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Medicare Program; Inpatient Psychiatric Facilities Prospective Payment System-Update for Fiscal Year Beginning October 1, 2015 (FY 2016)

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AGENCY:

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

ACTION:

Final rule.

SUMMARY:

This final rule updates the prospective payment rates for Medicare inpatient hospital services provided by inpatient psychiatric facilities (IPFs) (which are freestanding IPFs and psychiatric units of an acute care hospital or critical access hospital). These changes are applicable to IPF discharges occurring during fiscal year (FY) 2016 (October 1, 2015 through September 30, 2016). This final rule also implements: a new 2012-based IPF market basket; an updated IPF labor-related share; a transition to new Core Based Statistical Area (CBSA) designations in the FY 2016 IPF Prospective Payment System (PPS) wage index; a phase-out of the rural adjustment for IPF providers whose status changes from rural to urban as a result of the wage index CBSA changes; and new quality measures and reporting requirements under the IPF quality reporting program. This final rule also reminds IPFs of the October 1, 2015 implementation of the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM), and updates providers on the status of IPF PPS refinements.

DATES:

These regulations are effective October 1, 2015.

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FOR FURTHER INFORMATION CONTACT:

Katherine Lucas or Jana Lindquist, (410) 786-7723, for general information. Hudson Osgood, (410) 786-7897 or Bridget Dickensheets, (410) 786-8670, for information regarding the market basket and labor-related share.

Theresa Bean, (410) 786-2287, for information regarding the regulatory impact analysis. Rebecca Kliman, (410) 786-9723, or Jeffrey Buck, (410) 786-0407, for information regarding the inpatient psychiatric facility quality reporting program.

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SUPPLEMENTARY INFORMATION:

Availability of Certain Tables Exclusively Through the Internet on the CMS Web site

In the past, tables setting forth the Wage Index for Urban Areas Based on CBSA Labor Market Areas and the Wage Index Based on CBSA Labor Market Areas for Rural Areas were published in the Federal Register as an Addendum to the annual PPS rulemaking (that is, the PPS proposed and final rules or, when applicable, the current update notice). However, beginning in FY 2015, these wage index tables are no longer published in the Federal Register. Instead, these tables are available exclusively through the Internet. The wage index tables for this final rule are available exclusively through the Internet on the CMS Web site at http://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientPsychFacilPPS/​WageIndex.html.

To assist readers in referencing sections contained in this document, we are providing the following table of contents.

