating the relative weights, as described in the August 7, 2001 final rule (66 FR 41316, 41351 through 41353) and consequently, we only proposed to update the relative weights themselves.

As previously stated, we believe that improved coding of data, the availability of more complete data, and changes to the tier comorbidities and CMGs helped us decide to propose to update the relative weights assigned to the CMGs so that they could continue to accurately represent the differences in costs across CMGs and across tiers. Therefore, we proposed to recalculate the relative weights. However, we proposed no change to the methodology for calculating the relative weights. Instead, we proposed to update the relative weights (the relative weights that are multiplied by the standard payment conversion factor to assign relative payments for each CMG and tier) using the same methodology as described in the August 7, 2001 final rule (66 FR 41316, 41351 through 41353) and as noted previously in section V.C.3 of this final rule, using FY 2003 Medicare billing data. To summarize, we proposed to use the following basic steps to update the relative weights: The first step in calculating the CMG weights is to estimate the effects that comorbidities have on costs. The second step is to adjust the cost of each Medicare discharge (case) to reflect the effects found in the first step. In the third step, the adjusted costs from the second step are used to calculate “relative adjusted weights” in each CMG using the hospital-specific relative value method. The final steps are to calculate the CMG relative weights by modifying the “relative adjusted weight” with the effects of the existence of the comorbidity tiers (explained below) and normalize the weights to 1.

We proposed to make the tier and the CMG changes in such a way that total estimated aggregate payments to IRFs for FY 2006 would be the same with or without the changes (that is, in a budget neutral manner) for the following reasons. First, we believe that the results of RAND's analysis of 2002 and 2003 IRF cost data suggest that additional money does not need to be added to the IRF PPS. RAND's analysis found, for example, that if all IRFs had been paid based on 100 percent of the IRF PPS payment rates throughout all of 2002 (some IRFs were still transitioning to PPS payments during 2002), PPS payments during 2002 would have been 17 percent higher than IRFs' costs. Furthermore, RAND did not find evidence that the overall costliness of patients (average case mix) in IRFs increased substantially in 2002 compared with 1999. As discussed in detail in section VI.A of this final rule, RAND found that real case mix increased by at most 1.5 percent, and may have decreased by as much as 2.4 percent. The available evidence, therefore, suggests that IRF PPS payments, in aggregate, are likely adequate to pay for the types of patients IRFs treat.

The purpose of the CMG and tier changes is to ensure that the existing resources already in the IRF PPS are distributed better among IRFs according to the relative costliness of the types of patient they treat. Section 1886(j)(2)(C)(i) of the Act confers broad statutory authority upon the Secretary to adjust the classification and weighting factors to account for relative resource use. Consistent with that broad statutory authority, we proposed to update the relative weights to more accurately reflect the IRF case mix.

To ensure that total estimated aggregate payments to IRFs do not change, we proposed to apply a factor to the standard payment amount to ensure that estimated aggregate payments due to the proposed changes to the tier comorbidities, the CMGs, the weighted motor score, and the relative weights for FY 2006 are not greater or less than those that would have been made in FY 2006 without the proposed changes. In section VI.B.7 and section VI.B.8 of this final rule, we discuss the methodology and factor we proposed to apply to the standard payment amount.

Public comments and our responses on the proposed changes for updating the relative weights are summarized below.

Comment: Several commenters noted that, in many of the CMGs, the average length of stay has decreased. One commenter suggested that there might have been inconsistencies between the relative weights and the average length of stay values reported in the proposed Table 6 in the FY 2006 proposed rule (70 FR 30188, 30213 through 30219).

Response: RAND's analysis found that the average length of stay in IRFs has decreased substantially in recent years. This decrease is reflected in the average length of stay values for most of the CMGs in the proposed Table 6 in the FY 2006 proposed rule (70 FR 30188, 30213 through 30219). However, with the exception of determining IRF payments in certain transfer cases, the average length of stay does not affect IRF payments. CMS does not require IRFs to treat these average length of stay values as goals or targets for particular cases. IRFs are generally free to treat particular patients for as few or as many days as they deem medically appropriate. We encourage IRFs to admit patients for the length of time that results in the best quality of care for the patient. The Start Printed Page 47901length of stay portion of the proposed Table 6 in the FY 2006 proposed rule (70 FR 30188, 30213 through 30219) is provided for informational purposes only.

The relative weights for each of the CMGs and tiers represent the relative costliness of patients in those CMGs and tiers compared with patients in other CMGs and tiers. The average length of stay for each CMG and tier represents the average number of days patients in that CMG and tier were treated in IRFs, based on the FY 2003 data. IRF PPS payments are determined on a per-discharge basis, meaning that providers are paid a pre-determined payment amount according to that patient's CMG and tier classification, regardless of the number of days the patient is treated in the IRF. The only exceptions to this general policy are for very short-stay cases and for certain transfer cases. Because payments are made on a per-discharge basis, there is not necessarily any correlation between the number of days a patient is treated in the IRF and the payment amount for that patient. If, for example, the relative weight for a particular CMG in tier 1 is higher than the relative weight for that same CMG in the no-comorbidity tier, this means that cases in that CMG in tier 1 are expected to be more costly for the IRF to treat than cases in that CMG in the no-comorbidity tier. The average length of stay for patients in that CMG in tier 1, however, could be lower than the average length of stay of patients in that CMG in the no-comorbidity tier because the treatment for patients in that CMG in tier 1 could be much more intensive for a shorter period of time than the treatment for patients in the no-comorbidity tier, who could require less-intensive treatment over a longer period of time. Thus, the relative weights may not bear a relationship to the length of stay, and the two need not be consistent with each other.

Comment: Several commenters expressed concerns about decreases in the relative weights for certain CMGs, particularly for the stroke and traumatic brain injury CMGs. These commenters stated that, if the relative weights and, consequently, the payment rates for certain CMGs were to decrease, it could potentially lead to reduced access to IRF care for patients in the affected CMGs.

Response: The commenters were not clear as to which CMG weights they were using as a comparison with the proposed FY 2006 relative weights in Table 6 of the FY 2006 proposed rule (70 FR 30188, 30213 through 30219). We believe that the commenter was comparing the proposed FY 2006 relative weights published in the FY 2006 proposed rule (70 FR 30188, 30213 through 30219) to the FY 2005 relative weights published in the July 30, 2004 notice updating the payment rates (69 FR 45721). Because we proposed revised definitions of the CMGs, as described in section V.C.1 of this final rule, the proposed new relative weights for the proposed new CMGs cannot be compared with the FY 2005 relative weights based on the FY 2005 CMG definitions. The types of patients included in each CMG, as defined in Table 4 and Table 6 of the FY 2006 proposed rule (70 FR 30188, 30207 through 30210, 30213 through 30219) are likely not the same patients included in the CMGs under the FY 2005 CMG definitions.

Furthermore, as previously stated, the improved coding of data, the availability of more complete data, proposed changes to the tier comorbidities and CMGs, and changes in IRF cost structures contributed to our decision to propose to update the relative weights assigned to the CMGs so that the weights continue to represent the differences in costs across CMGs and across tiers. For these reasons, we have proposed to recalculate the relative weights to ensure that IRF payments remain aligned as closely as possible with the costs of care. We will continue to monitor beneficiaries' access to IRF care to ensure that the changes to the IRF classification system noted in this final rule do not impede access to IRF care for Medicare beneficiaries in general or for beneficiaries with any particular conditions. In particular, we believe it is important to ensure that stroke patients have appropriate access to rehabilitation services, as this population benefits considerably from receiving prompt rehabilitation care.

Nevertheless, we asked RAND to review the average relative weights for the stroke and traumatic brain injury RICs both under the FY 2005 CMG definitions and under the proposed new CMG definitions. The average relative weights were essentially identical within these two RICs, meaning that providers would use essentially the same relative weight to calculate payments for an “average” stroke patient and an “average” traumatic brain injury patient in FY 2006 as they used to calculate payments for the “average” stroke patient and the “average” traumatic brain injury patient in FY 2005. We believe, based on RAND's regression analysis of FY 2003 data, that the proposed changes to the classification system will improve the alignment of IRF payments with the costs of care and, thereby, improve access to care for IRF patients.

Comment: One commenter stated that if the proposed recalculation of the relative weights were to result in lower payments for some patients and, therefore, were to lead to payments that did not adequately cover treatment costs for those patients, then patients' access to IRF care might suffer. A couple of commenters requested that CMS phase in the proposed changes to the classification system.

Response: We considered proposing a phase in of the proposed changes to the classification system, but we believe a phase in of the changes would have introduced undue complication to the classification system because it would have required individual providers, fiscal intermediaries, and CMS to compute two different sets of CMGs to determine payments.

The intent of the proposed changes to the IRF classification system, including the proposed recalculation of the relative weights, was to ensure that IRF payments are aligned as closely as possible with the costs of care. We believe these proposed revisions will help us to ensure that IRF payments and costs continue to be aligned as appropriately as possible. We will continue to monitor beneficiaries' access to IRF care to ensure that the payment system continues to provide such access to IRF care.

To assist providers in adopting the changes to the classification system we are finalizing in this final rule, we will make the new GROUPER and PRICER software available for download on the CMS Web site as soon as possible and before implementation of the final changes. Furthermore, our analysis of the impacts, detailed in section XII of this final rule, indicate that aggregate effects on provider payments of the proposed changes are expected to be small.

Comment: One commenter noted that the proposed relative weights for the burn CMG (CMG 2101) for tier 1 and tier 2 are the same. The commenter asked whether this could be an error.

Response: This was not an error. The FY 2003 data do not contain enough patients in CMG 2101 in tiers 1 and 2 to estimate precise relative weights for each tier. Accordingly, RAND combined patients in these two tiers to estimate the proposed and final relative weights for both tiers.

Comment: Several commenters requested that CMS make available to the public the patient-level data on CMG assignments, the IRF-PAI data, the MedPAR files, and the cost report data RAND used for their analysis to enable the public to replicate RAND's analysis. Start Printed Page 47902

Response: The data files the commenters requested are generally available (and were generally available during the comment period for the FY 2006 proposed rule) through CMS's standard data distribution systems. Please refer to CMS's Web site at http://www.cms.hhs.gov/​researchers/​statsdata.asp for more information about obtaining data from CMS.

Comment: One commenter asked if CMS could provide the standard deviation information for the average length of stay information listed for each CMG and tier.

Response: We will consider posting this type of information on our Web site.

Comment: One commenter noted the operational challenges, such as the large number of revisions that need to be made to the GROUPER software, of implementing the changes to the IRF classification system that CMS has proposed and further requested that CMS make available the new CMG GROUPER to the public.

Response: We agree with the commenter that the operational issues of implementing the proposed changes to the classification system may be challenging, but we will provide the necessary assistance to ensure a smooth transition to the new tiers and CMGs, the new weighted motor score methodology, and the new relative weights. As is our practice, we will make the new GROUPER and PRICER software available for download on the CMS Web site as soon as possible and prior to implementation of the finalized changes. In addition, we will evaluate whether provider, fiscal intermediary, or regional office training may be required to promote understanding of any final changes and assist in the implementation of such changes. Our foremost goal will be to ensure a smooth implementation of changes because we believe that any final changes to the classification system will improve the accuracy of payments in the IRF PPS.

Comment: Several commenters requested that CMS evaluate the effects of the proposed changes to the IRF classification system after the changes are implemented and propose additional refinements to the classification system in future years, if necessary.

Response: We agree with the commenter that it will be important to evaluate the effects of any changes to the classification system to ensure that IRF payments continue to be aligned as closely as possible with the costs of care. CMS intends to monitor the data carefully to ensure that patients who require inpatient rehabilitation services have adequate access to these services. We will propose refinements if, in the future, we later identify the need to make modifications to the classification system to ensure that IRF payments remain aligned with the costs of care.

Final Decision: After carefully considering all the comments we received on the proposed re-calculation of the relative weights, we are finalizing our proposal to adopt the relative weights presented in Table 4, without change. However, we note that, after reviewing the average length of stay values in response to the comments we received, we have made a slight revision to the methodology for computing the average length of stay values reported in Table 4 to be consistent with the way we presented average length of stay values in the August 7, 2001 final rule (66 FR 41316).

Table 4.—Relative Weights for Case-Mix Groups (CMGs)

CMGCMG description (M = motor, C = cognitive, A = age)Relative weightsAverage length of stay
Tier 1Tier 2Tier 3NoneTier 1Tier 2Tier 3None
0101Stroke M > 51.050.76910.72990.64840.635081199
0102Stroke M > 44.45 and M < 51.05 and C > 18.50.94710.89890.79850.782011151110
0103Stroke M > 44.45 and M < 51.05 and C < 18.51.11621.05940.94110.921714131212
0104Stroke M > 38.85 and M < 44.451.18591.12550.99990.979213141313
0105Stroke M > 34.25 and M < 38.851.42331.35091.20011.175316171515
0106Stroke M > 30.05 and M < 34.251.65671.57241.39691.368018201818
0107Stroke M > 26.15 and M < 30.051.91211.81481.61221.579021232021
0108Stroke M < 26.15 and A > 84.52.21062.09811.86391.825427292424
0109Stroke M > 22.35 and M < 26.15 and A < 84.52.19762.08581.85291.814723262423
0110Stroke M < 22.35 and A < 84.52.62622.49262.21432.168630332828
0201Traumatic brain injury M > 53.35 and C > 23.50.81400.68260.60210.564810998
0202Traumatic brain injury M > 44.25 and M < 53.35 and C > 23.51.04370.87530.77200.72411210119
0203Traumatic brain injury M > 44.25 and C < 23.51.24871.04720.92360.866415151212
0204Traumatic brain injury M > 40.65 and M < 44.251.33561.12010.98790.926715161313
0205Traumatic brain injury M > 28.75 and M < 40.651.63811.37381.21161.136517181615
0206Traumatic brain injury M > 22.05 and M < 28.752.13791.79301.58141.483323222120
0207Traumatic brain injury M < 22.052.76572.31942.04571.918835292625
0301Non-traumatic brain injury M > 41.051.12930.95360.84400.776412121110
0302Non-traumatic brain injury M > 35.05 and M < 41.051.47291.24381.10081.012614161413
0303Non-traumatic brain injury M > 26.15 and M < 35.051.75751.48411.31361.208320191716
0304Non-traumatic brain injury M < 26.152.42212.04531.81031.665131252321
0401Traumatic spinal cord injury M > 48.450.98910.85170.76560.683712121010
0402Traumatic spinal cord injury M > 30.35 and M < 48.451.36401.17461.05580.942819161412
0403Traumatic spinal cord injury M > 16.05 and M < 30.352.37432.04461.83791.641222242322
0404Traumatic spinal cord injury M < 16.05 and A > 63.54.25673.66563.29502.942451463937
0405Traumatic spinal cord injury M < 16.05 and A < 63.53.24772.79672.51392.244932383328
0501Non-traumatic spinal cord injury M > 51.350.77050.64490.56410.50599887
Start Printed Page 47903
0502Non-traumatic spinal cord injury M > 40.15 and M < 51.351.03160.86340.75530.67741312109
0503Non-traumatic spinal cord injury M > 31.25 and M < 40.151.36761.14461.00130.897915151312
0504Non-traumatic spinal cord injury M > 29.25 and M < 31.251.71201.43281.25341.124020191615
0505Non-traumatic spinal cord injury M > 23.75 and M < 29.252.02891.69811.48551.332123221918
0506Non-traumatic spinal cord injury M < 23.752.76072.31062.02121.812629282523
0601Neurological M > 47.750.89650.73310.69660.6493111099
0602Neurological M > 37.35 and M < 47.751.19250.97520.92670.863613131212
0603Neurological M > 25.85 and M < 37.351.52661.24841.18631.105616171515
0604Neurological M < 25.851.95391.59791.51831.415122202019
0701Fracture of lower extremity M > 42.150.90550.77360.72650.65851211109
0702Fracture of lower extremity M > 34.15 and M < 42.151.17571.00440.94320.854913141312
0703Fracture of lower extremity M > 28.15 and M < 34.151.46361.25041.17421.064316171514
0704Fracture of lower extremity M < 28.151.79621.53451.44101.306220201918
0801Replacement of lower extremity joint M > 49.550.65610.55110.51090.45967776
0802Replacement of lower extremity joint M > 37.05 and M < 49.550.85700.71980.66730.6004101098
0803Replacement of lower extremity joint M > 28.65 and M < 37.05 and A > 83.51.27071.06720.98940.890115151312
0804Replacement of lower extremity joint M > 28.65 and M < 37.05 and A < 83.51.10690.92960.86180.775413121110
0805Replacement of lower extremity joint M > 22.05 and M < 28.651.39371.17051.08520.976317161413
0806Replacement of lower extremity joint M < 22.051.67261.40471.30231.171618191715
0901Other orthopedic M > 44.750.84120.76580.68050.60901011109
0902Other orthopedic M > 34.35 and M < 44.751.10541.00630.89420.800213131211
0903Other orthopedic M > 24.15 and M < 34.351.45831.32761.17971.055718191615
0904Other orthopedic M < 24.151.82811.66431.47881.323425232019
1001Amputation, lower extremity M > 47.650.96380.88880.79310.731211111110
1002Amputation, lower extremity M > 36.25 and M < 47.651.27091.17191.04570.964114151413
1003Amputation, lower extremity M < 36.251.78761.64831.47091.356119221918
1101Amputation, non-lower extremity M > 36.351.25441.04960.91890.846214151211
1102Amputation, non-lower extremity M < 36.351.87801.57131.37561.266819191817
1201Osteoarthritis M > 37.651.01840.87940.81060.731711121110
1202Osteoarthritis M > 30.75 and M < 37.651.31811.13831.04920.947015161413
1203Osteoarthritis M < 30.751.62381.40221.29251.166621191716
1301Rheumatoid, other arthritis M > 36.351.03380.96170.83250.735812131110
1302Rheumatoid, other arthritis M > 26.15 and M < 36.351.43241.33251.15341.019515181514
1303Rheumatoid, other arthritis M < 26.151.83081.70321.47431.303222212018
1401Cardiac M > 48.850.81720.73520.63960.580610998
1402Cardiac M > 38.55 and M < 48.851.10340.99260.86360.783912131211
1403Cardiac M > 31.15 and M < 38.551.37351.23561.07500.975916161413
1404Cardiac M < 31.151.74191.56711.36331.237621201816
1501Pulmonary M > 49.250.92220.89950.76870.739711121010
1502Pulmonary M > 39.05 and M < 49.251.16591.13710.97180.935212151212
1503Pulmonary M > 29.15 and M < 39.051.42691.39171.18941.144512171515
1504Pulmonary M < 29.151.88121.83481.56811.508921222018
1601Pain syndrome M > 37.151.00650.85440.77310.69041211109
1602Pain syndrome M > 26.75 and M < 37.151.38101.17241.06070.947315171413
1603Pain syndrome M < 26.751.69881.44211.30481.165319191716
1701Major multiple trauma without brain or spinal cord injury M > 39.251.01020.96340.83230.732112121110
1702Major multiple trauma without brain or spinal cord injury M > 31.05 and M < 39.251.33051.26881.09620.964314161513
1703Major multiple trauma without brain or spinal cord injury M > 25.55 and M < 31.051.58321.50981.30431.147417201716
1704Major multiple trauma without brain or spinal cord injury M < 25.551.98081.88891.63191.435526262120
1801Major multiple trauma with brain or spinal cord injury M > 40.851.21180.98320.82450.728215131210
1802Major multiple trauma with brain or spinal cord injury M > 23.05 and M < 40.851.93851.57281.31901.164920211816
Start Printed Page 47904
1803Major multiple trauma with brain or spinal cord injury M < 23.053.47842.82222.36682.090343333027
1901Guillian Barre M > 35.951.23621.09811.06770.934914131412
1902Guillian Barre M > 18.05 and M < 35.952.31622.05742.00041.751527252423
1903Guillian Barre M < 18.053.34392.97032.88812.528737393133
2001Miscellaneous M > 49.150.87430.73870.66230.6047101098
2002Miscellaneous M > 38.75 and M < 49.151.14480.96720.86710.791712131111
2003Miscellaneous M > 27.85 and M < 38.751.47891.24951.12021.022716161514
2004Miscellaneous M < 27.851.97561.66921.49641.366325222018
2101Burns M > 02.18582.18581.59101.476229241917
5001Short-stay cases, length of stay is 3 days or fewer0.22012
5101Expired, orthopedic, length of stay is 13 days or fewer0.63518
5102Expired, orthopedic, length of stay is 14 days or more1.600222
5103Expired, not orthopedic, length of stay is 15 days or fewer0.72048
5104Expired, not orthopedic, length of stay is 16 days or more1.877124

Based on RAND's regression analysis of FY 2003 data, the best data available for analysis, we believe these changes will increase the accuracy of IRF PPS payments.

VI. FY 2006 Federal Prospective Payment Rates

A. Reduction of the Standard Payment Amount To Account for Coding Changes

In the FY 2006 proposed rule (70 FR 30188), we proposed to reduce the standard payment amount by 1.9 percent to account for coding changes. Section 1886(j)(2)(C)(ii) of the Act requires the Secretary to adjust the per payment unit payment rate for IRF services to eliminate the effect of coding or classification changes that do not reflect real changes in case mix if the Secretary determines that changes in coding or classification of patients have resulted or will result in changes in aggregate payments under the classification system. As described below, in accordance with this section of the Act and based on research conducted by RAND under contract with us, we proposed to reduce the standard payment amount for patients treated in IRFs by 1.9 percent.

We proposed to reduce the standard payment amount by 1.9 percent because RAND's regression analysis of calendar year 2002 data found that payments to IRFs were about $140 million more than expected during 2002 because of changes in the classification of patients in IRFs, and that a portion of this increase in payments was due to coding changes that do not reflect real changes in case mix. If IRF patients have more costly impairments, lower functional status, or more comorbidities, and thus require more resources in the IRF in 2002 than in 1999, we would consider this a real change in case mix. Conversely, if IRF patients have the same impairments, functional status, and comorbidities in 2002 as they did in 1999 but are coded differently resulting in higher payment, we consider this a case mix increase due to coding. We believe that changes in payment amounts should accurately reflect changes in IRFs' patient case mix (that is, the true cost of treating patients), and should not be influenced by changes in coding practices.

Under the IRF PPS, payments for each Medicare rehabilitation patient are determined using a multi-step process. First, a patient is assigned to a particular CMG and a tier based on as many as four patient characteristics at admission: impairment, functional independence, comorbidities, and age. The amount of the payment for each patient is then calculated by taking the standard payment conversion factor ($12,958 in FY 2005) and adjusting it by multiplying by a relative weight, which depends on each patient's CMG and tier assignment.

For example, an 80-year old hip replacement patient with a motor score between 47 and 54 and no comorbidities would be assigned to a particular CMG and tier based on these characteristics. The CMG and tier to which he is assigned would have an associated relative weight, in this case 0.5511 in FY 2005 (69 FR at 45725). This relative weight would be multiplied by the standard payment conversion factor of $12,958 to equal the payment of $7,141 in FY 2005 (0.5511 × $12,958 = $7,141). However, based on the following discussion, we are lowering the standard payment amount by 1.9 percent to account for coding changes, as opposed to real case mix changes, that have increased payments to IRFs.

As described in the August 7, 2001 final rule, we contracted with RAND to analyze IRF data to support our efforts in developing the classification system and the IRF PPS. We have continued our contract with RAND to support us in developing potential refinements to the classification system and the PPS for the FY 2006 proposed rule (70 FR 30188) and this final rule. As part of this research, we asked RAND to examine changes in case mix and coding since the IRF PPS. To examine these changes, RAND compared 2002 data from the first year of implementation of the PPS with the 1999 (pre-PPS) data used to construct the IRF PPS.

RAND's analysis of the 2002 data, as described in more detail below, demonstrates that changes in the types of patients going to IRFs and changes in coding both caused increases in payments to IRFs between 1999 and 2002. The 2002 data are more complete than the 1999 data that were first used to design the IRF PPS because they include all Medicare-covered IRF cases. Although the 1999 data we used in designing the original standard payment rate for the IRF PPS were the best available data we had at the time, they were based on a sample (64 percent) of IRF cases.

In addition, such review was necessary because, as explained below, Start Printed Page 47905we believe that the implementation of the IRF PPS caused important changes in coding. The IRF PPS likely improved the accuracy and consistency of coding across IRFs, because of the educational programs that were implemented in 2001 and 2002 and because items that previously did not affect payments (such as comorbidities) became important factors for determining the PPS payments. Since these items now affect payments, there is greater incentive to code for them. In addition, the IRF PPS changed the instructions for coding some of the FIM items on the IRF-PAI, so that the same patient may have been correctly coded differently in 2002 than in 1999.

Although we believe implementation of the IRF PPS resulted in changes to how the patient assessment data have been coded, implementation of the IRF PPS may have also caused changes in case mix because it increased incentives for IRFs to take patients with greater impairment, lower function, or comorbidities. Under the Tax Equity and Fiscal Responsibility Act of 1982 (TEFRA) (Pub. L. 97-248), IRFs were paid on the basis of Medicare reasonable costs limited by a facility-specific target amount per discharge. IRFs were paid on a per discharge basis without per discharge adjustments being made for the impairments, functional status, or comorbidities of patients. Thus, IRFs had a strong incentive to admit less costly patients to ensure that the costs of treating patients did not exceed their TEFRA payments. Under the IRF PPS, however, IRFs' PPS payments are tied directly to the principle diagnosis and accompanying comorbidities of the patient. Thus, based on the characteristics of the patients (that is, impairments, functional status, and comorbidities), the more costly the patient is expected to be, the higher the PPS payment. Therefore, IRFs may have greater incentives than they had under TEFRA to admit more costly patients.

Thus, in light of these concerns, RAND performed an analysis using IRF Medicare claims data matched with FIM and IRF-PAI data. Comparing 2002 data (post-PPS) with 1999 data (pre-PPS), RAND found that the observed case mix the expected costliness of patients-in IRFs increased by 3.4 percent between the two time periods. Thus, we paid 3.4 percent, or about $140 million, more than expected during 2002 because of changes in the classification of cases in IRFs. However, RAND found little evidence that the patients admitted to IRFs in 2002 had higher resource needs (that is, more impairments, lower functioning, or more comorbidities) than the patients admitted in 1999. In fact, most of the changes in case mix that RAND documented from the acute care hospital records implied that IRF patients should have been less costly to treat in 2002 than in 1999. For example, RAND found a 16 percent decrease in the proportion of patients treated in IRFs following acute hospitalizations for stroke, when it compared the results of the 2002 data with the 1999 data. Stroke patients tend to be relatively more costly than other types of patients for IRFs because they tend to require more intensive services than other types of patients. A decrease in the proportion of stroke patients relative to other types of patients, therefore, would likely contribute to a decrease in the overall expected costliness of IRF patients. RAND also found a 22 percent increase in the proportion of cases treated in IRFs following a lower extremity joint replacement. Lower extremity joint replacement patients tend to be relatively less costly for IRFs than other types of patients because their care needs tend to be less intensive than other types of patients. For this reason, the increase in the proportion of these patients treated in IRFs would suggest a decrease in the overall expected costliness of IRF patients.

We asked RAND to quantify the amount of the case mix change that was due to real case mix change (that is, the extent to which IRF patients had more impairments, lower functioning, or more comorbidities) and the amount that was due to coding. However, while the data permit RAND to observe the total change in expected costliness of patients over time with some precision, estimating the amount of this total change that is real and the amount that is due to coding generally cannot be done with the same level of precision. Therefore, in order to quantify the amounts that were due to real case mix change and the amounts that were due to coding, RAND used two approaches to give a range of estimates within which the correct estimates would logically fall—(1) one that potentially underestimates the amount of real case mix change and overestimates the amount of case mix change due to coding; and (2) one that potentially overestimates real change and underestimates change due to coding. These two approaches give us a range of estimates, which should logically border the actual amount of real case mix and coding change. The first approach uses the following assumptions:

  • Changes over time in characteristics recorded during the acute hospitalizations preceding the inpatient rehabilitation facility stay were real case mix changes (as acute care hospitals had little incentive to change their coding of patients in response to the IRF PPS); and
  • Changes over time in IRF coding that did not correspond with changes in the characteristics recorded during the acute hospitalizations were attributable to changes in IRF coding practices.

To illustrate this point, suppose, for example, that the IRF records showed that there were a greater number of patients with a pulmonary condition in IRFs in 2002 than in 1999. Patients with a pulmonary condition tend to be relatively more costly for IRFs to treat than other types of patients, so an increase in the number of these patients would indicate an increase in the costliness of IRF patients (that is, an increase in IRFs' case mix). However, in 2002 IRFs had a much greater incentive to record if patients had a pulmonary condition than they did in 1999 because they got paid more for this condition in 2002, whereas they did not in 1999. Therefore, it is reasonable to expect that some of the increase in the number of patients with a pulmonary condition was due to the fact that IRFs were recording that condition for patients more frequently, not that there were really more patients of that type (although there may also have been some more patients of that type). To determine the extent to which IRFs may have just been coding that condition more often versus the extent to which there actually may have been more patients with a pulmonary condition going to IRFs than before, RAND looked at the one source of information that we believe was least likely to be influenced by the incentive to code patients with this condition more frequently in the IRF: the acute care hospital record from the stay preceding the IRF stay. We believe that the acute care hospitals are not likely to be influenced by IRF PPS policies that only affect IRF payments (that is, changes in IRF payment policies would not likely result in monetary benefits to the acute care hospitals). Thus, if RAND found a substantial increase in the number of IRF patients with a pulmonary condition in the acute care hospital before going to the IRF, it would be reasonable to assume that more patients with a pulmonary condition were going to IRFs (a real increase in case mix). However, if there was little change in the number of IRF patients with a pulmonary condition in the acute care hospital before going to the IRF, then we believe it is reasonable to assume that a portion of the increase in patients with a pulmonary condition in IRFs was due to the incentives to code more of these patients in the IRFs. Start Printed Page 47906

We believe that this first approach shows that both factors, real case mix change and coding change, contributed to the amount of observed change in 2002, the first IRF PPS rate year. However, these estimates (based on the best available data) do not fully address all of the variables that may have contributed to the change in case mix. For example, the model does not account for the possibility that patients could develop impairments, functional problems, or comorbidities after they leave the acute care hospital (prior to the IRF admission) that would make them more costly when they are in the IRF. We note that the introduction of a new payment system may have interrelated effects on providers as they adapt to new (or perceived) program incentives. Thus, an analysis of first year experience may not be fully representative of providers' behavior under a fully implemented system. In addition, hospital coding practices may change at a different rate in facilities where the IRF is a unit of an acute care hospital compared with freestanding IRF hospitals. Finally, we want to ensure that the rate reduction will not have an adverse effect on beneficiaries' access to IRF care.

For the reasons described above, we believed and continue to believe that we should provide some flexibility to account for the possibility that some of the observed changes may be attributable to other than coding changes. Thus, in determining the amount of the reduction in the standard payment amount, we examined RAND's second approach that recognizes the difficulty of precise measurement of real case mix and coding changes. Using this second approach, RAND developed an analytical procedure that allowed them to distinguish more fully between real case mix change and coding change based on patient characteristics. In part, this second approach involves analyzing some specific examples of coding that we know have changed over time, such as direct indications of improvements in impairment coding, changes in coding instruction for bladder and bowel functioning, and dramatic increases in coding of certain conditions that affect patients' placement into tiers (resulting in higher payments).

Using the two approaches, RAND found that real case mix changes in IRFs over this period ranged from a decrease of 2.4 percent (using the first approach) to an increase of 1.5 percent (using the second approach). This suggests that coding changes accounted for between 1.9 percent (if real case mix increased by 1.5 percent (that is, 3.4 percent minus 1.5 percent)) and 5.8 percent (if real case mix decreased by 2.4 percent (that is, 3.4 percent plus 2.4 percent)) of the increase in aggregate payments for 2002 compared with 1999. Thus, RAND recommended decreasing the standard per discharge payment amount by between 1.9 and 5.8 percent to adjust for the coding changes. We proposed to reduce the standard payment amount by the lower of these two numbers, 1.9 percent, because we believe it is a reasonable estimate for the amount of coding change, based on RAND's analysis of direct indications of coding change. That is, RAND analyzed specific examples of coding that we know have changed over time, such as direct indications of improvements in impairment coding, changes in coding instructions for bladder and bowel functioning, and dramatic increases in coding of certain conditions that affect patients' placement into tiers (resulting in higher payments) in deriving the 1.9 percent estimate.

We considered proposing a reduction to the standard payment amount by an amount up to 5.8 percent because RAND's first approach suggested that coding changes could possibly have been responsible for up to 5.8 percent of the observed increase in IRFs' case mix. Furthermore, a separate analysis by RAND found that if all IRFs had been paid based on 100 percent of the IRF PPS payment rates throughout all of 2002 (some IRFs were still transitioning to PPS payments during 2002), PPS payments during 2002 would have been 17 percent higher than IRFs' costs. This suggests that we could have proposed a reduction greater than 1.9 and up to 5.8 percent.

We decided to propose a reduction of 1.9 percent, the lowest possible amount of change attributable to coding change. The analyses described here are only the first of an ongoing series of studies to evaluate the existence and extent of payment increases due to coding changes. We will continue to review the need for any further reduction in the standard payment amount in subsequent years as part of our overall monitoring and evaluation of the IRF PPS.

Therefore, for FY 2006, we proposed to reduce the standard payment amount by the lowest amount (1.9 percent) attributable to coding changes. We believe this approach, which is supported by RAND's analysis of the data, will adequately adjust for the increased payments to IRFs caused by purely coding changes, but will still provide the flexibility to account for the possibility that some of the observed changes in case mix may be attributed to other than coding changes. Furthermore, we chose to propose a 1.9 percent reduction in the standard payment amount to recognize that IRFs' current cost structures may be changing as they strive to comply with other recent Medicare policy changes, such as the criteria for IRF classification commonly known as the “75 percent rule.”

Public comments and our responses on the proposed reduction of the standard payment amount to account for coding changes are summarized below.

Comment: Several commenters objected to CMS implementing an across the board reduction to payment rates to account for coding changes until the full impact of CMS's recent decision to enforce the 75 percent rule is known. These commenters generally also noted that RAND's analysis was based on 2002 data, which was the year facilities were transitioning to the IRF PPS.

Response: We believe a 1.9 percent reduction to the standard payment amount to account for coding changes is appropriate at this time for the following reasons. First, CMS is required by statute (section 1886(j)(2)(C)(ii) of the Act) to adjust payment rates for IRF services if we find evidence that changes in coding (that do not reflect real changes in case mix) have resulted or will result in changes in aggregate payments under the IRF classification system. As discussed in the proposed rule and above, CMS contracted with RAND to examine changes in case mix and coding since the IRF PPS, using the most current available data. Using regression analysis of calendar year 2002 data, RAND found that payments to IRFs were about $140 million more than expected during 2002 because of changes in the classification of patients in IRFs, and that a portion of this increase in payments was due to coding changes that do not reflect real changes in case mix. Specifically, RAND found that IRF payments were at least 1.9 percent higher because of changes in coding, based on direct indications of coding changes. Thus, we believe we have a responsibility to conform to the requirements of the statute and accordingly adjust payment rates for IRFs.

Second, analyses by RAND and by CMS's Office of the Actuary have both shown high Medicare margins among IRFs since implementation of the IRF PPS. RAND's analysis found that if all IRFs had been paid based on 100 percent of the IRF PPS payment rates throughout all of 2002 (some IRFs were still transitioning to PPS payments during 2002), PPS payments during 2002 would have been 17 percent higher than IRFs' costs. An analysis by CMS's Start Printed Page 47907Office of the Actuary supports these results. Given the evidence of high Medicare margins among IRFs, we believe that a 1.9 percent decrease in rates to account for coding changes will not affect beneficiary access to IRF services because IRFs will continue to be paid adequately to reflect the cost of resources needed to treat Medicare beneficiaries.

Furthermore, we continue to find evidence that enforcement of the 75 percent rule between July 2004 and July 2005 at the 50 percent compliance threshold did not have as large an impact on patients' access to IRF care as some industry analysts contend. At this time, CMS is finding no significant problems regarding access to care in IRFs; to the contrary, the trend is toward increasing utilization in all settings. For example, when we compared calendar years 2003 to 2004, we found that the number of IRF cases increased about 1.2 percent. We do not believe that beneficiary access to rehabilitation care will be unduly affected when IRFs have to meet a compliance threshold of 60 percent for cost reporting periods starting between July 1, 2005 and June 30, 2006. Based on the current available evidence, we do not believe that simultaneously reducing the standard payment amount by 1.9 percent to adjust for coding changes and phasing in enforcement of the 75 percent rule will have an undue effect on beneficiary access to IRF services. However, we will closely monitor the available data to ensure that beneficiaries' access to rehabilitation care is maintained.

Finally, we believe that the fact that 2002 was the year IRFs were transitioning to the IRF PPS further supports the finding that at least 1.9 percent of the payments in that year were due to coding changes and not to real changes in case mix. IRFs had not fully transitioned to the full Federal payment rates in 2002. Therefore, they were likely only beginning to adjust to the new incentives of the IRF PPS and had only begun changing their coding practices. Had the full Federal payment rates for 2002 been fully implemented in 2002, then providers might have changed their coding practices even more than they did in 2002.

Accordingly, RAND was likely only observing the initial provider responses to the new IRF PPS. Because RAND's estimate of the 1.9 percent is based on direct indication of coding changes that occurred in 2002, we believe that the 1.9 percent proposed reduction to the standard payment amount is appropriate at this time. In the future, we will examine later years of data in which providers were fully subject to the IRF PPS and make any necessary adjustments to the standard payment amount as we are required to do by statute to eliminate the effect on payments of coding or classification changes that do not reflect real changes in case mix.

Comment: A few commenters questioned RAND's assumption that characteristics of the patients recorded during the acute hospitalizations preceding the IRF stays are relevant for the condition of those same patients in the IRF stays.

Response: RAND's methodology in which they assumed that patient characteristics recorded during the acute hospitalizations preceding the IRF stays were relevant for the case mix of patients in the IRF stays produced a much higher estimate of the amount of coding change than we proposed to adopt in the FY 2006 proposed rule (70 FR 30188, 30221 though 30222). This methodology suggested a 5.8 percent reduction to the standard payment amount to account for coding change, as discussed above. As explained in the FY 2006 proposed rule (70 FR 30188, 30222), we used the estimate of the amount of coding change from RAND's second approach, which involved analyzing specific examples of coding that we know have changed over time, such as direct indications of improvements in impairment coding, changes in coding instructions for bladder and bowel functioning, and dramatic increases in coding of certain conditions that affect patients' placement into tiers (resulting in higher payments). This second approach produced the 1.9 percent estimate we proposed to use to adjust the standard payment amount.

Comment: One commenter requested that CMS conduct educational efforts for providers that instruct providers on how to code patients appropriately, rather than reducing the standard payment amount by 1.9 percent.

Response: As we discussed earlier in detail in this final rule under section VI.A, we proposed to reduce the standard payment amount by 1.9 percent to account for the effects of coding changes that occurred between 1999 and 2002 that resulted in higher than expected payments to IRFs, beginning in 2002. Section 1886(j)(2)(C)(ii) of the Act requires the Secretary to make such an adjustment to eliminate the effects of coding or classification changes that do not reflect real changes in case mix if the Secretary determines that changes in coding or classification of patients have resulted or will result in changes in aggregate payments under the classification system. RAND's regression analysis of calendar year 2002 data found that payments to IRFs were about $140 million more than expected during 2002 because of changes in the classification of patients in IRFs, and that a portion of this increase was due to coding changes that do not reflect real changes in case mix. Any provider education and training that CMS would conduct now would not revise RAND's finding that, based upon calendar year 2002 data, coding changes occurred that did not reflect real changes in case mix.

However, we agree with the commenter that provider education and training is important so that providers correctly code patients in IRFs. For this reason, CMS conducted extensive provider training in 2002 when the IRF PPS was first implemented, and we will continue to educate providers as to how to code the IRF-PAI items through our IRF-PAI coding help desk. We are open to considering other methods of provider education to encourage accurate provider coding. The primary resource providers should refer to is the IRF-PAI manual when they have questions regarding the correct way to code patients in IRFs. This manual is available on CMS's Web site at http://www.cms.hhs.gov/​providers/​IRFPPS/​IRFPAI-MANUAL040104.asp and is updated regularly. The 1.9 percent reduction adjustment to the standard payment amount is not intended to penalize providers for coding changes, but to reflect the statutory mandate to adjust IRF PPS payments when the Secretary determines that changes in coding or classification of patients have resulted or will result in changes in aggregate payments under the classification system.

Comment: One commenter questioned whether, in doing the analysis described above, RAND accounted for the 1.16 percent behavioral offset adjustment that CMS applied to the initial IRF PPS payment rates in the August 7, 2001 final rule (66 FR 41316).

Response: As explained in detail in RAND's report entitled “Preliminary Analyses of Changes in Coding and Case Mix Under the Inpatient Rehabilitation Facility Prospective Payment System” (available on RAND's Web site at http://www.rand.org/​publications/​TR/​TR213/​), RAND accounted for the 1.16 percent behavioral offset adjustment when they estimated the amount of observed case mix change that was due to real case mix change and the amount that was due to coding change. The range of estimates for the amount of case mix and coding change that RAND developed and that is reported above in this final rule contains an adjustment to Start Printed Page 47908account for this behavioral offset. If RAND had not taken account of the behavioral offset, their estimates of the amount of observed case mix change that was due to coding change would have been larger than noted in both the FY 2006 proposed rule (70 FR 30188) and in this final rule.

Comment: One commenter suggested that the proposed 1.9 percent reduction of the standard payment amount could be implemented without undue hardship for facilities.

Response: We agree with the commenter. RAND estimates that if all IRFs had been paid based on 100 percent of the IRF PPS payment rates throughout all of 2002 (some IRFs were still transitioning to PPS payments during 2002), PPS payments during 2002 would have been 17 percent higher than IRFs' costs. This suggests that IRF payments are likely more than adequate to support this type of adjustment for coding changes.

Final Decision: After carefully considering all the comments we received on the proposed 1.9 percent reduction to the standard payment amount to adjust for coding changes between 1999 and 2002 that did not reflect real changes in case mix and resulted in increases in aggregate payments under the IRF classification system, we are finalizing our proposal to adopt the adjustment described above. In accordance with section 1886(j)(2)(C)(ii) of the Act, and based on RAND's analysis of 2002 data compared with 1999 data, we believe this change is necessary to allow payment amounts to accurately reflect changes in IRFs' patient case mix (that is, the true cost of treating patients), and to ensure that they are not influenced by changes in coding practices.

We are finalizing our methodology for reducing the standard payment amount by 1.9 percent. First, we update the FY 2005 standard payment conversion factor by the estimated FY 2006 market basket of 3.6 percent (estimated for this final rule) to get the standard payment amount for FY 2006 ($12,958*1.036 = $13,425). Next, we multiply the FY 2006 standard payment amount by 0.981, which reduces the standard payment amount by 1.9 percent ($13,425*0.981 = $13,169). In section VI.B.7 of this final rule, we will further adjust the $13,169 by the budget neutrality factors for the wage index and the other final changes outlined in this final rule that will result in the FY 2006 standard payment conversion factor. In section VI.B.7 of this final rule, we provide a step-by-step calculation that results in the FY 2006 standard payment conversion factor.

B. Adjustments To Determine the FY 2006 Standard Payment Conversion Factor

1. Market Basket Used for IRF Market Basket Index

Under the broad authority of section 1886(j)(3)(C) of the Act, the Secretary establishes an increase factor that reflects changes over time in the prices of an appropriate mix of goods and services included in covered IRF services, which is referred to as a market basket index. The market basket needs to include both operating and capital. Thus, although the Secretary is required to develop an increase factor under section 1886(j)(3)(C) of the Act, this provision gives the Secretary discretion in the design of such factor.

The index currently used to update payments for rehabilitation facilities is the excluded hospital including capital market basket. This market basket is based on 1997 Medicare cost report data and includes Medicare-participating rehabilitation (IRF), LTCH, psychiatric (IPF), cancer, and children's hospitals.

We are unable to create a separate market basket specifically for rehabilitation hospitals due to the small number of facilities and the limited data that are provided (for instance, only about 25 percent of rehabilitation facility cost reports reported contract labor cost data for 2002). Since all IRFs are paid under the IRF PPS, nearly all LTCHs are paid under the LTCH PPS, and IPFs for cost reporting periods beginning on or after January 1, 2005 will be paid under the IPF PPS, in the FY 2006 proposed rule (70 FR 30188), we proposed and are finalizing to update payments for rehabilitation facilities using a market basket reflecting the operating and capital cost structures for IRFs, IPFs, and LTCHs, hereafter referred to as the RPL (rehabilitation, psychiatric, long-term care) market basket. As proposed and for this final rule, we are excluding children's and cancer hospitals from the RPL market basket because their payments are based entirely on reasonable costs subject to rate-of-increase limits established under the authority of section 1886(b) of the Act, which is implemented in § 413.40 of the regulations. They are not reimbursed under a prospective payment system. Also, the FY 2002 cost structures for children's and cancer hospitals are noticeably different than the cost structures of the IRFs, IPFs, and LTCHs. The services offered in IRFs, IPFs, and LTCHs are typically more labor-intensive then those offered in cancer and children's hospitals. Therefore, the compensation cost weights for IRFs, IPFs, and LTCHs are larger than those in cancer and children's hospitals. In addition, the depreciation cost weights for IRFs, IPFs, and LTCHs are noticeably smaller than those for children's and cancer hospitals.

In the following discussion, we provide a background on market baskets and describe the methodologies we proposed and are finalizing for purposes of determining the operating and capital portions of the FY 2002-based RPL market basket.

a. Overview of the RPL Market Basket

The RPL market basket is a fixed weight, Laspeyres-type price index that is constructed in three steps. First, a base period is selected (in this case, FY 2002), and total base period expenditures are estimated for a set of mutually exclusive and exhaustive spending categories based upon type of expenditure. Then the proportion of total operating costs that each category represents is determined. These proportions are called cost or expenditure weights. Second, each expenditure category is matched to an appropriate price or wage variable, referred to as a price proxy. In nearly every instance, these price proxies are price levels derived from publicly available statistical series that are published on a consistent schedule, preferably at least on a quarterly basis.

Finally, the expenditure weight for each cost category is multiplied by the level of its respective price proxy for a given period. The sum of these products (that is, the expenditure weights multiplied by their price levels) for all cost categories yields the composite index level of the market basket in a given period. Repeating this step for other periods produces a series of market basket levels over time. Dividing an index level for a given period by an index level for an earlier period produces a rate of growth in the input price index over that time period.

A market basket is described as a fixed-weight index because it answers the question of how much it would cost, at another time, to purchase the same mix of goods and services purchased to provide hospital services in a base period. The effects on total expenditures resulting from changes in the quantity or mix of goods and services (intensity) purchased subsequent to the base period are not measured. In this manner, the market basket measures only the pure price change. Only when the index is rebased would the quantity and intensity effects be captured in the cost weights. Therefore, we rebase the market basket periodically so the cost weights reflect changes in the mix of Start Printed Page 47909goods and services that hospitals purchase (hospital inputs) to furnish patient care between base periods.

The terms rebasing and revising, while often used interchangeably, actually denote different activities. Rebasing means moving the base year for the structure of costs of an input price index (for example, we are shifting the base year cost structure from FY 1997 to FY 2002). Revising means changing data sources, methodology, or price proxies used in the input price index. We are rebasing and revising the market basket used to update the IRF PPS.

b. Methodology for Operating Portion of the RPL Market Basket

As proposed, the operating portion of the FY 2002-based RPL market basket, which is being adopted in this final rule, consists of several major cost categories derived from the FY 2002 Medicare cost reports for IRFs, IPFs, and LTCHs: Wages, drugs, professional liability insurance and a residual. We choose FY 2002 as the base year because we believe this is the most recent, relatively complete year of Medicare cost report data. Due to insufficient Medicare cost report data for IRFs, IPFs, and LTCHs, cost weights for benefits, contract labor, and blood and blood products were developed using the FY 2002-based IPPS market basket (Section IV. Rebasing and Revision of the Hospital Market Baskets IPPS Hospital Rule for FY 2006), which we explain in more detail later in this section. For example, less than 30 percent of IRFs, IPFs, and LTCHs reported benefit cost data in FY 2002. We have noticed an increase in cost data for these expense categories over the last 4 years. The next time we propose to rebase the RPL market basket, there may be sufficient IRFs, IPFs, and LTCHs cost report data to develop the weights for these expenditure categories.

Since the cost weights for the RPL market basket are based on facility costs, as proposed and for this final rule, we are limiting our sample to hospitals with a Medicare average length of stay within a comparable range of the total facility average length of stay. We believe this provides a more accurate reflection of the structure of costs for Medicare treatments. Our goal is to measure cost shares that are reflective of case mix and practice patterns associated with providing services to Medicare beneficiaries.

As proposed, for this final rule, we are using those cost reports for IRFs and LTCHs whose Medicare average length of stay is within 15 percent (that is, 15 percent higher or lower) of the total facility average length of stay for the hospital. This is the same edit applied to the FY 1992 and FY 1997 excluded hospital with capital market baskets. We are using 15 percent because it includes those LTCHs and IRFs whose Medicare LOS is within approximately 5 days of the facility length of stay.

As proposed, for this final rule, we use a less stringent measure of Medicare length of stay for IPFs whose average length of stay is within 30 or 50 percent (depending on the total facility average length of stay) of the total facility length of stay. This less stringent edit allows us to increase our sample size by over 150 reports and produce a cost weight more consistent with the overall facility. The edit we applied to IPFs when developing the FY-1997 based excluded hospital with capital market basket was based on the best available data at the time.

The detailed cost categories under the residual (that is, the remaining portion of the market basket after excluding wages and salaries, drugs, and professional liability cost weights) are derived from the FY 2002-based IPPS market basket and the 1997 Benchmark Input-Output Tables published by the Bureau of Economic Analysis, U.S. Department of Commerce. The FY 2002-based IPPS market basket is developed using FY 2002 Medicare hospital cost reports with the most recent and detailed cost data. The 1997 Benchmark I-O is the most recent, comprehensive source of cost data for all hospitals. Consistent with the proposed rule, cost weights for benefits, contract labor, and blood and blood products for this final rule were derived using the FY 2002-based IPPS market basket. For example, the ratio of the benefit cost weight to the wages and salaries cost weight in the FY 2002-based IPPS market basket was applied to the RPL wages and salaries cost weight to derive a benefit cost weight for the RPL market basket. As proposed and for this final rule, the remaining operating cost categories were derived using the 1997 Benchmark Input-Output Tables aged to 2002 using relative price changes. (The methodology we used to age the data involves applying the annual price changes from the price proxies to the appropriate cost categories. We repeat this practice for each year.) Therefore, this methodology results in roughly 59 percent of the RPL market basket is accounted for by wages, drugs and professional liability insurance data from FY 2002 Medicare cost report data for IRFs, LTCHs, and IPFs.

Table 5 below sets forth the complete FY 2002-based RPL market basket including cost categories, weights, and price proxies. For comparison purposes, the corresponding FY 1997-based excluded hospital with capital market basket is listed as well.

As proposed and for this final rule, wages and salaries are 52.895 percent of total costs for the FY 2002-based RPL market basket compared to 47.335 percent for FY 1997-based excluded hospital with capital market basket. Employee benefits are 12.982 percent for the FY 2002-based RPL market basket compared to 10.244 percent for FY 1997-based excluded hospital with capital market basket. As a result, compensation costs (wages and salaries plus employee benefits) for the FY 2002-based RPL market basket are 65.877 percent of costs compared to 57.579 percent for the FY 1997-based excluded hospital with capital market basket. Of the 8 percentage point difference between the compensation shares, approximately 3 percentage points are due to the new base year (FY 2002 instead of FY 1997), 3 percentage points are due to the revised length of stay edit and the remaining 2 percentage points are due to the exclusion of other hospitals (that is, only including IRFs, IPFs, and LTCHs in the market basket).

Following the table is a summary outlining the choice of the proxies that we proposed and we are finalizing for the operating portion of the RPL market basket. The price proxies for the capital portion are described in more detail in the capital methodology section. (See section III.B.1.c of this rule.)Start Printed Page 47910

Table 5.—FY 2002-Based RPL Market Basket Cost Categories, Weights and Proxies With FY 1997-Based Excluded Hospital With Capital Market Basket Used for Comparison

Expense categoriesFY 1997-based excluded hospital with capital market basketFY 2002-based RPL market basketFY 2002 RPL market basket price proxies
Total100.000100.000
Compensation57.57965.877
Wages and Salaries *47.33552.895ECI—Wages and Salaries, Civilian Hospital Workers.
Employee Benefits *10.24412.982ECI—Benefits, Civilian Hospital Workers.
Professional fees Non-Medical *4.4232.892ECI—Compensation for Professional, Specialty & Technical Workers.
Utilities1.1800.656
Electricity0.7260.351PPI—Commercial Electric Power.
Fuel Oil, Coal, etc.0.2480.108PPI Refined Petroleum Products.
Water and Sewage0.2060.197CPI-U—Water & Sewage Maintenance.
Professional Liability Insurance0.7331.161CMS—Professional Liability Premium Index.
All Other Products and Services27.11719.265
All Other Prod. Products17.91413.323
Pharmaceuticals6.3185.103PPI Prescription Drugs.
Food: Direct Purchase1.1220.873PPI Processed Foods & Feeds.
Food: Contract Service1.0430.620CPI-U Food Away From Home.
Chemicals2.1331.100PPI Industrial Chemicals.
Blood and Blood Products **0.748
Medical Instruments1.7951.014PPI Medical Instruments & Equipment.
Photographic Supplies0.1670.096PPI Photographic Supplies.
Rubber and Plastics1.3661.052PPI Rubber & Plastic Products.
Paper Products1.1101.000PPI Converted Paper & Paperboard Products.
Apparel0.4780.207PPI Apparel.
Machinery and Equipment0.8520.297PPI Machinery & Equipment.
Miscellaneous Products0.7831.963PPI Finished Goods less Food and Energy.
All Other Services9.2035.942
Telephone0.3480.240CPI-U—Telephone Services.
Postage0.7020.682CPI-U—Postage.
All Other: Labor Intensive*4.4532.219ECI—Compensation for Private Service Occupations.
All Other: Non-Labor Intensive3.7002.800CPI-U All Items.
Capital-Related Costs8.96810.149
Depreciation5.5866.186
Fixed Assets3.5034.250Boeckh Institutional Construction: 23 year useful life.
Movable Equipment2.0831.937WPI—Machinery & Equipment: 11 year useful life.
Interest Costs2.6822.775
Non-profit2.2802.081Average yield on domestic municipal bonds (Bond Buyer 20 bonds)—vintage weighted (23 years).
For-profit0.4020.694Average yield on Moody's Aaa bonds—vintage weighted (23 years).
Other Capital-Related Costs0.6991.187CPI-U—Residential Rent.
* Labor-related.
** Blood and blood related products is included in miscellaneous products.
Note: Due to rounding, weights may not sum to total.

Below we provide the proxies that we are using for the FY 2002-based RPL market basket in this final rule. We made no changes to the proposed price proxies in this final rule. With the exception of the Professional Liability proxy, all the price proxies for the operating portion of the RPL market basket are based on Bureau of Labor Statistics (BLS) data and are grouped into one of the following BLS categories:

  • Producer Price Indexes—Producer Price Indexes (PPIs) measure price changes for goods sold in other than retail markets. PPIs are preferable price proxies for goods that hospitals purchase as inputs in producing their outputs because the PPIs would better reflect the prices faced by hospitals. For example, we use a special PPI for prescription drugs, rather than the Consumer Price Index (CPI) for prescription drugs because hospitals generally purchase drugs directly from the wholesaler. The PPIs that we use measure price change at the final stage of production.
  • Consumer Price Indexes—Consumer Price Indexes (CPIs) measure change in the prices of final goods and services bought by the typical consumer. Because they may not represent the price faced by a producer, we used CPIs only if an appropriate PPI was not available, or if the expenditures were more similar to those of retail consumers in general rather than purchases at the wholesale level. For example, the CPI for food purchased away from home is used as a proxy for contracted food services.
  • Employment Cost Indexes—Employment Cost Indexes (ECIs) measure the rate of change in employee wage rates and employer costs for employee benefits per hour worked. These indexes are fixed-weight indexes and strictly measure the change in wage Start Printed Page 47911rates and employee benefits per hour. Appropriately, they are not affected by shifts in employment mix.

We evaluated the price proxies using the criteria of reliability, timeliness, availability, and relevance. Reliability indicates that the index is based on valid statistical methods and has low sampling variability. Timeliness implies that the proxy is published regularly, at least once a quarter. Availability means that the proxy is publicly available. Finally, relevance means that the proxy is applicable and representative of the cost category weight to which it is applied. The CPIs, PPIs, and ECIs selected by us to be used in this regulation meet these criteria.

We note that the proxies are the same as those used for the FY 1997-based excluded hospital with capital market basket. Because these proxies meet our criteria of reliability, timeliness, availability, and relevance, we believe they continue to be the best measure of price changes for the cost categories. For further discussion on the FY 1997-based excluded hospital with capital market basket, see the IPPS final rule (67 FR at 50042), published in the Federal Register on August 1, 2002.

Wages and Salaries

For measuring the price growth in the FY 2002-based RPL market basket, we use the ECI for wages and salaries for civilian hospital workers as the proxy for wages for measuring the price growth of wages in the FY 2002-based RPL market basket.

Employee Benefits

The FY 2002-based RPL market basket uses the ECI for employee benefits for civilian hospital workers.

Nonmedical Professional Fees

The ECI for compensation for professional and technical workers in private industry is applied to this category since it includes occupations such as management and consulting, legal, accounting and engineering services.

Fuel, Oil, and Gasoline

The percentage change in the price of gas fuels as measured by the PPI (Commodity Code #0552) is applied to this component.

Electricity

The percentage change in the price of commercial electric power as measured by the PPI (Commodity Code #0542) is applied to this component.

Water and Sewerage

The percentage change in the price of water and sewage maintenance as measured by the Consumer Price Index (CPI) for all urban consumers (CPI Code # CUUR0000SEHG01) is applied to this component.

Professional Liability Insurance

The FY 2002-based RPL market basket uses the percentage change in the hospital professional liability insurance (PLI) premiums as estimated by the CMS Hospital professional liability index for the proxy of this category. In the FY 1997-based excluded hospital with capital market basket, the same price proxy was used.

We continue to research options for improving our proxy for professional liability insurance. This research includes exploring various options for expanding our current survey, including the identification of another entity that would be willing to work with us to collect more complete and comprehensive data. We are also exploring other options such as third party or industry data that might assist us in creating a more precise measure of PLI premiums. At this time we have not identified a preferred option, therefore, no change is implemented in the proxy in this final rule.

Pharmaceuticals

The percentage change in the price of prescription drugs as measured by the PPI (PPI Code #PPI32541DRX) is used as a proxy for this category. This is a special index produced by BLS and is the same proxy used in the 1997-based excluded hospital with capital market basket.

Food, Direct Purchases

The percentage change in the price of processed foods and feeds as measured by the PPI (Commodity Code #02) is applied to this component.

Food, Contract Services

The percentage change in the price of food purchased away from home as measured by the CPI for all urban consumers (CPI Code #CUUR0000SEFV) is applied to this component.

Chemicals

The percentage change in the price of industrial chemical products as measured by the PPI (Commodity Code #061) is applied to this component. While the chemicals hospital's purchase include industrial as well as other types of chemicals, the industrial chemicals component constitutes the largest proportion by far. Thus, we believe that commodity Code #061 is the appropriate proxy.

Medical Instruments

The percentage change in the price of medical and surgical instruments as measured by the PPI (Commodity Code #1562) is applied to this component.

Photographic Supplies

The percentage change in the price of photographic supplies as measured by the PPI (Commodity Code #1542) is applied to this component.

Rubber and Plastics

The percentage change in the price of rubber and plastic products as measured by the PPI (Commodity Code #07) is applied to this component.

Paper Products

The percentage change in the price of converted paper and paperboard products as measured by the PPI (Commodity Code #0915) is used.

Apparel

The percentage change in the price of apparel as measured by the PPI (Commodity Code #381) is applied to this component.

Machinery and Equipment-

The percentage change in the price of machinery and equipment as measured by the PPI (Commodity Code #11) is applied to this component.

Miscellaneous Products -

The percentage change in the price of all finished goods less food and energy as measured by the PPI (Commodity Code #SOP3500) is applied to this component. Using this index removes the double-counting of food and energy prices, which are captured elsewhere in the market basket. The weight for this cost category is higher than in the 1997-based index because the weight for blood and blood products (1.322) is added to it. In the 1997-based excluded hospital with capital market basket we included a separate cost category for blood and blood products, using the BLS Producer Price Index for blood and derivatives as a price proxy. A review of recent trends in the PPI for blood and derivatives suggests that its movements may not be consistent with the trends in blood costs faced by hospitals. While this proxy did not match exactly with the product hospitals are buying, its trend over time appears to be reflective of the historical price changes of blood purchased by hospitals. However, an apparent divergence in trends in the PPI for blood and derivatives and trends in blood costs faced by hospitals over recent years led us to reevaluate whether the PPI for blood and derivatives was an appropriate measure Start Printed Page 47912of the changing price of blood. As discussed in the FY 2006 proposed rule (70 FR 30188), we ran test market baskets classifying blood in 3 separate cost categories: Blood and blood products, contained within chemicals as was done for the 1992-based excluded hospital with capital market basket, and within miscellaneous products. These categories use as proxies the following PPIs: the PPI for blood and blood products, the PPI for chemicals, and the PPI for finished goods less food and energy, respectively. Of these three proxies, the PPI for finished goods less food and energy moved most like the recent blood cost and price trends. In addition, the impact on the overall market basket by using different proxies for blood was negligible, mostly due to the relatively small weight for blood in the market basket.

Therefore, as proposed, for this final rule, we are using the PPI for finished goods less food and energy for the blood proxy because we believe it would best be able to proxy only price changes rather than nonprice factors such as changes in quantities or required tests associated with blood purchased by hospitals. We will continue to evaluate this proxy for its appropriateness and will explore the development of alternative price indexes to proxy the price changes associated with this cost.

Telephone

The percentage change in the price of telephone services as measured by the CPI for all urban consumers (CPI Code #CUUR0000SEED) is applied to this component.

Postage

The percentage change in the price of postage as measured by the CPI for all urban consumers (CPI Code #CUUR0000SEEC01) is applied to this component.

All Other Services, Labor Intensive-

The percentage change in the ECI for compensation paid to service workers employed in private industry is applied to this component.

All Other Services, Nonlabor Intensive-

The percentage change in the all-items component of the CPI for all urban consumers (CPI Code #CUUR0000SA0) is applied to this component.

c. Methodology for Capital Portion of the RPL Market Basket -

Unlike for the operating costs of the FY 2002-based RPL market basket, we did not have IRFs, IPFs, and LTCHs FY 2002 Medicare cost report data for the capital cost weights, due to a change in the FY 2002 cost reporting requirements. Rather, as was proposed, for this final rule we are using these hospitals' expenditure data for the capital cost categories of depreciation, interest, and other capital expenses for the most recent year available (FY 2001), and aging the data to a FY 2002 base year using relevant price proxies. -

As proposed, for this final rule we calculated weights for the RPL market basket capital costs using the same set of Medicare cost reports used to develop the operating share for IRFs, IPFs, and LTCHs. As proposed, for this final rule the resulting capital weight for the FY 2002 base year is 10.149 percent. This is based on FY 2001 Medicare cost report data for IRFs, IPFs, and LTCHs, aged to FY 2002 using relevant price proxies.

Lease expenses are not a separate cost category in the market basket, but are distributed among the cost categories of depreciation, interest, and other, reflecting the assumption that the underlying cost structure of leases is similar to capital costs in general. We assumed 10 percent of lease expenses are overhead and assigned them to the other capital expenses cost category as overhead. We base this assignment of 10 percent of lease expenses to overhead on the common assumption that overhead is 10 percent of costs. The remaining lease expenses were distributed to the three cost categories based on the weights of depreciation, interest, and other capital expenses not including lease expenses. -

Depreciation contains two subcategories: Building and fixed equipment and movable equipment. As proposed, for this final rule the split between building and fixed equipment and movable equipment was determined using the FY 2001 Medicare cost reports for IRFs, IPFs, and LTCHs. This methodology was also used to compute the 1997-based index (67 FR at 50044). -

As proposed, for this final rule total interest expense cost category is split between the government/nonprofit and for-profit hospitals. The 1997-based excluded hospital with capital market basket allocated 85 percent of the total interest cost weight to the government/nonprofit interest, proxied by average yield on domestic municipal bonds, and 15 percent to for-profit interest, proxied by average yield on Moody's Aaa bonds. -

As proposed, for this final rule we derived the split using the relative FY 2001 Medicare cost report data for IPPS hospitals on interest expenses for the government/nonprofit and for-profit hospitals. Due to insufficient Medicare cost report data for IRFs, IPFs and LTCHs, as proposed and for this final rule, we used the same split used in the IPPS capital input price index, which is 75-25. We believe it is important that this split reflects the latest relative cost structure of interest expenses for hospitals. Therefore, as proposed in the FY 2006 proposed rule (70 FR 30188) we are using a 75-25 split to allocate interest expenses to government/nonprofit and for-profit. See the IPPS Rule for FY 2006, Section IV.D, Capital Input Price Index Section (70 FR 23406). -

Since capital is acquired and paid for over time, capital expenses in any given year are determined by both past and present purchases of physical and financial capital. The vintage-weighted capital index is intended to capture the long-term consumption of capital, using vintage weights for depreciation (physical capital) and interest (financial capital). These vintage weights reflect the purchase patterns of building and fixed equipment and movable equipment over time. Depreciation and interest expenses are determined by the amount of past and current capital purchases. Therefore, as proposed, for this final rule we are using the vintage weights to compute vintage-weighted price changes associated with depreciation and interest expense. -

Vintage weights are an integral part of the FY 2002-based RPL market basket. Capital costs are inherently complicated and are determined by complex capital purchasing decisions, over time, based on such factors as interest rates and debt financing. In addition, capital is depreciated over time instead of being consumed in the same period it is purchased. The capital portion of the FY 2002-based RPL market basket reflects the annual price changes associated with capital costs, and is a useful simplification of the actual capital investment process. By accounting for the vintage nature of capital, we are able to provide an accurate, stable annual measure of price changes. Annual non-vintage price changes for capital are unstable due to the volatility of interest rate changes and, therefore, do not reflect the actual annual price changes for Medicare capital-related costs. The capital component of the FY 2002-based RPL market basket reflects the underlying stability of the capital acquisition process and provide hospitals with the ability to plan for changes in capital payments.-

To calculate the vintage weights for depreciation and interest expenses, we need a time series of capital purchases for building and fixed equipment and movable equipment. We found no single source that provides the best time series of capital purchases by hospitals for all Start Printed Page 47913of the above components of capital purchases. The early Medicare Cost Reports did not have sufficient capital data to meet this need because these data were not required. While the AHA Panel Survey provided a consistent database back to 1963, it did not provide annual capital purchases. The AHA Panel Survey provided a time series of depreciation expenses through 1997 which could be used to infer capital purchases over time. From 1998 to 2001, total hospital depreciation expenses were calculated by multiplying the AHA Annual Survey total hospital expenses by the ratio of depreciation to total hospital expenses from the Medicare cost reports. Beginning in 2001, the AHA Annual survey began collecting depreciation expenses. We hope to be able to use this data in any future rebasings. -

In order to estimate capital purchases from AHA data on depreciation and interest expenses, the expected life for each cost category (building and fixed equipment, movable equipment, and debt instruments) is needed. Due to insufficient Medicare cost report data for IRFs, IPFs and LTCHs, as proposed, for this final rule, we are using FY 2001 Medicare cost reports for IPPS hospitals to determine the expected life of building and fixed equipment and movable equipment. We believe this data source reflects the latest relative cost structure of depreciation expenses for hospitals. The expected life of any piece of equipment can be determined by dividing the value of the asset (excluding fully depreciated assets) by its current year depreciation amount. This calculation yields the estimated useful life of an asset if depreciation were to continue at current year levels, assuming straight-line depreciation. From the FY 2001 Medicare cost reports for IPPS hospitals the expected life of building and fixed equipment was determined to be 23 years, and the expected life of movable equipment was determined to be 11 years.

Between the publication of the June 24, 2005 proposed rule and this final rule, we conducted a further review of the methodology used to derive the useful life of an asset. Based on this brief analysis into the capital cost structures of hospitals, we are not changing the expected life of fixed and moveable assets for the final rule. -

As proposed, for this final rule, we are using the fixed and movable weights derived from FY 2001 Medicare cost reports for IRFs, IPFs and LTCHs to separate the depreciation expenses into annual amounts of building and fixed equipment depreciation and movable equipment depreciation. By multiplying the annual depreciation amounts by the expected life calculations from the FY 2001 Medicare cost reports, year-end asset costs for building and fixed equipment and movable equipment could be determined. We then calculated a time series back to 1963 of annual capital purchases by subtracting the previous year asset costs from the current year asset costs. From this capital purchase time series we were able to calculate the vintage weights for building and fixed equipment, movable equipment, and debt instruments. Each of these sets of vintage weights are explained in detail below. -

As proposed, for this final rule, for building and fixed equipment vintage weights, the real annual capital purchase amounts for building and fixed equipment derived from the AHA Panel Survey were used. The real annual purchase amount was used to capture the actual amount of the physical acquisition, net of the effect of price inflation. This real annual purchase amount for building and fixed equipment was produced by deflating the nominal annual purchase amount by the building and fixed equipment price proxy, the Boeckh Institutional Construction Index. This is the same proxy used for the FY 1997-based excluded hospital with capital market basket. We believe this proxy continues to meet our criteria of reliability, timeliness, availability, and relevance. Since building and fixed equipment has an expected life of 23 years, the vintage weights for building and fixed equipment are deemed to represent the average purchase pattern of building and fixed equipment over 23-year periods. With real building and fixed equipment purchase estimates available back to 1963, sixteen 23-year periods are averaged to determine the average vintage weights for building and fixed equipment that are representative of average building and fixed equipment purchase patterns over time. Vintage weights for each 23-year period are calculated by dividing the real building and fixed capital purchase amount in any given year by the total amount of purchases in the 23-year period. This calculation is done for each year in the 23-year period, and for each of the sixteen 23-year periods. The average of each year across the sixteen 23-year periods is used to determine the 2002 average building and fixed equipment vintage weights.-

As proposed, for this final rule, for movable equipment vintage weights, the real annual capital purchase amounts for movable equipment derived from the AHA Panel Survey were used to capture the actual amount of the physical acquisition, net of price inflation. This real annual purchase amount for movable equipment was calculated by deflating the nominal annual purchase amount by the movable equipment price proxy, the Producer Price Index for Machinery and Equipment. This is the same proxy used for the FY 1997-based excluded hospital with capital market basket. We believe this proxy, which meets our criteria, is the best measure of price changes for this cost category. Since movable equipment has an expected life of 11 years, the vintage weights for movable equipment are deemed to represent the average purchase pattern of movable equipment over 11-year periods. With real movable equipment purchase estimates available back to 1963, twenty-eight 11-year periods are averaged to determine the average vintage weights for movable equipment that are representative of average movable equipment purchase patterns over time. Vintage weights for each 11-year period are calculated by dividing the real movable capital purchase amount for any given year by the total amount of purchases in the 11-year period. This calculation is done for each year in the 11-year period, and for each of the twenty-eight 11-year periods. The average of each year across the twenty-eight 11-year periods is used to determine the FY 2002 average movable equipment vintage weights.-

As proposed, for this final rule, for interest vintage weights, the nominal annual capital purchase amounts for total equipment (building and fixed, and movable) derived from the AHA Panel and Annual Surveys were used. Nominal annual purchase amounts were used to capture the value of the debt instrument. Since hospital debt instruments have an expected life of 23 years, the vintage weights for interest are deemed to represent the average purchase pattern of total equipment over 23-year periods. With nominal total equipment purchase estimates available back to 1963, sixteen 23-year periods are averaged to determine the average vintage weights for interest that are representative of average capital purchase patterns over time. Vintage weights for each 23-year period are calculated by dividing the nominal total capital purchase amount for any given year by the total amount of purchases in the 23-year period. This calculation is done for each year in the 23-year period and for each of the sixteen 23-year periods. The average of the sixteen 23-year periods is used to determine the FY 2002 average interest vintage weights. The vintage weights for the index are presented in Table 6 below.-Start Printed Page 47914

In addition to the price proxies for depreciation and interest costs described above in the vintage weighted capital section, as proposed, for this final rule, we used the CPI-U for Residential Rent as a price proxy for other capital-related costs. The price proxies for each of the capital cost categories are the same as those used for the IPPS final rule (67 FR at 50044) capital input price index.

Table 6.—CMS FY 2002-Based RPL Market Basket Capital Vintage Weights

YearFixed assets (23 year weights)Movable assets (11 year weights)Interest: capital-related (23 year weights)
10.0210.0650.010
20.0220.0710.012
30.0250.0770.014
40.0270.0820.016
50.0290.0860.019
60.0310.0910.023
70.0330.0950.026
80.0350.1000.029
90.0380.1060.033
100.0400.1120.036
110.0420.1170.039
120.0450.043
130.0470.048
140.0490.053
150.0510.056
160.0530.059
170.0560.062
180.0570.064
190.0580.066
200.0600.070
210.0600.071
220.0610.074
230.0610.076
Total1.00001.00001.0000
-

The final FY 2006 update for IRF PPS using the FY 2002-based RPL market basket is 3.6 percent. This is based on Global Insight's 2nd quarter 2005 forecast, incorporating two more quarters of historical data than published in the FY 2006 IRF proposed rule. This includes increases in both the operating section and the capital section. Global Insight, Inc. is a nationally recognized economic and financial forecasting firm that contracts with CMS to forecast the components of the market baskets. Using the current FY 1997-based excluded hospital with capital market basket (66 FR at 41427), Global Insight's second quarter 2005 forecast for FY 2006 is also 3.6 percent. Table 7 below compares the FY 2002-based RPL market basket and the FY 1997-based excluded hospital with capital market basket percent changes. For both the historical and forecasted periods between FY 2000 and FY 2008, the difference between the two market baskets is minor with the exception of FY 2002 where the FY 2002-based RPL market basket increased three tenths of a percentage point higher than the FY 1997-based excluded hospital with capital market basket. This is primarily due to the FY 2002-based RPL market basket having a larger compensation (that is, the sum of wages and salaries and benefits) cost weight than the FY 1997-based index and the price changes associated with compensation costs increasing much faster than the prices of other market basket components. Also contributing is the all other nonlabor intensive cost weight, which is smaller in the FY 2002-based RPL market basket than in the FY 1997-based index, and the slower price changes associated with these costs.

Table 7.—FY 2002-Based RPL Market Basket and FY 1997-Based Excluded Hospital With Capital Market Basket Percent Changes, FY 2000-FY 2008

Fiscal year (FY)Rebased FY 2002-based RPL market basketFY 1997-based excluded hospital market basket with capital
Historical data:
FY 20003.13.1
FY 20014.04.0
FY 20023.93.6
FY 20033.83.7
FY 20043.63.7
Average FYs 2000-20043.73.6
Forecast:
FY 20053.83.9
FY 20063.63.6
FY 20073.23.1
FY 20083.12.9
Start Printed Page 47915
Average FYs 2005-20083.43.4
 Source: Global Insight, Inc. 2nd Qtr 2005, @USMACRO/CNTL0605 @CISSIM/TL0505.SIM.

Comment: One commenter recommended that the current update be increased to reflect the differences between the updates given in FY 2004 and FY 2005 and the final market basket increases. Another commenter recommended that CMS adopt a forecast error adjustment.

Response: There is currently no mechanism for adjusting for forecast error in the IRF PPS. Also, the FY 2005 updates is not based on historical data. The forecast error for FY 2005 will not be available until we publish the 2005q4 forecast (with historical data through 2005q3) version of the market basket. We have been actively working with our contractor to minimize forecast error. The specific details of our analysis are provided in the response to following comment.

Comment: Several commenters requested that CMS review and revise the methodology used to forecast the FY 2006 market basket. They are concerned that the proposed FY 2006 update of 3.1 percent is a dramatic underestimation. One commenter requested that CMS make the calculation of the projected FY 2006 available to the public.

Response: Before we published the FY 2006 proposed rule, we had been actively working with our forecasting firm, Global Insight, Inc. (GII), to improve the forecasting accuracy of the market baskets. GII is a nationally recognized economic and financial forecasting firm that contracts with CMS to forecast the components of the market baskets. Among other services GII provides to CMS, GII calculates projected inflation factors for price proxies using models that take into account sectoral, national, and global economic trends.

Over the last several years, dramatic fluctuations in the price of certain costs have made it difficult to forecast price proxy inflation. The driving force behind a significant portion of this uncertainty has been the instability of energy costs. With our input and consultation, however, GII recently re-evaluated and modified their forecasting models to help improve their forecasting accuracy. Using these improved forecasting models, GII calculated updated inflation factors for the major cost categories in Table 8.

Table 8.—Comparison of the 4 Quarter Moving Average Percent Changes for Several Cost Category Weights Between the FY 2006 Proposed and Final Rules

Expense categoryFY 2002-based cost weightsGII 2004q4 forecast of FY 2006 (Proposed Rule)GII 2005q2 forecast of FY 2006 (Final Rule)
Total—RPL02100.003.13.6
Compensation65.8773.53.9
Utilities0.6560.83.6
Professional Fees2.8923.63.8
Professional Liability Insurance1.1618.45.2
All Other19.2652.53.2
All Other Products13.3232.63.5
All Other Services5.9422.42.6
Capital10.1490.91.1

d. Labor-Related Share

Section 1886(j)(6) of the Act specifies that the Secretary shall adjust the proportion (as estimated by the Secretary from time to time) of rehabilitation facilities' costs which are attributable to wages and wage-related costs, of the prospective payment rates computed under paragraph (3) for area differences in wage levels by a factor (established by the Secretary) reflecting the relative hospital wage level in the geographic area of the rehabilitation facility compared to the national average wage level for such facilities. Not later than October 1, 2001 (and at least every 36 months thereafter), the Secretary shall update the factor under the preceding sentence on the basis of information available to the Secretary (and updated as appropriate) of the wages and wage-related costs incurred in furnishing rehabilitation services. Any adjustments or updates made under this paragraph for a fiscal year shall be made in a manner that assures that the aggregated payments under this subsection in the fiscal year shall be made in a manner that assures that the aggregated payments under this subsection in the fiscal year are not greater or less than those that would have been made in the year without such adjustment.