Table of Contents

I. Executive Summary

A. Purpose

B. Summary of the Major Provisions

C. Summary of Impacts

II. Background

A. Overview of the Legislative Requirements for the IPF PPS

B. Overview of the IPF PPS

C. Annual Requirements for Updating the IPF PPS

III. Provisions of the Final Rule and Responses to Comments

A. Market Basket for the IPF PPS

1. Background

2. Overview of the 2012-Based IPF Market Basket

3. Creating an IPF-Specific Market Basket

a. Development of Cost Categories and Weights

i. Medicare Cost Reports

ii. Final Major Cost Category Computation

iii. Derivation of the Detailed Operating Cost Weights

iv. Derivation of the Detailed Capital Cost Weights

v. 2012-Based IPF Market Basket Cost Categories and Weights

b. Selection of Price Proxies

i. Price Proxies for the Operating Portion of the 2012-Based IPF Market Basket

ii. Price Proxies for the Capital Portion of the 2012-Based IPF Market Basket

iii. Summary of Price Proxies of the 2012-Based IPF Market Basket

4. FY 2016 Market Basket Update

5. Productivity Adjustment

6. Labor-Related Share

B. Updates to the IPF PPS Rates for FY 2016 (Beginning October 1, 2015)

1. Determining the Standardized Budget-Neutral Federal Per Diem Base Rate

2. FY 2016 Update of the Federal Per Diem Base Rate and Electroconvulsive

Therapy (ECT) Payment per Treatment

C. Updates to the IPF PPS Patient-Level Adjustment Factors

1. Overview of the IPF PPS Adjustment Factors

2. IPF-PPS Patient-Level Adjustments

a. MS-DRG Assignment

b. Payment for Comorbid Conditions

3. Patient Age Adjustments

4. Variable Per Diem Adjustments

D. Updates to the IPF PPS Facility-Level Adjustments

1. Wage Index Adjustment

a. Background

b. Wage Index for FY 2016

c. OMB Bulletins and Transitional Wage Index

d. Adjustment for Rural Location and The Phase Out the Rural Adjustment for IPFs Losing Their Rural Adjustment Due to CBSA Changes

e. Budget Neutrality Adjustment

2. Teaching Adjustment

3. Cost of Living Adjustment for IPFs Located in Alaska and Hawaii

4. Adjustment for IPFs With a Qualifying Emergency Department (ED)

E. Other Payment Adjustments and Policies

1. Outlier Payment Overview

2. Update to the Outlier Fixed Dollar Loss Threshold Amount

3. Update to IPF Cost-to-Charge Ratio Ceilings

IV. Other Payment Policy Issues

A. ICD-10-CM and ICD-10-PCS Implementation

B. Status of Future IPF PPS Refinements

V. Inpatient Psychiatric Facilities Quality Reporting (IPFQR) Program

A. Background

1. Statutory Authority

2. Covered Entities

3. Considerations in Selecting Quality Measures

B. Retention of IPFQR Program Measures Adopted in Previous Payment Determinations

C. Removal of HBIPS-4 From the IPFQR Program Measure Set for the FY 2017 Payment Determination and Subsequent Years

D. New Quality Measures for the FY 2018 Payment Determination and Subsequent Years

1. TOB-3 Tobacco Use Treatment Provided or Offered at Discharge and the Subset Measure TOB-3a Tobacco Use Treatment at Discharge (NQF # 1656)

2. SUB-2 Alcohol Use Brief Intervention Provided or Offered and SUB-2a Alcohol Use Brief Intervention (NQF # 1663)

3. Transition Record With Specified Elements Received by Discharged Patients (Discharges From an Inpatient Facility to Home/Self Care or Any Other Site of Care) (NQF #0647) and Removal of HBIPS-6

4. Timely Transmission of Transition Record (Discharges From an Inpatient Facility to Home/Self Care or Any Other Site of Care) (NQF # 0648) and Removal of HBIPS-7

5. Screening for Metabolic Disorders

6. Summary of Measures for the FY 2018 Payment Determination and Subsequent YearsStart Printed Page 46653

E. Possible IPFQR Program Measures and Topics for Future Consideration

F. Changes to Reporting Requirements

1. Changes to Reporting by Age and Quarter for the FY 2017 Payment Determination and Subsequent Years

2. Changes to Aggregate Population Count Reporting for the FY 2017 Payment Determination and Subsequent Years

3. Changes to Sampling Requirements for FY 2018 Payment Determination and Subsequent Years

G. Public Display and Review Requirements

H. Form, Manner, and Timing of Quality Data Submission

1. Procedural and Submission Requirements

2. Change to the Reporting Periods and Submission Timeframes

3. Population and Sampling

4. Data Accuracy and Completeness Acknowledgement (DACA) Requirements

I. Reconsideration and Appeals Procedures

J. Exceptions to Quality Reporting Requirements

VI. Provisions of the Final Regulations

VII. Collection of Information Requirements

A. Wage Estimates

B. ICRs Regarding the Inpatient Psychiatric Quality Reporting (IPFQR) Program

1. Changes in Time Required To Chart-Abstract Data Based on Reporting Requirements

2. Estimated Burden of IPFQR Program

C. Summary of Annual Burden Estimates

D. ICRs Regarding the Hospital and Health Care Complex Cost Report (CMS-2552-10)

E. Submission of PRA-Related Comments

VIII. Regulatory Impact Analysis

A. Statement of Need

B. Overall Impact

C. Anticipated Effects

1. Budgetary Impact

2. Impact on Providers

3. Results

4. Effects of Updates to the IPFQR Program

5. Effect on Beneficiaries

D. Alternatives Considered

E. Accounting Statement

Regulations Text

Addendum—FY 2016 Rates and Adjustment Factors

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 meanings in alphabetical order below:

ADC Average Daily Census

AHA American Hospital Association

AHE Average Hourly Earning

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

BEA Bureau of Economic Analysis

BLS Bureau of Labor Statistics

CAH Critical Access Hospital

CBSA Core-Based Statistical Area

CCR Cost-to-Charge Ratio

CPI Consumer Price Index

CPI-U Consumer Price Index for all Urban Consumers

DRGs Diagnosis-Related Groups

ECI Employment Cost Index

ESRD End State Renal Disease

FR Federal Register

FTE Full-time equivalent

FY Federal Fiscal Year (October 1 through September 30)

GDP Gross Domestic Product

GME Graduate Medical Education

HHA Home Health Agency

HBIPS Hospital Based Inpatient Psychiatric Services

ICD-9-CM International Classification of Diseases, 9th Revision, Clinical Modification

ICD-10-CM International Classification of Diseases, 10th Revision, Clinical Modification

ICD-10-PCS International Classification of Diseases, 10th Revision, Procedure Coding System

IGI IHS Global Insight, Inc.

I-O Input—Output

IPFs Inpatient Psychiatric Facilities

IPFQR Inpatient Psychiatric Facilities Quality Reporting

IPPS Inpatient Prospective Payment System

IRFs Inpatient Rehabilitation Facilities

LOS Length of Stay

LTCHs Long-Term Care Hospitals

MAC Medicare Administrative Contractor

MedPAR Medicare Provider Analysis and Review File

MFP Multifactor Productivity

MMA Medicare Prescription Drug, Improvement, and Modernization Act of 2003

MSA Metropolitan Statistical Area

NAICS North American Industry Classification System

NQF National Quality Forum

OES Occupational Employment Statistics

OMB Office of Management and Budget

OPPS Outpatient Prospective Payment System

PLI Professional Liability Insurance

PPI Producer Price Index

PPS Prospective Payment System

RPL Rehabilitation, Psychiatric, and Long-Term Care

RY Rate Year (July 1 through June 30)

SCHIP State Children's Health Insurance Program

SNF Skilled Nursing Facility

SOC Standard Occupational Classification

TEFRA Tax Equity and Fiscal Responsibility Act of 1982 (Pub. L. 97-248)

I. Executive Summary

A. Purpose

This final rule updates the prospective payment rates for Medicare inpatient hospital services provided by inpatient psychiatric facilities (IPFs) for discharges occurring during the FY 2016 (October 1, 2015 through September 30, 2016). For the Inpatient Psychiatric Facility Quality Reporting (IPFQR) Program, it also changes certain measures collected under the program and modifies reporting requirements for certain program measures.

B. Summary of the Major Provisions

In this final rule, we updated the IPF Prospective Payment System (PPS), as specified in 42 CFR 412.428. The updates include the following:

  • Effective for the FY 2016 IPF PPS update, we adopted a 2012-based IPF market basket. However, we revised the proposed 2012-based IPF market basket based on public comments. Specifically, we revised the methodology for calculating the Wages and Salaries and the Employee Benefits cost weights. The final 2012-based IPF market basket resulted in a labor-related share of 75.2 percent for FY 2016.
  • We adjusted the 2012-based IPF market basket update (currently estimated to be 2.4 percent) by a reduction for economy-wide productivity (currently estimated to be 0.5 percent) as required by section 1886(s)(2)(A)(i) of the Social Security Act (the Act), and further reduced by 0.2 percentage point as required by section 1886(s)(2)(A)(ii) of the Act, resulting in an estimated market basket update of 1.7 percent.
  • We updated the IPF PPS per diem rate from $728.31 to $743.73. Providers that failed to report quality data for FY 2016 payment will receive a final FY 2016 per diem rate of $729.10.
  • We updated the electroconvulsive therapy (ECT) payment per treatment from $313.55 to $320.19. Providers that failed to report quality data for FY 2016 payment will receive a FY 2016 ECT payment per treatment of $313.89.
  • We adopted new Office of Management and Budget (OMB) Core-Based Statistical Area (CBSA) delineations for the FY 2016 IPF PPS wage index and future IPF PPS wage indices. We implemented these CBSA changes using a 1-year transition with a blended wage index for all providers, consisting of a blend of fifty percent of the FY 2016 IPF wage index using the current OMB delineations and fifty percent of the FY 2016 IPF wage index using the revised OMB delineations.
  • We phased out the rural adjustment for the 37 rural IPFs that will be re-designated as urban IPFs due to the OMB CBSA changes. Specifically, we phased out the 17 percent rural adjustment for these 37 providers over 3 years (two-thirds of the adjustment given in FY 2016, one-third of the adjustment given in FY 2017, and no rural adjustment thereafter).
  • We used the updated labor-related share of 75.2 percent (based on the final 2012-based IPF market basket) and CBSA rural and urban wage indices for FY 2016, and established a wage index budget-neutrality adjustment of 1.0041.Start Printed Page 46654
  • We updated the fixed dollar loss threshold amount from $8,755 to $9,580 in order to maintain estimated outlier payments at 2 percent of total estimated aggregate IPF PPS payments.
  • We finalized that the national urban and rural cost-to-charge ratio (CCR) ceilings for FY 2016 will be 1.7339 and 1.9041, respectively, and the national median CCR will be 0.4650 for urban IPFs and 0.6220 for rural IPFs. The national median CCR is applied to new IPFs that have not yet submitted their first Medicare cost report, to IPFs for which the CCR calculation data are inaccurate or incomplete, and to IPFs whose overall CCR exceeds 3 standard deviations above the national geometric mean.
  • We note that IPF PPS patient-level and facility-level adjustments, other than those mentioned above, remain the same as in FY 2015.

In addition:

  • We remind providers that International Classification of Diseases, 10th Revision, Clinical Modification/Procedure Coding System (ICD-10-CM/PCS) will be implemented on October 1, 2015.
  • As we continue our analysis for future IPF PPS refinements, we find, from preliminary analysis of 2012 to 2013 data, that over 20 percent of IPF stays reported no ancillary costs, such as laboratory and drug costs, in their cost reports, or laboratory or drug charges on their claims. Because we expect that most patients requiring hospitalization for active psychiatric treatment will need drugs and laboratory services, we remind providers that the IPF PPS per diem payment rate includes the cost of all ancillary services, including drugs and laboratory services. We pay only the IPF for services furnished to a Medicare beneficiary who is an inpatient of that IPF, except for certain professional services, and payments are considered to be payments in full for all inpatient hospital services provided directly or under arrangement (see 42 CFR 412.404(d)), as specified in 42 CFR 409.10.

For the IPFQR Program, we are adopting several new measures and data submission requirements for the IPFQR Program. First, we adopted five new measures beginning with the FY 2018 payment determination:

  • TOB-3—Tobacco Use Treatment Provided or Offered at Discharge and the subset measure TOB-3a Tobacco Use Treatment at Discharge (National Quality Forum (NQF) #1656);
  • SUB-2—Alcohol Use Brief Intervention Provided or Offered and the subset measure SUB-2a Alcohol Use Brief Intervention (NQF #1663);
  • Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) (NQF) #0647);
  • Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) (NQF #0648); and
  • Screening for Metabolic Disorders.

We removed HBIPS-4 Patients Discharged on Multiple Antipsychotic Medications, beginning with the FY 2017 payment determination. We also removed the Hospital Based Inpatient Psychiatric Services (HBIPS)-6 Post-Discharge Continuing Care Plan (NQF #0557) and HBIPS-7 Post-Discharge Continuing Care Plan Transmitted to the Next Level of Care Provider Upon Discharge (NQF #0558) measures, beginning with the FY 2018 payment determination.