The labor-related share is determined by identifying the national average proportion of operating costs that are related to, influenced by, or vary with the local labor market. Using our current definition of labor-related, the labor-related share is the sum of the relative importance of wages and salaries, fringe benefits, professional fees, labor-intensive services, and a portion of the capital share from an appropriate market basket. As proposed, for this final rule, we are using the FY 2002-based RPL market basket costs to determine the labor-related share for the IRF PPS. The labor-related share for FY 2006 is the sum of the FY 2006 relative importance of each labor-related cost category, and reflects the different rates of price change for these cost categories between the base year (FY 2002) and FY 2006. For this final rule, we are revising the labor-related share to reflect Global Insight's second quarter 2005 forecast, incorporating two more quarters of Start Printed Page 47916historical data than published in the FY 2006 IRF proposed rule. Thus, for this final rule, the sum of the relative importance for FY 2006 for operating costs (wages and salaries, employee benefits, professional fees, and labor-intensive services) is 71.708 percent, as shown in the chart below. The portion of capital that is influenced by local labor markets is estimated to be 46 percent, which is the same percentage currently used in the IRF prospective payment system. Since the relative importance for capital is 9.037 percent of the FY 2002-based RPL market basket in FY 2006, we took 46 percent of 9.037 percent to determine the capital labor-related share for FY 2006. The result is 4.157 percent, which we add to 71.708 percent for the operating cost amount to determine the total labor-related share for FY 2006. Thus, the labor-related share that we are using for IRF PPS in FY 2006 is 75.865 percent. This labor-related share is determined using the same methodology as employed in calculating all previous IRF labor-related shares (66 FR at 41357).

Table 9 below shows the final FY 2006 relative importance labor-related share using the 2002-based RPL market basket and the labor-related share using the FY 1997-based excluded hospital with capital market.

Table 9.—Total Labor-Related Share

Cost categoryFY 2002-based RPL market basket relative importance (percent) FY 2006FY 1997 excluded hospital with capital market basket relative importance (percent) FY 2006
Wages and salaries52.59248.185
Employee benefits14.02811.542
Professional fees2.9214.558
All other labor intensive services2.1674.450
Subtotal71.70868.735
Labor-related share of capital costs4.1573.289
Total75.86572.024

Public comments that we received are summarized below.

Comment: Several commenters objected to our proposal to change the labor-related share to 75.958 percent. One commenter suggested CMS maintain the FY 2005 labor-related share of 72.359 percent until CMS can develop an IRF-specific wage index. Another commenter stated there is no precedent to change the labor-related share. Another commenter requested that if CMS implemented a change in the LRS, they request a transition where the transitional labor-related share would be composed of 80 percent of the current labor-related share and 20 percent of the proposed labor-related share.

Response: Identical to previous updates, the labor-related share is calculated as the sum of the relative importance of those costs that are related to, influenced by, or vary with the local labor market. Specifically, the FY 2006 labor related share is equal to the relative importance of wages and salaries, fringe benefits, professional fees, labor-intensive services, and a portion of the capital share from the RPL market basket.

We calculate the labor-related relative importance for FY 2006 in four steps. First, we compute the FY 2006 price index level for the total market basket and each cost category of the market basket. Second, we calculate a ratio for each cost category by dividing the FY 2006 price index level for that cost category by the total market basket price index level. Third, we determine the FY 2006 relative importance for each cost category by multiplying this ratio by the base year (FY 2002) weight. Finally, we sum the FY 2006 relative importance for each of the labor-related cost categories (wages and salaries, employee benefits, nonmedical professional fees, labor-intensive services, and capital-related expenses) to produce the FY 2006 labor-related relative importance.

The price proxies that move the different cost categories in the market basket do not necessarily change at the same rate, and the relative importance captures these changes. Accordingly, the relative importance figure more closely reflects the cost share weights for FY 2006 when compared to the base year weights from the RPL market basket. Thus, the LRS has been and should be revised with each fiscal year update.

CMS disagrees with the commenter's suggestion to transition from the FY 2005 to the FY 2006 labor-related share. We note the FY 2006 labor-related share is based on the same methodology used to calculate the FY 2005 labor-related share (that is, it is composed of the costs that are related to, influenced by, or vary with the local labor market). Furthermore, the FY 2006 labor-related share is based on the 2002-based RPL market basket, which we believe adequately reflects the current cost structures of Medicare-participating IRFs. Therefore, we do not believe a transition is necessary.

Comment: Several commenters suggested that we include professional liability insurance (PLI) in the labor-related share since these costs are included in the wage index. The commenters also claim that professional liability insurance costs are wage-related.

Response: The wage index includes, as a fringe benefit cost, PLI for those policies that list actual names or specific titles of covered employees (59 FR 45358). The benefit cost weight in the market basket, included in the labor-related share, is also based on the same wage index benefit data. Therefore, the labor-related share includes these PLI costs. General PLI coverage maintained by hospitals is not recognized as a wage-related cost for purposes of the wage index or labor-related share.

Although general PLI costs do vary by geographic region, this variance is primarily influenced by state legislation and risk level, not by local wage rates. In fact, areas with high wage indices may have low relative PLI costs. For example, the malpractice geographic price indices, used in the Medicare physician payment system, for San Francisco, Los Angeles, and Boston regions are below 1, while their hospital wage indices for comparable areas are much greater than 1.

Comment: Several commenters recommended CMS delay the implementation of the RPL market Start Printed Page 47917basket until CMS has reviewed the accuracy of the cost report data. Specifically, they requested CMS investigate HealthSouth's claim to have omitted home office and some depreciation costs from their 2002 and 2003 Medicare cost reports.

Response: The FY 2006 market basket update is based on the RPL market basket using FY 2002 Medicare cost report data. CMS has determined that, in the absence of FY 2002 HealthSouth home office cost report data, we will not incorporate preliminary FY 2004 HealthSouth home office costs into the 2002-based RPL market basket. (Due to a change in Medicare cost report requirements beginning with FY 2002, we used FY 2001 capital costs aged to FY 2002 in the 2002-based RPL market basket. Therefore, HealthSouth's depreciation costs were included in the RPL market basket and reflected in the FY 2006 market basket update.)

Home office costs represent only one of many cost categories (including but not limited to salaries, benefits, professional liability insurance, and pharmaceuticals) that are used to develop the cost category weights. We believe the absence of HealthSouth home office costs in this market basket has a minor impact on the distribution of these weights and, by extension, the final market basket update itself. When CMS receives full FY 2004 Medicare cost report data from HealthSouth, we plan to re-evaluate this decision.

Final Decision: We are finalizing our decision to update payments for rehabilitation facilities using the RPL market basket reflecting the operating and capital cost structures for IRFs, IPFs, and LTCHs.

2. Area Wage Adjustment

Section 1886(j)(6) of the Act requires the Secretary to adjust the proportion (as estimated by the Secretary from time to time) of rehabilitation facilities' costs that are attributable to wages and wage-related costs by a factor (established by the Secretary) reflecting the relative hospital wage level in the geographic area of the rehabilitation facility compared to the national average wage level for those facilities. Not later than October 1, 2001 and at least every 36 months thereafter, the Secretary is required to update the factor under the preceding sentence on the basis of information available to the Secretary (and updated as appropriate) of the wages and wage-related costs incurred in furnishing rehabilitation services. Any adjustments or updates made under section 1886(j)(6) of the Act for a FY shall be made in a manner that assures the aggregated payments under section 1886(j)(6) of the Act are not greater or less than those that will have been made in the year without such adjustment.

In our August 1, 2003 final rule (68 FR 45674), we acknowledged that on June 6, 2003, the Office of Management and Budget (OMB) issued “OMB Bulletin No. 03-04,” announcing revised definitions of Metropolitan Statistical Areas, and new definitions of Micropolitan Statistical Areas and Combined Statistical Areas. A copy of the Bulletin may be obtained at the following Internet address: http://www.whitehouse.gov/​omb/​bulletins/​b03-04.html. At that time, we did not propose to apply these new definitions known as the Core-Based Statistical Areas (CBSAs). After further analysis and discussed in detail in section VI.B.2.d, we proposed to revised labor market area definitions as a result of the OMB revised definitions to adjust the FY 2006 IRF PPS payment rate. In addition, the IPPS is applying these revised definitions as discussed in the August 11, 2004 final rule (69 FR at 49207). We will adopt the CBSA-based geographic classifications as proposed in the FY 2006 IRF PPS proposed rule (70 FR 30188) and described below in section VI.B.2.d and section VI.B.2.e.

a. Revisions to the IRF PPS Geographic Classification

As discussed in the August 7, 2001 final rule, which implemented the IRF PPS (66 FR at 41316), in establishing an adjustment for area wage levels under § 412.624(e)(1), the labor-related portion of an IRF's Federal prospective payment is adjusted by using an appropriate wage index. As set forth in § 412.624(e)(1), an IRF's wage index is determined based on the location of the IRF in an urban or rural area as defined in §412.602 and further defined in § 412.62(f)(1)(ii) and § 412.62(f)(1)(iii) as urban and rural areas, respectively. An urban area, under the IRF PPS, is defined in § 412.62(f)(1)(ii) as a Metropolitan Statistical Area (MSA) or New England County Metropolitan Area (NECMA) as defined by the Office of Management and Budget (OMB). Under § 412.62(f)(1)(iii), a rural area is defined as any area outside of an urban area. In general, an urban area is defined as a Metropolitan Statistical Area (MSA) or New England County Metropolitan Area (NECMA) as defined by the Office of Management and Budget. Under § 412.62(f)(1)(iii), a rural area is defined as any area outside of an urban area. The urban and rural area geographic classifications defined in § 412.62(f)(1)(ii) and (f)(1)(iii), respectively, were used under the IPPS from FYs 1985 through 2004 (as specified in § 412.63(b)), and have been used under the IRF PPS since it was implemented for cost reporting periods beginning on or after January 1, 2002.

The wage index used for the IRF PPS is calculated by using the acute care IPPS wage index data on the basis of the labor market area in which the acute care hospital is located, but without taking into account geographic reclassification under sections 1886(d)(8) and (d)(10) of the Act commonly referred to as “pre-reclassification”. In addition, Section 4410 of Pub. L. 105-33 (BBA) provides that for the purposes of section 1886(d)(3)(E) of the Act, that the area wage index applicable to hospitals located in an urban area of a State may not be less than the area wage index applicable to hospitals located in rural areas in the State. Consistent with past IRF policy, we treat this provision, commonly referred to as the “rural floor”, as applicable to the acute inpatient hospitals and not IRFs. Therefore, the hospital wage index used for IRFs is commonly referred to as “pre-floor” indicating that the “rural floor” provision is not applied. As a result, the applicable IRF wage index value is assigned to the IRF on the basis of the labor market area in which the IRF is geographically located.

In the FY 2006 IRF PPS proposed rule (70 FR 30188, 30235), we described the labor markets that have been used for area wage adjustments under the IRF PPS since its implementation of cost reporting periods beginning on or after January 1, 2002. Previously, we have not described the labor market areas used under the IRF PPS in detail. However, we published each area's wage index in the IRF PPS final rules and update notices, each year and noted the use of the geographic area in applying the wage index adjustment in the IRF PPS payment examples in the final regulation implementing the IRF PPS (69 FR 41316, 41367 through 41368). The IRF industry has also understood that the same labor market areas in use under the IPPS (from the time the IRF PPS was implemented, for cost reporting periods beginning on or after January 1, 2002) are used under the IRF PPS. The OMB adopted new statistical area definitions (70 FR 30188, 30235-30238) and we proposed to adopt the new labor market area definitions based on these areas under the IRF PPS. Therefore, we are providing a more detailed description of the current IRF PPS labor market areas in this final rule, in order for the public to better understand the change to the IRF PPS labor market areas. Start Printed Page 47918

The current IRF PPS labor market areas are defined based on the definitions of MSAs, Primary MSAs (PMSAs), and NECMAs issued by the OMB (commonly referred to collectively as “MSAs”). These MSA definitions are used before October 1, 2005, under the IRF PPS and other prospective payment systems, such as LTCH, IPF, Home Health Agency (HHA), and SNF (Skilled Nursing Facility) PPSs. In the IPPS final rule (67 FR at 49026 through 49034), revised labor market area definitions were adopted under the hospital IPPS (§ 412.64(b)), which are effective October 1, 2004 for acute care hospitals. These new CBSA standards were announced by the OMB late in 2000.

b. Current IRF PPS Labor Market Areas Based on MSAs

As mentioned earlier, since the implementation of the IRF PPS in the August 7, 2001 IRF PPS final rule, we used labor market areas to further characterize urban and rural areas as determined under § 412.602 and further defined in § 412.62(f)(1)(ii) and (f)(1)(iii) for discharges before October 1, 2005. We defined labor market areas under the IRF PPS based on the definitions of MSAs, PMSAs, and NECMAs issued by the OMB, which is consistent with the IPPS approach. The OMB also designates Consolidated MSAs (CMSAs). A CMSA is a metropolitan area with a population of 1 million or more, comprising two or more PMSAs (identified by their separate economic and social character). For purposes of the wage index, we use the PMSAs rather than CMSAs because they allow a more precise breakdown of labor costs (as described in section VI.B.2.d.ii of this final rule). If a metropolitan area is not designated as part of a PMSA, we use the applicable MSA. -

These different designations use counties as the building blocks upon which they are based. Therefore, IRFs are assigned to either an MSA, PMSA, or NECMA based on whether the county in which the IRF is located is part of that area. All of the counties in a State outside a designated MSA, PMSA, or NECMA are designated as rural. For the purposes of calculating the wage index, we combine all of the counties in a State outside a designated MSA, PMSA, or NECMA together to calculate the statewide rural wage index for each State.

c. Core-Based Statistical Areas (CBSAs)

OMB reviews its Metropolitan Area definitions preceding each decennial census. As discussed in the IPPS final rule (69 FR at 49027), in the fall of 1998, OMB chartered the Metropolitan Area Standards Review Committee to examine the Metropolitan Area standards and develop recommendations for possible changes to those standards. Three notices related to the review of the standards, providing an opportunity for public comment on the recommendations of the Committee, were published in the Federal Register on the following dates: December 21, 1998 (63 FR at 70526); October 20, 1999 (64 FR at 56628); and August 22, 2000 (65 FR at 51060).

In the December 27, 2000 Federal Register (65 FR at 82228 through 82238), OMB announced its new standards. In that notice, OMB defines CBSA, beginning in 2003, as “a geographic entity associated with at least one core of 10,000 or more population, plus adjacent territory that has a high degree of social and economic integration with the core as measured by commuting ties.” The standards designate and define two categories of CBSAs: MSAs and Micropolitan Statistical Areas (65 FR at 82235 through 82238).

According to OMB, MSAs are based on urbanized areas of 50,000 or more population, and Micropolitan Statistical Areas (referred to in this discussion as Micropolitan Areas) are based on urban clusters of at least 10,000 population, but less than 50,000 population. Counties that do not fall within CBSAs (either MSAs or Micropolitan Areas) are deemed “Outside CBSAs.” In the past, OMB defined MSAs around areas with a minimum core population of 50,000, and smaller areas were “Outside MSAs.” On June 6, 2003, OMB announced the new CBSAs, comprised of MSAs and the new Micropolitan Areas based on Census 2000 data. (A copy of the announcement may be obtained at the following Internet address: http://www.whitehouse.gov/​omb/​bulletins/​fy04/​b04-03.html.)

The new CBSA designations recognize 49 new MSAs and 565 new Micropolitan Areas, and revise the composition of many of the existing MSAs. There are 1,090 counties in MSAs under the new CBSA designations (previously, there were 848 counties in MSAs). Of these 1,090 counties, 737 are in the same MSA as they were prior to the change in designations, 65 are in a different MSA, and 288 were not previously designated to any MSA. There are 674 counties in Micropolitan Areas. Of these, 41 were previously in an MSA, while 633 were not previously designated to an MSA. There are five counties that previously were designated to an MSA but are no longer designated to either an MSA or a new Micropolitan Area: Carter County, KY; St. James Parish, LA; Kane County, UT; Culpepper County, VA; and King George County, VA. For a more detailed discussion of the conceptual basis of the new CBSAs, refer to the IPPS final rule (67 FR at 49026 through 49034).

d. Revisions to the IRF PPS Labor Market Areas

In its June 6, 2003 announcement, OMB cautioned that these new definitions “should not be used to develop and implement Federal, State, and local non-statistical programs and policies without full consideration of the effects of using these definitions for such purposes. These areas should not serve as a general-purpose geographic framework for non-statistical activities, and they may or may not be suitable for use in program funding formulas.”

We currently use MSAs to define labor market areas for purposes of the wage index. In fact, MSAs are also used to define labor market areas for purposes of the wage index for many of the other Medicare prospective payment systems (for example, LTCH, SNF, HHA, IPF, and Outpatient). While we recognize MSAs are not designed specifically to define labor market areas, we believe they represent a reasonable and appropriate proxy for this purpose, because they are based upon characteristics we believe also generally reflect the characteristics of unified labor market areas. For example, CBSAs reflect a core population plus an adjacent territory that reflects a high degree of social and economic integration. This integration is measured by commuting ties, thus demonstrating that these areas may draw workers from the same general areas. In addition, the most recent CBSAs reflect the most up-to-date information. The OMB reviews its Metropolitan Area (MA) definitions preceding each decennial census to reflect recent population changes and the CBSAs are based on the Census 2000 data. Thus, we proposed to adopt the new CBSA designations to define labor market areas for the purposes of the IRF PPS.

Historically, Medicare PPSs have utilized MA definitions developed by OMB. The labor market areas currently used under the IRF PPS are based on the MA definitions issued by OMB. OMB reviews its MA definitions preceding each decennial census to reflect more recent population changes. Thus, the CBSAs are OMB's latest MA definitions based on the Census 2000 data. Because we believe that the OMB's latest MA designations more accurately reflect the local economies and wage levels of the areas in which hospitals are currently located, we proposed to adopt the Start Printed Page 47919revised labor market area designations based on the OMB's CBSA designations.

As specified in § 412.624(e)(1), we explained in the August 7, 2001 final rule that the IRF PPS wage index adjustment was intended to reflect the relative hospital wage levels in the geographic area of the hospital as compared to the national average hospital wage level. Since OMB's CBSA designations are based on Census 2000 data and reflect the most recent available geographic classifications, we will adopt the labor market area definitions used under the IRF PPS as proposed in the FY 2006 IRF PPS proposed rule (70 FR 30188). Specifically, we will revise the IRF PPS labor market definitions based on the OMB's new CBSA designations effective for IRF PPS discharges occurring on or after October 1, 2005. Accordingly, we will revise § 412.602 to specify that for discharges occurring on or after October 1, 2005, the application of the wage index under the IRF PPS will be made on the basis of the location of the facility in an urban or rural area as defined in § 412.64(b)(1)(ii)(A) through (C) as proposed in the FY 2006 IRF PPS proposed rule (70 FR 30188).

As a conforming change, we will revise § 412.602, definitions for rural and urban areas effective for discharges occurring on or after October 1, 2005 will be defined in § 412.64(b)(1)(ii)(A) through (C) as proposed in the FY 2006 IRF PPS proposed rule (70 FR 30188) and adopted in this final rule. In addition (as proposed in the FY 2006 IRF PPS proposed rule at 70 FR 30188), we will revise the regulation text to explicitly reference urban and rural definitions for a cost-reporting period beginning on or after January 1, 2002, with respect to discharges occurring during the period covered by such cost reports but before October 1, 2005 under § 412.62(f)(1)(ii) and § 412.62(f)(1)(iii).

We note that these are the same labor market area definitions (based on the OMB's new CBSA-based designations) implemented under the IPPS at § 412.64(b), which are effective for those hospitals beginning October 1, 2004 as discussed in the IPPS final rule (69 FR at 49026 through 49034). The similarity between the IPPS and the IRF PPS includes the adoption in the initial implementation of the IRF PPS of the same labor market area definitions under the IRF PPS that existed under the IPPS at that time, as well as the use of acute care hospitals' pre-reclassification and pre-floor wage data in calculating the IRF PPS wage index. In addition, the OMB's CBSA-based designations reflect the most recent available geographic classifications and more accurately reflects current labor markets. Therefore, we believe that revising the IRF PPS labor market area definitions based on OMB's CBSA-based designations are consistent with our historical practice of modeling IRF PPS policy after IPPS policy.

In sections VI.B.2.d.i. through VI.B.2.d.iii of this final rule and as described in the FY 2006 IRF PPS proposed rule (70 FR 30188), we describe the composition of the IRF PPS labor market areas based on the OMB's new CBSA designations.

i. New England MSAs

As stated above, in the August 7, 2001 final rule, we currently use NECMAs to define labor market areas in New England, because these are county-based designations rather than the 1990 MSA definitions for New England, which used minor civil divisions such as cities and towns. Under the current MSA definitions, NECMAs provided more consistency in labor market definitions for New England compared with the rest of the country, where MSAs are county-based. Under the new CBSAs, OMB has now defined the MSAs and Micropolitan Areas in New England on the basis of counties. The OMB also established New England City and Town Areas, which are similar to the previous New England MSAs.

To create consistency among all labor market areas and to maintain these areas on the basis of counties, we proposed to and are adopting in this final rule to use the county-based areas for all MSAs in the nation, including those in New England. Census has now defined the New England area based on counties, creating a city- and town-based system as an alternative. We believe that adopting county-based labor market areas for the entire country except those in New England will lead to inconsistencies in our designations. Adopting county-based labor market areas for the entire country provides consistency and stability in the Medicare payment program because all the labor market areas throughout the country, including New England, will be defined using the same system (that is, counties) rather than different systems in different areas of the country, and minimizes programmatic complexity.

We have consistently employed a county-based system for New England for precisely that reason: To maintain consistency with the labor market area definitions used throughout the country. Because we have never used cities and towns for defining IRF labor market areas, employing a county-based system in New England maintains that consistent practice. We note that this is consistent with the implementation of the CBSA-based designations under the IPPS for New England (see 69 FR at 49028). Accordingly, as specified in the FY 2006 proposed rule (70 FR 30188), we are using the New England MSAs as determined under the new CBSA-based labor market area definitions in defining the revised IRF PPS labor market areas in this final rule.

ii. Metropolitan Divisions

Under OMB's new CBSA designations, a Metropolitan Division is a county or group of counties within a CBSA that contains a core population of at least 2.5 million, representing an employment center, plus adjacent counties associated with the main county or counties through commuting ties. A county qualifies as a main county if 65 percent or more of its employed residents work within the county and the ratio of the number of jobs located in the county to the number of employed residents is at least 0.75. A county qualifies as a secondary county if 50 percent or more, but less than 65 percent, of its employed residents work within the county and the ratio of the number of jobs located in the county to the number of employed residents is at least 0.75. After all the main and secondary counties are identified and grouped, each additional county that already has qualified for inclusion in the MSA falls within the Metropolitan Division associated with the main/secondary county or counties with which the county at issue has the highest employment interchange measure. Counties in a Metropolitan Division must be contiguous (65 FR at 82236).

The construct of relatively large MSAs being comprised of Metropolitan Divisions is similar to the current construct of the CMSAs comprised of PMSAs. As noted above, in the past, OMB designated CMSAs as Metropolitan Areas with a population of 1 million or more and comprised of two or more PMSAs. Under the IRF PPS, we currently use the PMSAs rather than CMSAs to define labor market areas because they comprise a smaller geographic area with potentially varying labor costs due to different local economies. We believe that CMSAs may be too large of an area with a relatively large number of hospitals, to accurately reflect the local labor costs of all the individual hospitals included in that relatively “large” area. A large market area designation increased the likelihood of including many hospitals located in areas with very different labor market conditions within the same Start Printed Page 47920market area designation. This variation could increase the difficulty in calculating a single wage index that will be relevant for all hospitals within the market area designation. Similarly, we believe that MSAs with a population of 2.5 million or greater may be too large of an area to accurately reflect the local labor costs of all the individual hospitals included in that relatively “large” area. Furthermore, as indicated above, Metropolitan Divisions represent the closest approximation to PMSAs, the building block of the current IRF PPS labor market area definitions, and therefore, will most accurately maintain our current structuring of the IRF PPS labor market areas. As implemented under the IPPS (69 FR at 49029), we proposed and for this final rule, we are using the Metropolitan Divisions where applicable (as describe below) under the new CBSA-based labor market area definitions.

In addition to being comparable to the organization of the labor market areas under the current MSA designations (that is, the use of PMSAs rather than CMSAs), we believe that using Metropolitan Divisions where applicable (as described below) under the IRF PPS will result in a more accurate adjustment for the variation in local labor market areas for IRFs. Specifically, if we were to recognize the relatively “larger” CBSA that comprises two or more Metropolitan Divisions as an independent labor market area for purposes of the wage index, it will be too large and will include the data from too many hospitals to compute a wage index that will accurately reflect the various local labor costs of all the individual hospitals included in that relatively “large” CBSA.

As mentioned earlier, a large market area designation increases the likelihood of including many hospitals located in areas with very different labor market conditions within the same market area designation. This variation could increase the difficulty in calculating a single wage index that will be relevant for all hospitals within the market area designation. Rather, by recognizing Metropolitan Divisions where applicable (as described below) under the new CBSA-based labor market area definitions under the IRF PPS, we believe that in addition to more accurately maintaining the current structuring of the IRF PPS labor market areas, the local labor costs will be more accurately reflected, thereby resulting in a wage index adjustment that better reflects the variation in the local labor costs of the local economies of the IRFs located in these relatively “smaller” areas. In section VI.B.2.d.ii.of this final rule, we describe where Metropolitan Divisions will be applicable under the new CBSA-based labor market area definitions under the IRF PPS final rule.

Under the OMB's CBSA-based designations, there are 11 MSAs containing Metropolitan Divisions: Boston; Chicago; Dallas; Detroit; Los Angeles; Miami; New York; Philadelphia; San Francisco; Seattle; and Washington, DC. Although these MSAs were also CMSAs under the prior definitions, in some cases their areas have been altered. Under the current IRF PPS MSA designations, Boston is a single NECMA. Under the CBSA-based labor market area designations, it is comprised of four Metropolitan Divisions. Los Angeles will go from four PMSAs under the current IRF PPS MSA designations to two Metropolitan Divisions under the CBSA-based labor market area designations. The New York CMSA will go from 15 PMSAs under the current IRF PPS MSA designations to four Metropolitan Divisions under the CBSA-based labor market area designations. The five PMSAs in Connecticut under the current IRF PPS MSA designations will become separate MSAs under the CBSA-based labor market area designations because two MSAs became separate MSAs. The number of PMSAs in New Jersey, under the current IRF PPS MSA designations will go from five to two, with the consolidation of two New Jersey PMSAs (Bergen-Passaic and Jersey City) into the New York-Wayne-White Plains, NY-NJ Division, under the CBSA-based labor market area designations. In San Francisco, under the CBSA-based labor market area designations there are only two Metropolitan Divisions. Currently, there are six PMSAs, some of which are now separate MSAs under the current IRF PPS labor market area designations.

Under the current IRF PPS labor market area designations, Cincinnati, Cleveland, Denver, Houston, Milwaukee, Portland, Sacramento, and San Juan are all designated as CMSAs, but will no longer be designated as CMSAs under the CBSA-based labor market area designations. As noted previously, the population threshold to be designated a CMSA under the current IRF PPS labor market area designations is 1 million. In most of these cases, counties currently in a PMSA will become separate, independent MSAs under the CBSA-based labor market area designations, leaving only the MSA for the core area under the CBSA-based labor market area designations.

We note that subsequent to the publication of the FY 2006 IRF PPS proposed rule (70 FR 30188), titles to certain CBSAs were changed based on OMB Bulletin No. 05-02 (November 2004). The title changes listed below are nomenclatures that do not result in substantive changes to the CBSA-based designations. Thus, these changes are listed below and will be incorporated into the FY 2007 CBSA-based urban wage index tables.

  • CBSA 36740: Orlando-Kissimmee, FL
  • CBSA 37620: Parkersburg-Marietta-Vienna, WV-OH
  • CBSA 42060: Santa Barbara-Santa Monica, CA
  • CBSA 13644: Bethesda-Gaithersburg-Frederick, MD
  • CBSA 32580: McAllen-Edinburg-Mission, TX
  • CBSA 26420: Huston-Sugar Land-Baytown, TX
  • CBSA 35644: New York-White Plains-Wayne, NY-NJ

ii. Micropolitan Areas Under the New OMB CBSA-Based Designations, Micropolitan

Areas are essentially a third area definition consisting primarily of areas that are currently rural, but also include some or all of areas that are currently designated as urban MSA. As discussed in greater detail in the IPPS final rule (69 FR at 49029 through 49032), how these areas are treated will have significant impacts on the calculation and application of the wage index. Specifically, whether or not Micropolitan Areas are included as part of the respective statewide rural wage indices will impact the value of the statewide rural wage index of any State that contains a Micropolitan Area because a hospital's classification as urban or rural affects which hospitals' wage data are included in the statewide rural wage index. As discussed above in section VI.B.2.b of this final rule, we combine all of the counties in a State outside a designated urban area to calculate the statewide rural wage index for each State.

Including Micropolitan Areas as part of the statewide rural labor market would result in an increase to the statewide rural wage index because hospitals located in those Micropolitan Areas typically have higher labor costs than other rural hospitals in the State. Alternatively, if Micropolitan Areas were to be recognized as independent labor market areas, because there would be so few hospitals in those areas to complete a wage index, the wage indices for IRFs in those areas could become relatively unstable as they might change considerably from year to year.

Since the implementation of the IRF PPS, we used MSAs to define urban labor market areas and group all the Start Printed Page 47921hospitals in counties within each State that are not assigned to an MSA into a statewide rural labor market area. Therefore, we used the terms “urban” and “rural” wage indices in the past for ease of reference. However, the introduction of Micropolitan Areas by the OMB potentially complicates this terminology because these areas include many hospitals that are currently included in the statewide rural labor market areas.

We proposed to treat Micropolitan Areas as rural labor market areas under the IRF PPS for the reasons outlined below. That is, counties that are assigned to a Micropolitan Area under the CBSA-based designations would be treated the same as other “rural” counties that are not assigned to either an MSA or a Micropolitan Area. Therefore, in determining an IRF's applicable wage index (based on IPPS hospital wage index data) an IRF in a Micropolitan Area under OMB's CBSA designations would be classified as “rural” and would be assigned the statewide rural wage index for the State in which it resides.

In the IPPS final rule (69 FR at 49029 through 49032), we discuss our evaluation of the impact of treating Micropolitan areas as part of the statewide rural labor market area instead of treating Micropolitan Areas as independent labor market areas for hospitals paid under the IPPS. As an alternative to treating Micropolitan Areas as part of the statewide rural labor market area for purposes of the IRF PPS, in the FY 2006 proposed rule (70 FR 30188), we examined treating Micropolitan Areas as separate (urban) labor market areas, just as we did when implementing the revised labor market areas under the IPPS.

As discussed in greater detail in that same final rule, the designation of Micropolitan Areas as separate urban areas for wage index purposes will have a dramatic impact on the calculation of the wage index. This is because Micropolitan areas encompass smaller populations than MSAs, and tend to include fewer hospitals per Micropolitan area. Currently, there are only 25 MSAs with one hospital in the MSA. However, under the new CBSA-based definitions, there are 373 Micropolitan Areas with one hospital, and 49 MSAs with only one hospital.

Since Micropolitan Areas encompass smaller populations than MSAs, they tend to include fewer hospitals per Micropolitan Area, recognizing Micropolitan Areas as independent labor market areas will generally increase the potential for dramatic shifts in those areas' wage indices from one year to the next because a single hospital (or group of hospitals) could have a disproportionate effect on the wage index of the area. The large number of labor market areas with only one hospital and the increased potential for dramatic shifts in the wage indexes from one year to the next is a problem for several reasons. First, it creates instability in the wage index from year to year for a large number of hospitals. Second, it reduces the averaging effect (this averaging effect allows for more data points to be used to calculate the representative standard of measured labor costs within a market area) lessening some of the incentive for hospitals to operate efficiently. This incentive is inherent in a system based on the average hourly wages for a large number of hospitals, as hospitals could profit more by operating below that average. In labor market areas with a single hospital, high wage costs are passed directly into the wage index with no counterbalancing averaging with lower wages paid at nearby competing hospitals. Third, it creates an arguably inequitable system when so many hospitals have wage indexes based solely on their own wages, while other hospitals' wage indexes are based on an average hourly wage across many hospitals. Therefore, in order to minimize the potential instability in payment levels from year to year, we believe it will be appropriate to treat Micropolitan Areas as part of the statewide rural labor market area under the IRF PPS.

For the reasons noted above, and consistent with the treatment of these areas under the IPPS, we proposed and are adopting Micropolitan Areas as independent labor market areas under the IRF PPS. Under the new CBSA-based labor market area definitions, Micropolitan Areas are considered a part of the statewide rural labor market area. Accordingly, we will determine an IRF PPS statewide rural wage index using the acute-care IPPS hospital wage data (the rational for using IPPS hospital wage data is discussed in section III.B.2.f of this final rule) from hospitals located in non-MSA areas assign the statewide rural wage index to IRFs located in those areas.

e. Implementation of the CBSA-Based Labor Market Areas

Under section 1886(j) of the Act, as added by section 4421 of the Balanced Budget Act of 1997 (BBA) (Pub. L. 105-33) and as amended by section 125 of the Medicare, Medicaid, and State Children's Health Insurance Program (SCHIP) Balanced Budget Refinement Act of 1999 (BBRA) (Pub. L. 106-113) and section 305 of the Medicare, Medicaid, and SCHIP Benefits Improvement and Protection Act of 2000 (BIPA) (Pub. L. 106-554), which requires the implementation of such prospective payment system, the Secretary generally has broad authority in developing the IRF PPS, including whether and how to make adjustments to the IRF PPS.

In the FY 2006 IRF PPS proposed rule (70 FR 30188), Table 3 listed IRFs that submitted an IRF-PAI in the past 18-months. The data in Table 3 was obtained from a report we requested in February 2005 from the Iowa Foundation for Medical Care (IFMC). IFMC is the CMS contractor where the IRF-PAI database is located. Table 3 listed each IRF's provider number; provider name; and State and county location; existing MSA-based labor market area designation; and its CBSA-based designation. The purpose of Table 3 was to only facilitate an understanding of the policies related to the proposed change to the IRF PPS labor market areas discussed above by illustrating an IRF's change from the MSA-based designation to the proposed CBSA-based designation. Thus, FIs will not be instructed to use Table 3 in the FY 2006 IRF PPS proposed rule (70 FR 30188) to alter the information regarding an IRF's State and county location or to make changes to the provider specific file based on Table 3 of the FY 2006 IRF PPS proposed rule.

Table 1 of the addendum of this final rule is a crosswalk file of all counties/areas in the United States, Guam, Puerto Rico, and the Virgin Islands with the corresponding State and county code, county and State name, FY 2006 MSA number, FY 2006 MSA-based urban or rural designation, FY 2006 MSA-based wage index, FY 2006 CBSA-based wage index, FY 2006 CBSA number, FY 2006 CBSA-based urban or rural designation, and FY 2006 blended one-year transition wage index as discussed below in Section VI.B.2.e. Table 1 of the addendum to this final rule will be used by FIs to determine the FY 2006 one-year transition wage index for IRFs located in areas as documented in the FI's provider specific file.

When the revised labor market areas based on OMB's new CBSA-based designations were adopted under the IPPS beginning on October 1, 2004, a transition to the new designations was established due to the scope and substantial implications of these new CBSA-based designations in order to buffer the subsequent substantial impacts on numerous hospitals. As discussed in the IPPS final rule (69 FR at 49032), during FY 2005, a blend of Start Printed Page 47922wage indices is calculated for those acute care IPPS hospitals experiencing a drop in their wage index because of the adoption of the new labor market areas. The most substantial decrease in wage index impacts urban acute-care hospitals that were designated as rural under the CBSA-based designations.

In the FY 2006 IRF PPS proposed rule (70 FR 30188), we recognize that, just like IPPS hospitals, IRFs may experience decreases in their wage index as a result of the labor market area changes. Our data analysis for the FY 2006 IRF PPS proposed rule (70 FR 30188) indicated that a majority of IRFs either expect no change in wage index or an increase in wage index based on CBSA definitions. Based on this analysis for the FY 2006 IRF PPS proposed rule (70 FR 30188), we found a very small number of IRFs (3 percent) will experience a decline of 5 percent or more in the wage index based on CBSA designations. A 5 percent decrease in the wage index for an IRF may result in a noticeable decrease in their wage index compared to what their wage index would have been for FY 2006 under the MSA-based designations. We also found that a very small number of IRFs (4 percent) would experience a change in either rural or urban designation under the CBSA-based definitions. Since a majority of IRFs would not be significantly impacted by the labor market areas, we did not propose a transition to the new CBSA-based labor market area, nor did we propose to adopt a hold harmless policy, nor an “out-commuting” policy for the purposes of the IRF PPS wage index.

Public comments and our responses on the proposed changes for implementing the area wage adjustments are summarized below:

Comment: A large number of commenters urged CMS to develop a transition policy or implement a similar transition policy as was implemented under the IPPS to minimize the fiscal impact of the change in wage index. Many advocated for a one-year transition with a blended wage index, equal to 50 percent of the FY 2006 MSA wage index and 50 percent of the FY 2006 CBSA-based wage index. We also received a few comments recommending a multi-year transition and possibly a permanent blended wage index. Overall, commenters expressed concerns for IRFs that would experience a significant decrease in the wage index. In general, commenters request that we mitigate the impact of the change from the MSA-based designation to the CBSA-based designations over time with a transition policy.

Response: We recognize that some IRFs will experience decreases in their applicable wage index as a result of the conversion from the MSA-based designations to the CBSA-based designations. After further analysis of various transition options suggested by commenters as well as our further data analysis to support the policies in this final rule, we considered various transition options to determine a transition policy that would mitigate the impact on IRFs that would experience a decrease in the wage index, and buffer the overall impact on the unadjusted payment rate. Based on the commenters' recommendations, we carefully reviewed various budget neutral transition policies such as a blended wage index as well as a floor and ceiling approach as discussed in detail below.

We reviewed a floor and ceiling transition policy option. Although this option seemed to minimize the impact on IRFs, we found that this approach would provide relief to IRFs that experience a decrease in the wage index, but with respect to IRFs that would get a significant increase in the wage index, it would also limit the amount they could expect their wage index to increase. The difficulty of developing a floor and ceiling transition policy is determining an appropriate floor and a ceiling that would best mitigate IRFs that experience a decrease in the wage index while lessening the overall impact on the unadjusted base payment kept us from choosing this option. -

Although a few commenters recommended a permanent blended wage index (comprised of the MSA-based wage index and the CBSA-based wage index), we do not believe this is appropriate. Beginning in FY 2006, acute care hospital will receive 100 percent of the IPPS wage index based on the new CBSA wage index. From FY 2006 and forward, CMS will no longer maintain the geographic classifications based on MSAs. Therefore, MSA-based wage indexes will not be able to reflect the same amount of accuracy as they currently represent by having the geographical classification updated annually. By developing a permanent blended wage index, CMS would only be geographically updating the CBSA-based areas and not the MSA-based areas. Consequently, we believe that implementation of a permanent blended wage index would result in a wage index that is not as accurate as a wage index based on the CBSA methodology, as thoroughly discussed in section VI.B.2.d.

Several commenters suggested that IRFs be afforded the same transition as adopted by IPPS (69 FR 48916, 49032-49034). Therefore, another budget neutral one-year transition policy we considered would blend the wage index for IRFs that would experience a reduction in the wage index. The blended wage index would consist of 50 percent of the FY 2006 MSA-based wage index and 50 percent of the FY 2006 CBSA-based wage index (both based on the FY 2001 hospital wage data), only for IRFs that experience a decrease due solely to the changes in the labor market definitions. Although some commenters recommended this transition policy, we believe that this would not allow all IRFs the ability to transition from the MSA-based wage index to the CBSA-based wage index because this transition policy only focuses on the blending the wage index for IRFs that experience a decrease in the wage index. In addition, we found that this would change the budget neutrality factor applied to the base rates from 0.9996 if there was no transition to 0.9977 under this transition policy. Therefore, the budget neutrality factor under the transition policy for only those IRFs that experience a decrease in the wage index would reduce the unadjusted base rate by approximately more than 20 dollars. The overall impact based on the reduction of the unadjusted base rate would result in all IRFs experiencing a reduction in payments. Under this approach, we found that IRFs would experience a significant reduction in the unadjusted payment amount, which would not mitigate the change in estimated payments for IRFs.

The last one-year budget neutral blended transition policy we analyzed would allow all IRFs to transition from an MSA-based wage index to a CBSA-based wage index. This transition policy would be comprised of 50 percent of the FY 2006 MSA-based wage index and 50 percent of the FY 2006 CBSA-based wage index (both based on the FY 2001 hospital wage data) for all IRFs. As discussed in the FY 2006 IRF PPS proposed rule (70 FR 30188), the one-year blended wage index for all IRFs would result in a slight decrease of budget neutrality factor applied to the base rates from 0.9996 if there was no transition to 0.9995 under this transition policy. As a result, the budget neutrality factor applied to the unadjusted payment amount would reduce the unadjusted payment amount by approximately 1 dollar as compared to fully adopting the CBSA-based designations. This slight decrease to the unadjusted payment amount will lessen the overall payment reduction impact Start Printed Page 47923on all providers—regardless of urban or rural designations.

Although a blended wage index for all IRFs would also help IRFs that are adversely affected by the changes from MSAs to CBSAs, it would reduce the expected higher CBSA wage index values for IRFs that are positively affected by the changes (compared to fully adopting the CBSA-based wage index). To clarify, a blended wage index for IRFs that experience any increase due to the change from an MSA-based wage index to a CBSA-based wage index would be lessened. Thus, this would allow all IRFs one year to financially prepare for a change in wage index due to the change from FY 2005 MSA-based to FY 2006 CBSA-based designations—regardless of an increase or decrease in wage index.

In addition, although the blended wage index would limit the wage index increase for IRFs that experience an increase due to the change from an MSA-based wage index to a CBSA-based wage index during FY 2006, these IRFs will continue to see an increase in their wage index. However, the dampening effect of the blended wage index for IRFs that experience an increase in their wage index does not significantly impact these IRFs based solely on the wage index. The increase in the wage index these IRFs would experience would still take effect because the blended wage index would be an average of the MSA-based wage index and a CBSA-based wage index and the CBSA-based wage index would be greater than the MSA-based wage index. Therefore, IRFs in this scenario would not be significantly impacted by a blended wage index. In other words, IRFs that have higher CBSA wage index values and are subject to the blend will continue to have a benefit of having their payment derived, in part, from the higher CBSA wage index. We believe this option helps create an equitable situation for all IRFs.

Many commenters urged and supported a transition to adopting the CBSA-based designations. Thus, this blended wage index (50 percent of the FY 2006 MSA-based wage index and 50 percent of the FY 2006 CBSA-based wage index and both based on the FY 2001 hospital wage data) would provide IRFs a one-year transition from the MSA-based designations to the CBSA-based designations. In addition, the one year transition of a blended wage for all IRFs would result in 93 percent of all IRFs experiencing a wage index change between a decrease by up to 2 percent or an increase by up to 2 percent. In any given year, even under the MSA-based wage index, many IRFs experience a 2 percent change in wage index and this 2 percent change would most likely be a wage index change that would not significantly impact IRF payments based solely on the wage index. Thus, from year to year, almost all IRFs are expected to experience a minimal change in wage index values. In comparison, if we fully adopted the CBSA-based wage index without a transition as proposed, 85 percent of the IRFs would experience a change between a decrease by up to 2 percent or an increase by up to 2 percent. By providing a one year transition for all IRFs to receive a blended wage index (50 percent of the FY 2006 MSA-based wage index and 50 percent of the FY 2006 CBSA-based wage index and both based on the FY 2001 hospital wage data), a larger majority of IRFs will experience a minimal change in wage index from FY 2005 to FY 2006.

We decided not to provide for a longer transition, as recommended by a few commenters, because we have already, in effect, provided one year at a higher wage index level for all IRFs by retaining the previous labor market definitions for two years after the new labor market definitions became available. For example, we did not implement the new labor market area definitions as quickly as was done for facilities paid under the IPPS. Furthermore, since most IRFs benefit from a one year blended wage index, there will be minimal affect on IRFs. Thus, a one year transition is sufficient to minimize the impact of adopting the CBSA-based designations because we believe that the transition period allows IRFs sufficient time to adjust their necessary business practices. In addition to the one year blended wage index, we are implementing a longer, 3-year hold harmless transition (as discussed in this section below of this final rule (section VI.B.2.e)) for a group of IRFs that during FY 2005 are as designated as rural, and for FY 2006 will be designated as urban under the new CBSA-based geographic designation method. We are implementing a longer hold harmless transition for these IRFs because, as a group they experience a reduction in payments due to the labor market revisions and the loss of the rural adjustment.

The statute confers broad authority to the Secretary under 1886(j)(6) of the Act to establish factor for area wage differences by a factor such that budget neutral wage index options may be considered. After consideration of the recommendations presented by the commenters and based on our further analysis, we will implement a budget neutral one-year transition policy such that a blended wage index (50 percent of the FY 2006 MSA-based wage index and 50 percent of the FY 2006 CBSA-based wage index that are both based on the FY 2001 hospital wage data) will apply to all IRFs. This transition policy will be effective for discharges occurring on or after October 1, 2005 and on or before September 30, 2006. This transition will mitigate the large negative impacts for IRFs that experience a decrease in the wage index and allow all IRFs to transition from the MSA-based wage index to the CBSA-based wage index for one-year. Therefore, for FY 2007 and subsequent years, we will adopt the full CBSA-based wage index for all IRFs.

Comment: Several commenters requested CMS to consider a multi-year hold harmless policy as was implemented by IPPS.

Response: As discussed in the August 11, 2004 IPPS final rule (69 FR at 49032), during FY 2005, a hold harmless policy was implemented to minimize the overall impact of hospitals that were in FY 2004 designated as urban under the MSA designations, but will become rural under the CBSA designations. In the same final rule, hospitals were afforded a three-year hold harmless policy because the IPPS determined that acute-care hospitals that changed designations from urban to rural will be substantially impacted by the significant change in wage index. Although we considered a hold harmless policy in our FY 2006 proposed rule, we did not propose a hold harmless policy because we believed that rural IRFs (under the MSA-based designations) that change to an urban designation (based on the CBSA-based geographic classification) would experience a significant increase to the wage index under the CBSA-based designations that would mitigate a significant decrease in payments. However, many commenters urged CMS to reconsider a hold harmless policy because the commenters demonstrated that some rural facilities would experience undue hardship with the loss of the rural adjustment under § 412.624(e)(3).

In our analysis (discussed in the FY 2006 IRF PPS proposed rule (70 FR 30188)), we found that 91 percent of rural facilities that would be designated as urban under the CBSA-based definitions will experience an increase in the wage index. A majority (74 percent) of rural facilities that become urban will experience at least a 5 percent to 10 percent or more increase in wage index. Although these rural IRFs experience wage index increases, several commenters emphasized that a Start Printed Page 47924majority of rural providers that change designations may experience a wage index increase of at least 5 percent or more, the loss of the rural adjustment would be such a large negative impact on the rural IRFs that it may potentially cause undue hardship for these rural facilities.

In response to the commenters concerns, we considered different hold harmless policies such as a multi-year hold harmless policy as well as a phase-out of the rural adjustment for rural IRFs under the MSA-based designations that received a rural adjustment of 19.14 percent in FY 2005. A commenter recommended a phase-out of the FY 2005 rural adjustment of 19.14 percent because this option allows IRFs that change designations, from rural to urban, time to adjust to the loss of the 19.14 percent rural adjustment which would result in loss of payments. Other commenters concurred that the loss of the FY 2005 rural adjustment far exceeds the urban CBSA-based increase in wage index. Thus, commenters believed that this would have significant payment implications, particularly large negative impacts for rural IRFs that change designations because they will experience significant payment losses.

After further consideration of hold harmless policies as recommended by commenters, we have decided to implement a hold harmless policy to mitigate significant payment implications, particularly large negative impacts. We will implement a 3 year budget neutral hold harmless policy for those IRFs that meet the definition in § 412.602 as rural in FY 2005 and will become urban under the FY 2006 CBSA-based designations. We will afford existing IRFs designated in FY 2005 as rural IRFs (pursuant to § 412.602) and redesignated as an urban facility in FY 2006 (pursuant to § 412.602) in FY 2006, whose payment is lower because of such redesignation, a 3 year time span to adjust to the loss of the FY 2005 rural adjustment of 19.14 percent because the loss of the 19.14 percent rural adjustment would result in a significant loss of payments. This adjustment will be in addition to the one-year blended wage index (comprised of FY 2006 MSA-based wage index and FY 2006 CBSA-based wage index both based on FY 2001 hospital data) for all IRFs. -

Although our intent under our hold harmless policy is to mitigate the negative payment effect upon a rural facility that is redesignated as an urban facility (effective FY 2006), the hold harmless policy should not result in an IRF that comes under the hold harmless policy to realize greater payments than the IRF would have if instead the IRF would have been paid under its rural designation in FY 2006 including the FY 2005 rural adjustment of 19.14 percent. Therefore, we will make the appropriate payment modification to the additional adjustment made under our hold harmless policy so that an existing FY 2005 rural IRF that is redesignated from rural to urban in FY 2006 will in FY 2006 or FY 2007 not realize payments that are greater than what the payments would have been if the facility would have instead been paid under its rural designation in FY 2006 including the FY 2005 rural adjustment of 19.14 percent. In other words, if an existing FY 2005 IRF is redesignated from rural to urban in FY 2006, and it will realize an increase in payments during the one year transition due to the hold harmless policy, it will not receive the full two-thirds of the 19.14 percent rural adjustment. However, if this same IRF realizes a decrease in payment in FY 2007 solely because of such redesignation in FY 2006, it will receive one-third of the 19.14 percent rural adjustment in such case.

As stated above, the hold harmless policy is specifically for FY 2005 rural IRFs that become urban in FY 2006 and that experience a loss in payment because of this redesignation. Thus, we are not implementing a hold harmless policy for urban facilities (under the MSA-based designation) that become rural (under the CBSA-based designation) because these IRFs will receive the updated FY 2006 rural adjustment of 21.3 percent that they did not receive in FY 2005 as an urban facility. The gain of this payment adjustment should more than mitigate the loss of the wage index decreases associated with the rural designations. For FY 2005, rural facilities that remain rural under the FY 2006 CBSA-based designation, we are not extending the hold harmless policy for these IRFs because these rural IRFs will receive the updated FY 2006 rural adjustment of 21.3 percent, which is higher than the FY 2005 rural adjustment of 19.14 percent. We are also not extending the hold harmless policy for facilities that remain in their urban geographic designations from the MSA-based designation to the CBSA-based designation because we have mitigated the impact of the change in wage index value by implementing a one year transition wage index (comprised of 50 percent FY 2006 MSA-based wage index and 50 percent of the FY 2006 CBSA-based wage index) for all IRFs as discussed in detail above. As was previously stated, the purpose of the hold harmless policy is to mitigate the significant payment implications for existing rural IRFs that may need time to adjust to the loss of their FY 2005 rural payment adjustment that experience a reduction in payments solely because of such redesignation. Our decision to implement the hold harmless policy only for existing FY 2005 rural IRFs that will be adversely impacted, is supported by comments received primarily requesting implementation of a method that mitigates the adverse payment impacts because of the loss of the rural adjustment.

Due to our review and analysis, we determined that a 3 year budget neutral hold harmless policy would best accomplish the goals of mitigating the loss of the rural adjustment for existing FY 2005 rural IRFs. The incremental steps needed to reduce the impact of the loss of the FY 2005 rural adjustment of 19.14 percent will be phased out for years FY 2006, FY 2007, and FY 2008.

Thus, the budget neutral 3 year hold harmless policy will apply to the existing FY 2005 rural IRFs (under the MSA-based designation) that will change designations and experience a reduction in payments due to the loss of the FY 2005 rural adjustment of 19.14 percent and meets the intent of this policy. The hold harmless policy will allow existing FY 2005 rural IRFs adversely affected by the change in designation to receive two-thirds of the FY 2005 rural adjustment of 19.14 percent (specifically 12.76 percent hold harmless adjustment) for FY 2006 as well as the blended wage index (comprised of 50 percent of the FY 2006 MSA-based wage index and 50 percent of the FY 2006 CBSA-based wage index both based on FY 2001 hospital data). For FY 2007, existing FY 2005 rural IRFs that are a part of the FY 2006 hold harmless policy will receive the full FY 2007 CBSA wage index and one-third of the FY 2005 rural adjustment of 19.14 percent (specifically, a 6.38 percent hold harmless adjustment). For FY 2008, existing FY 2005 rural IRFs that are a part of the FY 2006 hold harmless policy will receive the full FY 2008 CBSA-based wage index without a rural adjustment as long as the IRF is designated as urban under the FY 2008 CBSA-based designation (illustrated in Table 10 below). Start Printed Page 47925

Table 10.—IRF 3-Year Hold Harmless Policy for IRFs Designated as Rural Under the MSA-Based Designation

FY 2006FY 2007FY 2008
Wage Index50% of MSA Wage Index and 50% of CBSA Wage IndexFull FY 2007 CBSA Wage IndexFull FY 2008 CBSA Wage Index
Rural Adjustment (Phase out)*12.766.38N/A
*Based on the FY 2005 Rural Adjustment of 19.14 percent.

As is shown by the table, making incremental reductions to the 19.14 percent rural adjustment that certain rural IRFs received during FY 2005 results in these IRFs still being paid a portion of that rural adjustment in FY 2006 and FY 2007.

We believe that an incremental reduction of the FY 2005 rural adjustment of 19.14 percent is appropriate because of our analysis to implement a one third compared to a two thirds hold harmless adjustment of the 19.14 percent rural adjustment in FY 2006. We analyzed the 34 IRFs (in our analysis file) that would be impacted by the hold harmless policy to determine the effect on their IRF PPS payments if we did not implement a hold harmless policy. We also reviewed the payment impacts on these IRFs if the hold harmless policy implemented one third of the FY 2005 rural adjustment of 19.14 percent versus two thirds of the FY 2005 rural adjustment of 19.14 percent in FY 2006 (as described in the section XII).

We found that if we did not adopt a hold harmless policy, the 34 rural IRFs that change designations from a rural facility (under the MSA-based designations) to an urban facility (under the CBSA-based designations) would experience a significant reduction in per case payment. We also considered a one year hold harmless policy that would allow the 34 IRFs in our analysis to receive a blended wage index as well as only a one third of the FY 2005 rural adjustment of 19.14 percent. Based on our analysis, a one year hold harmless policy would slightly mitigate the payment reductions for rural IRFs in our analysis file.

Our analysis of whether a multi-year hold harmless policy would provide a sufficient buffer to the loss of payments, found that a 3 year hold harmless policy of two thirds of the 19.14 percent rural adjustment in the FY 2006 and one third in FY 2007 would be the most appropriate. Based on a 3 year hold harmless policy, we found these IRFs would be mitigated from significant payment reductions. We determined that a 3 year hold harmless policy that provides two thirds of the 19.14 percent adjustment in FY 2006 and one third in FY 2007 would appropriately mitigate the adverse payment impacts for existing FY 2005 rural IRFs that are designated as urban IRFs in FY 2006.

To determine whether an existing FY 2005 rural IRF would meet part of the criteria for the hold harmless policy, we have developed Table 2 in the addendum. Table 2 of this addendum is a crosswalk file of counties/areas in the United States and Puerto Rico that would change from a rural MSA-based designation to an urban area under the CBSA-based designation. These areas are listed in Table 2 of the addendum to identify areas affected by the budget neutral 3 year hold harmless policy as described in this section. Table 2 of the addendum provides the State and county code, State and county name, MSA number, MSA rural designations, FY 2006 MSA-based wage index, FY 2006 CBSA-based wage index, CBSA number, CBSA urban designations, and the applicable FY 2006 transition wage index as described in section VI.2.B.e. The FIs will also be instructed to use Table 2 of the addendum to identify IRFs in these areas that will be impacted by the budget neutral 3 year hold harmless policy (as discussed in detail in this section) based on the FI's existing data in the provider specific file.

As a conforming change to §412.624(e), we are finalizing the hold harmless policy by adding new paragraph (e)(7). Paragraph (e)(7) of §412.624(e) will read as follows: Adjustments for certain facilities geographically redesignated in FY 2006.

(i) General. For a facility defined as an urban facility under §412.602 in FY 2006 that was previously defined as a rural facility in FY 2005 as the term rural was defined in FY 2005 under §412.602 and whose payment, after applying the adjustment under this paragraph, will be lower only because of being defined as an urban facility in FY 2006 and it no longer qualified for the rural adjustment under §412.624(e)(3) in FY 2006, CMS will adjust the facility's payment using the following method:

(A) For discharges occurring on or after October 1, 2005, and on or before September 30, 2006, the facility's payment will be increased by an adjustment of two thirds of its prior FY 2005 19.14 percent rural adjustment.

(B) For discharges occurring on or after October 1, 2006, and on or before September 30, 2007, the facility's payment will be increased by an adjustment of one third of its FY 2005 19.14 percent rural adjustment.

(ii) Exception. For discharges occurring on or after October 1, 2005 and on or before September 30, 2007, facilities whose payments, after applying the adjustment under this paragraph (e)(7)(i) of this section, will be higher because of being defined as an urban facility in FY 2006 and no longer being qualified for the rural adjustment under 412.624(e)(3) in FY 2006, CMS will adjust the facility's payment by a portion of the applicable additional adjustment described in paragraph (e)(7)(i)(A) and (e)(7)(i)(B) of this section as determined by us.

In addition, we did not receive comments regarding section 505 of the MMA that established a new section 1886(d)(13) of the Act. As discussed in the FY 2006 IRF PPS proposed rule (70 FR 30188), the new section 1886(d)(13) requires that the Secretary establish a process to make adjustments to the hospital wage index based on commuting patterns of hospital employees. We believe that this requirement for an “out-commuting” or “out-migration” adjustment applies specifically to the IPPS. Therefore, we are not implementing such an adjustment for the IRF PPS in this final rule.

Comment: A number of commenters advised us that Table 3 of the FY 2006 IRF PPS proposed rule contained a formatting problem that resulted in provider numbers, provider names, state and county location, MSA-based designation, and CBSA-based designations to be misaligned.

Response: Once this error was brought to our attention, we immediately published a public use file on our webpage to show the provider level Start Printed Page 47926table as developed in Microsoft Excel. The web address for the FY 2006 IRF PPS proposed rule's public use files may be found at http://www.cms.hhs.gov/​providers/​irfpps/​fy06nprm.asp. Table 3, as published in the FY 2006 IRF PPS proposed rule (70 FR 30188), was produced for informational purposes only. Therefore, the information an IRF's FI has on file for each IRF will not be altered based on Table 3. We will not be reproducing a provider level table that crosswalks the MSA-based and CBSA-based designations for this final rule as it was only published in the proposed rule to help facilitate the public's understanding of the proposed policy.

For the purposes of determining a wage index for FY 2006 IRF PPS rate year, we will publish a crosswalk table (Table 1 of this addendum) listing the State and county code, State and county name, the MSA-based designations, CBSA-based designations and the blended wage index (comprised of 50 percent of the FY 2006 MSA-based wage index and 50 percent of the FY 2006 CBSA-base wage index both based on the FY 2001 hospital wage data) for discharges occurring on or after October 1, 2005 and on or before September 30, 2006. In the FY 2006 IRF PPS proposed rule (70 FR 30188), we published a FY 2006 CBSA urban and rural wage index table to illustrate the proposed policy to fully adopt the FY 2006 CBSA wage index. Since we are no longer fully adopting the FY 2006 CBSA wage index, we will publish a table for FIs to determine an IRFs blended wage index values for FY 2006 (specifically a blend of 50 percent FY 2006 MSA-based wage index and 50 percent of the FY 2006 CBSA-based wage index). Thus, Table 1 of this addendum will be used by FIs to determine the FY 2006 one-year blended transitional wage index (comprised of FY 2006 MSA-based and FY 2006 CBSA-based wage index) as finalized in this rule.

Final Decision: In summary (as discussed in detail above in the comments and responses, and based on further analysis of various policy options to implement the CBSA-based designations), we will implement a budget neutral one-year transition policy that blends the FY 2006 MSA-based wage index and FY 2006 CBSA-based wage index (both based on FY 2001 hospital wage data) for discharges occurring on or after October 1, 2005 and on or before September 30, 2006 for all IRFs. In addition to the blended wage index for FY 2006, we will implement a budget neutral 3 year hold harmless policy for existing FY 2005 rural IRFs that will lose the FY 2005 rural adjustment of 19.14 percent, experience a loss in payments due to the change from an MSA-based rural designation to a CBSA-based urban designation, and meets the intent of the hold harmless policy (as discussed in detail above).

f. Wage Index Data

In the August 7, 2001 final rule, we established an IRF wage index based on FY 1997 acute care hospital wage data to adjust the FY 2002 IRF payment rates. For the FY 2003 IRF PPS payment rates, we applied the same wage adjustment as used for FY 2002 IRF PPS rates because we determined that the application of the wage index and labor-related share used in FY 2002 provided an appropriate adjustment to account for geographic variation in wage levels that was consistent with the statute. For the FY 2004 IRF PPS payment rates, we used the hospital wage index based on FY 1999 acute care hospital wage data. For the FY 2005 IRF PPS payment rates, we used the hospital wage index based on FY 2000 acute care hospital wage data. As was proposed in the FY 2006 IRF PPS proposed rule (70 FR 30188) and for this final rule, we will use FY 2001 acute care hospital wage data for FY 2006 IRF PPS payment rates because it is the most recent final data available. As was proposed in the FY 2006 IRF PPS proposed rule (70 FR 30188), and for this final rule, we will adopt the methodology discussed in the proposed rule (70 FR at 30188, 30241) to calculate a wage index in the event that there is no hospital data for an area (urban or rural) under the CBSA-based designations (70 FR 30188, 30241).

A summary of public comments and our responses on the wage index data are discussed below:

Comment: Many commenters argue that a majority of IRFs are hospital units and should be treated the same as hospitals whereby IRFs should be allowed to be reclassified to the same geographic area as the hospital. One commenter urged CMS to develop instructions and begin collecting IRF-specific wage index data in order to allow IRFs to establish a geographic reclassification criteria for IRFs. Commenters also urged CMS to use FY 2002 hospital wage data for the FY 2006 IRF PPS rate year because it is more current than the finalized data available. One commenter request that CMS develop a “rural floor” like that of IPPS.

Response: In the August 1, 2001 final rule (66 FR at 41358) we established FY 2002 IRF PPS wage index values for the 2002 IRF PPS fiscal year calculated from the same data used to compute the FY 2001 acute care hospital inpatient wage index data without taking into account geographic reclassification under sections 1886(d)(8) and (d)(10) of the Act and without applying the “rural floor” under section 4410 of Pub. L. 105-33 (BBA) (as discussed in section VI.B.2.a of this final rule). Acute care hospital inpatient wage index data is also used to establish the wage index adjustment used in other PPSs (for example, LTCH, IPF, HHA, and SNF). As we discussed in the August 7, 2001 final rule (66 FR at 41316, 41358), since hospitals that are excluded from the IPPS are not required to provide wage-related information on the Medicare cost report and because we would need to establish instructions for the collection of this IRF data it is not appropriate at this time to implement a wage index specific to IRF facilities. Because we do not have an IRF specific wage index that we can compare to the hospital wage index, we are unable to determine at this time the degree, if any, to which the acute care hospital data fully represent IRF wages or if a geographic reclassification adjustment under the IRF PPS is appropriate.

Although commenters request CMS to develop a “rural floor” like the IPPS, we believe the “rural floor” is applicable only to the acute care hospital payment system. Furthermore, as stated in section VI.B.2, section 4410 of the Balanced Budget Act of 1997 (Pub. L. 105-33) applies specifically to acute care hospitals and not excluded hospitals and excluded units. Thus, we believe that the acute care hospital “pre-reclassification and pre-floor” wage data is the best proxy and most appropriate wage index. In addition and as discussed above in section VI.B.2.e we will implement a blended wage index to mitigate the impacts an IRF may experience as a result of the change from MSA-based designations to CBSA-based designations. Furthermore, under the IRF PPS, IRFs are paid a rural adjustment under § 412.624(e)(3) as discussed in detail in section VI.B.4 to account for higher costs among rural facilities versus urban facilities.

Although commenters request instructions to be developed in order to collect IRF specific wage data, we did not propose to develop instructions at this time. At this time, we are unable to develop a separate wage index for rehabilitation facilities. Further, in order to accumulate the data needed, we would need to make modifications to the cost report. In the future, we will continue to research wage data specific to IRF facilities. Because we do not have an IRF specific wage index that we can compare to the hospital wage index, we are unable to determine at this time the degree to which the acute care hospital Start Printed Page 47927data fully represents IRF wages. However, we continue to believe it is an appropriate proxy because the hospital wage data is currently the most appropriate data for adjusting payments made to IRFs.

Several comments request the ability to allow IRFs to reclassify like that of acute care hospitals. To emphasize and as discussed in section VI.B.2, we believe that actual location of an IRF as opposed to the location of affiliated providers is most appropriate for determining the wage adjustment because the data support the premise that the prevailing wages in the area in which a facility is located influences the cost of a case. As demonstrated by the update rural adjustment and research conducted by RAND. The research and findings that update the rural adjustment is discussed in detail in section VI.B.4. We continue to review the facility adjustment to account for higher costs in different types of IRFs by updating our facility adjustments.

Final Decision: We believe that a wage index based on acute care hospital wage data is the best proxy and most appropriate wage index to use in adjusting payments to IRFs, since both acute care hospitals and IRFs compete in the same labor markets. Since acute care hospitals compete in the same labor market areas as IRFs, the wage data of acute care hospitals would accurately capture the relationship of wages and wage-related costs of IRF in an area as comparable to the national average.

Therefore, as we proposed in the FY 2006 proposed rule (70 FR 30188) and for this final rule, we continue to believe that a wage index based on acute care hospital data is the best and most appropriate wage index to use in adjusting payments to IRFs, since both acute care hospitals and IRFs compete in the same labor markets. Also, we will continue to use the same method for calculating wage indices as was indicated in the August 7, 2001 final rule (69 FR at 41357 through 41358). In addition, 1886(d)(8) and 1886(d)(10) of the Act which permits reclassification is applicable only to inpatient acute care hospitals at this time. The wage adjustment established under the IRF PPS is based on an IRF's actual location without regard to the urban or rural designation of any related or affiliated provider. Therefore, we continue to believe reclassification of IRFs is inappropriate at this time.

In adopting the CBSA-based designations, we recognize that there may be geographic areas where there are no hospitals, and thus no hospital wage data on which to base the calculation of the IRF PPS wage index. We found that for FY 2006, this occurred in two States—Massachusetts and Puerto Rico—where, using the CBSA-based designations, there were no hospitals located in rural areas. If rural IRFs open in Massachusetts or Puerto Rico for FY 2006, we proposed and for this final rule, we are using the rural FY 2001 MSA-based hospital wage data for Massachusetts and Puerto Rico to determine the wage index of such IRFs. In other words, we proposed and as finalized in this final rule, we will use the same wage data (the FY 2001 hospital wage data) used to calculate the FY 2006 IRF wage index. However, as we proposed in the FY 2006 proposed rule (70 FR 30188), for this final rule, rather than using CBSA-based designations, we will use MSA-based designations to determine the rural wage index of any States where there is no wage data available under the CBSA-based designations. By using such MSA-based designations there will be rural wage indices for both Massachusetts and Puerto Rico. We believe this is the most reasonable approach, as we are using the same hospital wage data used to calculate the CBSA-based wage indices.

In the event this occurs in urban areas where IRFs are located, as we proposed in the FY 2006 proposed rule (70 FR 30188), for this final rule, we will use the average of the urban hospital wage data throughout the State as a reasonable proxy for the urban areas without hospital wage data. Therefore, urban IRFs located in geographic areas without any hospital wage data will receive a wage index based on the average wage index for all urban areas within the State. This does not presently affect any urban IRFs for FY 2006 because there are no IRFs located in urban areas without hospital wage data. However, the policy will apply to future years when there may be urban IRFs located in geographic areas with no corresponding hospital wage data.

We believe this policy is reasonable because it maintains a CBSA-based wage index system, while creating an urban proxy for IRFs located in urban areas without corresponding hospital wage data. We note that we could not apply a similar averaging in rural areas, because in the rural areas there is no State rural hospital wage data available for averaging on a State-wide basis. For example, in Massachusetts and Puerto Rico, using a CBSA-based designation system, there are simply no rural hospitals in the State upon which we could base an average.

In addition, we note that the Secretary has broad authority under 1886(j)(6) to update the wage index on the basis of information available to the Secretary (and updated as appropriate) of the wages and wage-related costs incurred in furnishing rehabilitation services. Therefore, for FY 2006, as we proposed in the FY 2006 proposed rule (70 FR 30188), for this final rule, we will use FY 2001 MSA-based hospital wage data for rural Massachusetts and rural Puerto Rico in the event there are rural IRFs in such States. To clarify for rural areas without hospital wage data, we will use the most recent final years wage index available. In addition, for FY 2006 and thereafter, we are finalizing our proposed policy to calculate a statewide urban average in the event that there exist urban IRFs in geographic areas with no corresponding hospital wage data. Although we solicited comments on these approaches to calculate the wage index values for areas without hospital wage data for this and subsequent fiscal years, we did not receive any comments regarding our proposed methodology as discussed in our FY 2006 IRF PPS proposed rule. As a result, for any urban areas where there is no urban hospital wage data, we will calculate an average of the urban hospital wage data throughout the State as a reasonable proxy.

For the reasons discussed above, as we proposed in the FY 2006 proposed rule (70 FR 30188), for this final rule, we will continue the use of the acute care hospital inpatient wage index data generated from cost reporting periods beginning during FY 2001 without taking into account geographic reclassification as specified under sections 1886(d)(8) and (d)(10) of the Act and without applying the “rural floor” under section 4410 of Pub. L. 105-33 (BBA) (as discussed in section VI.B.2.a of this final rule). We believe that data from FY 2001 cost reporting periods to determine the applicable wage index values under the IRF PPS in this final rule are appropriate because these are the most recent final available data. These data are the same FY 2001 acute care hospital inpatient wage data that were used to compute the IPPS FY 2005 wage indices. The final IRF wage indices are computed as follows:

  • Compute an average hourly wage for each urban and rural area.
  • Compute a national average hourly wage.
  • Divide the average hourly wage for each urban and rural area by the national average hourly wage—the result is a wage index for each urban and rural area.

The one-year blended wage index values that are applicable for IRF PPS discharges occurring on or after October Start Printed Page 479281, 2005 and on or before September 30, 2006 are shown in Table 1 of the addendum of this final rule.

In addition, for this final rule as we proposed in the FY 2006 proposed rule (70 FR 30188), any adjustment or update to the IRF wage index made as specified under section 1886(j)(6) of the Act will be made in a budget neutral manner that assures that the estimated aggregated payments under this subsection in the FY year are not greater or less than those that will have been made in the year without such adjustment. Therefore, as we proposed in the FY 2006 proposed rule (70 FR 30188), for this final rule, we will calculate a budget-neutral wage adjustment factor as specified in § 412.624(e)(1). We will continue to use the following steps to ensure that the FY 2006 IRF standard payment conversion factor reflects the one-year blended FY 2006 MSA and CBSA wage indices (both based on FY 2001 hospital wage data) and to the labor-related share in a budget neutral manner:

Step 1 Determine the total amount of the estimated FY 2005 IRF PPS rates using the FY 2005 standard payment conversion factor and the labor-related share and the wage indices from FY 2005 (as published in the July 30, 2004 final notice).

Step 2 Calculate the total amount of estimated IRF PPS payments using the FY 2005 standard payment conversion factor and the updated CBSA-based FY 2006 labor-related share and FY 2006 blended wage indices described above.

Step 3 Divide the amount calculated in step 1 by the amount calculated in step 2, which equals the FY 2006 budget-neutral wage adjustment factor of 0.9995 (as discussed in section VI.B.7 and VI.B.8).

Step 4 Apply the FY 2006 budget-neutral wage adjustment factor from step 3 to the FY 2005 IRF PPS standard payment conversion factor after the application of the market basket update, described above, to determine the FY 2006 standard payment conversion factor.

3. Teaching Status Adjustment

In the FY 2006 proposed rule (70 FR 30188), we proposed to implement a teaching status adjustment for IRFs that are, or are part of, teaching institutions. Section 1886(j)(3)(A)(v) of the Act requires the Secretary to adjust the prospective payment rates for the IRF PPS by such factors as the Secretary determines are necessary to properly reflect variations in necessary costs of treatment among rehabilitation facilities. Under this authority, in the August 7, 2001 final rule (66 FR 41316, 41359), we considered implementing an adjustment for IRFs that are, or are part of, teaching institutions. However, because the results of our regression analysis, using FY 1999 data, showed that the indirect teaching cost variable was not significant, we did not implement a payment adjustment for indirect teaching costs in that final rule. The regression analysis conducted by RAND for the FY 2006 proposed rule (70 FR 30188), using FY 2003 data, shows that the indirect teaching cost variable is significant in explaining the higher costs of IRFs that have teaching programs. Therefore, we proposed to establish a facility level adjustment to the Federal per discharge base rate for IRFs that are, or are part of, teaching institutions for the reasons discussed below (the “teaching status adjustment”).

The purpose of the proposed teaching status adjustment is to account for the higher indirect operating costs experienced by facilities that participate in graduate medical education programs.

We proposed to implement the proposed teaching status adjustment in a budget neutral manner (that is, keeping estimated aggregate payments for FY 2006 with the proposed teaching adjustment the same as estimated aggregate payments for FY 2006 without the proposed teaching adjustment) for the reasons discussed below. (As a conforming change, we proposed to revise § 412.624 by adding a new section (e)(4) as the teaching status adjustment. Specifically, § 412.624(e)(4) would be for discharges on or after October 1, 2005. We proposed to adjust the Federal prospective payment on a facility basis by a factor that we specified for facilities that are teaching institutions or units of teaching institutions. We proposed that this adjustment be made on a claim basis as an interim payment and the final payment in full for the claim would be made during the final settlement of the cost report. Thus, we proposed to redesignate the current (e)(4) and (e)(5) as (e)(5) and (e)(6)).

Medicare makes direct graduate medical education (GME) payments (for direct costs such as resident and teaching physician salaries, and other direct teaching costs) to all teaching hospitals including those paid under the IPPS, and those that were once paid under the TEFRA rate of increase limits but are now paid under other PPSs. These direct GME payments are made separately from payments for hospital operating costs and are not part of the PPSs. However, the direct GME payments may not address the higher indirect operating costs which may often be experienced by teaching hospitals. For teaching hospitals paid under the TEFRA rate-of-increase limits, Medicare did not make separate medical education payments because payments to these hospitals were based on the hospitals' reasonable costs. Because payments under TEFRA were based on hospitals' reasonable costs, the higher indirect costs that might be associated with teaching programs would automatically have been factored into the TEFRA payments.

When the IRF PPS was implemented, we did not adjust payments to IRFs for indirect medical education costs because we did not find that adjustments for such costs were supported by the regression analyses or by the impact analyses. As discussed in the August 7, 2001 final rule (69 FR 41316, 41359), the indirect teaching variable was not significant for either the fully specified regression or the payment regression in RAND's analysis. Furthermore, the impacts among the various classes of facilities reflecting the fully phased-in IRF PPS illustrated that IRFs with the highest measure of indirect teaching would lose approximately 2 percent of estimated payments under the IRF PPS when compared with payments under TEFRA rate-of-increase limits. These impacts did not account for changes in behavior that facilities were likely to adopt in response to the inherent incentives of the IRF PPS, and we believed that IRFs could change their behavior to mitigate any potential reduction in payments.

The earlier research conducted by RAND was based on 1999 data and on a sample of IRFs. RAND recently conducted research to support us in developing potential refinements to the IRF classification system and the PPS. The regression analysis conducted by RAND for this final rule, using FY 2003 data, showed that the indirect teaching cost variable is significant in explaining the higher costs of IRFs that have teaching programs.

In conducting the analysis on the FY 2003 data, RAND used the resident counts that were reported on the hospital cost reports (worksheet S-3, Part 1, line 25, column 9 for freestanding IRF hospitals and worksheet S-3, Part 1, line 14 (or line 14.01 for subprovider 2), column 9 for rehabilitation units of acute care hospitals). That is, for the freestanding rehabilitation hospitals, RAND used the number of residents and interns reported for the entire hospital. For the rehabilitation units of acute care hospitals, RAND used the number of residents and interns reported for the rehabilitation unit (reported separately Start Printed Page 47929on the cost report from the number reported for the rest of the hospital). RAND did not distinguish between different types of resident specialties, nor did they distinguish among the different types of services residents provide, because this information is not reported on the cost reports.

RAND used regression analysis (with the logarithm of costs as the dependent variable) to re-examine the effect of IRFs' teaching status on the costs of care. With FY 2003 data that include all Medicare-covered IRF discharges, RAND found a statistically significant difference in costs between IRFs with teaching programs and those without teaching programs in the regression analysis. The different results obtained using the FY 2003 data (compared with the 1999 data) may be due to improvements in IRF coding after implementation of the IRF PPS. More accurately coded data may have allowed RAND to determine better the differences in case mix among hospitals with and without teaching programs, which would then have allowed the effect of whether or not an IRF has a teaching program to become significant in the regression analysis. There are two main reasons that indirect operating costs may be higher in teaching hospitals: (1) Because the teaching activities themselves result in inefficiencies that increase costs, and (2) because patients needing more costly services tend to be treated more often in teaching hospitals than in non-teaching hospitals, that is, the case mix that is drawn to teaching hospitals. Quantifying more precisely the amount of cost increase that is due to teaching hospitals' case mix allows RAND to more precisely quantify the amount of increase due to the inefficiencies associated with a teaching program.

We proposed to treat the teaching status adjustment as an additional payment to the Federal prospective payment rate, similar to the IME payments made under the IPPS (see § 412.105). In addition, we proposed that the teaching status adjustments for the IRF PPS facilities would be made on a claim basis as interim payments, but the final payment in full for the cost reporting period would be made through the cost report. The difference between those interim payments and the actual teaching status adjustment amount computed in the cost report would be adjusted through lump sum payments/recoupments when the cost report is filed and later settled.