Second, we made several changes regarding how facilities report data for IPFQR Program measures:

  • Beginning with the FY 2017 payment determination, we are requiring that measures be reported as a single yearly count rather than by quarter and age.
  • Beginning with the FY 2017 payment determination, we are requiring that aggregate population counts be reported as a single yearly number rather than by quarter.
  • Beginning with the FY 2018 payment determination, we will allow uniform sampling for certain measures.

C. Summary of Impacts

Provision descriptionTotal transfers
FY 2016 IPF PPS payment rate updateThe overall economic impact of this final rule is an estimated $75 million in increased payments to IPFs during FY 2016.
Provision descriptionCosts
New quality reporting program requirementsThe total costs beginning in FY 2016 for IPFs as a result of the final new quality reporting requirements are estimated to be $6.31 million.

II. Background

A. Overview of the Legislative Requirements for the IPF PPS

Section 124 of the Medicare, Medicaid, and SCHIP (State Children's Health Insurance Program) Balanced Budget Refinement Act of 1999 (BBRA) (Pub. L. 106-113) required the establishment and implementation of an IPF PPS. Specifically, section 124 of the BBRA mandated that the Secretary of the Department Health and Human Services (the Secretary) develop a per diem PPS for inpatient hospital services furnished in psychiatric hospitals and psychiatric units including an adequate patient classification system that reflects the differences in patient resource use and costs among psychiatric hospitals and psychiatric units.

Section 405(g)(2) of the Medicare Prescription Drug, Improvement, and Modernization Act of 2003 (MMA) (Pub. L. 108-173) extended the IPF PPS to distinct part psychiatric units of critical access hospitals (CAHs).

Section 3401(f) of the Patient Protection and Affordable Care Act (Pub. L. 111-148) as amended by section 10319(e) of that Act and by section 1105(d) of the Health Care and Education Reconciliation Act of 2010 (Pub. L. 111-152) (hereafter referred to as “the Affordable Care Act”) added subsection (s) to section 1886 of the Act.

Section 1886(s)(1) of the Act titled “Reference to Establishment and Implementation of System” refers to section 124 of the BBRA, which relates to the establishment of the IPF PPS.

Section 1886(s)(2)(A)(i) of the Act requires the application of the productivity adjustment described in section 1886(b)(3)(B)(xi)(II) of the Act to the IPF PPS for the Rate Year (RY) beginning in 2012 (that is, a RY that coincides with a FY) and each subsequent RY. For the RY beginning in 2015 (that is, FY 2016), the current estimate of the productivity adjustment is equal to 0.5 percent, which we are implementing in this FY 2016 final rule.

Section 1886(s)(2)(A)(ii) of the Act requires the application of an “other adjustment” that reduces any update to an IPF PPS base rate by percentages Start Printed Page 46655specified in section 1886(s)(3) of the Act for the RY beginning in 2010 through the RY beginning in 2019. For the RY beginning in 2015 (that is, FY 2016), section 1886(s)(3)(D) of the Act requires the reduction to be 0.2 percentage point. We are implementing that reduction in this FY 2016 IPF PPS final rule.

Section 1886(s)(4) of the Act requires the establishment of a quality data reporting program for the IPF PPS beginning in RY 2014.

To implement and periodically update these provisions, we have published various proposed and final rules in the Federal Register. For more information regarding these rules, see the CMS Web site at http://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientPsychFacilPPS/​index.html?​redirect=​/​InpatientPsychFacilPPS/​.

B. Overview of the IPF PPS

The November 2004 IPF PPS final rule (69 FR 66922) established the IPF PPS, as required by section 124 of the BBRA and codified at subpart N of part 412 of the Medicare regulations. The November 2004 IPF PPS final rule set forth the per diem federal rates for the implementation year (the 18-month period from January 1, 2005 through June 30, 2006), and provided payment for the inpatient operating and capital costs to IPFs for covered psychiatric services they furnish (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 IPF PPS). Covered psychiatric services include services for which benefits are provided under the fee-for-service Part A (Hospital Insurance Program) of the Medicare program.