As in the IPF PPS, we proposed to calculate a teaching adjustment based on the IRF's “teaching variable,” which would be one plus the ratio of the number of FTE residents training in the IRF (subject to limitations described further below) to the IRF's average daily census (ADC). In RAND's cost regressions for the FY 2006 proposed rule (70 FR 30188), using data from FY 2003, the logarithm of the teaching variable had a coefficient value of 1.083. We proposed to convert this cost effect to a teaching status payment adjustment by treating the regression coefficient as an exponent and raising the teaching variable to a power equal to the coefficient value, then estimated at 1.083 (that is, the teaching status adjustment would be calculated by raising the teaching variable (1 + FTE residents/ADC) to the 1.083 power). For a facility with a teaching variable of 0.10, and using a coefficient based upon the coefficient value (1.083) from the FY 2003 data, this method would yield a 10.9 percent increase in the per discharge payment; for a facility with a teaching variable of 0.05, the payment would increase by 5.4 percent. We note that the coefficient value of 1.083 was based on regression analysis holding all other components of the payment system constant. In the FY 2006 proposed rule (70 FR 30188) we noted that, because we were proposing a number of other revisions to the payment system, the coefficient value was subject to change for the final rule depending on the other revisions included in the final rule. Moreover, we noted that we had concerns that IRFs' responses to other proposed changes described in the FY 2006 proposed rule (70 FR 30188) would influence the effects of a teaching variable on IRFs' costs.

In addition, we proposed that the teaching adjustment limit the incentives for IRFs to add FTE residents for the purpose of increasing their teaching adjustment, as has been done in the payment systems for psychiatric facilities and acute inpatient hospitals. Thus, we proposed to impose a cap on the number of FTE residents that may be counted for purposes of calculating the teaching adjustment, similar to that established by sections 4621 (IME FTE cap for IPPS hospitals) and 4623 (direct GME FTE cap for all hospitals) of the BBA. We noted that the FTE resident cap already applies to teaching hospitals, including IRFs, for purposes of direct GME payments as specified in § 413.75 through § 413.83. The proposed cap would limit the number of residents that teaching hospitals may count for the purposes of calculating the IRF PPS teaching status adjustment, not the number of residents teaching institutions can hire or train.

The proposed FTE resident cap would be identical in freestanding teaching rehabilitation hospitals and in distinct part rehabilitation units with GME programs. Similar to the regulations for counting FTE residents under the IPPS as described in § 412.105(f), we proposed to calculate a number of FTE residents that trained in the IRF during a “base year” and use that FTE resident number as the cap. An IRF's FTE resident cap would ultimately be determined based on the final settlement of the IRF's most recent cost reporting period ending on or before November 15, 2003. We also proposed that, similar to new IPPS teaching hospitals, IRFs that first begin training residents after November 15, 2003 would initially receive an FTE cap of “0”. The FTE caps for new IRFs (as well as existing IRFs) that start training residents in a new GME program (as defined in § 413.79(l)) may be subsequently adjusted in accordance with the policies that are being applied in the IPF PPS (as described in § 412.424(d)(1)(iii)(B)(2)), which in turn are made in accordance with the policies described in 42 CFR 413.79(e) for IPPS hospitals. However, contrary to the policy for IME FTE resident caps under the IPPS, we would not allow IRFs to aggregate the FTE resident caps used to compute the IRF PPS teaching status adjustment through affiliation agreements. We proposed these policies because we believe it is important to limit the total pool of resident FTE cap positions within the IRF community and avoid incentives for IRFs to add FTE residents in order to increase their payments. In proposing not to allow affiliation agreements, we also wanted to avoid the possibility of hospitals transferring residents between IPPS and IRF training settings in order to increase Medicare payments. We recognize that under the regulations applicable to the IPPS IME adjustment, a new teaching hospital that trains residents from an existing program (not a new program as defined in 42 CFR 413.79(l)) can receive an adjustment to its IME FTE cap by entering into a Medicare GME affiliation agreement (see § 412.105(f)(1)(vi), § 413.75(b), and § 413.79(f)) with other hospitals. However, this option would not be available to new teaching IRFs because, as noted above, we proposed not to allow IRFs to aggregate the FTE resident caps used to compute the IRF PPS teaching adjustment through affiliation agreements.

We also proposed that residents with less than full-time status and residents rotating through the rehabilitation hospital or unit for less than a full year Start Printed Page 47930be counted in proportion to the time they spend in their assignment with the IRF (for example, a resident on a full-time, 3-month rotation to the IRF would be counted as 0.25 FTEs for purposes of counting residents to calculate the ratio). No FTE resident time counted for purposes of the IPPS IME adjustment would be allowed to be counted for purposes of the teaching status adjustment for the IRF PPS.

We proposed that the denominator used to calculate the teaching status adjustment under the IRF PPS would be the IRF's average daily census (ADC) from the current cost reporting period because it is closely related to the IRF's patient load, which determines the number of interns and residents the IRF can train. We also believe the ADC is a measure that can be defined precisely and is difficult to manipulate. Although the IPPS IME adjustment uses the hospital's number of beds as the denominator, the capital PPS (as specified at § 412.322) and the IPF PPS (as specified at § 412.424) both use the ADC as the denominator for the indirect graduate medical education adjustments.

If a rehabilitation hospital or unit has more FTE residents in a given year than in the base year (the base year being used to establish the cap), we would base payments in that year on the lower number (the cap amount). This approach would be consistent with the IME adjustment under the IPPS and the IPF PPS. The IRF would be free to add FTE residents above the cap amount, but it would not be allowed to count the number of FTE residents above the cap for purposes of calculating the teaching adjustment. This means that the cap would be an upper limit on the number of FTE residents that may be counted for purposes of calculating the teaching status adjustment. IRFs could adjust their number of FTE residents counted for purposes of calculating the teaching adjustment as long as they remained under the cap.

On the other hand, if a rehabilitation hospital or unit were to have fewer FTE residents in a given year than in the base year (that is, fewer residents than its FTE resident cap), an adjustment in payments in that year would be based on the lower number (the actual number of FTE residents the facility hires and trains). We proposed to implement the teaching status adjustment in such a way that total estimated aggregate payments to IRFs for FY 2006 would be the same with and without the proposed adjustment (that is, in a budget neutral manner). This is because we believe that the results of RAND's analysis of 2002 and 2003 IRF cost data suggest that additional money does not need to be added to the IRF PPS. RAND's analysis found, for example, that if all IRFs had been paid based on 100 percent of the IRF PPS payment rates throughout all of 2002 (some IRFs were still transitioning to PPS payments during 2002), PPS payments during 2002 would have been 17 percent higher than IRFs' costs. We noted that we were open to examining other evidence regarding the amount of aggregate payments in the system.

An adjustment to payments based on an IRF's teaching status is consistent with section 1886 (j)(3)(A)(v) of the Act, which confers broad statutory authority upon the Secretary to adjust the per payment unit payment rate by such factors as the Secretary determines are necessary to properly reflect variations in necessary costs of treatment among rehabilitation facilities.

In the FY 2006 proposed rule, we discussed some concerns we had with implementing a teaching status adjustment at this time, including concerns about the volatility of the data, concerns about the effect that other proposed changes could have on the magnitude of the teaching status adjustment, and concerns about the best way to count residents who provide services to IRF patients. These concerns are described in more detail in the FY 2006 proposed rule (70 FR 30188). As a result of these concerns, we specifically solicited comments on our consideration of a teaching status adjustment.

Public comments and our responses on the proposed teaching status adjustment are summarized below.

Comment: Several commenters questioned CMS's rationale for not allowing affiliation agreements, if CMS is only concerned about not increasing the pool of residents in IRFs. One commenter suggested that allowing affiliation agreements among IRFs would not necessarily increase the total pool of residents in IRFs.

Response: In the FY 2006 proposed rule (70 FR 30188), we stated that we are not allowing IRFs to enter into affiliation agreements with IPPS hospitals for the purposes of aggregating the FTE resident caps because we want to avoid the possibility that hospitals will transfer residents between IPPS and IRF training settings in order to increase Medicare payments. In deciding on our proposal not to allow affiliation agreements under the IRF PPS, we considered several factors. First, in general, we considered that IPPS hospitals provide training to residents in a wide range of specialties. Because of the wide variety of training provided, IPPS hospitals often need to send residents to train at other hospitals, since the case mix of one hospital might not be sufficiently broad to provide residents with an acceptable range of training opportunities in a particular specialty. The broad nature of the training offered at IPPS hospitals, and hence, the need to cross-train residents, is a primary reason for permitting IPPS hospitals under the Balanced Budget Act of 1997 to enter into GME affiliation agreements with other IPPS hospitals. However, because IRFs are a highly specialized type of provider, we do not believe that a significant amount of cross-training is required among IRFs. Although we imagine that there could be instances in which residents training in one IRF could receive a different type of training experience in another IRF, we believe these situations are likely to be limited and do not warrant having an affiliation agreement policy to allow IRFs to aggregate their FTE resident caps for the teaching status adjustment. Furthermore, we note that even without a specific affiliations policy, IRFs are not precluded from cross-training residents amongst themselves or with IPPS hospitals. If cross-training is necessary, it can be done in such a way that the overall number of FTE residents training in each facility remains unchanged. Accordingly, we are finalizing our proposed policy to not create a specific GME affiliation provision for the IRF teaching status adjustment. In the future, if we find there is in fact a need to allow affiliation agreements among IRFs, we may consider revising this policy in a future rulemaking process.

Comment: Several commenters noted possible inaccuracies in the teaching status information for a few of the facilities in the rate setting file we posted on the CMS website in conjunction with the FY 2006 proposed rule (70 FR 30188).

Response: To clarify, the rate setting file posted on the CMS website will not be used to determine payments for providers. The fiscal intermediaries use their own data files to determine whether the IRFs under their responsibility qualify for teaching status adjustment payments and the amounts of any such payments. Therefore, if providers have concerns about their particular teaching status data, they should contact their fiscal intermediaries to ensure that the fiscal intermediaries have the correct information.

With regard to the information in the rate setting file posted on the CMS website, this information was used to compute the value of the coefficient used as the exponent in the formula for Start Printed Page 47931the proposed teaching status adjustment. Consequently, we asked RAND to investigate the accuracy of the information. RAND has made the appropriate corrections to the information and, using the revised information, has recomputed the coefficient used as the exponent. Based on this and the incorporation of the HealthSouth home office cost data from FY 2004 (as described in detail in section IV of this final rule), we have revised the exponent from 1.083, which is what we had proposed in the FY 2006 proposed rule (70 FR 30188), to 0.9012 for this final rule.

Comment: Several commenters objected to our proposal to implement the proposed teaching adjustment based on analysis of one year of data. However, several other commenters suggested that such concerns were unfounded and did not warrant overriding RAND's statistically valid findings.

Response: Since publication of the FY 2006 proposed rule (70 FR 30188), RAND has further analyzed FY 2002 and FY 2003 data, and has found that the teaching status variable is significantly related to costs in both sets of data. Furthermore, we believe that IRFs with teaching programs may have been underrepresented in the 1998 and 1999 data used to construct the IRF PPS, and that this may have contributed to the lack of a statistically significant finding using the pre-PPS data. In addition, the statistically significant difference in costs between teaching and non-teaching facilities has been validated in other inpatient settings, including IPPS hospitals and IPFs. Therefore, we are reassured that this result does not represent an aberration based on only a single year's data, but instead represents a result of using more recent, more complete data. However, we will continue to evaluate the need for this adjustment in the future. If we later find that the other refinements described in this final rule constitute enough of an improvement to the system by more appropriately accounting for the variation in costs among different types of IRF patients that the teaching status adjustment becomes unnecessary, we will consider eliminating the adjustment in the future. However, we believe there is enough evidence at this time that IRFs with teaching programs have higher costs to implement the adjustment.

Comment: One commenter requested that CMS change the data that will be used to establish the FTE resident cap for IRFs from our proposal to use IRFs' most recent cost reporting periods ending on or before November 15, 2003, to use IRFs' most recent cost reporting periods ending on or before November 15, 2004 to ensure that the FTE resident caps will be based on the most accurate historical resident count data possible.

Response: We agree with this commenter and are revising our methodology for setting the FTE resident cap accordingly. Since we published the FY 2006 proposed rule (70 FR 30188), the FTE resident cap used for the teaching status adjustment for IPFs has been set similarly based on cost reporting periods ending on or before November 15, 2004. We believe this change is appropriate and maintains consistency within the Medicare program.

Comment: One commenter requested that CMS have a process in place for re-examining the teaching status data, especially the data used to set the FTE resident cap, so that facilities would have the opportunity to rectify any problems with the data that might affect payments.

Response: We agree with this commenter. We recognize that there may be problems with some of the resident count data on the historical cost reports, since this data has not previously been used for payment adjustments in the IRF PPS. For this reason, we proposed in the FY 2006 proposed rule (70 FR 30188) that an IRF's FTE resident cap would ultimately be determined based on the final settlement of the IRF's most recent cost reporting period ending on or before November 15, 2003 and, based on this and the previous comment (refer to the response above), we are changing this to the final settlement of the IRF's most recent cost reporting period ending on or before November 15, 2004. We believe this will allow facilities the opportunity to ensure the accuracy of the FTE resident count data before the final settlement of the cost report data. In case this does not occur, we will authorize the fiscal intermediaries to resolve any disputes that may occur regarding the data used to set an IRF's FTE resident cap and correct any inaccuracies.

With regard to the FTE resident count data or the average daily census data used to compute an IRF's teaching status adjustment, we specifically note in this final rule that any teaching status adjustments for the IRF PPS facilities will be made on a claim basis as interim payments, but the final payments in full for the cost reporting periods will be made through the final settlement of the cost report. The difference between the interim payments and the actual teaching status adjustment amounts computed in the cost reports will be adjusted through lump sum payments/recoupments when the cost report is filed and later settled. We believe this process gives providers and fiscal intermediaries ample opportunity to ensure that the data used to compute the teaching status adjustment payments is as complete and accurate as possible. As the proposed teaching status adjustment is implemented, we will monitor the situation and issue further guidance to the fiscal intermediaries as necessary to ensure fair and accurate payments for this adjustment.

Comment: The majority of commenters expressed support for CMS eventually implementing an IRF teaching status adjustment, especially since teaching IRFs were likely underrepresented in the 1998 and 1999 data used in the August 7, 2001 final rule to design the IRF PPS. However, while supporting the adjustment, several commenters suggested that CMS wait to implement a teaching status adjustment for at least a year, until data from FY 2004 (or later) can be analyzed.

Response: CMS considered carefully the suggestion to wait an additional year or more before implementing the proposed teaching status adjustment. However, RAND's regression analyses of calendar year 2002 and FY 2003 data both support the need for a teaching status adjustment for IRFs because they both indicate that IRFs with teaching programs have significantly higher costs than IRFs without teaching programs. Given RAND's findings, we believe it is important to adjust IRF payments accordingly in order to better align IRF payments with the costs of care. In addition, we believe it is important to maintain consistency with other parts of the Medicare program, such as the IPF PPS that recently instituted a teaching status adjustment for IPFs based on regression analysis that shows that IPFs with teaching programs have significantly higher costs than IPFs without teaching programs.

Comment: Several commenters strongly disagreed with the proposed implementation of a teaching status adjustment for IRFs. Among the reasons cited were that it was based on analysis of a single year of data, that it would support inefficiencies in teaching hospitals (when the purpose of a PPS is to encourage providers to operate efficiently), that the data do not adequately support the need for a teaching status adjustment, that it would reduce payments to non-teaching hospitals, and that teaching hospitals would likely continue to operate even if they do not receive the adjustment.

Response: We carefully considered these comments. However, we continue Start Printed Page 47932to believe that an IRF teaching status adjustment is warranted at this time because RAND's regression analysis, based on calendar year 2002 and FY 2003 data shows that IRFs with teaching programs have significantly higher costs than non-teaching IRFs. Although we do not believe it is appropriate to encourage or perpetuate inefficiencies, we believe that IRFs with teaching programs provide a valuable service to beneficiaries and to the Medicare program. To the extent that the residency training services, therefore, lead to higher indirect costs of providing care, we believe it is important to recognize these differences and encourage access to care in these facilities. While, as one commenter notes, teaching IRFs more than likely would continue to operate even without the IRF teaching status adjustment, the intent of the adjustment is to better align payments in these facilities with the costs of care.

Furthermore, we believe that IRFs with teaching programs may have been underrepresented in the 1998 and 1999 data used to construct the IRF PPS, and that this may have contributed to the lack of a statistically significant finding using the pre-PPS data. In addition, the statistically significant difference in costs between teaching and non-teaching facilities has been validated in other inpatient settings, including IPPS hospitals and IPFs.

We proposed, and are finalizing in this final rule, to implement the IRF teaching status adjustment in a budget neutral manner in order to ensure that estimated aggregate payments to IRFs for FY 2006 will be the same with or without the teaching status adjustment. Given that the impact on IRFs without teaching programs of this provision is not large (see Table 13 of this final rule), we do not believe that implementing the teaching status adjustment in a budget neutral manner will unduly affect non-teaching IRFs. However, the teaching status adjustment will help to better align payments with the costs of care in teaching IRFs.

Furthermore, we believe that a teaching status adjustment for IRFs is consistent with the teaching status adjustment recently implemented in the IPF PPS.

Comment: One commenter suggested that CMS track the percentage of time residents spend in the rehabilitation unit of the hospital to compute the teaching adjustment, instead of using the resident and intern to ADC ratio we proposed in the proposed rule.

Response: This information is not currently captured in the cost report data, which would make this suggestion substantially more difficult to implement than the teaching status variable we proposed in the FY 2006 proposed rule (70 FR 30188). We also believe that collecting this type of information would impose additional costs on acute care hospitals that have IRF units, because they would be required to record the amount of time residents spend on rehabilitation units. We also believe that it would be difficult if not impossible to audit this type of information.

Comment: One commenter suggested that CMS focus the teaching adjustment on rehabilitation education programs, to the exclusion of other resident training programs.

Response: Information on resident specialties is not currently reported in the cost report data. We believe that collecting and reporting this new type of data would impose undue additional costs on IRFs and on hospitals that have IRF units. Furthermore, we believe that this policy would contradict the way that residency programs traditionally operate because they require residents from different specialties to rotate in different areas of the hospital to gain experience in various areas of medicine.

Comment: One commenter recommended that an exception process be allowed to enable IRF teaching programs to apply for an increase in their cap should a compelling reason arise, such as an expansion of the teaching hospital or unit or the addition of a new program.

Response: Similar to the GME resident cap policy for IPPS hospitals, we will not allow exceptions to the FTE resident caps for IRFs due to expansions of existing facilities or additions of new teaching programs. As we indicated previously, we believe it is important to limit the total pool of FTE resident cap positions within the IRF community.

Final Decision: After carefully considering all of the comments we received on the proposed IRF teaching status adjustment, we are finalizing our decision to adopt the proposed policy in this final rule, with the following revisions.

In RAND's most recent cost regressions using data from FY 2003, including the HealthSouth home office cost data from FY 2004 (as described in detail in section IV of this final rule), the logarithm of the teaching variable has a coefficient value of 0.9012 (as opposed to the coefficient value of 1.083 we proposed in the FY 2006 proposed rule (70 FR 30188)). In the final policy, we are converting this cost effect to a teaching status payment adjustment by treating the regression coefficient as an exponent and raising the teaching variable to a power equal to the coefficient value of 0.9012 (that is, the teaching status adjustment would be calculated by raising the teaching variable (1 + FTE residents/ADC) to the 0.9012 power).

Secondly, based on a commenter's suggestion, we are changing the base period for determining an IRF's FTE resident cap from the final settlement of the IRF's most recent cost reporting period ending on or before November 15, 2003, which was what we had proposed in the FY 2006 proposed rule (70 FR 30188), to the final settlement of the IRF's most recent cost reporting period ending on or before November 15, 2004. Thus, the policy in the IRF PPS would be consistent with the FTE resident cap policy in the IPF PPS.

4. Adjustment for Rural Location

In the FY 2006 proposed rule (70 FR 30188), we proposed to update the adjustment to the Federal prospective payment amount for IRFs located in rural areas from 19.14 percent to 24.1 percent, based on analysis of FY 2003 data. Consistent with the broad statutory authority conferred upon the Secretary in section 1886(j)(3)(A)(v) of the Act, we adjust the Federal prospective payment amount associated with a CMG to account for an IRF's geographic wage variation, low-income patients and, if applicable, teaching status and location in a rural area, as described in § 412.624(e).

Under the broad statutory authority conferred upon the Secretary in section 1886(j)(3)(A)(v) of the Act, we proposed to increase the adjustment to the Federal prospective payment amount for IRFs located in rural areas from 19.14 percent to 24.1 percent. We proposed this change because RAND's regression analysis, using the best available data we had (FY 2003), indicated that rural facilities had 24.1 percent higher costs of caring for Medicare patients than urban facilities. We noted that we proposed to use the same statistical approach, as described in the November 3, 2000 proposed rule (65 FR 66304, 66356 through 66357) and adopted in the August 7, 2001 final rule (66 FR at 41359) to estimate the proposed update to the rural adjustment. The statistical approach RAND used when the PPS was first implemented, for the FY 2006 proposed rule (70 FR 30188), and for this final rule relies on the coefficient determined from the regression analysis. The 19.14 percent rural adjustment has been applied to payments for IRFs located in rural areas since the implementation of the IRF PPS. We noted that the FY 2003 data are the best available data we have, just as the 1998 Start Printed Page 47933and 1999 data used in the initial development of the IRF PPS were the best available data at that time.

We proposed to implement the proposed update to the rural adjustment so that total estimated aggregate payments for FY 2006 are the same with the proposed update to the adjustment as they would have been without the proposed update to the adjustment (that is, in a budget neutral manner). We proposed to make this update to the rural adjustment in a budget neutral manner because we believed and continue to believe that the results of RAND's analysis of 2002 and 2003 IRF cost data (as discussed previously in section IV of this final rule) suggest that additional money does not need to be added to the IRF PPS. RAND's analysis found, for example, that if all IRFs had been paid based on 100 percent of the IRF PPS payment rates throughout all of 2002 (some IRFs were still transitioning to PPS payments during 2002), PPS payments during 2002 would have been 17 percent higher than IRFs' costs.

This is consistent with section 1886(j)(3)(A)(v) of the Act which confers broad statutory authority upon the Secretary to adjust the per payment unit payment rate by such factors as the Secretary determines are necessary to properly reflect variations in necessary costs of treatment among rehabilitation facilities. To ensure that total estimated aggregate payments to IRFs do not change, we proposed to apply a factor to the standard payment amount to ensure that the estimated aggregate payments under this subsection in the FY are not greater or less than those that would have been made in the year without the proposed update to the adjustment. In sections VI.B.7 and VI.B.8 of this final rule, we discuss the methodology and factor we proposed to apply to the standard payment amount.

Public comments and our responses on the proposed update to the rural adjustment are summarized below.

Comment: Overall, commenters generally supported this proposal. Some said that CMS should delay implementing the proposal until the full effects of the 75 percent rule can be analyzed.

Response: For the reasons discussed in section IV of this final rule, we do not believe we should wait until the full effects of the 75 percent rule can be analyzed before implementing any of the proposed changes in this final rule. Making the changes now does not preclude us from making additional revisions in the future if we find any potential effects of the 75 percent rule on IRFs' case mix or cost structures that would warrant such refinements.

Comment: One commenter expressed concerns that the proposed increases to the facility-level adjustments would encourage inefficiencies in the provision of care.

Response: While we agree with the commenter that one of the purposes of a PPS is to encourage the efficient provision of services, we also believe it is important to recognize that certain providers, such as those operating in rural areas, may incur higher costs than other providers, for reasons largely beyond their control. To encourage the efficient provision of care in rural areas, so that Medicare beneficiaries have adequate access to IRF services in these areas, we believe it is important to recognize the differential in costs between urban and rural providers.

Final Decision: After carefully considering all of the comments we received on this proposed change to the rural adjustment, we are finalizing our decision to adopt the update to the rural adjustment in this final rule, with the following change.

In RAND's most recent cost regressions using data from FY 2003, including the HealthSouth home office cost data from FY 2004 (as described in detail in section IV of this final rule), rural facilities were found to have 21.3 percent higher costs of caring for Medicare patients than urban facilities (rather than the 24.1 percent we proposed in the FY 2006 proposed rule (70 FR 30188)). Thus, we are implementing a rural adjustment of 21.3 percent.

5. Adjustment for Disproportionate Share of Low-Income Patients

In the FY 2006 proposed rule (70 FR 30188), we proposed to update the low-income patient (LIP) adjustment to the Federal prospective payment rate, based on analysis of FY 2003 data. Consistent with the broad statutory authority conferred upon the Secretary in section 1886(j)(3)(A)(v) of the Act, we adjust the Federal prospective payment amount associated with a CMG to account for an IRF's geographic wage variation, low-income patients and, if applicable, teaching status and location in a rural area, as described in § 412.624(e).

Under the broad statutory authority conferred upon the Secretary in section 1886(j)(3)(A)(v) of the Act, we proposed to update the low-income patient (LIP) adjustment to the Federal prospective payment rate to account for differences in costs among IRFs associated with differences in the proportion of low-income patients they treat. RAND's regression analysis of 2003 data indicates that the LIP formula could be updated to better distribute current payments among facilities according to the proportion of low-income patients they treat. Although the formula used prior to October 1, 2005 appropriately distributed LIP-adjusted payments among facilities when the IRF PPS was first implemented, we believe the formula should be updated from time to time to reflect changes in the costs of caring for low-income patients.

The proposed LIP adjustment is based on the formula used to account for the costs of furnishing care to low-income patients as discussed in the August 7, 2001 final rule (67 FR at 41360). We proposed to update the LIP adjustment from the power of 0.4838 to the power of 0.636. Therefore, the formula we proposed to use to calculate the LIP adjustment was as follows:

(1 + DSH patient percentage) raised to the power of (0.636)

We note that we proposed to use the same statistical approach, as described in the August 7, 2001 final rule (66 FR at 41359 through 41360), that was used to develop the original LIP adjustment. We note that the FY 2003 data we proposed to use in calculating this adjustment are the best available data, just as the 1998 and 1999 data used in the initial development of the IRF PPS were the best available data at that time.

We proposed to implement this update to the LIP adjustment so that total estimated aggregate payments for FY 2006 would be the same with the proposed update to the adjustment as they would have been without the update to the adjustment (that is, in a budget neutral manner). We proposed to make this proposed update to the LIP adjustment in a budget neutral manner because we believed and continue to believe that the results of RAND's analysis of 2002 and 2003 IRF cost data (as discussed previously in this final rule) suggest that additional money does not need to be added to the IRF PPS. Start Printed Page 47934RAND's analysis found, for example, that if all IRFs had been paid based on 100 percent of the IRF PPS payment rates throughout all of 2002 (some IRFs were still transitioning to PPS payments during 2002), PPS payments during 2002 would have been 17 percent higher than IRFs' costs.

This is consistent with section 1886 (j)(3)(A)(v) of the Act which confers broad statutory authority upon the Secretary to adjust the per payment unit payment rate by such factors as the Secretary determines are necessary to properly reflect variations in necessary costs of treatment among rehabilitation facilities. To ensure that total estimated aggregate payments to IRFs do not change, we proposed to apply a factor to the standard payment amount to ensure that the estimated aggregate payments under this subsection in the FY are not greater or less than those that would have been made in the year without the proposed update to the adjustment. In sections VI.B.7 and VI.B.8 of this final rule, we discuss the methodology and factor we proposed to apply to the standard payment amount.

Public comments and our responses on the proposed update to the LIP adjustment are summarized below.

Comment: Overall, commenters generally supported this proposal. Some said that CMS should delay implementing the proposal until the full effects of the 75 percent rule can be analyzed.

Response: For the reasons discussed in section IV of this final rule, we do not believe we should wait until the full effects of the 75 percent rule can be analyzed before implementing any of the proposed changes in this final rule. Making the changes now does not preclude us from making additional revisions in the future if we find any potential effects of the 75 percent rule on IRFs' case mix or cost structures that would warrant such refinements.

Comment: One commenter expressed concerns that the proposed increases to the facility-level adjustments would encourage inefficiencies in the provision of care.

Response: While we agree with the commenter that one of the purposes of a PPS is to encourage the efficient provision of services, we also believe it is important to recognize that certain providers, such as those providers that treat a higher proportion of low-income patients, may incur higher costs than other providers, for reasons largely beyond their control. To encourage the efficient provision of care among providers that treat a large number of low-income patients, so that low-income Medicare beneficiaries have adequate access to IRF services, we believe it is important to recognize the higher costs these providers incur.

Final Decision: After carefully considering all of the comments we received on this proposed change to the LIP adjustment, we are finalizing our decision to adopt the proposed policy in this final rule, with the following change.

Based on RAND's most recent cost regressions using data from FY 2003, including the HealthSouth home office cost data from FY 2004 (as described in detail in section IV of this final rule), we are updating the LIP adjustment to the power of 0.6229 (rather than the value of 0.636 we proposed in the FY 2006 proposed rule (70 FR 30188)). Therefore, the formula for calculating the LIP adjustment will be as follows: (1 + DSH patient percentage) raised to the power of (0.6229) where the DSH patient percentage =

6. Update to the Outlier Threshold Amount

In the FY 2006 proposed rule (70 FR 30188), we proposed to update the outlier threshold amount, based on analysis of FY 2003 data. Consistent with the broad statutory authority conferred upon the Secretary in sections 1886(j)(4)(A)(i) and 1886(j)(4)(A)(ii) of the Act, we proposed to update the outlier threshold amount from the $11,211 threshold amount for FY 2005 to $4,911 in FY 2006 to maintain total estimated outlier payments at 3 percent of total estimated payments. In the August 7, 2001 final rule, we discussed our rationale for setting estimated outlier payments at 3 percent of total estimated payments (66 FR at 41362). In the FY 2006 proposed rule (70 FR 30188), we proposed to continue using 3 percent for the same reasons outlined in the August 7, 2001 final rule. We believed and continue to believe that it is necessary to update the outlier threshold amount because RAND's analysis of the calendar year 2002 and FY 2003 data indicates that total estimated outlier payments will not equal 3 percent of total estimated payments in FY 2006 unless we update the outlier loss threshold. We will continue to analyze the estimated outlier payments for subsequent years and adjust as appropriate in order to maintain estimated outlier payments at 3 percent of total estimated payments. The reasons for estimated outlier payments not equaling 3 percent of total estimated payments are discussed in more detail below.

Section 1886(j)(4) of the Act provides the Secretary with the authority to make payments in addition to the basic IRF prospective payments for cases incurring extraordinarily high costs. In the August 7, 2001 final rule, we codified at § 412.624(e)(4) of the regulations (which we proposed to redesignate as § 412.624(e)(5) in the FY 2006 proposed rule (70 FR 30188)) the provision to make an adjustment for additional payments for outlier cases that have extraordinarily high costs relative to the costs of most discharges. Providing additional payments for outliers strongly improves the accuracy of the IRF PPS in determining resource costs at the patient and facility level because facilities receive additional compensation over and above the adjusted Federal prospective payment amount for uniquely high-cost cases. These additional payments reduce the financial losses that would otherwise be caused by treating patients who require more costly care and, therefore, reduce the incentives to underserve these patients.

Under § 412.624(e)(4) (which we proposed to redesignate as § 412.624(e)(5) in the FY 2006 proposed rule (70 FR 30188)), we would make outlier payments for any discharges if the estimated cost of a case exceeds the adjusted IRF PPS payment for the CMG plus the adjusted threshold amount. In the FY 2006 proposed rule (70 FR 30188), we proposed to make this $4,911, which would then be adjusted for each IRF by the facility's wage adjustment, its LIP adjustment, its rural adjustment, and its teaching status adjustment, if applicable. In the FY 2006 proposed rule (70 FR 30188), we stated that we would calculate the estimated cost of a case by multiplying the IRF's overall cost-to-charge ratio by the Medicare allowable covered charge. In accordance with § 412.624(e)(4) (which we proposed in the FY 2006 proposed rule (70 FR 30188) to Start Printed Page 47935redesignate as § 412.624(e)(5)), we also stated that we would pay outlier cases 80 percent of the difference between the estimated cost of the case and the outlier threshold (the sum of the adjusted IRF PPS payment for the CMG and the adjusted fixed threshold dollar amount).

Consistent with the broad statutory authority conferred upon the Secretary in sections 1886(j)(4)(A)(i) and 1886(j)(4)(A)(ii) of the Act, and in accordance with the methodology stated in the August 1, 2003 final rule (68 FR at 45692 through 45693), we proposed in the FY 2006 proposed rule (70 FR 30188) to continue to apply a ceiling to an IRF's cost-to-charge ratios (CCR). Also, in the August 1, 2003 final rule (68 FR at 45693 through 45694), we stated the methodology we use to adjust IRF outlier payments and the methodology we use to make these adjustments. We indicated that the methodology is codified in § 412.624(e)(4) (which we proposed in the FY 2006 proposed rule (70 FR 30188) to redesignate as § 412.624(e)(5)) and § 412.84(i)(3).

On February 6, 2004, we issued manual instructions in Change Request 2998 stating that we would set forth the upper threshold (ceiling) and the national CCRs applicable to IRFs in each year's annual notice of prospective payment rates published in the Federal Register. The upper threshold CCR for IRFs that we proposed in the FY 2006 proposed rule (70 FR 30188) for FY 2006 would be 1.52 based on CBSA-based geographic designations. We proposed to base this upper threshold CCR on the CBSA-based geographic designations because the CBSAs are the geographic designations we proposed in the FY 2006 proposed rule (70 FR 30188) to adopt for purposes of computing the proposed wage index adjustment to IRF payments for FY 2006.

In addition, in the FY 2006 proposed rule (70 FR 30188), we proposed to update the national urban and rural CCRs for IRFs. Under § 412.624(e)(4) (which we proposed in the FY 2006 proposed rule (70 FR 30188) to redesignate as § 412.624(e)(5)) and § 412.84(i)(3), we proposed to apply the national CCRs to the following situations:

  • New IRFs that have not yet submitted their first Medicare cost report.
  • IRFs whose operating or capital CCR is in excess of 3 standard deviations above the corresponding national geometric mean.
  • Other IRFs for whom accurate data with which to calculate either an operating or capital CCR (or both) are not available.

In the FY 2006 proposed rule (70 FR 30188), we proposed to use the national CCR based on the facility location of either urban or rural in each of the three situations cited above. Specifically, for FY 2006, we estimated a proposed national CCR of 0.631 for rural IRFs and 0.518 for urban IRFs. For new facilities, we proposed to use these national ratios until the facility's actual CCR could be computed using the first tentative settled or final settled cost report data, which would then be used for the subsequent cost report period.

In the August 7, 2001 final rule (66 FR at 41362 through 41363), we describe the process by which we calculate the outlier threshold. In the FY 2006 proposed rule (70 FR 30188), we proposed to use this same process for the FY 2006 IRF PPS. We proposed to simulate aggregate payments with and without an outlier policy, and then apply an iterative process to determine a threshold that would result in the simulated outlier payments being equal to 3 percent of total simulated payments under the simulation. In the FY 2006 proposed rule (70 FR 30188), we noted that the simulation analysis used to calculate the proposed outlier threshold amount included all of the other proposed changes to the PPS discussed in the FY 2006 proposed rule (70 FR 30188). As stated in the FY 2006 proposed rule (70 FR 30188), we proposed to continue to analyze the estimated outlier payments for subsequent years and adjust as appropriate in order to maintain estimated outlier payments at 3 percent of total estimated payments.

In the FY 2006 proposed rule (70 FR 30188), we proposed to update the threshold amount so that estimated outlier payments would continue to equal 3 percent of total estimated payments under the IRF PPS. RAND found that 2002 outlier payments were equal to 3.1 percent of total payments in 2002. Nevertheless, the outlier loss threshold is affected by cost-to-charge ratios because the cost-to-charge ratios are used to compute the estimated cost of a case, which in turn is used to determine if a particular case qualifies for an outlier payment or not. For example, if the cost-to-charge ratio decreases, then the estimated costs of a case with the same reported charges would decrease. Thus, the chances that the case would exceed the outlier loss threshold and qualify for an outlier payment would decrease, decreasing the likelihood that the case would qualify for an outlier payment. If fewer cases were to qualify for outlier payments, then total estimated outlier payments could fall below 3 percent of total estimated payments.

As we discussed in the FY 2006 proposed rule (70 FR 30188), our analyses of cost report data from FY 1999 through FY 2002 (and projections for FY 2004 through FY 2006) indicate that the overall cost-to-charge ratios in IRFs have been falling since the IRF PPS was implemented. We are still analyzing possible reasons for this finding. However, because cost-to-charge ratios are used to determine whether a particular case qualifies for an outlier payment, this drop in the cost-to-charge ratios is likely responsible for much of the drop in total estimated outlier payments below 3 percent of total estimated payments. Thus, as we discussed in the FY 2006 proposed rule (70 FR 30188), the outlier threshold would need to be lowered for FY 2006 in order that total estimated outlier payments would equal 3 percent of total estimated payments.

In addition, we proposed in the FY 2006 proposed rule (70 FR 30188) to adjust the outlier threshold for FY 2006 because RAND's analysis of calendar year 2002 and FY 2003 data indicates that many of the other proposed changes discussed in the FY 2006 proposed rule (70 FR 30188) would affect what the outlier threshold would need to be in order for total estimated outlier payments to equal 3 percent of total estimated payments. The outlier loss threshold is affected by the definitions of all other elements of the IRF PPS, including the structure of the CMGs and the tiers, the relative weights, the policies for very short-stay cases and for cases in which the patient expires in the facility (that is, cases that qualify for the special CMG assignments), and the facility-level adjustments (such as the rural adjustment, the LIP adjustment, and the proposed teaching status adjustment). In the FY 2006 proposed rule (70 FR 30188), we proposed to change many of these components of the IRF PPS. For the reasons discussed above and in the FY 2006 proposed rule (70 FR 30188), then, we believed and continue to believe that it is appropriate to update the outlier loss threshold for FY 2006. We also stated in the FY 2006 proposed rule (70 FR 30188) that we expect to continue to adjust the outlier threshold in the future when the data indicate that total estimated outlier payments would deviate from equaling 3 percent of total estimated payments.

Public comments and our responses on the proposed update to the outlier threshold amount are summarized below. Start Printed Page 47936

Comment: One commenter suggested that CMS notify fiscal intermediaries that, as a result of the lowering of the outlier threshold amount, more cases would likely qualify for outlier payments. Such notification would enable the fiscal intermediaries to adjust their systems accordingly.

Response: We agree with the commenter's suggestion and will notify the fiscal intermediaries about the change to the outlier threshold amount and the implications of this for the number of cases that qualify for outlier payments.

Comment: Several commenters requested that CMS incorporate any unused outlier payments from years in which aggregate outlier payments are below the 3 percent target back into the base payments.

Response: We have responded to similar comments a number of times in the context of other prospective payment systems, including in rules at 70 FR 24168, 24196-24197, 57 FR 39784, 58 FR 46347, 59 FR 45408, 60 FR 45856, 61 FR 27496, and 56 FR 43227, 61 FR 46229-46230. As we have explained before and as explained below, we do not make adjustments to PPS payment rates to account for differences between projected and actual outlier payments in a previous year. We believe our outlier policies are consistent with the statute and the goals of the prospective payment system and are equitable.

In accordance with section 1886(j)(4) of the Act, we implemented the IRF PPS outlier policy at 42 CFR 412.624(d)(1). These regulations provide that CMS determines a reduction factor equal to the estimated proportion of additional outlier payments described in paragraph (e)(4) of this section (which is redesignated as (e)(5) in this final rule). We set outlier criteria before the beginning of each fiscal year so that outlier payments are projected to equal 3 percent of estimated total IRF PPS payments. In doing so, we use the best available data at the time to make our estimates. We do not believe that Congress intended that the standardized amounts for a given fiscal year should be adjusted (upward or downward) to reflect any difference between projected and actual outlier payments for a past year. Payments for a given discharge in a given fiscal year are generally intended to reflect or address the average costs of that discharge in that year; that goal would be undermined if we adjusted PPS payments to account for “underpayments” or “overpayments” in other years.

Outlier payments are “funded” through a prospective adjustment to the base rates. We do not set money aside into a discrete “pool” dedicated solely for outlier payments. Outlier payments are based on estimates. If outlier payments for a given year turn out to be greater than projected, we do not recoup money from hospitals; if outlier payments for a given year are lower than projected, we do not make an adjustment to account for the difference. If estimates turn out to be inaccurate, we believe the more appropriate action is to continue to examine the outlier policy and to try to refine the methodology for setting outlier thresholds. Thus, consistent with this approach, for this final rule we are finalizing our decision to update the outlier threshold amount to $5,132 for FY 2006 to make estimated outlier payments equal to 3 percent of total estimated IRF PPS payments in FY 2006.

Comment: One commenter indicated a concern about the methodology used by CMS to estimate cost and charge growth for the purposes of calculating the outlier threshold amount. This commenter recommended an alternative methodology for the IPPS and encouraged CMS to apply that same methodology to the IRF PPS to ensure that the full 3 percent of outlier funds is used.

Response: We have reviewed the comments submitted for consideration in the IPPS, and we appreciate the alternative methodologies suggested by the commenters and have considered them carefully. The cost-to-charge ratio applied to charges provides Medicare the most accurate measure of a provider's per-case cost for the purpose of paying for high-cost outlier cases at the point that we process the initial claim. The cost-to-charge ratio is based on the providers' own cost and charge information as reported by the providers. For the purposes of this final rule, we have used the same methodology for projecting cost and charge growth that is used in the IPPS and in other Medicare payment systems, and we believe this methodology is appropriate for IRFs for the same reasons it is appropriate for IPPS hospitals. This methodology ensures that we pay the appropriate amounts over and above the standard PPS payment amount for unusually high-cost cases.

Comment: Overall, commenters generally supported the proposal to decrease the outlier threshold. Some said that CMS should delay implementing the proposal until the full effects of the 75 percent rule can be analyzed.

Response: For the reasons discussed in section IV of this final rule, we do not believe we should wait until the full effects of the 75 percent rule can be analyzed before implementing any of the proposed changes in this final rule. Making the changes now does not preclude us from making additional revisions in the future if we find any potential effects of the 75 percent rule on IRFs' case mix or cost structures that would warrant such refinements.

Final Decision: After carefully considering all of the comments we received on this proposed change to the outlier threshold amount, we are finalizing our decision to adopt the proposed policy in this final rule (including the redesignation of § 412.624(e)(4) as § 412.624(e)(5)), with the following change.

Using data from FY 2003, and including the HealthSouth home office cost data from FY 2004 (as described in detail in section IV of this final rule), RAND has calculated the outlier threshold amount of $5,132 (instead of the $4,911 outlier threshold amount we proposed in the FY 2006 proposed rule (70 FR 30188)) that would maintain estimated outlier payments at 3 percent of total estimated IRF payments for FY 2006. Therefore, we are finalizing our decision to set the FY 2006 outlier loss threshold at $5,132.

In addition, we are finalizing our decision to adopt the proposed upper threshold CCR for IRFs for FY 2006 of 1.52 based on CBSA-based geographic designations. We are basing this upper threshold CCR on the CBSA-based geographic designations because the CBSAs are the geographic designations we are adopting (with a one-year transition policy as described in section VI.B.2.e of this final rule) for the purposes of computing the wage index adjustment to IRF payments for FY 2006.

We are also finalizing our decision to update the national urban and rural CCRs for IRFs. Under § 412.624(e)(4) (which we are redesignating as § 412.624(e)(5) in this final rule), we will apply the national CCRs to the following situations:

  • New IRFs that have not yet submitted their first Medicare cost report.
  • IRFs whose operating or capital CCR is in excess of 3 standard deviations above the corresponding national geometric mean.
  • Other IRFs for whom data with which to calculate either an operating or capital CCR (or both) are not available.

The national CCR based on the facility location of either urban or rural will be used in each of the three situations cited above. Specifically, for FY 2006, we are adopting a national CCR of 0.631 for Start Printed Page 47937rural IRFs and 0.518 for urban IRFs. For new facilities, we will use these national ratios until the facility's actual CCR can be computed using the first tentative settled or final settled cost report data, which will then be used for the subsequent cost report period.

7. Budget Neutrality Factor Methodology for Fiscal Year 2006

In the FY 2006 proposed rule (70 FR 30188), we proposed to make a revision (for FY 2006) to the methodology found in § 412.624(d) in order to make the proposed changes to the tiers and CMGs, the rural adjustment, the LIP adjustment, and the proposed teaching status adjustment in a budget neutral manner. Accordingly, we proposed to revise § 412.624(d) by adding a section § 412.624(d)(4) for fiscal year 2006 and, as applicable, for fiscal years thereafter to the extent the adjustments are updated in the future. Specifically, we proposed to revise the methodology found in § 412.624(d) by adding a new paragraph (d)(4). The addition of this paragraph would provide for the application of a factor, as specified by the Secretary, which would be applied to the standard payment amount in order to make the proposed changes described in the preamble of the FY 2006 proposed rule (70 FR 30188) in a budget neutral manner for FY 2006. In addition, this paragraph would be used in future years if we propose refinements to the above-cited adjustments.

Final Decision: We did not specifically receive any comments on the proposed budget neutrality factor methodology for FY 2006. Therefore, we are finalizing our decision to adopt this budget neutrality factor methodology for FY 2006, with the change that we are incorporating HealthSouth home office cost data from FY 2004 (as described in detail in section IV of this final rule) into the data we used previously to compute the budget neutrality factors. Based on RAND's analysis of FY 2003 data, including the HealthSouth home office cost data from FY 2004 (as described in detail in section IV of this final rule) and using the methodology described in section VI.B.8 of this final rule, we will apply the market basket increase factor (estimated for this final rule to be 3.6 percent) to the standard payment conversion factor for FY 2005 ($12,958), which equals $13,425. Then, we will apply a one-time reduction to the standard payment amount of 1.9 percent to adjust for coding changes that increased payment to IRFs (as discussed in section VI.A of this final rule), which equals $13,169. We will then apply the budget neutral wage adjustment (as discussed in section VI.B.2.f of this final rule) of 0.9995 to $13,169, which will result in a standard payment amount of $13,163. For FY 2006 and any applicable FYs thereafter, to the extent any of the adjustments are updated, we will apply budget neutrality factors to the standard payment amount using § 412.624(c)(3)(ii), which incorporates by reference § 412.624(d)(4), for the applicable changes to the tiers and CMGs, the rural adjustment, the LIP adjustment, and the teaching status adjustment we are finalizing in this final rule. We note that even if we do not update any of the adjustments (and therefore utilize § 412.624(d)(4)), we will use § 412.624(c)(3) to update the payment rates for FY 2006 and thereafter. The next section contains a detailed explanation of these budget neutrality factors we are finalizing in this final rule, including the steps for computing these factors and how they will affect total estimated aggregate payments and estimated payments to individual IRF providers. The factors we will apply (as discussed in the next section) are 0.9995 for the tier and CMG changes, 0.9889 for the teaching status adjustment, 0.9961 for the change to the rural adjustment, and 0.9851 for the change to the LIP adjustment. We have combined these factors, by multiplying the four factors together, into one budget neutrality factor for all four of these changes (0.9995 * 0.9889 * 0.9961 * 0.9851 = 0.9699). We will apply this overall budget neutrality factor to $13,163, resulting in a standard payment conversion factor for FY 2006 of $12,767. Note that the FY 2006 standard payment conversion factor will be lower than it was in FY 2005 because it needs to be reduced to ensure that estimated aggregate payments for FY 2006 will remain the same as they otherwise would have been without the proposed changes. If we do not decrease the standard payment conversion factor, each of the changes we are finalizing in this final rule would increase total estimated aggregate payments by increasing payments to rural and teaching facilities, and to facilities with a higher average case mix of patients and facilities that treat a higher proportion of low-income patients. To assess how overall estimated payments to a particular type of IRF will likely be affected by any of the changes we are finalizing in this final rule, please see Table 13 of this final rule.

The FY 2006 standard payment conversion factor would be applied to each CMG relative weight shown in Table 4, Relative Weights for Case-Mix Groups, to compute the unadjusted IRF prospective payment rates for FY 2006 shown in Table 12. To further clarify, the budget neutrality factors described above will only be applied for FY 2006 and in applicable years thereafter to the extent the adjustments are updated. Therefore, for fiscal years 2006 and thereafter, we will generally use the methodology as described in § 412.624(c)(3)(ii).

8. Description of the Methodology Used To Implement the Changes in a Budget Neutral Manner

Section 1886(j)(2)(C)(i) of the Act confers broad statutory authority upon the Secretary to adjust the classification and weighting factors in order to account for relative resource use. In addition, section 1886(j)(2)(C)(ii) provides that insofar as the Secretary determines that such adjustments for a previous fiscal year (or estimates of such adjustments for a future fiscal year) did (or are likely to) result in a change in aggregated payments under the classification system during the fiscal year that are a result of changes in the coding or classification of patients that do not reflect real changes in case mix, the Secretary shall adjust the per payment unit payment rate for subsequent years to eliminate the effect of such coding or classification changes. Similarly, section 1886(j)(3)(A)(v) of the Act confers broad statutory authority upon the Secretary to adjust the per discharge payment rate by such factors as the Secretary determines are necessary to properly reflect variations in necessary costs of treatment among IRFs. Consistent with this broad statutory authority, we proposed in the FY 2006 proposed rule (70 FR 30188) to better distribute aggregate payments among IRFs to more accurately reflect their case mix and the increased costs associated with IRFs that have teaching programs, are located in rural areas, or treat a high proportion of low-income patients.

Furthermore, to ensure that total estimated aggregate payments to IRFs would not change with these proposed changes, we also proposed in the FY 2006 proposed rule (70 FR 30188) to apply a factor to the standard payment amount for each of the proposed changes to ensure that estimated aggregate payments in FY 2006 would not be greater or less than those that would have been made in the year without the proposed changes.

Final Decision: We did not specifically receive any comments on the description of the methodology used to implement the changes in a budget neutral manner. Therefore, we are finalizing our decision to adopt this Start Printed Page 47938budget neutrality factor methodology for FY 2006, with the change that we are incorporating HealthSouth home office cost data from FY 2004 (as described in detail in section IV of this final rule) into the data we used previously to compute the budget neutrality factors. Based on RAND's analysis of FY 2003 data, including the HealthSouth home office cost data from FY 2004 (as described in detail in section IV of this final rule) and using the methodology described below, we will apply the budget neutrality factors to the standard payment amount for each of the changes described below to ensure that estimated aggregate payments in FY 2006 will be the same with or without the changes. We are finalizing our decision in this final rule to calculate these four factors using the following steps:

Step 1 Determine the FY 2006 IRF PPS standard payment amount using the FY 2005 standard payment conversion factor increased by the estimated market basket of 3.6 percent (estimated for this final rule) and reduced by 1.9 percent to account for coding changes (as discussed in section VI.A of this final rule).

Step 2 Multiply the CBSA-based budget neutrality factor discussed in this preamble by the standard payment amount computed in step 1 to account for the wage index and labor-related share (0.9995), as discussed in section VI.B.2.f of this final rule.

Step 3 Calculate the estimated total amount of IRF PPS payments for FY 2006 (with no change to the tiers and CMGs, no teaching status adjustment, and no changes to the rural and LIP adjustments).

Step 4 Apply the new tier and CMG assignments (as discussed in section V of this final rule) to calculate the estimated total amount of IRF PPS payments for FY 2006.

Step 5 Divide the amount calculated in step 3 by the amount calculated in step 4 to determine the factor (0.9995) that maintains the same total estimated aggregate payments in FY 2006 with and without the changes to the tier and CMG assignments.

Step 6 Apply the factor computed in step 5 to the standard payment amount from step 2, and calculate estimated total IRF PPS payment for FY 2006.

Step 7 Apply the change to the rural adjustment (as discussed in section VI.B.4 of this final rule) to calculate the estimated total amount of IRF PPS payments for FY 2006.

Step 8 Divide the amount calculated in step 6 by the amount calculated in step 7 to determine the factor (0.9961) that keeps total estimated payments in FY 2006 the same with and without the change to the rural adjustment.

Step 9 Apply the factor computed in step 8 to the standard payment amount from step 6, and calculate estimated total IRF PPS payment for FY 2006.

Step 10 Apply the change to the LIP adjustment (as discussed in section VI.B.5 of this final rule) to calculate the estimated total amount of IRF PPS payments for FY 2006.

Step 11 Divide the amount calculated in step 9 by the amount calculated in step 10 to determine the factor (0.9851) that maintains the same total estimated aggregate payments in FY 2006 with and without the change to the LIP adjustment.

Step 12 Apply the factor computed in step 11 to the standard payment amount from step 9, and calculate estimated total IRF PPS payments for FY 2006.

Step 13 Apply the teaching status adjustment (as discussed in section VI.B.3 of this final rule) to calculate the estimated total amount of IRF PPS payments for FY 2006.

Step 14 Divide the amount calculated in step 12 by the amount calculated in step 13 to determine the factor (0.9889) that maintains the same total estimated aggregate payments in FY 2006 with and without the teaching status adjustment.

As discussed in section VI.B.9 of this final rule, the FY 2006 IRF PPS standard payment conversion factor that accounts for the new tier and CMG assignments, the changes to the rural and the LIP adjustments, and the teaching status adjustment applies the following factors: the market basket update, the reduction of 1.9 percent to account for coding changes, the budget-neutral CBSA-based wage index and labor-related share budget neutrality factor of 0.9995, the tier and CMG changes budget neutrality factor of 0.9995, the rural adjustment budget neutrality factor of 0.9961, the LIP adjustment budget neutrality factor of 0.9851, and the teaching status adjustment budget neutrality factor of 0.9889.

Each of these budget neutrality factors lowers the standard payment amount. The budget neutrality factor for the tier and CMG changes lowers the standard payment amount from $13,163 to $13,156. The budget neutrality factor for the change to the rural adjustment lowers the standard payment amount from $13,156 to $13,105. The budget neutrality factor for the change to the LIP adjustment lowers the standard payment amount from $13,105 to $12,910. Finally, the budget neutrality factor for the teaching status adjustment lowers the standard payment amount from $12,910 to $12,767. As indicated previously, the standard payment conversion factor will be lowered in order to ensure that total estimated payments for FY 2006 with the changes equal total estimated payments for FY 2006 without the changes. This is because these four changes would otherwise result in an increase, on average, to total estimated aggregate payments to IRFs, because IRFs with teaching programs, IRFs located in rural areas, IRFs with higher case mix, and IRFs with higher proportions of low-income patients would receive higher payments. To maintain the same total estimated aggregate payments to all IRFs, then, we are redistributing payments among IRFs. Thus, some redistribution of payments occurs among facilities, while total estimated aggregate payments do not change. To determine how the changes we are finalizing in this final rule are estimated to affect payments among different types of facilities, please see Table 13 in this final rule.

9. Description of the IRF Standard Payment Conversion Factor for Fiscal Year 2006

In the August 7, 2001 final rule, we established a standard payment amount referred to as the budget neutral conversion factor under § 412.624(c). In accordance with the methodology described in § 412.624(c)(3)(i), the budget neutral conversion factor for FY 2002, as published in the August 7,2001 final rule, was $11,838.00. Under § 412.624(c)(3)(i), this amount reflects, as appropriate, any adjustments for outlier payments, budget neutrality, and coding and classification changes as described in § 412.624(d).

The budget neutral conversion factor is a standardized payment amount and the amount reflects the budget neutrality adjustment for FY 2002. The statute required a budget neutrality adjustment only for FYs 2001 and 2002. Accordingly, we believed it was more consistent with the statute to refer to the standard payment as a standard payment conversion factor, rather than refer to it as a budget neutral conversion factor. Consequently, we changed all references to budget neutral conversion factor to “standard payment conversion factor.”

Under § 412.624(c)(3)(i), the standard payment conversion factor for FY 2002 of $11,838 reflected the budget neutrality adjustment described in § 412.624(d)(2). Under the then existing § 412.624(c)(3)(ii), we updated the FY 2002 standard payment conversion factor ($11,838) to FY 2003 by applying an increase factor (the market basket) of Start Printed Page 479393.0 percent, as described in the update notice published in the August 1, 2002 Federal Register (67 FR at 49931). This yielded the FY 2003 standard payment conversion factor of $12,193.00 that was published in the August 1, 2002 update notice (67 FR at 49931). The FY 2003 standard payment conversion factor ($12,193) was used to update the FY 2004 standard payment conversion factor by applying an increase factor (the market basket) of 3.2 percent and budget neutrality factor of 0.9954, as described in the August 1, 2003 Federal Register (68 FR at 45689). This yielded the FY 2004 standard payment conversion factor of $12,525 that was published in the August 1, 2003 Federal Register (68 FR at 45689). The FY 2004 standard payment conversion factor ($12,525) was used to update the FY 2005 standard payment conversion factor by applying an increase factor (the market basket) of 3.1 percent and budget neutrality factor of 1.0035, as described in the July 30, 2004 Federal Register (69 FR at 45766). This yielded the FY 2005 standard payment conversion factor of $12,958 as published in the July 30, 2004 Federal Register (69 FR at 45766).

In the FY 2006 proposed rule (70 FR 30188), we proposed to use the revised methodology in accordance with § 412.624(c)(3)(ii) and as described in section VI.B.7 of the FY 2006 proposed rule (70 FR 30188) to propose an update to the standard payment conversion factor for FY 2006.

Final Decision: We did not specifically receive any comments on the proposed standard payment conversion factor for FY 2006. Therefore, we are finalizing our decision to adopt the proposed methodology for computing the standard payment conversion factor, with the change that we are incorporating HealthSouth home office cost data from FY 2004 (as described in detail in section IV of this final rule) into the FY 2003 data we used previously to compute the final standard payment conversion factor for FY 2006. Based on RAND's analysis of FY 2003 data, including the HealthSouth home office cost data from FY 2004 (as described in detail in section IV of this final rule) and using the methodology we are finalizing in section VI.B.7 and section VI.B.8 of this final rule, we will calculate the standard payment conversion factor for FY 2006 by applying the market basket increase factor (estimated for this final rule to be 3.6 percent) to the standard payment conversion factor for FY 2005 ($12,958), which equals $13,425. Then, we will apply a one-time reduction to the standard payment amount of 1.9 percent to adjust for coding changes that increased payment to IRFs, which equals $13,169. We will then apply the budget neutral wage adjustment of 0.9995 to $13,169, which will result in a standard payment amount of $13,163. Next, we will apply a budget neutrality factor for FY 2006 for the budget-neutral refinements to the tiers and CMGs, the teaching status adjustment, the rural adjustment, and the adjustment for the proportion of low-income patients (of 0.9699) to $13,163, which will result in a standard payment conversion factor for FY 2006 of $12,767. The FY 2006 standard payment conversion factor will be applied to each CMG weight shown in Table 4 of this final rule, Relative Weights for Case-Mix Groups, to compute the unadjusted IRF prospective payment rates for FY 2006 shown in Table 12 of this final rule.

10. Example of the Methodology for Adjusting the Federal Prospective Payment Rates

To illustrate the methodology that we will use to adjust the Federal prospective payments (as described in section VI.B.7 and section VI.B.8 of this final rule), we provide an example in Table 11 below. Note that the methodology we are finalizing in this final rule has changed somewhat from the methodology we proposed in the FY 2006 proposed rule (70 FR 30188) because, upon further analysis, CMS discovered that the example used to illustrate the proposed adjustments to the Federal prospective payments in the FY 2006 proposed rule (70 FR 30188) did not calculate payments as accurately as the one we are finalizing in this final rule. Therefore, we have made a slight adjustment to the methodology we are finalizing in this final rule to ensure that payments are calculated as accurately as possible. Accordingly, we will multiply the teaching status adjustment, if applicable, by the wage adjusted Federal payment amount, rather than by the rural and LIP adjusted Federal payment amount as we proposed in the FY 2006 proposed rule (70 FR 30188), and add the resulting amount to the FY 2006 adjusted Federal prospective payment to compute the total FY 2006 adjusted Federal prospective payment (as illustrated in the following example).

We summarize 3 examples for computing total FY 2006 adjusted Federal prospective payment rates in Table 11 below. These examples are based on 3 beneficiaries classified into CMG 0110 (without comorbidities) receiving care in 3 different hypothetical IRFs. IRFs A, B, and C have the following characteristics:

  • Facility A is a non-teaching IRF located in rural Duke County, Massachusetts with a disproportionate share hospital (DSH) adjustment of 5 percent (1.031) and the FY 2006 blended wage index of 1.0216;
  • Facility B is a teaching IRF located in urban Queens County, New York with a disproportionate share hospital (DSH) adjustment of 10 percent (1.0612) and a FY 2006 blended wage index of 1.3449. The teaching status adjustment of 1.0910 will also be applied; and,
  • Facility C is a non-teaching IRF located in Kings County, California with a disproportionate share hospital (DSH) adjustment of 20 percent (1.1203) and a FY 2006 blended wage index of 0.9797. The Kings County, California IRF was designated as a rural facility in FY 2005 (based on the MSA designation), but is classified as urban in FY 2006 (based on the CBSA designation). Therefore, this IRF will receive a hold harmless adjustment of 12.76 percent. The hold harmless adjustment applies to IRFs that are defined as rural under § 412.602 during FY 2005 and are classified as urban under § 412.602 in FY 2006 (as discussed in detail in section VI.B.2.e).

To calculate each IRF's total adjusted Federal prospective payment, we compute the wage-adjusted Federal prospective payment and multiply the result by the appropriate low-income patient adjustment, and the rural adjustment (if applicable). In order to calculate the teaching hospital adjustment (if applicable), we multiply the teaching adjustment by the Wage Adjusted Federal payment. Then, we apply the amount to the Adjusted Rural and LIP Federal Prospective Payment Rate. Table 11 illustrates the components of the adjusted payment calculation.

Table 11.—Example of Computing an IRF's Federal Prospective Payment

Facility A Dukes County, MAFacility B Queens County, NYFacility C Kings County, CA
Federal Prospective Payment$27,686.52$27,686.52$27,686.52
Start Printed Page 47940
Labor Share× 0.75865× 0.75865× 0.75865
Labor Portion of Federal Payment= $21,004.38= $21,004.38= $21,004.38
FY 2006 Transition Wage Index (shown in Table 1 in the addendum)× 1.0216× 1.3449× 0.9797
Wage-Adjusted Amount= $21,458.07= $28,248.79= $20,577.99
Nonlabor Amount$6,682.14$6,682.14$6,682.14
Wage-Adjusted Federal Payment$28,140.21$34,930.93$27,260.13
Rural Adjustment× 1.2130× 1.0000× 1.1276
Subtotal= $34,134.08= $34,930.93= $30,738.52
LIP Adjustment1.03101.06121.1203
FY 2006 Adjusted Rural and LIP Federal Prospective Payment Rate$35,192.24$37,068.70$34,436.37
Wage-Adjusted Federal Payment$28,140.21$34,930.93$27,260.13
Teaching status adjustment× 1.0000× 1.0900× 1.0000
= $28,140.21= $38,074.71= $27,260.13
Teaching Status addition to FY 2006 Adjusted Rural and LIP Federal Prospective Payment Rate$0.00$3,143.78$0.00
Total FY 2006 Adjusted Federal Prospective Payment$35,192.24$40,212.49$34,436.37

Thus, the adjusted payment for Facility A will be $35,192.24, the adjusted payment for Facility B will be $40,212.49, and the adjusted payment for Facility C will be $34,436.37.

Table 12.—FY 2006 Payment Rate Table Based on All Refinements

CMGPayment Rate Tier 1Payment Rate Tier 2Payment Rate Tier 3Payment Rate No Comorbidity
0101$9,819.10$9,318.63$8,278.12$8,107.05
010212,091.6311,476.2610,194.459,983.79
010314,250.5313,525.3612,015.0211,767.34
010415,140.3914,369.2612,765.7212,501.45
010518,171.2717,246.9415,321.6815,005.06
010621,151.0920,074.8317,834.2217,465.26
010724,411.7823,169.5520,582.9620,159.09
010828,222.7326,786.4423,796.4123,304.88
010928,056.7626,629.4123,655.9723,168.27
011033,528.7031,823.0228,269.9727,686.52
020110,392.348,714.757,687.017,210.80
020213,324.9211,174.969,856.129,244.58
020315,942.1513,369.6011,791.6011,061.33
020417,051.6114,300.3212,612.5211,831.18
020520,913.6217,539.3015,468.5014,509.70
020627,294.5722,891.2320,189.7318,937.29
020735,309.6929,611.7826,117.4524,497.32
030114,417.7712,174.6110,775.359,912.30
030218,804.5115,879.5914,053.9112,927.86
030322,438.0018,947.5016,770.7315,426.37
030430,922.9526,112.3523,112.1021,258.33
040112,627.8410,873.659,774.428,728.80
040217,414.1914,996.1213,479.4012,036.73
040330,312.6926,103.4123,464.4720,953.20
040454,345.2946,798.7242,067.2737,565.62
040541,463.3935,705.4732,094.9628,660.64
05019,836.978,233.447,201.866,458.83
050213,170.4411,023.039,642.928,648.37
050317,460.1514,613.1112,783.6011,463.49
050421,857.1018,292.5616,002.1614,350.11
050525,902.9721,679.6418,965.3817,006.92
050635,245.8629,499.4325,804.6623,141.46
060111,445.629,359.498,893.498,289.61
060215,224.6512,450.3811,831.1811,025.58
060319,490.1015,938.3215,145.4914,115.20
060424,945.4420,400.3919,384.1418,066.58
070111,560.529,876.559,275.238,407.07
070215,010.1612,823.1712,041.8310,914.51
070318,685.7815,963.8614,991.0113,587.92
Start Printed Page 47941
070422,932.0919,590.9618,397.2516,676.26
08018,376.437,035.896,522.665,867.71
080210,941.329,189.698,519.427,665.31
080316,223.0313,624.9412,631.6711,363.91
080414,131.7911,868.2011,002.609,899.53
080517,793.3714,943.7713,854.7512,464.42
080621,354.0817,933.8016,626.4614,957.82
090110,739.609,776.978,687.947,775.10
090214,112.6412,847.4311,416.2510,216.15
090318,618.1216,949.4715,061.2313,478.12
090423,339.3521,248.1218,879.8416,895.85
100112,304.8311,347.3110,125.519,335.23
100216,225.5814,961.6513,350.4512,308.66
100322,822.2921,043.8518,778.9817,313.33
110116,014.9213,400.2411,731.6010,803.44
110223,976.4320,060.7917,562.2916,173.24
120113,001.9111,227.3010,348.939,341.61
120216,828.1814,532.6813,395.1412,090.35
120320,731.0517,901.8916,501.3514,893.98
130113,198.5212,278.0210,628.539,393.96
130218,287.4517,012.0314,725.4613,015.96
130323,373.8221,744.7518,822.3916,637.95
140110,433.199,386.308,165.777,412.52
140214,087.1112,672.5211,025.5810,008.05
140317,535.4715,774.9113,724.5312,459.32
140422,238.8420,007.1717,405.2515,800.44
150111,773.7311,483.929,813.999,443.75
150214,885.0514,517.3612,406.9711,939.70
150318,217.2317,767.8315,185.0714,611.83
150424,017.2823,424.8920,019.9319,264.13
160112,849.9910,908.129,870.178,814.34
160217,631.2314,968.0313,541.9612,094.18
160321,688.5818,411.2916,658.3814,877.39
170112,897.2212,299.7310,625.979,346.72
170216,986.4916,198.7713,995.1912,311.22
170320,212.7119,275.6216,652.0014,648.86
170425,288.8724,115.5920,834.4718,327.03
180115,471.0512,552.5110,526.399,296.93
180224,748.8320,079.9416,839.6714,872.28
180344,408.7336,031.0330,216.9426,686.86
190115,782.5714,019.4413,631.3311,935.87
190229,570.9326,266.8325,539.1122,361.40
190342,691.5737,921.8236,872.3732,283.91
200111,162.199,430.988,455.587,720.20
200214,615.6612,348.2411,070.2710,107.63
200318,881.1215,952.3714,301.5913,056.81
200425,222.4921,310.6819,104.5417,443.55
210127,906.1127,906.1120,312.3018,846.65
50010.000.000.002810.02
51010.000.000.0018,108.32
51020.000.000.0020,429.75
51030.000.000.009,197.35
51040.000.000.0023,964.94

VII. Quality of Care in IRFs

The IRF-PAI is the patient data collection instrument for IRFs. Currently, the IRF-PAI contains a blend of the functional independence measures items and quality and medical needs questions. The quality and medical needs questions (which are currently collected on a voluntary basis) may need to be modified to encapsulate those data necessary for calculation of quality indicators in the future.

We awarded a contract to the Research Triangle Institute (RTI) with the primary tasks of identifying quality indicators pertinent to the inpatient rehabilitation setting and determining what information is necessary to calculate those quality indicators. These tasks included reviewing literature and other sources for existing rehabilitation quality indicators. It also involved identifying organizations involved in measuring or monitoring quality of care in the inpatient rehabilitation setting. In addition, RTI was tasked with performing independent testing of the quality indicators identified in their research.

Once RTI has issued a final report, taking into account and responding to public comments in the Federal Register as part of the Paperwork Reduction Act process, we will publish our rationale for revising the IRF-PAI. Then in accordance with the Paperwork Start Printed Page 47942Reduction Act, we will publish our proposed revisions to the IRF-PAI and solicit public comments. The revised IRF-PAI will need to be approved by OMB before it is used in IRFs.

We have supported the development of valid quality measures and have been engaged in a variety of quality improvement efforts focused in other post-acute care settings such as nursing homes. However, any new quality-related data collected from the IRF-PAI would have to be analyzed to determine the feasibility of developing a payment method that accounts for the performance of the IRF in providing the necessary rehabilitative care.

Medicare beneficiaries are the primary users of IRF services. Any quality measures must be carefully constructed to address the unique characteristics of this population. Similarly, we need to consider how to design effective incentives; that is, superior performance measured against pre-established benchmarks and/or performance improvements.

In addition, while our efforts to develop the various post-acute care PPSs, including the IRF PPS, have generated substantial improvements over the preexisting cost-based systems, each of these individual systems was developed independently. As a result, we have focused on phases of a patient's illness as defined by a specific site of service, rather than on the entire post-acute episode. As the differentiation among provider types (such as SNFs and IRFs) becomes less pronounced, we need to investigate a more coordinated approach to payment and delivery of post-acute services that focuses on the overall post-acute episode.

This could entail a strategy of developing payment policy that is as neutral as possible regarding provider and patient decisions about the use of particular post-acute services. That is, Medicare should provide payments sufficient to ensure that beneficiaries receive high quality care in the most appropriate setting, so that admissions and any transfers between settings occur only when consistent with good care, rather than to generate additional revenues. In order to accomplish this objective, we need to collect and compare clinical data across different sites of service.

In fact, in the long run, our ability to compare clinical data across care settings is one of the benefits that will be realized as a basic component of the Department's interest in the use of a standardized electronic health record (EHR) across all settings including IRFs. It is also important to recognize the complexity of the effort, not only in developing an integrated assessment tool that is designed using health information standards, but in examining the various provider-centric prospective payment methodologies and considering payment approaches that are based on patient characteristics and outcomes. MedPAC has recently taken a preliminary look at the challenges in improving the coordination of our post-acute care payment methods, and suggested that it may be appropriate to explore additional options for paying for post-acute services. We agree that CMS, in conjunction with MedPAC and other stakeholders, should consider a full range of options in analyzing our post-acute care payment methods, including the IRF PPS.

We also want to encourage incremental changes that will help us build towards these longer term objectives. For example, medical records tools are now available that could allow better coordinated discharge planning procedures. These tools can be used to ensure communication of a standardized data set that then can be used to establish a comprehensive IRF care plan. Improved communications may reduce the incidence of potentially avoidable re-hospitalizations and other negative impacts on quality of care that occur when patients are transferred to IRFs without a full explanation of their care needs. We are looking at ways that Medicare providers can use these tools to generate timely data across settings.

It is important to note that some of the ideas discussed above may exceed our current statutory authority. However, we believe that it is useful to encourage discussion of a broad range of ideas for debate of the relative advantages and disadvantages of the various policies affecting this important component of the health care sector. Thus, we solicited comments on these and other approaches.

Comment: Most commenters were supportive of the concept of providing incentives for high quality and improved patient outcomes within the structure of Medicare's payment systems. Commenters were also generally supportive of advancing approaches that resulted in more consistent payments for similar services across the various post acute care settings and a more seamless system of care, though several noted important distinctions between the type of care provided in IRF compared to other settings. For example, one commenter objected to the implication that the differentiation among provider types (such as SNFs and IRFs) could become less pronounced. This commenter stated that there is a big difference in care and rehabilitation between these two types of facilities and suggested that we ask patients about this difference. Many Commenters noted that, in advancing these policy goals, CMS should facilitate stakeholder input to ensure that the knowledge and experience of providers, beneficiaries, and others with critical knowledge is factored into the development process.

Response: CMS appreciates the thoughtful comments provided on these important issues. By advancing a more seamless system of payments and benefits in post acute care, Medicare can ensure that patients receive high quality care in the most appropriate setting, and that decisions about where patients receive care are guided by decisions of patients and their families working with physicians, rather than in response to financial incentives or barriers created by administrative guidelines. In addition, pay for performance has the potential to promote real improvements in quality and outcomes as demonstrated by the work CMS has advanced already; for example, the Premier Hospital Demonstration.

We agree with commenters that CMS should involve stakeholders and work collaboratively with providers, patients and practitioners in the field to advance these objectives. In developing additional IRF-PAI quality items and related quality measures through our research with RTI, as described in section VII above, RTI has already begun to do that by convening meetings of a Technical Expert Panel to consider the critical methodological and clinical issues. The research we are conducting through the RTI contract will provide data that will promote and advance efforts to develop and consider pay for performance approaches in IRFs, as well as approaches to measuring and rewarding quality improvement more broadly in post acute care. We also agree that, in developing a more integrated strategy for payment and care delivery within Medicare's post acute benefits, it will be important to consider not only how various provider types are similar but also how they are different.

VIII. Miscellaneous Public Comments Within the Scope of the Proposed Rule

Comment: We received a comment regarding a change made to § 412.25(a) when the inpatient psychiatric facility (IPF) PPS was published on November 15, 2004 (69 FR 66922). The commenter requested that we add the reference to a rehabilitation unit that was removed by the IPF PPS final rule.

Response: We agree with making the change requested by the commenter. Start Printed Page 47943Section 412.1 specifies the scope of part 412. In order to expand the existing scope of part 412 the IPF PPS final rule revised § 412.1 by redesignating paragraphs (a)(2) and (a)(3) as paragraphs (a)(3) and (a)(4) and adding a new paragraph (a)(2). The added paragraph (a)(2) specified that in accordance with section 124 of Pub. L. 106-113 we were establishing a per diem prospective payment system for the inpatient operating and capital costs of hospital inpatient services furnished to Medicare beneficiaries by a psychiatric facility that meets the conditions of subpart N of part 412. Redesignated as paragraph (a)(3) is the paragraph that specifies the statutory basis for the establishment of the IRF PPS.

In order to conform § 412.25(a) to the revision we made as stipulated above to § 412.1 the IPF PPS final rule revised § 412.25(a), which specifies the basis for exclusion from being paid under the IPPS. Prior to publishing the IPF PPS final rule, § 412.25(a) read as follows:

(a) Basis for exclusion. In order to be excluded from the prospective payment systems specified in § 412.1(a)(1), a psychiatric or rehabilitation unit must meet the following requirements.

When the IPF PPS final rule revised § 412.25(a) the intended purpose of the revision was to include a reference to new paragraph (a)(2) that, as stipulated above, we had added to § 412.1. However, when we revised § 412.25(a), we inadvertently removed the words “or rehabilitation” from the existing § 412.25(a). Therefore, in order to correct the inadvertent removal of the words “or rehabilitation” from § 412.25(a), we are making a technical correction so that § 412.25(a) will read as follows:

(a) Basis for exclusion. In order to be excluded from the prospective payment systems as specified in § 412.1(a)(1) and be paid under the inpatient psychiatric facility prospective payment system as specified in § 412.1(a)(2) or the inpatient rehabilitation facility prospective payment system as specified in § 412.1(a)(3), a psychiatric or rehabilitation unit must meet the following requirements.

IX. Miscellaneous Public Comments Outside the Scope of the Proposed Rule

Comment: We received a number of comments expressing concerns about various aspects of CMS's enforcement of the 75 percent rule. Several commenters stated that enforcement of the 75 percent rule would lead many IRFs to close, would arbitrarily exclude patients in certain RICs from receiving treatment in IRFs, and would create access to care problems for patients.

Response: These comments are not specifically related to the proposed changes to the IRF PPS that were discussed in the FY 2006 proposed rule (70 FR 30188). We responded to similar comments in the May 7, 2004 final rule (69 FR 25752) that established the changes to the criteria for being classified as an IRF. Because the responses to these comments in the May 7, 2004 final rule are very lengthy, we refer the reader to that final rule for the detailed responses to these and other comments regarding the 75 percent rule.

Comment: One commenter asked that we provide the algorithm (that is, the computer software) that the fiscal intermediaries use in their presumptive determinations of IRF compliance with the 75 percent rule.

Response: We will take this into consideration, and may make the computer software available to all interested parties at a future date.

Comment: One commenter suggested that CMS consider implementing a cost-of-living adjustment for IRFs located in Alaska, to offset higher non-labor costs in Alaska.

Response: In the August 7, 2001 final rule (66 FR 41316, 41361), we referred to Section 1886(j)(4)(B), which authorizes, but does not require, the Secretary to take into account the unique circumstances of IRFs located in Alaska and Hawaii. In the data used to prepare the August 7, 2001 final rule, there was only one IRF in Hawaii and one in Alaska. In the August 7, 2001 final rule, we explained that, due to the small number of IRFs in Alaska and Hawaii in the data, analyses were inconclusive regarding whether a cost-of-living adjustment would improve payment equity for these facilities. Therefore, we did not implement an adjustment for facilities located in Alaska and Hawaii in the August 7, 2001 final rule.

In the FY 2003 data used for the FY 2006 proposed rule (70 FR 30188) and for this final rule, there were 3 IRFs in Alaska and 1 IRF in Hawaii. We continue to believe that this may be too small a number of facilities for us to determine, based on analysis of the data, whether a cost-of-living adjustment would improve payment equity for these facilities. However, we will consider conducting such an analysis in the future.