The IPF PPS established the federal per diem base rate for each patient day in an IPF derived from the national average daily routine operating, ancillary, and capital costs in IPFs in FY 2002. The average per diem cost was updated to the midpoint of the first year under the IPF PPS, standardized to account for the overall positive effects of the IPF PPS payment adjustments, and adjusted for budget-neutrality.

The federal per diem payment under the IPF PPS is comprised of the federal per diem base rate described above and certain patient- and facility-level payment adjustments that were found in the regression analysis to be associated with statistically significant per diem cost differences.

The patient-level adjustments include age, Diagnosis-Related Group (DRG) assignment, comorbidities, and variable per diem adjustments to reflect higher per diem costs in the early days of an IPF stay. Facility-level adjustments include adjustments for the IPF's wage index, rural location, teaching status, a cost-of-living adjustment for IPFs located in Alaska and Hawaii, and the presence of a qualifying emergency department (ED).

The IPF PPS provides additional payment policies for: Outlier cases; interrupted stays; and a per treatment adjustment for patients who undergo electroconvulsive therapy (ECT). During the IPF PPS mandatory 3-year transition period, stop-loss payments were also provided; however, since the transition ended in 2008, these payments are no longer available.

A complete discussion of the regression analysis that established the IPF PPS adjustment factors appears in the November 2004 IPF PPS final rule (69 FR 66933 through 66936).

Section 124 of the BBRA did not specify an annual rate update strategy for the IPF PPS and was broadly written to give the Secretary discretion in establishing an update methodology. Therefore, in the November 2004 IPF PPS final rule, we implemented the IPF PPS using the following update strategy:

  • Calculate the final federal per diem base rate to be budget-neutral for the 18-month period of January 1, 2005 through June 30, 2006.
  • Use a July 1 through June 30 annual update cycle.
  • Allow the IPF PPS first update to be effective for discharges on or after July 1, 2006 through June 30, 2007.

In RY 2012, we proposed and finalized switching the IPF PPS payment rate update from a rate year that begins on July 1 and ends on June 30 to one that coincides with the federal fiscal year that begins October 1 and ends on September 30. In order to transition from one timeframe to another, the RY 2012 IPF PPS covered a 15-month period from July 1, 2011 through September 30, 2012. Therefore, the update cycle for FY 2016 will be October 1, 2015 through September 30, 2016. For further discussion of the 15-month market basket update for RY 2012 and changing the payment rate update period to coincide with a FY period, we refer readers to the RY 2012 IPF PPS proposed rule (76 FR 4998) and the RY 2012 IPF PPS final rule (76 FR 26432).

C. Annual Requirements for Updating the IPF PPS

In November 2004, we implemented the IPF PPS in a final rule that appeared in the November 15, 2004 Federal Register (69 FR 66922). In developing the IPF PPS, to ensure that the IPF PPS is able to account adequately for each IPF's case-mix, we performed an extensive regression analysis of the relationship between the per diem costs and certain patient and facility characteristics to determine those characteristics associated with statistically significant cost differences on a per diem basis. For characteristics with statistically significant cost differences, we used the regression coefficients of those variables to determine the size of the corresponding payment adjustments.

In that final rule, we explained that we believe it is important to delay updating the adjustment factors derived from the regression analysis until we have IPF PPS data that include as much information as possible regarding the patient-level characteristics of the population that each IPF serves. Therefore, we indicated that we did not intend to update the regression analysis and the patient- and facility-level adjustments until we complete that analysis. Until that analysis is complete, we stated our intention to publish a notice in the Federal Register each spring to update the IPF PPS (71 FR 27041). We have begun the necessary analysis to make refinements to the IPF PPS using more current data to set the adjustment factors; however, we did not make any refinements in this final rule. Rather, as explained in section V.B. of this final rule, we expect that in future rulemaking we will be ready to propose potential refinements.

In the May 6, 2011 IPF PPS final rule (76 FR 26432), we changed the payment rate update period to a RY that coincides with a FY update. Therefore, update notices are now published in the Federal Register in the summer to be effective on October 1. When proposing changes in IPF payment policy, a proposed rule would be issued in the spring and the final rule in the summer in order to be effective on October 1. For further discussion on changing the IPF PPS payment rate update period to a RY that coincides with a FY, see the IPF PPS final rule published in the Federal Register on May 6, 2011 (76 FR 26434 through 26435). For a detailed list of updates to the IPF PPS, see 42 CFR 412.428.

Our most recent IPF PPS annual update occurred in an August 6, 2014, Federal Register final rule (79 FR 45938) (hereinafter referred to as the August 2014 IPF PPS final rule) updated the IPF PPS payment rates for FY 2015. That rule updated the IPF PPS per diem payment rates that were published in the August 2013 IPF PPS notice (78 FR Start Printed Page 4665646734) in accordance with our established policies.

III. Provisions of the Final Rule and Responses to Comments

On May 1, 2015 we published a proposed rule in the Federal Register (80 FR 25012) entitled Medicare Program; Inpatient Psychiatric Facilities Prospective Payment System—Update for Fiscal Year Beginning October 1, 2015 (FY 2016). The May 1, 2015 proposed rule (herein referred to as the FY 2016 IPF PPS proposed rule) proposed updates to the prospective payment rates for Medicare inpatient hospital services provided by inpatient psychiatric facilities. In addition to the updates, we proposed to: Adopt a 2012-based IPF market basket and update the labor-related share; adopt new OMB CBSA delineations for the FY 2016 IPF Wage Index; and phase out the rural adjustment for 37 rural providers that would become urban providers as a result of the new CBSA delineations. Additionally, the proposed rule reminded providers of the October 1, 2015 implementation of the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM/PCS) for the IPF PPS, updated providers on the status of IPF PPS refinements, and proposed new quality reporting requirements for the IPFQR Program.

We received a total of 76 comments on these proposals from 51 providers, 12 industry groups or associations, 6 industry consultants, 4 advocacy groups, 1 independent congressional agency, and 2 anonymous sources. Of the 76 comments, 12 focused on payment policies, and 73 focused on the quality reporting proposals. A summary of the proposals, the comments, and our responses follows.

A. Market Basket for the IPF PPS

1. Background

The input price index that was used to develop the IPF PPS was the Excluded Hospital with Capital market basket. This market basket was based on 1997 Medicare cost reports for Medicare participating inpatient rehabilitation facilities (IRFs), IPFs, long-term care hospitals (LTCHs), cancer hospitals, and children's hospitals. Although “market basket” technically describes the mix of goods and services used in providing health care at a given point in time, this term is also commonly used to denote the input price index (that is, cost category weights and price proxies) derived from that market basket. Accordingly, the term “market basket,” as used in this document, refers to an input price index.

Beginning with the May 2006 IPF PPS final rule (71 FR 27046 through 27054), IPF PPS payments were updated using a 2002-based rehabilitation, psychiatric, and long-term care (RPL) market basket reflecting the operating and capital cost structures for freestanding IRFs, freestanding IPFs, and LTCHs. Cancer and children's hospitals were excluded 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 and not through a PPS. Also, the 2002 cost structures for cancer and children's hospitals are noticeably different than the cost structures of freestanding IRFs, freestanding IPFs, and LTCHs. See the May 2006 IPF PPS final rule (71 FR 27046 through 27054) for a complete discussion of the 2002-based RPL market basket.