Comment: Some commenters suggested changes to the items on the IRF-PAI, such as deleting the transfer to tub item and revising the instructions for the items that describe preventable conditions that occur on admission to the IRF and preventable conditions that occur while the patient is in an IRF.

Response: We have contracted with the Research Triangle Institute (RTI) to analyze and recommend changes to the IRF-PAI that would improve our ability to assess quality of care in IRFs. Any changes to the IRF-PAI that CMS might decide to propose in the future, based on RTI's recommendations, would require clearance by the Office of Management and Budget. However, we will take the commenters suggestions into consideration.

Comment: Several commenters suggested that CMS allow general hospitals to increase physiatrist training if they also decrease training in one or more specialties reimbursed under the inpatient PPS.

Response: This comment does not relate to the IRF PPS and is outside the scope of this rule. We will forward it to the component of the Agency that works on the IPPS for their consideration.

IX. Provisions of the Final Regulations

The provisions of this final rule restate the provisions of the FY 2006 proposed rule (70 FR 30188), except as noted elsewhere in the preamble. Following is a highlight of the changes we made from the proposed rule:

  • We are adding 2 codes that were not on the proposed list of ICD-9-CM codes to be removed from the comorbidity tiers (V46.11 and V46.12). We are adding these codes to the list to be removed because these codes are derived from code V46.1, which was determined by RAND to have no positive impact on payment when controlling for the CMG.
  • We are adding the following codes to the list of comorbidities we proposed in the proposed rule: 250.1 (insulin dependent diabetes without mention of complications, not stated as controlled), code 428.1-Left Heart Failure, code 428.20-Systolic Heart Failure Unspecified, code 428.21-Systolic Heart Failure Acute, code 428.22-Systolic Heart Failure Chronic, code 428.23-Systolic Hear Failure Acute on Chronic, code 428.30-Diastolic Heart Failure Unspecified, code 428.31-Diastolic Heart Failure Acute, code 428.32-Diastolic Heart Failure Chronic, code 428.33-Diastolic Heart Failure Acute on Chronic, code 428.40-Combined Systolic and Diastolic Heart Failure Unspecified, code 428.41-Combined Systolic and Diastolic Heart Failure Acute, code 428.42-Combined Systolic and Diastolic Heart Failure Chronic, and code 428.43-Combined Systolic and Diastolic Heart Failure Acute on Chronic. For this final rule, we decided to add these codes to the list of Start Printed Page 47944comorbidities we proposed in the proposed rule because of the increased costs associated with these codes. After receiving the comments to add additional codes to the list of comorbidity codes used to increase the CMG payment rate, our Medical Officers, similar to RAND's TEP, believe that several of the codes suggested should be added to these tiers that increase payment for the CMG.
  • We are updating the market basket estimate, based on the FY 2002-based RPL market basket and the Global Insight's 2nd quarter 2005 forecast, to 3.6 percent (from 3.1 percent in the proposed rule).
  • We are changing our proposed policy to adopt the CBSA-based wage index without a transition to implementing the CBSA-based wage index with a budget neutral one-year blended wage index. Thus, the FY 2006 wage index is comprised of 50 percent of the FY 2006 MSA-based wage index and 50 percent of the FY 2006 CBSA-based wage index (both based on FY 2001 hospital wage data) for all IRFs.
  • We are changing our proposed policy to not adopt a hold harmless policy to adopting a budget neutral 3 year hold harmless policy for FY 2005 rural IRFs that will be classified as urban under the FY 2006 CBSA-based designations. The 3 year hold harmless policy will only apply to existing rural FY 2005 IRFs that will experience a decrease in payments due solely to the loss of the FY 2005 rural adjustment of 19.14 percent because of the adoption of the CBSA-based designations.
  • We are changing the exponent for the teaching status adjustment formula to 0.9012 (from 1.083 in the proposed rule), based on RAND's most recent cost regressions using data from FY 2003, including the HealthSouth home office cost data from FY 2004 (as described in detail in section IV of this final rule).
  • We are changing the rural adjustment to 21.3 percent (from 24.1 percent in the proposed rule), based on RAND's most recent cost regressions using data from FY 2003, including the HealthSouth home office cost data from FY 2004 (as described in detail in section IV of this final rule).
  • We are changing the exponent for the LIP adjustment formula to 0.6229 (from 0.636 in the proposed rule), based on RAND's most recent cost regressions using data from FY 2003, including the HealthSouth home office cost data from FY 2004 (as described in detail in section IV of this final rule).
  • We are changing the outlier threshold amount to $5,132 (from $4,911 in the proposed rule), based on RAND's most recent cost regressions using data from FY 2003, including the HealthSouth home office cost data from FY 2004 (as described in detail in section IV of this final rule).
  • We are changing the base period for determining an IRF's FTE resident cap from the final settlement of the IRF's most recent cost reporting period ending on or before November 15, 2003, which was what we had proposed in the FY 2006 proposed rule, to the final settlement of the IRF's most recent cost reporting period ending on or before November 15, 2004.
  • We are changing the budget neutrality factors applied to the standard payment amount in the methodology used to implement the changes in a budget neutral manner (section VI.B.8 of this final rule) to 0.9995 for the changes to the tier comorbidities and the CMGs, 0.9961 for the change to the rural adjustment, 0.9851 for the change to the LIP adjustment, and 0.9889 for the implementation of the new teaching status adjustment. These changes are necessary to ensure that the tier and CMG changes, the rural adjustment change, the LIP adjustment change, and the implementation of the new teaching status adjustment will be done in a budget neutral manner for FY 2006 (that is, such that estimated aggregate IRF payments for FY 2006 with the changes will equal estimated aggregate IRF payment in FY 2006 without the changes).
  • We are changing the budget neutrality factor for the wage index changes for FY 2006 to 0.9995, to ensure that the wage index changes described in section VI.B.2 of this final rule will be made in a budget neutral manner.
  • We are changing the standard payment conversion factor for FY 2006 to $12,767 (from $12,658 in the proposed rule), based on RAND's most recent cost regressions using data from FY 2003, including the HealthSouth home office cost data from FY 2004 (as described in detail in section IV of this final rule).

X. Collection of Information Requirements

This document does not impose information collection and recordkeeping requirements. Consequently, it need not be reviewed by the Office of Management and Budget under the authority of the Paperwork Reduction Act of 1995.

XI. Regulatory Impact Analysis

A. Introduction

The August 7, 2001 final rule established the IRF PPS for the payment of Medicare services for cost reporting periods beginning on or after January 1, 2002. We incorporated a number of elements into the IRF PPS, such as case-level adjustments, a wage adjustment, an adjustment for the percentage of low-income patients, a rural adjustment, and an outlier payment policy. This final rule updates the FY 2005 IRF PPS payment rates specified in the July 30, 2004 notice (69 FR 45721) and implements policy changes with regard to the IRF PPS based on analyses conducted by RAND under contract with us on CY 2002 and FY 2003 data (updated from the 1999 data used to design the IRF PPS).

In constructing these impacts, we do not attempt to predict behavioral responses, nor do we make adjustments for future changes in such variables as discharges or case-mix. We note that certain events may combine to limit the scope or accuracy of our impact analysis, because such an analysis is future-oriented and, thus, susceptible to forecasting errors due to other changes in the forecasted impact time period. Some examples of such possible events are newly legislated general Medicare program funding changes by the Congress, or changes specifically related to IRFs. In addition, changes to the Medicare program may continue to be made as a result of the BBA, the BBRA, the BIPA, or new statutory provisions. Although these changes may not be specific to the IRF PPS, the nature of the Medicare program is such that the changes may interact, and the complexity of the interaction of these changes could make it difficult to predict accurately the full scope of the impact upon IRFs.

We have examined the impacts of this final rule as required by Executive Order 12866 (September 1993, Regulatory Planning and Review) and the Regulatory Flexibility Act (RFA) and Impact on Small Hospitals (September 19, 1980, Pub. L. 96-354), section 1102(b) of the Social Security Act, the Unfunded Mandates Reform Act of 1995 (Pub. L. 104-4), and Executive Order 13132.

1. Executive Order 12866

Executive Order 12866 (as amended by Executive Order 13258, which merely reassigns responsibility of duties) directs agencies to assess all costs and benefits of available regulatory alternatives and, if regulation is necessary, to select regulatory approaches that maximize net benefits (including potential economic, environmental, public health and safety effects, distributive impacts, and equity). A regulatory impact analysis Start Printed Page 47945(RIA) must be prepared for major rules with economically significant effects ($100 million or more in any 1 year).

We estimate that the cost to the Medicare program for IRF services in FY 2006 will increase by $210 million over FY 2005 levels. The updates to the IRF labor-related share and wage indices are made in a budget neutral manner. We are making changes to the CMGs and the tiers, the teaching status adjustment, and the rural and LIP adjustments in a budget neutral manner (that is, in order that total estimated aggregate payments with the changes equal total estimated aggregate payments without the changes). This means that we are improving the distribution of payments among facilities depending on the mix of patients they treat, their teaching status, their geographic location (rural vs. urban), and the percentage of low-income patients they treat, without changing total estimated aggregate payments. To redistribute payments among facilities, we lowered the base payment amount, which then gets adjusted upward for each facility according to the facility's characteristics. This redistribution will not, however, affect estimated aggregate payments to facilities. Thus, the changes to the IRF labor-related share and the wage indices, the changes to the CMGs, the tiers, and the motor score index, the teaching status adjustment, the update to the rural adjustment, and the update to the LIP adjustment have no overall effect on estimated costs to the Medicare program. Therefore, the estimated increased cost to the Medicare program is due to the combined effect of the updated IRF market basket of 3.6 percent, the 1.9 percent reduction to the standard payment conversion factor to account for changes in coding that affect total aggregate payments, and the update to the outlier threshold amount. We have determined that this final rule is a major rule as defined in 5 U.S.C. 804(2). Based on the overall percentage change in payments per case estimated using our payment simulation model (a 3.4 percent increase), we estimate that the total impact of these changes for estimated FY 2006 payments compared to estimated FY 2005 payments will be approximately a $210 million increase. This amount does not reflect changes in IRF admissions or case-mix intensity, which also may affect the overall estimated change in payments from FY 2005 to FY 2006.

2. Regulatory Flexibility Act (RFA)

The RFA requires agencies to analyze the economic impact of our regulations on small entities. If we determine that the regulation will impose a significant burden on a substantial number of small entities, we must examine options for reducing the burden. For purposes of the RFA, small entities include small businesses, nonprofit organizations, and government agencies. Most IRFs and most other providers and suppliers are considered small entities, either by nonprofit status or by having revenues of $6 million to $29 million in any 1 year. (For details, see the Small Business Administration's regulation that set forth size standards for health care industries at 65 FR 69432.) Because we lack data on individual hospital receipts, we cannot determine the number of small proprietary IRFs. Therefore, we assume that all IRFs (approximate total of 1,200 IRFs, of which approximately 60 percent are nonprofit facilities) are considered small entities for the purpose of the analysis that follows. Medicare fiscal intermediaries and carriers are not considered to be small entities. Individuals and States are not included in the definition of a small entity.

3. Impact on Rural Hospitals

Section 1102(b) of the Act requires us to prepare a regulatory impact analysis for any final rule that may have a significant impact on the operations of a substantial number of small rural hospitals. This analysis must conform to the provisions of section 603 of the RFA. With the exception of hospitals located in certain New England counties, for purposes of section 1102(b) of the Act, we previously defined a small rural hospital as a hospital with fewer than 100 beds that is located outside of a Metropolitan Statistical Area (MSA) or New England County Metropolitan Area (NECMA). However, under the new labor market definitions that we are adopting, we will no longer employ NECMAs to define urban areas in New England. Therefore, for purposes of this analysis, we now define a small rural hospital as a hospital with fewer than 100 beds that is located outside of a Metropolitan Statistical Area (MSA).

As discussed in detail below, the rates and policies set forth in this final rule will not have an adverse impact on rural hospitals based on the data of the 169 rural units and 21 rural hospitals in our database of 1,188 IRFs for which data were available.

4. Unfunded Mandates Reform Act

Section 202 of the Unfunded Mandates Reform Act of 1995 (Pub. L. 104-4) also requires that agencies assess anticipated costs and benefits before issuing any final rule that may result in expenditures in any 1 year by State, local, or tribal governments, in the aggregate, or by the private sector, of at least $110 million. This final rule will not mandate any requirements for State, local, or tribal governments, nor will it affect private sector costs.

5. Executive Order 13132

Executive Order 13132 establishes certain requirements that an agency must meet when it promulgates a final rule that imposes substantial direct requirement costs on State and local governments, preempts State law, or otherwise has Federalism implications. We have reviewed this final rule in light of Executive Order 13132 and have determined that it will not have any negative impact on the rights, roles, or responsibilities of State, local, or tribal governments.

6. Overall Impact

The following analysis, in conjunction with the remainder of this document, demonstrates that this final rule is consistent with the regulatory philosophy and principles identified in Executive Order 12866, the RFA, and section 1102(b) of the Act. We have determined that the final rule has a significant economic impact on a substantial number of small entities or a significant impact on the operations of a substantial number of small rural hospitals.

B. Anticipated Effects of the Final Rule

We discuss below the impacts of this final rule on the budget and on IRFs.

1. Basis and Methodology of Estimates

In this final rule, we are implementing policy changes and payment rate updates for the IRF PPS. Based on the overall percentage change in payments per discharge estimated using a payment simulation model developed by RAND under contract with CMS (a 3.4 percent increase), we estimate the total impact of these changes for estimated FY 2006 payments compared to estimated FY 2005 payments to be approximately a $210 million increase. This amount does not reflect changes in hospital admissions or case-mix intensity, which also may affect the overall change in payments from FY 2005 to FY 2006.

We have prepared separate impact analyses of each of the changes to the IRF PPS. RAND's payment simulation model relies on the most recent available data (FY 2003) to enable us to estimate the impacts on payments per discharge of certain changes we are implementing in this final rule.

The data used in developing the quantitative analyses of estimated changes in payments per discharge Start Printed Page 47946presented below are taken from the FY 2003 MedPAR file and the most current Provider-Specific File that is used for payment purposes. Data from the most recently available IRF cost reports were used to estimate costs and to categorize hospitals. The data also include the FY 2004 home office costs for HealthSouth facilities, as described in section IV of the preamble to this final rule.

Our analysis has several qualifications. First, we do not make adjustments for behavioral changes that hospitals may adopt in response to the policy changes, and we do not adjust for future changes in such variables as admissions, lengths of stay, or case-mix. Second, due to the interdependent nature of the IRF PPS payment components, it is very difficult to precisely quantify the impact associated with each change.

Using cases in the FY 2003 MedPAR file, we simulated payments under the IRF PPS given various combinations of payment parameters.

The changes discussed separately below are the following:

  • The effects of the annual market basket update (using the rehabilitation hospital, psychiatric hospital, and long-term care hospital (RPL) market basket) to IRF PPS payment rates required by sections 1886(j)(3)(A)(i) and 1886(j)(3)(C) of the Act.
  • The effects of applying the budget-neutral labor-related share and wage index adjustment, as required under section 1886(j)(6) of the Act.
  • The effects of the decrease to the standard payment amount to account for the increase in estimated aggregate payments due to changes in coding, as required under section 1886(j)(2)(C)(ii) of the Act.
  • The effects of the budget-neutral changes to the tier comorbidities, CMGs, motor score index, and relative weights, under the authority of section 1886(j)(2)(C)(i) of the Act.
  • The effects of the one year budget-neutral transition policy for adopting the new CBSA-based geographic area definitions announced by OMB in June 2003.
  • The effects of the 3 year budget-neutral hold-harmless policy for IRFs that are rural under § 412.602 during FY 2005, but are urban under § 412.602 during FY 2006 and lose the rural adjustment resulting in a loss of estimated IRF PPS payments and meets the intent of the hold harmless policy.
  • The effects of the implementation of a budget-neutral teaching status adjustment, as permitted under section 1886(j)(3)(A)(v) of the Act.
  • The effects of the budget-neutral update to the percentage amount by which payments are adjusted for IRFs located in rural areas, as permitted under section 1886(j)(3)(A)(v) of the Act.
  • The effects of the budget-neutral update to the formula used to calculate the payment adjustment for IRFs based on the percentage of low-income patients they treat, as permitted under section 1886(j)(3)(A)(v) of the Act.
  • The effects of the change to the outlier loss threshold amount to maintain total estimated outlier payments at 3 percent of total estimated payments to IRFs in FY 2006, consistent with section 1886(j)(4) of the Act.
  • The total change in estimated payments based on the FY 2006 policies relative to estimated payments based on FY 2005 policies.

To illustrate the impacts of the FY 2006 estimated changes, our analysis begins with a FY 2005 baseline simulation model using: IRF charges from FY 2003 inflated to FY 2005 using the market basket; the FY 2005 PRICER; the estimated percent of outlier payments in FY 2005; the FY 2005 CMG GROUPER (version 1.22); the MSA designations for IRFs based on OMB's MSA definitions prior to June 2003; the FY 2005 wage index; the FY 2005 labor-market share; the FY 2005 formula for the LIP adjustment; and the FY 2005 percentage amount of the rural adjustment.

Each policy change is then added incrementally to this baseline model, finally arriving at an FY 2006 model incorporating all of the changes to the IRF PPS. This allows us to isolate the effects of each change. Note that, in computing estimated payments per discharge for each of the policy changes, the outlier loss threshold has been adjusted so that estimated outlier payments are 3 percent of total estimated payments.

Our final comparison illustrates the percent change in estimated payments per discharge from FY 2005 to FY 2006. One factor that affects the changes in IRFs' estimated payments from FY 2005 to FY 2006 is that we currently estimate total outlier payments during FY 2005 to be 1.2 percent of total estimated payments. As discussed in the August 7, 2001 final rule (66 FR at 41362), our policy is to set total estimated outlier payments at 3 percent of total estimated payments. Because estimated outlier payments during FY 2005 were below 3 percent of total payments, estimated outlier payments in FY 2006 are projected to increase by an additional 1.8 percent over estimated payments in FY 2005 because of the change in the outlier loss threshold to achieve the 3 percent target.

2. Analysis of Table 13

Table 13 displays the results of our analysis. The table categorizes IRFs by geographic location, including urban or rural location and location with respect to CMS' nine regions of the country. In addition, the table divides IRFs into those that are separate rehabilitation hospitals (otherwise called freestanding hospitals in this section), those that are rehabilitation units of a hospital (otherwise called hospital units in this section), rural or urban facilities by ownership (otherwise called for-profit, non-profit, and government), and by teaching status. The top row of the table shows the overall impact on the 1,188 IRFs included in the analysis.

The next twelve rows of Table 13 contain IRFs categorized according to their geographic location, designation as either a freestanding hospital or a unit of a hospital, and by type of ownership: All urban, which is further divided into urban units of a hospital, urban freestanding hospitals, by type of ownership, and rural, which is further divided into rural units of a hospital, rural freestanding hospitals, and by type of ownership. There are 998 IRFs located in urban areas included in our analysis. Among these, there are 802 IRF units of hospitals located in urban areas and 196 freestanding IRF hospitals located in urban areas. There are 190 IRFs located in rural areas included in our analysis. Among these, there are 169 IRF units of hospitals located in rural areas and 21 freestanding IRF hospitals located in rural areas. There are 354 for-profit IRFs. Among these, there are 295 IRFs in urban areas and 59 IRFs in rural areas. There are 708 non-profit IRFs. Among these, there are 603 urban IRFs and 105 rural IRFs. There are 126 government-owned IRFs. Among these, there are 100 urban IRFs and 26 rural IRFs.

The following three parts of Table 13 show IRFs grouped by their geographic location within a region, and the last part groups IRFs by teaching status. First, IRFs located in urban areas are categorized with respect to their location within a particular one of nine geographic regions. Second, IRFs located in rural areas are categorized with respect to their location within a particular one of the nine CMS regions. In some cases, especially for rural IRFs located in the New England, Mountain, and Pacific regions, the number of IRFs represented is small. Finally, IRFs are grouped by teaching status, including non-teaching IRFs, IRFs with an intern and resident to ADC ratio less than 10 percent, IRFs with an intern and resident to ADC ratio greater than or Start Printed Page 47947equal to 10 percent and less than or equal to 19 percent, and IRFs with an intern and resident to ADC ratio greater than 19 percent.

Table 13.—Projected Impact of FY 2006 Refinements to the IRF PPS

Facility classification (1)Number of IRFs (2)Number of cases (3)FY06 Wage Index and Labor-share (4)Outlier (5)Market Basket (6)New CMG, new tiers, and motor score (7)Rural adjust. (8)New LIP adjust. (9)Teach. Status adjust. (10)1.9% reduct. (11)Total change % (12)
Total1,188461,7380.0%1.8%3.6%0.0%0.0%0.0%0.0%−1.9%3.4
Urban unit802261,2290.12.33.60.9−0.20.10.5−1.95.3
Rural unit16934,664−1.33.13.61.71.3−0.1−0.9−1.95.5
Urban hospital196158,9680.20.53.6−1.70.0−0.1−0.5−1.90.0
Rural hospital216,877−1.67.03.6−0.71.30.0−1.0−1.96.5
Urban For-Profit295154,5260.40.73.6−1.80.00.0−0.8−1.90.0
Rural For-Profit5911,952−1.93.83.60.21.30.2−1.0−1.94.2
Urban Non-Profit603237,3840.02.13.61.0−0.20.00.5−1.95.0
Rural Non-Profit10523,793−1.04.13.61.71.3−0.3−0.8−1.96.7
Urban Government10028,287−0.22.53.60.50.00.51.7−1.96.7
Rural Government265,796−1.52.63.61.41.30.3−1.0−1.94.8
Urban998420,1970.11.63.6−0.1−0.10.00.1−1.93.2
Rural19041,541−1.43.83.61.21.3−0.1−0.9−1.95.7
Urban by region:
New England3520,612−0.31.73.6−0.7−0.3−0.3−0.6−1.91.1
Middle Atlantic15676,962−0.42.03.61.1−0.20.01.6−1.95.8
South Atlantic12473,6770.40.63.6−0.50.10.0−0.3−1.91.9
East North Central18969,3150.12.33.61.2−0.2−0.20.1−1.94.9
East South Central5430,4730.20.03.6−1.40.40.1−0.5−1.90.6
West North Central7122,217−0.12.13.60.6−0.2−0.10.1−1.94.2
West South Central18476,0880.51.83.6−0.7−0.3−0.1−0.5−1.92.3
Mountain6924,287−0.21.23.6−2.2−0.1−0.1−0.5−1.9−0.2
Pacific11626,5660.82.23.6−0.8−0.31.10.0−1.94.7
Rural by region:
New England49240.42.13.61.71.2−0.4−0.9−1.95.9
Middle Atlantic195,377−1.18.23.61.51.4−0.4−1.0−1.910.3
South Atlantic225,440−1.02.53.61.21.30.1−1.0−1.94.8
East North Central285,618−1.03.03.61.91.2−0.4−0.9−1.95.5
East South Central205,362−1.92.23.61.11.30.3−0.7−1.93.9
West North Central305,351−1.32.33.62.71.2−0.2−0.6−1.95.8
West South Central5412,016−1.74.33.60.31.30.1−1.0−1.94.9
Mountain9902−3.29.43.62.61.2−0.4−0.9−1.910.2
Pacific45510.92.83.6−2.71.1−0.8−0.8−1.92.0
Teaching status:
Non-teaching1,053400,0720.01.63.6−0.10.0−0.1−0.9−1.92.2
Resident to ADC less than 10%7139,8880.32.53.60.3−0.30.22.2−1.97.0
Resident to ADC 10%-19%4217,793−0.92.83.60.4−0.31.19.1−1.914.3
Resident to ADC greater than 19%223,985−0.14.13.60.0−0.31.119.5−1.927.4

3. Impact of the Market Basket Update to the IRF PPS Payment Rates (Using the RPL Market Basket) (Column 6)

In column 6 of Table 13, we present the estimated effects of the market basket update to the IRF PPS payment rates, as discussed in section VI.B.1 of this final rule. Section 1886(j)(3)(A)(i) of the Act requires us annually to update the per discharge prospective payment rate for IRFs by an increase factor specified by the Secretary and based on an appropriate percentage increase in a market basket of goods and services comprising services for which payment is made to IRFs, as specified in section 1886(j)(3)(C) of the Act.

As discussed in detail in section VI.B.1 of this final rule, we are using a new market basket that reflects the operating and capital cost structures of inpatient rehabilitation facilities, inpatient psychiatric facilities, and long-term care hospitals, referred to as the RPL market basket. The FY 2006 update for IRF PPS payments using the FY 2002-based RPL market basket and the Global Insight's 2nd quarter 2005 forecast will be 3.6 percent.

In the aggregate, and across all hospital groups, the update will result in a 3.6 percent increase in overall estimated payments to IRFs.

4. Impact of the 1.9 Percent Decrease in the Standard Payment Amount To Account for Coding Changes (Column 11)

In column 11 of Table 13, we present the estimated effects of the decrease in the standard payment amount to account for the increase in aggregate payments due to changes in coding that do not reflect real changes in case mix, as discussed in section VI.A of this final rule. Section 1886(j)(2)(C)(ii) of the Act requires us to adjust the per discharge PPS payment rate to eliminate the effect of coding or classification changes that do not reflect real changes in case mix if we determine that such changes result in a change in aggregate payments under the classification system.

In the aggregate, and across all hospital groups, the update will result in a 1.9 percent decrease in overall estimated payments to IRFs. Thus, we estimate that the 1.9 percent reduction in the standard payment amount will result in a cost savings to the Medicare program of approximately $120 million.

5. Impact of the Changes to the CMGs and Tiers and Recalibration of Relative Weights (Column 7)

In column 7 of Table 13, we present the estimated effects of the changes to the tier comorbidities, the CMGs, the motor score index, and the recalibration of the relative weights, as discussed in section V of this final rule. Section 1886(j)(2)(C)(i) of the Act requires us to Start Printed Page 47948adjust from time to time the classifications and weighting factors as appropriate to reflect changes in treatment patterns, technology, case mix, number of payment units for which payment under the IRF PPS is made, and any other factors which may affect the relative use of resources.

As described in section V.A.3 of this final rule, we are updating the tier comorbidities to remove certain comorbid condition codes from the list of comorbid conditions used to increase payment that we believe no longer merit additional payments, moving dialysis patients to tier one to increase payments for these patients, and aligning payments with the comorbidity conditions according to their effects on the relative costliness of patients. We are also updating the CMGs and the relative weights for the CMGs so that they better reflect the relative costliness of different types of IRF patients. We are also replacing the previous, unweighted motor score index with a weighted motor score index that better estimates the relative costliness of IRF patients. Finally, we are changing the GROUPER software so that, in cases where the provider has coded a 0 for the transfer to toilet item on the IRF-PAI, the GROUPER will change this raw score of 0 to a 2 instead of a 1.

To assess the impact of these changes, we compared estimated aggregate payments using the FY 2005 CMG relative weights (GROUPER version 1.22) to estimated aggregate payments using the FY 2006 CMG relative weights (GROUPER version 1.30). We note that, under the authority in section 1886(j)(2)(C)(i) of the Act and consistent with our rationale as described in section VI.B.8 of this final rule, we have applied a budget neutrality factor to ensure that the overall estimated payment impact of the tier and CMG changes is budget neutral (that is, in order that total estimated aggregate payments for FY 2006 with the change are equal to total estimated aggregate payment for FY 2006 without the change). Because we found that the relative weights we will use for calculating the FY 2006 payment rates are slightly higher, on average, than the relative weights we used in FY 2005, and that the effect of this would have been to increase estimated aggregate payments in FY 2006, the budget neutrality factor for the CMG and tier changes lowers the standard payment amount somewhat. Because the lower standard payment amount is balanced by the higher average weights, the effect is no change in overall estimated payments to IRFs. However, the distribution of estimated payments among facilities is affected, with some facilities receiving higher estimated payments and some facilities receiving lower estimated payments as a result of the tier and CMG changes, as shown in column 7 of Table 13.

Although, in the aggregate, these changes will not change overall estimated payments to IRFs, as shown in the zero impact in the first row of column 7, there are distributional effects of these changes. On average, the impacts of these changes on any particular group of IRFs are very small, with urban IRFs experiencing a 0.1 percent decrease and rural IRFs experiencing a 1.2 percent increase in estimated aggregate payments. The largest impacts are a 2.7 percent increase among rural IRFs in the West North Central region and a 2.7 percent decrease among rural IRFs in the Pacific region.

6. Impact of the Adoption (With a Blended One-Year Transition) of the New CBSA Labor Market Areas and the Changes to the Labor Share (Column 4)

In accordance with the broad discretion under section 1886(j)(6) of the Act, we previously defined hospital labor market areas based on the definitions of Metropolitan Statistical Areas (MSAs), Primary MSAs (PMSAs), and New England County Metropolitan Areas (NECMAs) issued by OMB as discussed in section VI.B.2 of this final rule. On June 6, 2003, OMB announced new Core-Based Statistical Areas (CBSAs), comprised of MSAs and the new Micropolitan Statistical Areas based on Census 2000 data. We are adopting the new CBSA definitions with a one-year blended transition as described in section VI.B.2 of this final rule, consistent with the inpatient prospective payment system, including the 49 new Metropolitan areas designated under the new definitions. We are also adopting CBSA definitions in New England in place of NECMAs. We are not adopting the newly defined Micropolitan Statistical Areas for use in the payment system, as Micropolitan Statistical Areas will remain part of the statewide rural areas for purposes of the IRF PPS payments, consistent with payments under the inpatient prospective payment system.

The estimated effects of these changes to the new CBSA-based designations with a one year blended transition, combined with the new labor share, are isolated in column 4 of Table 13 by holding all other payment parameters constant in this simulation. That is, column 4 shows the percentage changes in estimated payments when going from a model using the FY 2005 MSA designations to a model using the FY 2006 CBSA designations blended with the FY 2006 MSA designations and using the new labor share. As described in section VI.B.2 of this final rule, we are implementing a blended wage index for FY 2006 equal to 50 percent of the FY 2006 CBSA wage index value and 50 percent of the FY 2006 MSA wage index value for all IRFs for one year. The estimated effects of this policy are shown in column 4 of table 13.

Table 14 below compares the shifts in wage index values for IRFs for FY 2006 relative to FY 2005. A small number of IRFs (0.9 percent) will experience an increase of between 5 and 10 percent and 0.6 percent of IRFs will experience an increase of more than 10 percent. A small number of IRFs (0.6 percent) will experience decreases in their wage index values of at least 5 percent, but less than 10 percent. Furthermore, IRFs that will experience decreases in their wage index values of greater than 10 percent will be 0.1 percent.

The following table shows the projected impact for IRFs.

Table 14.—Impact of the FY 2006 Blended Transition Wage Index

Percent change in area wage indexPercent of IRFs
Decrease Greater Than 10.00.1
Decrease Between 5.0 and 10.00.6
Decrease Between 2.0 and 5.02.7
Decrease Between 0 and 2.031.0
No Change37.2
Increase Between 0 and 2.024.5
Increase Between 2.0 and 5.02.4
Increase Between 5.0 and 10.00.9
Increase Greater Than 10.00.6
Total 1100.0
1 May not exactly equal 100 percent due to rounding.

In addition, our analysis file consisted of 34 rural IRFs that change designations from a rural facility (under the MSA-based designations) to an urban facility (under the CBSA-based designations) and would experience estimated payment reductions due to the loss of the 19.14 percent rural adjustment. Based on our analysis, these IRFs would experience a reduction in estimated payments of between approximately $207 to up to approximately $3,070 (average amount of approximately $1,472) without a hold harmless policy.

Based on our estimates, the hold harmless policy would mitigate the estimated payment reductions of those rural IRFs in our analysis file. Although, we found that 5 IRFs would experience estimated payment increases under the hold harmless policy of between Start Printed Page 47949approximately $9 to approximately $380, these IRFs will not receive additional payments under the hold harmless policy. The remaining 29 rural IRFs under our hold harmless policy can expect estimated payment reductions of between approximately $32 to approximately $1,167 (average amount of approximately $426) in FY 2006 compared to our estimates above.

7. Impact of the Change to the Outlier Threshold Amount (Column 5)

We estimate total outlier payments in FY 2005 to be approximately 1.2 percent of total estimated payments, so we are updating the threshold from $11,211 in FY 2005 to $5,132 in FY 2006 in order to set total estimated outlier payments in FY 2006 equal to 3 percent of total estimated payments in FY 2006.

The impact of this change (as shown in column 5 of table 13) is to increase total estimated payments to IRFs by about 1.8 percent.

The effect on payments to rural IRFs will be to increase estimated payments by 3.8 percent, and the effect on payments to urban IRFs will be to increase estimated payments by 1.6 percent. The largest effect will be a 9.4 percent increase in estimated payments to rural IRFs in the Mountain region, and the smallest effect will be no change in estimated payments for urban IRFs located in the East South Central region.

8. Impact of the Budget-Neutral Teaching Status Adjustment (Column 10)

In column 10 of Table 13, we present the estimated effects of the budget-neutral implementation of a teaching status adjustment to the Federal prospective payment rate for IRFs that have teaching programs, as discussed in section VI.B.3 of this final rule. Section 1886(j)(3)(A)(v) of the Act requires the Secretary to adjust the Federal prospective payment rates for IRFs under the IRF PPS for such factors as the Secretary determines are necessary to properly reflect variations in necessary costs of treatment among rehabilitation facilities. Under the authority of section 1886(j)(3)(A)(v) of the Act, we are applying a budget neutrality factor to ensure that the overall estimated payment impact of the teaching status adjustment is budget neutral (that is, in order that total estimated aggregate payments for FY 2006 with the adjustment will equal total estimated aggregate payments for FY 2006 without the adjustment). Because IRFs with teaching programs will receive additional payments from the implementation of this new teaching status adjustment, the effect of the budget neutrality factor will be to reduce the standard payment amount, therefore reducing estimated payments to IRFs without teaching programs. By design, however, the estimated increases in payments to teaching facilities will balance the estimated decreases in payments to non-teaching facilities, and total estimated aggregate payments to all IRFs will remain unchanged. Therefore, the first row of column 10 of Table 13 contains our projection of a zero impact in the aggregate. However, the rest of column 10 gives the estimated distributional effects among different types of providers of this change. Some providers' estimated payments increase and some decrease with this change.

On average, the estimated impacts of this change on any particular group of IRFs are very small, with urban IRFs experiencing a 0.1 percent estimated increase and rural IRFs experiencing a 0.9 percent estimated decrease.

The largest decrease in estimated payments is a 1.0 percent decrease among freestanding rural IRFs, rural for-profit facilities, rural government-owned facilities, and rural facilities in the Middle Atlantic, South Atlantic, and West South Central regions.

Overall, non-teaching hospitals will experience a 0.9 percent estimated decrease. The largest impacts are a 19.5 percent estimated increase among teaching facilities with intern and resident to ADC ratios greater than 19 percent. Teaching facilities that have intern and resident to ADC ratios greater than or equal to 10 percent and less than or equal to 19 percent will experience an estimated increase of 9.1 percent. Teaching facilities with resident and intern to ADC ratios less than 10 percent will experience an estimated increase of 2.2 percent.

9. Impact of the Update to the Rural Adjustment (Column 8)

In column 8 of Table 13, we present the estimated effects of the budget-neutral update to the percentage adjustment to the Federal prospective payment rates for IRFs located in rural areas, as discussed in section VI.B.4 of this final rule. Section 1886(j)(3)(A)(v) of the Act requires the Secretary to adjust the Federal prospective payment rates for IRFs under the IRF PPS for such factors as the Secretary determines are necessary to properly reflect variations in necessary costs of treatment among rehabilitation facilities.

In accordance with section 1886(j)(3)(A)(v) of the Act, we are changing the rural adjustment percentage, based on FY 2003 data with an adjustment to account for the absence of HealthSouth home office costs in that year (see the discussion in section IV of the preamble to this final rule), from 19.14 percent to 21.3 percent.

Because we are making this update to the rural adjustment in a budget neutral manner under the broad authority conferred by section 1886(j)(3)(A)(v) of the Act, estimated payments to urban facilities will decrease in proportion to the total increase in estimated payments to rural facilities. To accomplish this estimated redistribution of resources between urban and rural facilities, we applied a budget neutrality factor to reduce the standard payment amount. Rural facilities will receive an increase to the standard payment amount, and urban facilities will not. Overall, estimated aggregate payments to IRFs will not change, as indicated by the zero impact we project in the first row of column 8. However, estimated payments will be redistributed among rural and urban IRFs, as indicated by the rest of the column. On average, because there are a relatively small number of rural facilities, the estimated impacts of this change on urban IRFs are relatively small, with all urban IRFs experiencing a 0.1 percent estimated decrease. The estimated impact on rural IRFs is somewhat larger, with rural IRFs experiencing a 1.3 percent estimated increase. The largest estimated impacts are a 1.4 percent estimated increase among rural IRFs in the Middle Atlantic region and a 0.3 percent estimated decrease among urban facilities in the New England, West South Central, and Pacific regions, and among all categories of teaching facilities.

10. Impact of the Update to the LIP Adjustment (Column 9)

In column 9 of Table 13, we present the estimated effects of the budget-neutral update to the adjustment to the Federal prospective payment rates for IRFs according to the percentage of low-income patients they treat, as discussed in section VI.B.5 of this final rule. Section 1886(j)(3)(A)(v) of the Act requires the Secretary to adjust the Federal prospective payment rates for IRFs under the IRF PPS for such factors as the Secretary determines are necessary to properly reflect variations in necessary costs of treatment among rehabilitation facilities.

In accordance with section 1886(j)(3)(A)(v) of the Act, we are changing the formula for the LIP adjustment, based on FY 2003 data with an adjustment to account for the absence of HealthSouth home office costs in that year (see the discussion in Start Printed Page 47950section IV of the preamble to this final rule), to raise the amount of 1 plus the DSH patient percentage to the power of 0.6229 instead of the power of 0.4838. Therefore, the formula to calculate the low-income patient or LIP adjustment will be as follows:

(1 + DSH patient percentage) raised to the power of (.6229)

Where DSH patient percentage =

Because we are making this update to the LIP adjustment in a budget neutral manner, estimated payments will be redistributed among providers, according to their low-income percentages, but total estimated aggregate payments to facilities will not change. To do this, we applied a budget neutrality factor that lowered the standard payment amount in proportion to the amount of estimated payment increase that is attributable to the increased LIP adjustment payments. This will result in no change to estimated aggregate payments, which is reflected in the projected zero impact shown in the first row of column 9 of Table 13. The remaining rows of the column show the estimated impacts on different categories of providers. On average, the estimated impacts of this change on any particular group of IRFs are small, with urban IRFs experiencing no change in estimated aggregate payments and rural IRFs experiencing a 0.1 percent decrease in estimated aggregate payments. The largest estimated impacts are a 1.1 percent estimated increase among IRFs with 10 percent or higher intern and resident to ADC ratios and a 0.8 percent estimated decrease among rural IRFs in the Pacific region.

11. All Changes (Column 12)

Column 12 of Table 13 compares our estimates of the payments per discharge, incorporating all changes reflected in this final rule for FY 2006, to our estimates of payments per discharge in FY 2005 (without these changes). This column includes all of the policy changes.

Column 12 reflects all estimated FY 2006 changes relative to FY 2005, shown in columns 4 though 11. The average estimated increase for all IRFs is approximately 3.4 percent. This estimated increase includes the effects of the 3.6 percent market basket update. It also reflects the 1.8 percentage point difference between the estimated outlier payments in FY 2005 (1.2 percent of total estimated payments) and the estimate of the percentage of outlier payments in FY 2006 (3 percent), as described in section VI.B.6 of this final rule. As a result, payments per discharge are estimated to be 1.8 percent lower in FY 2005 than they would have been had the 3 percent target outlier payment percentage been met, resulting in a 1.8 percent greater increase in total estimated FY 2006 payments than would otherwise have occurred.

It also includes the estimated impact of the one-time 1.9 percent reduction in the standard payment conversion factor to account for changes in coding that increased payments to IRFs. Because we are making the remainder of the changes outlined in this final rule in a budget-neutral manner, they do not affect total estimated IRF payments in the aggregate. However, as described in more detail in each section, they do affect the estimated distribution of payments among providers.

There might also be interactive effects among the various factors comprising the payment system that we are not able to isolate. For these reasons, the estimated values in column 12 may not equal the sum of the estimated changes described above.

12. Accounting Statement

As required by OMB Circular A-4 (available at http://www.whitehouse.gov/​omb/​circulars/​a004/​a-4.pdf), in Table 15 below, we have prepared an accounting statement showing the classification of the expenditures associated with the provisions of this final rule. This table provides our best estimate of the increase in Medicare payments under the IRF PPS as a result of the changes presented in this final rule based on the data for 1,188 IRFs in our database. All expenditures are classified as transfers to Medicare providers (that is, IRFs).

Table 15.—Accounting Statement: Classification of Estimated Expenditures, From FY 2005 to FY 2006

[In millions]

CategoryTransfers
Annualized Monetized Transfers$210.
From Whom to Whom?Federal Government to IRF Medicare Providers.

13. Alternatives Considered

Because we have determined that this final rule will have a significant economic impact on IRFs, we will discuss the alternative changes to the IRF PPS that we considered. We reviewed the options considered in the proposed rule and took into consideration comments received during the public comment period as discussed in the preamble of this final rule.

The other option we considered before deciding to update the CMGs with the fiscal year 2003 data was to maintain the same CMG structure but recalculate the relative weights for the current CMGs using the 2003 data. After carefully reviewing the results of RAND's regression analysis, which compared the predictive ability of the CMGs under 3 scenarios (not updating the CMGs or the relative weights, updating only the relative weights and not the CMGs, and updating both the relative weights and the CMGs), we believe (based on RAND's analysis and a careful review of the comments we received on the FY 2006 proposed rule (70 FR 30188)) that updating both the relative weights and the CMGs will allow the classification system to do a better job of reflecting changes in treatment patterns, technology, case mix, and other factors which may affect the relative use of resources. For these reasons, we believe these changes will Start Printed Page 47951improve the accuracy of payments in the IRF PPS.

We considered alternative options before deciding to implement an objective weighted motor score methodology for classifying patients into CMGs. The first of these options was to keep the non-weighted motor score methodology used previously. However, we considered weighted motor score methodologies because RAND's regression analysis indicated that the weighted methodologies would substantially improve the predictive ability of the system. We had not previously proposed weighted motor score methodologies for the IRF PPS because most experts previously believed that the data were not complete and accurate enough before the IRF PPS (although they were the most complete and accurate data available at the time). However, the technical expert panel that reviewed RAND's analyses and advised RAND regarding the methodology generally indicated that the data are now sufficient to support a weight motor score.

RAND assessed different weighting methodologies for both the motor score index and the cognitive score index. They discovered that weighting the motor score index improved the predictive ability of the system, whereas weighting the cognitive score index did not. Furthermore, the cognitive score index has never had much of an effect (in some RICs, it has no effect) on the assignment of patients to CMGs because the motor score tends to be much stronger at predicting a patient's expected costs in an IRF than the cognitive score. For these reasons, we proposed a weighting methodology for the motor score index, but proposed to use the same cognitive score index used previously for the IRF classification system. We believe that it would be futile to expend resources on changing the cognitive score methodology at this time when it would not benefit the Medicare program.

We considered various weighted motor score methodologies, including one which would require computing 378 different weights (18 different weights for the motor and cognitive indices that could all differ across 21 RICs). Rather than introduce this level of complexity to the system, RAND decided to explore simpler weighting methodologies that would still increase the predictive power of the system.

We also considered defining some simple combinations of the items that make up the motor score index and assigning weights to the groups of items instead of to the individual items. For example, we considered summing the three transfer items together to form a group with a weight of two, since they contributed about twice as much in the cost regression as the self-care items. We also considered assigning the self-care items a weight of one and the bladder and bowel items as a group a weight close to zero, since they contributed little to predicting cost in the regression analysis. We tried a number of variations and combinations of this, but RAND's TEP generally rejected these weighting schemes. They believed that introducing elements of subjectivity into the development of the weighting scheme may invite controversy, and that it is better to use an objective algorithm to derive the appropriate weights. We agree that an objective weighting scheme is best because it is based on regression analysis of the amount that various components of the motor score index contribute to predicting patient costs, using the best available data we have. For this reason, we decided to adopt the weighting scheme that applies the average optimal weights.

We considered a reduction to the standard payment amount by an amount up to 5.8 percent because one of RAND's methodologies for determining the amount of real change in case mix and the amount of coding change that occurred between 1999 and 2002 suggested that coding change could possibly have been responsible for up to 5.8 percent of the observed increase in IRFs' case mix. Furthermore, a separate analysis by RAND found that if all IRFs had been paid based on 100 percent of the IRF PPS payment rates throughout all of 2002 (some IRFs were still transitioning to PPS payments during 2002), PPS payments during 2002 would have been 17 percent higher than IRFs' costs. This suggests that we could potentially have implemented a reduction greater than 1.9 and up to 5.8 percent.

We decided to implement a 1.9 percent reduction to the standard payment amount, the lowest possible amount of change attributable to coding change for the following reasons. First, the analyses described in this final rule are only the first of an ongoing series of studies to evaluate the existence and extent of payment increases due to coding changes. We will continue to review the need for any further reduction in the standard payment amount in subsequent years as part of our overall monitoring and evaluation of the IRF PPS. Second, we believe this approach, which is supported by RAND's analysis of the data, will adequately adjust for the increased payments to IRFs caused purely by coding changes, but will still provide the flexibility to account for the possibility that some of the observed changes in case mix may be attributed to other than coding changes. Furthermore, we chose the amount of the reduction in the standard payment amount in order to recognize that IRFs' current cost structures may be changing as they strive to comply with other recent Medicare policy changes, such as the criterion for IRF classification commonly known as the “75 percent rule.” We considered the public comments we received on this issue and believe that 1.9 percent is the appropriate reduction to the standard payment amount at this time.

We considered no transition to implement the CBSA-based geographic classifications. However, based on further analysis (and in response to comments), we considered various transition options. One option we considered was a 1-year budget neutral transition with a blended wage index (comprised of the FY 2006 MSA-based wage index and FY 2006 CBSA-based wage index) for IRFs that would experience a decrease in the wage index. We also considered floor and ceiling options as requested by commenters. However, the options did not reflect the policy goals to mitigate the overall impact of IRFs transitioning from the MSA-based wage index to the CBSA-based wage index while lessening the overall impact on the unadjusted base payment that would be equitable to all IRFs.

We also considered not adopting a hold harmless policy. However, based on additional review we determined that it was appropriate to implement a budget neutral 3 year hold harmless policy that would better reflect policy and maintain fiscal integrity of existing FY 2005 rural IRFs that will be redesignated as urban facilities under the CBSA-based designation.

We considered not proposing to add a teaching status adjustment to the IRF PPS because we had some concerns about proposing a teaching status adjustment for IRFs. The policy implications of implementing a teaching status adjustment on the basis of the results of RAND's recent analysis caused us to seek assurance that these results did not reflect an aberration based on only a single year's data and that the teaching status adjustment could be implemented in such a way that it would be equitable to all IRFs.

However, the regression analysis conducted by RAND for CY 2002 and FY 2003 showed a statistically significant difference in costs between IRFs with teaching programs and those without teaching programs. After Start Printed Page 47952reviewing RAND's analysis and the comments we received on the teaching status adjustment we proposed in the FY 2006 proposed rule (70 FR 30188), which were generally favorable, we determined that a teaching status adjustment for IRFs is appropriate at this time. We will continue to analyze the need for this adjustment in future data.

We believe that the analysis conducted by RAND using calendar year 2002 and FY 2003 data (the best available data we have and the first available data since implementation of the IRF PPS) left us little option other than to update the rural and LIP adjustments and the outlier loss threshold amount. The regression analysis indicated that facility-level adjustments (the rural and the LIP adjustments) should be updated to better reflect the costs of care among different types of IRF facilities. Similarly the regression analysis indicated that the outlier threshold amount needed to be updated so that estimated outlier payments for FY 2006 would equal 3 percent of total estimated IRF payments for FY 2006.

14. Conclusion

Overall, estimated payments per discharge for IRFs in FY 2006 are projected to increase by 3.4 percent, as reflected in column 12 of Table 13. IRFs in urban areas will experience a 3.2 percent increase in estimated payments per discharge compared with FY 2005. IRFs in rural areas, meanwhile, will experience a 5.7 percent estimated increase. Rehabilitation units in urban areas will experience a 5.3 percent increase in estimated payments per discharge, while freestanding rehabilitation hospitals in urban areas will experience no change in estimated payments per discharge. Rehabilitation units in rural areas will experience a 5.5 percent increase in estimated payments per discharge, while freestanding rehabilitation hospitals in rural areas will experience a 6.5 percent increase in estimated payments per discharge.

Overall, the largest estimated payment increase will be 27.4 percent among teaching IRFs with an intern and resident to ADC ratio greater than 19 percent and 14.3 percent among teaching IRFs with an intern and resident to ADC ratio greater than or equal to 10 percent and less than or equal to 19 percent. This is largely due to the teaching status adjustment. Other than for teaching IRFs, the largest estimated payment increase will be 10.3 percent among rural IRFs located in the Middle Atlantic region. This is due largely to the change in the CBSA-based designation from urban to rural, whereby the number of cases in the rural Middle Atlantic Region that will receive the new rural adjustment of 21.3 percent is projected to increase. The only overall decrease in estimated payments will occur among urban IRFs located in the Mountain census region, a decrease in estimated payments of 0.2 percent. This is due largely to the change in the CBSA-based designation from rural to urban. For non-profit IRFs, we found that rural non-profit facilities will receive the largest estimated payment increase of 6.7 percent. Conversely, for-profit urban facilities are projected to experience no change in payments for FY 2006.

In accordance with the provisions of Executive Order 12866, this regulation was reviewed by the Office of Management and Budget.

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List of Subjects in 42 CFR Part 412

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For the reasons set forth in the preamble, CMS amends 42 CFR chapter IV part 412 as set forth below:

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PART 412—PROSPECTIVE PAYMENT SYSTEMS FOR INPATIENT HOSPITAL SERVICES

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1. The authority citation for part 412 continues to read as follows:

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Authority: Secs. 1102 and 1871 of the Social Security Act (42 U.S.C. 1302 and 1395hh).

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2. Section 412.25 is amended by revising paragraph (a), introductory text, to read as follows:

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Excluded hospital units: Common requirements.

(a) Basis for exclusion. In order to be excluded from the prospective payment systems as specified in § 412.1(a)(1) and be paid under the inpatient psychiatric facility prospective payment system as specified in § 412.1(a)(2) or the inpatient rehabilitation facility prospective payment system as specified in § 412.1(a)(3), a psychiatric or rehabilitation unit must meet the following requirements.

* * * * *
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3. Section 412.602 is amended by revising the definitions of “Rural area” and “Urban area” to read as follows:

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Definitions.
* * * * *

Rural area means: For cost-reporting periods beginning on or after January 1, 2002, with respect to discharges occurring during the period covered by such cost reports but before October 1, 2005, an area as defined in § 412.62(f)(1)(iii). For discharges occurring on or after October 1, 2005, rural area means an area as defined in § 412.64(b)(1)(ii)(C).

* * * * *

Urban area means: For cost-reporting periods beginning on or after January 1, 2002, with respect to discharges occurring during the period covered by such cost reports but before October 1, 2005, an area as defined in § 412.62(f)(1)(ii). For discharges occurring on or after October 1, 2005, urban area means an area as defined in § 412.64(b)(1)(ii)(A) and § 412.64(b)(1)(ii)(B).

[Amended]
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4. Section 412.622 is amended by—

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A. In paragraph (b)(1), removing the cross references “§§ 413.85 and 413.86 of this chapter” and adding in their place “§ 413.75 and § 413.85 of this chapter”.

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B. In paragraph (b)(2)(i), removing the cross reference to “§ 413.80 of this chapter” and adding in its place “§ 413.89 of this chapter”.

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5. Section 412.624 is amended by—

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A. In paragraph (d)(1), removing the cross reference to “paragraph (e)(4)” and adding in its place “paragraph (e)(5)”.

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B. Adding a new paragraph (d)(4).

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C. Revising paragraphs (e)(4) and (e)(5).

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D. Adding new paragraphs (e)(6) and (e)(7).

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E. In paragraph (f)(2)(v), removing the cross references to “paragraphs (e)(1), (e)(2), and (e)(3) of this section” and adding in their place “paragraphs (e)(2), (e)(3), (e)(4), and (e)(7) of this section”.

End Amendment Part

The revisions and additions read as follows:

Methodology for calculating the Federal prospective payment rates.
* * * * *

(d) * * *

(4) Payment adjustment for Federal fiscal year 2006 and applicable Federal fiscal years. CMS adjusts the standard payment conversion factor based on any updates to the adjustments specified in paragraph (e)(2), (e)(3), (e)(4) and (e)(7), of this section, and to any revision specified in § 412.620(c) by a factor as specified by the Secretary.

(e) * * *

(4) Adjustments for teaching hospitals. For discharges on or after October 1, 2005, CMS adjusts the Federal prospective payment on a facility basis by a factor as specified by CMS for facilities that are teaching institutions or units of teaching institutions. This adjustment is made on Start Printed Page 47953a claim basis as an interim payment and the final payment in full for the claim is made during the final settlement of the cost report.

(5) Adjustment for high-cost outliers. CMS provides for an additional payment to an inpatient rehabilitation facility if its estimated costs for a patient exceed a fixed dollar amount (adjusted for area wage levels and factors to account for treating low-income patients, for rural location, and for teaching programs) as specified by CMS. The additional payment equals 80 percent of the difference between the estimated cost of the patient and the sum of the adjusted Federal prospective payment computed under this section and the adjusted fixed dollar amount. Effective for discharges occurring on or after October 1, 2003, additional payments made under this section will be subject to the adjustments at § 412.84(i), except that national averages will be used instead of statewide averages. Effective for discharges occurring on or after October 1, 2003, additional payments made under this section will also be subject to adjustments at § 412.84(m).

(6) Adjustments related to the patient assessment instrument. An adjustment to a facility's Federal prospective payment amount for a given discharge will be made, as specified under § 412.614(d), if the transmission of data from a patient assessment instrument is late.

(7) Adjustments for certain facilities geographically redesignated in FY 2006.

(i) General. For a facility defined as an urban facility under § 412.602 in FY 2006 that was previously defined as a rural facility in FY 2005 as the term rural was defined in FY 2005 under § 412.602 and whose payment, after applying the adjustment under this paragraph, will be lower only because of being defined as an urban facility in FY 2006 and it no longer qualified for the rural adjustment under § 412.624(e)(3) in FY 2006, CMS will adjust the facility's payment using the following method:

(A) For discharges occurring on or after October 1, 2005, and on or before September 30, 2006, the facility's payment will be increased by an adjustment of two thirds of its prior FY 2005 19.14 percent rural adjustment.

(B) For discharges occurring on or after October 1, 2006, and on or before September 30, 2007, the facility's payment will be increased by an adjustment of one third of its FY 2005 19.14 percent rural adjustment.

(ii) Exception. For discharges occurring on or after October 1, 2005 and on or before September 30, 2007, facilities whose payments, after applying the adjustment under this paragraph (e)(7)(i) of this section, will be higher because of being defined as an urban facility in FY 2006 and no longer being qualified for the rural adjustment under § 412.624(e)(3) in FY 2006, CMS will adjust the facility's payment by a portion of the applicable additional adjustment described in paragraph (e)(7)(i)(A) and (e)(7)(i)(B) of this section as determined by us.

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(Catalog of Federal Domestic Assistance Program No. 93.773, Medicare—Hospital Insurance; and Program No. 93.774, Medicare—Supplementary Medical Insurance Program)

Dated: July 26, 2005.

Mark B. McClellan,

Administrator, Centers for Medicare & Medicaid Services.

Approved: July 27, 2005.

Michael O. Leavitt,

Secretary.

End Signature

The following addendum will not appear in the Code of Federal Regulations.

Start Printed Page 47954

Table 1.—FY 2006 IRF PPS Transition Wage Index Table

[For discharges occurring on or after October 1, 2005 and on or before September 30, 2006]

SSA state/ county codeCounty nameMSA No.MSA urban/rural2006 MSA-based WI2006 CBSA-based WICBSA No.CBSA urban/ruralTransition wage index *
01000Autauga County, Alabama5240Urban0.83000.830033860Urban0.8300
01010Baldwin County, Alabama5160Urban0.79320.762899901Rural0.7780
01020Barbour County, Alabama01Rural0.76370.762899901Rural0.7633
01030Bibb County, Alabama01Rural0.76370.915713820Urban0.8397
01040Blount County, Alabama1000Urban0.91980.915713820Urban0.9178
01050Bullock County, Alabama01Rural0.76370.762899901Rural0.7633
01060Butler County, Alabama01Rural0.76370.762899901Rural0.7633
01070Calhoun County, Alabama0450Urban0.78810.788111500Urban0.7881
01080Chambers County, Alabama01Rural0.76370.762899901Rural0.7633
01090Cherokee County, Alabama01Rural0.7637.762899901Rural0.7633
01100Chilton County, Alabama01Rural0.76370.915713820Urban0.8397
01110Choctaw County, Alabama01Rural0.76370.762899901Rural0.7633
01120Clarke County, Alabama01Rural0.76370.762899901Rural0.7633
01130Clay County, Alabama01Rural0.76370.762899901Rural0.7633
01140Cleburne County, Alabama01Rural0.76370.762899901Rural0.7633
01150Coffee County, Alabama01Rural0.76370.762899901Rural0.7633
01160Colbert County, Alabama2650Urban0.78830.788322520Urban0.7883
01170Conecuh County, Alabama01Rural0.76370.762899901Rural0.7633
01180Coosa County, Alabama01Rural0.76370.762899901Rural0.7633
01190Covington County, Alabama01Rural0.76370.762899901Rural0.7633
01200Crenshaw County, Alabama01Rural0.76370.762899901Rural0.7633
01210Cullman County, Alabama01Rural0.76370.762899901Rural0.7633
01220Dale County, Alabama2180Urban0.75960.762899901Rural0.7612
01230Dallas County, Alabama01Rural0.76370.762899901Rural0.7633
01240De Kalb County, Alabama01Rural0.76370.762899901Rural0.7633
01250Elmore County, Alabama5240Urban0.83000.830033860Urban0.8300
01260Escambia County, Alabama01Rural0.76370.762899901Rural0.7633
01270Etowah County, Alabama2880Urban0.80490.804923460Urban0.8049
01280Fayette County, Alabama01Rural0.76370.762899901Rural0.7633
01290Franklin County, Alabama01Rural0.76370.762899901Rural0.7633
01300Geneva County, Alabama01Rural0.76370.753720020Urban0.7587
01310Greene County, Alabama01Rural0.76370.833646220Urban0.7987
01320Hale County, Alabama01Rural0.76370.833646220Urban0.7987
01330Henry County, Alabama01Rural0.76370.753720020Urban0.7587
01340Houston County, Alabama2180Urban0.75960.753720020Urban0.7567
01350Jackson County, Alabama01Rural0.76370.762899901Rural0.7633
01360Jefferson County, Alabama1000Urban0.91980.915713820Urban0.9178
01370Lamar County, Alabama01Rural0.76370.762899901Rural0.7633
01380Lauderdale County, Alabama2650Urban0.78830.788322520Urban0.7883
01390Lawrence County, Alabama21030Urban0.88940.889419460Urban0.8894
01400Lee County, Alabama0580Urban0.82150.821512220Urban0.8215
01410Limestone County, Alabama3440Urban0.88510.885126620Urban0.8851
01420Lowndes County, Alabama01Rural0.76370.830033860Urban0.7969
01430Macon County, Alabama01Rural0.76370.762899901Rural0.7633
01440Madison County, Alabama3440Urban0.88510.885126620Urban0.8851
01450Marengo County, Alabama01Rural0.76370.762899901Rural0.7633
01460Marion County, Alabama01Rural0.76370.762899901Rural0.7633
01470Marshall County, Alabama01Rural0.76370.762899901Rural0.7633
01480Mobile County, Alabama5160Urban0.79320.799533660Urban0.7964
01490Monroe County, Alabama01Rural0.76370.762899901Rural0.7633
01500Montgomery County, Alabama5240Urban0.83000.830033860Urban0.8300
01510Morgan County, Alabama2030Urban0.88940.889419460Urban0.8894
01520Perry County, Alabama01Rural0.76370.762899901Rural0.7633
01530Pickens County, Alabama01Rural0.76370.762899901Rural0.7633
01540Pike County, Alabama01Rural0.76370.762899901Rural0.7633
01550Randolph County, Alabama01Rural0.76370.762899901Rural0.7633
01560Russell County, Alabama1800Urban0.86900.869017980Urban0.8690
01570St Clair County, Alabama1000Urban0.91980.915713820Urban0.9178
01580Shelby County, Alabama1000Urban0.91980.915713820Urban0.9178
01590Sumter County, Alabama01Rural0.76370.762899901Rural0.7633
01600Talladega County, Alabama01Rural0.76370.762899901Rural0.7633
01610Tallapoosa County, Alabama01Rural0.76370.762899901Rural0.7633
01620Tuscaloosa County, Alabama8600Urban0.84400.833646220Urban0.8388
01630Walker County, Alabama01Rural0.76370.915713820Urban0.8397
01640Washington County, Alabama01Rural0.76370.762899901Rural0.7633
01650Wilcox County, Alabama01Rural0.76370.762899901Rural0.7633
01660Winston County, Alabama01Rural0.76370.762899901Rural0.7633
02013Aleutians County East, Alaska02Rural1.16371.174699902Rural1.1692
Start Printed Page 47955
02016Aleutians County West, Alaska02Rural1.16371.174699902Rural1.1692
02020Anchorage County, Alaska0380Urban1.21091.216511260Urban1.2137
02030Angoon County, Alaska02Rural1.16371.174699902Rural1.1692
02040Barrow-North Slope County, Alaska02Rural1.16371.174699902Rural1.1692
02050Bethel County, Alaska02Rural1.16371.174699902Rural1.1692
02060Bristol Bay Borough County, Alaska02Rural1.16371.174699902Rural1.1692
02068Denali County, Alaska02Rural1.16371.174699902Rural1.1692
02070Bristol Bay County, Alaska02Rural1.16371.174699902Rural1.1692
02080Cordova-Mc Carthy County, Alaska02Rural1.16371.174699902Rural1.1692
02090Fairbanks County, Alaska02Rural1.16371.114621820Urban1.1392
02100Haines County, Alaska02Rural1.16371.174699902Rural1.1692
02110Juneau County, Alaska02Rural1.16371.174699902Rural1.1692
02120Kenai-Cook Inlet County, Alaska02Rural1.16371.174699902Rural1.1692
02122Kenai Peninsula Borough, Alaska02Rural1.16371.174699902Rural1.1692
02130Ketchikan County, Alaska02Rural1.16371.174699902Rural1.1692
02140Kobuk County, Alaska02Rural1.16371.174699902Rural1.1692
02150Kodiak County, Alaska02Rural1.16371.174699902Rural1.1692
02160Kuskokwin County, Alaska02Rural1.16371.174699902Rural1.1692
02164Lake and Peninsula Borough, Alaska02Rural1.16371.174699902Rural1.1692
02170Matanuska County, Alaska02Rural1.16371.216511260Urban1.1901
02180Nome County, Alaska02Rural1.16371.174699902Rural1.1692
02185North Slope Borough, Alaska02Rural1.16371.174699902Rural1.1692
02188Northwest Arctic Borough, Alaska02Rural1.16371.174699902Rural1.1692
02190Outer Ketchikan County, Alaska02Rural1.16371.174699902Rural1.1692
02200Prince Of Wales County, Alaska02Rural1.16371.174699902Rural1.1692
02201Prince of Wales-Outer Ketchikan Census Area, Alaska02Rural1.16371.174699902Rural1.1692
02210Seward County, Alaska02Rural1.16371.174699902Rural1.1692
02220Sitka County, Alaska02Rural1.16371.174699902Rural1.1692
02230Skagway-Yakutat County, Alaska02Rural1.16371.174699902Rural1.1692
02231Skagway-Yakutat-Angoon Census Area, Alaska02Rural1.16371.174699902Rural1.1692
02232Skagway-Hoonah-Angoon Census Area, Alaska02Rural1.16371.174699902Rural1.1692
02240Southeast Fairbanks County, Alaska02Rural1.16371.174699902Rural1.1692
02250Upper Yukon County, Alaska02Rural1.16371.174699902Rural1.1692
02260Valdz-Chitna-Whitier County, Alaska02Rural1.16371.174699902Rural1.1692
02261Valdex-Cordove Census Area, Alaska02Rural1.16371.174699902Rural1.1692
02270Wade Hampton County, Alaska02Rural1.16371.174699902Rural1.1692
02280Wrangell-Petersburg County, Alaska02Rural1.16371.174699902Rural1.1692
02282Yakutat Borough, Alaska02Rural1.16371.174699902Rural1.1692
02290Yukon-Koyukuk County, Alaska02Rural1.16371.174699902Rural1.1692
03000Apache County, Arizona03Rural0.91400.893699903Rural0.9038
03010Cochise County, Arizona03Rural0.91400.893699903Rural0.9038
03020Coconino County, Arizona2620Urban1.06111.078722380Urban1.0699
03030Gila County, Arizona03Rural0.91400.893699903Rural0.9038
03040Graham County, Arizona03Rural0.91400.893699903Rural0.9038
03050Greenlee County, Arizona03Rural0.91400.893699903Rural0.9038
03055La Paz County, Arizona03Rural0.91400.893699903Rural0.9038
03060Maricopa County, Arizona6200Urban0.99820.998238060Urban0.9982
03070Mohave County, Arizona4120Urban1.11210.893699903Rural1.0029
03080Navajo County, Arizona03Rural0.91400.893699903Rural0.9038
03090Pima County, Arizona8520Urban0.89260.892646060Urban0.8926
03100Pinal County, Arizona6200Urban0.99820.998238060Urban0.9982
03110Santa Cruz County, Arizona03Rural0.91400.893699903Rural0.9038
03120Yavapai County, Arizona03Rural0.91400.989239140Urban0.9516
03130Yuma County, Arizona9360Urban0.88710.887149740Urban0.8871
04000Arkansas County, Arkansas04Rural0.77030.740699904Rural0.7555
04010Ashley County, Arkansas04Rural0.77030.740699904Rural0.7555
04020Baxter County, Arkansas04Rural0.77030.740699904Rural0.7555
04030Benton County, Arkansas2580Urban0.86360.863622220Urban0.8636
04040Boone County, Arkansas04Rural0.77030.740699904Rural0.7555
04050Bradley County, Arkansas04Rural0.77030.740699904Rural0.7555
04060Calhoun County, Arkansas04Rural0.77030.740699904Rural0.7555
04070Carroll County, Arkansas04Rural0.77030.740699904Rural0.7555
04080Chicot County, Arkansas04Rural0.77030.740699904Rural0.7555
04090Clark County, Arkansas04Rural0.77030.740699904Rural0.7555
04100Clay County, Arkansas04Rural0.77030.740699904Rural0.7555
04110Cleburne County, Arkansas04Rural0.77030.740699904Rural0.7555
04120Cleveland County, Arkansas04Rural0.77030.867338220Urban0.8188
04130Columbia County, Arkansas04Rural0.77030.740699904Rural0.7555
Start Printed Page 47956
04140Conway County, Arkansas04Rural0.77030.740699904Rural0.7555
04150Craighead County, Arkansas3700Urban0.81440.814427860Urban0.8144
04160Crawford County, Arkansas2720Urban0.83030.828322900Urban0.8293
04170Crittenden County, Arkansas4920Urban0.92340.921732820Urban0.9226
04180Cross County, Arkansas04Rural0.77030.740699904Rural0.7555
04190Dallas County, Arkansas04Rural0.77030.740699904Rural0.7555
04200Desha County, Arkansas04Rural0.77030.740699904Rural0.7555
04210Drew County, Arkansas04Rural0.77030.740699904Rural0.7555
04220Faulkner County, Arkansas4400Urban0.88260.882630780Urban0.8826
04230Franklin County, Arkansas04Rural0.77030.828322900Urban0.7993
04240Fulton County, Arkansas04Rural0.77030.740699904Rural0.7555
04250Garland County, Arkansas04Rural0.77030.924926300Urban0.8476
04260Grant County, Arkansas04Rural0.77030.882630780Urban0.8265
04270Greene County, Arkansas04Rural0.77030.740699904Rural0.7555
04280Hempstead County, Arkansas04Rural0.77030.740699904Rural0.7555
04290Hot Spring County, Arkansas04Rural0.77030.740699904Rural0.7555
04300Howard County, Arkansas04Rural0.77030.740699904Rural0.7555
04310Independence County, Arkansas04Rural0.77030.740699904Rural0.7555
04320Izard County, Arkansas04Rural0.77030.740699904Rural0.7555
04330Jackson County, Arkansas04Rural0.77030.740699904Rural0.7555
04340Jefferson County, Arkansas6240Urban0.86730.867338220Urban0.8673
04350Johnson County, Arkansas04Rural0.77030.740699904Rural0.7555
04360Lafayette County, Arkansas04Rural0.77030.740699904Rural0.7555
04370Lawrence County, Arkansas04Rural0.77030.740699904Rural0.7555
04380Lee County, Arkansas04Rural0.77030.740699904Rural0.7555
04390Lincoln County, Arkansas04Rural0.77030.867338220Urban0.8188
04400Little River County, Arkansas04Rural0.77030.740699904Rural0.7555
04410Logan County, Arkansas04Rural0.77030.740699904Rural0.7555
04420Lonoke County, Arkansas4400Urban0.88260.882630780Urban0.8826
04430Madison County, Arkansas04Rural0.77030.863622220Urban0.8170
04440Marion County, Arkansas04Rural0.77030.740699904Rural0.7555
04450Miller County, Arkansas8360Urban0.84130.841345500Urban0.8413
04460Mississippi County, Arkansas04Rural0.77030.740699904Rural0.7555
04470Monroe County, Arkansas04Rural0.77030.740699904Rural0.7555
04480Montgomery County, Arkansas04Rural0.77030.740699904Rural0.7555
04490Nevada County, Arkansas04Rural0.77030.740699904Rural0.7555
04500Newton County, Arkansas04Rural0.77030.740699904Rural0.7555
04510Ouachita County, Arkansas04Rural0.77030.740699904Rural0.7555
04520Perry County, Arkansas04Rural0.77030.882630780Urban0.8265
04530Phillips County, Arkansas04Rural0.77030.740699904Rural0.7555
04540Pike County, Arkansas04Rural0.77030.740699904Rural0.7555
04550Poinsett County, Arkansas04Rural0.77030.814427860Urban0.7924
04560Polk County, Arkansas04Rural0.77030.740699904Rural0.7555
04570Pope County, Arkansas04Rural0.77030.740699904Rural0.7555
04580Prairie County, Arkansas04Rural0.77030.740699904Rural0.7555
04590Pulaski County, Arkansas4400Urban0.88260.882630780Urban0.8826
04600Randolph County, Arkansas04Rural0.77030.740699904Rural0.7555
04610St Francis County, Arkansas04Rural0.77030.740699904Rural0.7555
04620Saline County, Arkansas4400Urban0.88260.882630780Urban0.8826
04630Scott County, Arkansas04Rural0.77030.740699904Rural0.7555
04640Searcy County, Arkansas04Rural0.77030.740699904Rural0.7555
04650Sebastian County, Arkansas2720Urban0.83030.828322900Urban0.8293
04660Sevier County, Arkansas04Rural0.77030.740699904Rural0.7555
04670Sharp County, Arkansas04Rural0.77030.740699904Rural0.7555
04680Stone County, Arkansas04Rural0.77030.740699904Rural0.7555
04690Union County, Arkansas04Rural0.77030.740699904Rural0.7555
04700Van Buren County, Arkansas04Rural0.77030.740699904Rural0.7555
04710Washington County, Arkansas2580Urban0.86360.863622220Urban0.8636
04720White County, Arkansas04Rural0.77030.740699904Rural0.7555
04730Woodruff County, Arkansas04Rural0.77030.740699904Rural0.7555
04740Yell County, Arkansas04Rural0.77030.740699904Rural0.7555
05000Alameda County, California5775Urban1.52201.522036084Urban1.5220
05010Alpine County, California05Rural1.02971.052499905Rural1.0411
05020Amador County, California05Rural1.02971.052499905Rural1.0411
05030Butte County, California1620Urban1.05421.054217020Urban1.0542
05040Calaveras County, California05Rural1.02971.052499905Rural1.0411
05050Colusa County, California05Rural1.02971.052499905Rural1.0411
05060Contra Costa County, California5775Urban1.52201.522036084Urban1.5220
Start Printed Page 47957
05070Del Norte County, California05Rural1.02971.052499905Rural1.0411
05080Eldorado County, California6920Urban1.18481.170040900Urban1.1774
05090Fresno County, California2840Urban1.04071.053623420Urban1.0472
05100Glenn County, California05Rural1.02971.052499905Rural1.0411
05110Humboldt County, California05Rural1.02971.052499905Rural1.0411
05120Imperial County, California05Rural1.02970.885620940Urban0.9577
05130Inyo County, California05Rural1.02971.052499905Rural1.0411
05140Kern County, California0680Urban1.00361.003612540Urban1.0036
05150Kings County, California05Rural1.02970.929625260Urban0.9797
05160Lake County, California05Rural1.02971.052499905Rural1.0411
05170Lassen County, California05Rural1.02971.052499905Rural1.0411
05200Los Angeles County, California4480Urban1.17321.173231084Urban1.1732
05210Los Angeles County, California4480Urban1.17321.173231084Urban1.1732
05300Madera County, California2840Urban1.04070.852131460Urban0.9464
05310Marin County, California7360Urban1.47121.471241884Urban1.4712
05320Mariposa County, California05Rural1.02971.052499905Rural1.0411
05330Mendocino County, California05Rural1.02971.052499905Rural1.0411
05340Merced County, California4940Urban1.05751.057532900Urban1.0575
05350Modoc County, California05Rural1.02971.052499905Rural1.0411
05360Mono County, California05Rural1.02971.052499905Rural1.0411
05370Monterey County, California7120Urban1.38231.382341500Urban1.3823
05380Napa County, California8720Urban1.35171.253134900Urban1.3024
05390Nevada County, California05Rural1.02971.052499905Rural1.0411
05400Orange County, California5945Urban1.16111.161142044Urban1.1611
05410Placer County, California6920Urban1.18481.170040900Urban1.1774
05420Plumas County, California05Rural1.02971.052499905Rural1.0411
05430Riverside County, California6780Urban1.09701.097040140Urban1.0970
05440Sacramento County, California6920Urban1.18481.170040900Urban1.1774
05450San Benito County, California05Rural1.02971.472241940Urban1.2510
05460San Bernardino County, California6780Urban1.09701.097040140Urban1.0970
05470San Diego County, California7320Urban1.12671.126741740Urban1.1267
05480San Francisco County, California7360Urban1.47121.471241884Urban1.4712
05490San Joaquin County, California8120Urban1.05641.056444700Urban1.0564
05500San Luis Obispo County, California7460Urban1.11181.111842020Urban1.1118
05510San Mateo County, California7360Urban1.47121.471241884Urban1.4712
05520Santa Barbara County, California7480Urban1.07711.077142060Urban1.0771
05530Santa Clara County, California7400Urban1.47441.472241940Urban1.4733
05540Santa Cruz County, California7485Urban1.47791.477942100Urban1.4779
05550Shasta County, California6690Urban1.18351.183539820Urban1.1835
05560Sierra County, California05Rural1.02971.052499905Rural1.0411
05570Siskiyou County, California05Rural1.02971.052499905Rural1.0411
05580Solano County, California8720Urban1.35171.427946700Urban1.3898
05590Sonoma County, California7500Urban1.29611.296142220Urban1.2961
05600Stanislaus County, California5170Urban1.19661.196633700Urban1.1966
05610Sutter County, California9340Urban1.03631.036349700Urban1.0363
05620Tehama County, California05Rural1.02971.052499905Rural1.0411
05630Trinity County, California05Rural1.02971.052499905Rural1.0411
05640Tulare County, California8780Urban0.99750.997547300Urban0.9975
05650Tuolumne County, California05Rural1.02971.052499905Rural1.0411
05660Ventura County, California8735Urban1.11051.110537100Urban1.1105
05670Yolo County, California9270Urban0.93781.170040900Urban1.0539
05680Yuba County, California9340Urban1.03631.036349700Urban1.0363
06000Adams County, Colorado2080Urban1.09041.090419740Urban1.0904
06010Alamosa County, Colorado06Rural0.93680.936899906Rural0.9368
06020Arapahoe County, Colorado2080Urban1.09041.090419740Urban1.0904
06030Archuleta County, Colorado06Rural0.93680.936899906Rural0.9368
06040Baca County, Colorado06Rural0.93680.936899906Rural0.9368
06050Bent County, Colorado06Rural0.93680.936899906Rural0.9368
06060Boulder County, Colorado1125Urban1.00461.004614500Urban1.0046
06070Chaffee County, Colorado06Rural0.93680.936899906Rural0.9368
06080Cheyenne County, Colorado06Rural0.93680.936899906Rural0.9368
06090Clear Creek County, Colorado06Rural0.93681.090419740Urban1.0136
06100Conejos County, Colorado06Rural0.93680.936899906Rural0.9368
06110Costilla County, Colorado06Rural0.93680.936899906Rural0.9368
06120Crowley County, Colorado06Rural0.93680.936899906Rural0.9368
06130Custer County, Colorado06Rural0.93680.936899906Rural0.9368
06140Delta County, Colorado06Rural0.93680.936899906Rural0.9368
06150Denver County, Colorado2080Urban1.09041.090419740Urban1.0904
Start Printed Page 47958
06160Dolores County, Colorado06Rural0.93680.936899906Rural0.9368
06170Douglas County, Colorado2080Urban1.09041.090419740Urban1.0904
06180Eagle County, Colorado06Rural0.93680.936899906Rural0.9368
06190Elbert County, Colorado06Rural0.93681.090419740Urban1.0136
06200El Paso County, Colorado1720Urban0.97920.979217820Urban0.9792
06210Fremont County, Colorado06Rural0.93680.936899906Rural0.9368
06220Garfield County, Colorado06Rural0.93680.936899906Rural0.9368
06230Gilpin County, Colorado06Rural0.93681.090419740Urban1.0136
06240Grand County, Colorado06Rural0.93680.936899906Rural0.9368
06250Gunnison County, Colorado06Rural0.93680.936899906Rural0.9368
0