In the May 1, 2009 IPF PPS notice (74 FR 20376), we expressed our interest in exploring the possibility of creating a stand-alone IPF market basket that reflects the cost structures of only IPF providers. One available option was to combine the Medicare cost report data from freestanding IPF providers with Medicare cost report data from hospital-based IPF providers. We indicated that an examination of the Medicare cost report data comparing freestanding IPFs and hospital-based IPFs showed differences between cost levels and cost structures. At that time, we were unable to fully understand these differences even after reviewing explanatory variables such as geographic variation, case mix (including DRG, comorbidity, and age), urban or rural status, teaching status, and presence of a qualifying emergency department. As a result, we continued to research ways to reconcile the differences and solicited public comment for additional information that might help us to better understand the reasons for the variations in costs and cost structures, as indicated by the Medicare cost report data (74 FR 20376). We summarized the public comments we received and our responses in the April 2010 IPF PPS notice (75 FR 23111 through 23113). Despite receiving comments from the public on this issue, we were still unable to sufficiently reconcile the observed differences in costs and cost structures between hospital-based and freestanding IPFs, and, therefore, we did not believe it to be appropriate at that time to incorporate data from hospital-based IPFs with those of freestanding IPFs to create a stand-alone IPF market basket.

Beginning with the RY 2012 IPF PPS final rule (76 FR 26432), IPF PPS payments were updated using a 2008-based RPL market basket reflecting the operating and capital cost structures for freestanding IRFs, freestanding IPFs, and LTCHs. The major changes for RY 2012 included: Updating the base year from FY 2002 to FY 2008; using a more specific composite chemical price proxy; breaking the professional fees cost category into two separate categories (Labor-related and Nonlabor-related); and adding two additional cost categories (Administrative and Facilities Support Services and Financial Services), which were previously included in the residual All Other Services cost categories. The RY 2012 IPF PPS proposed rule (76 FR 4998) and RY 2012 final rule (76 FR 26432) contain a complete discussion of the development of the 2008-based RPL market basket.

In the FY 2016 IPF PPS proposed rule, we proposed to create a 2012-based IPF market basket, using Medicare cost report data for both freestanding and hospital-based IPFs.

We received several general comments on the creation of an IPF market basket.

Comment: One commenter supported CMS' use of an IPF-specific market basket, but recommended that CMS develop separate update percentages for freestanding units and hospital-based units. They stated patients treated in hospital-based units have more complex medical conditions and require more resources compared to freestanding facilities. They believe combining these two facilities for the purpose of establishing one market basket rate update could result in underpayments for Medicare patients treated in hospital-based facilities.

Response: We appreciate the commenter's support of an IPF-specific market basket. However, we respectfully disagree with their recommendation to develop two specific market basket update percentages for hospital-based and freestanding units. The regression analysis from which the IPF PPS base rate payment (and related adjustments) was derived reflects data from both freestanding and hospital-based providers. As a result, we believe it is appropriate to update those rates with a market basket based on data from both types of providers. Moreover, we do not believe we have a large enough sample size to create a freestanding-specific IPF market basket. Finally, the IPF PPS already provides patient-level adjustments, including certain principal diagnoses and comorbidities that reflect the higher costs and resources Start Printed Page 46657associated with more medically complex patients.

Comment: One commenter stated their appreciation of the discussion in the proposed rule regarding the progress that CMS has made in the development of an IPF-specific market basket. They support CMS' efforts to ensure that the IPF payment system is updated to reflect current costs and resource use.

Response: We appreciate the commenter's support for the proposed 2012-based IPF market basket.

Comment: One commenter did not support the adoption of the stand-alone IPF market basket. They stated they still have major reservations about its accuracy. They urged CMS to publicly release the detailed data files that support the proposed IPF-specific market basket and to distinguish cost factors in order to “evaluate the materiality of the consolidation effect on the market basket” and to allow time for the industry to gain a clearer understanding of the proposal, and the consolidation of the IPF provider types in order to enable commenters' informed response to the proposal.

Response: We appreciate the commenter's concern for the adoption of the 2012-based IPF market basket. However, we disagree with delaying the IPF-specific market basket. We believe we provided a clear description of the proposal and a sufficiently detailed data file to enable informed comment.

All of the data used to develop the proposed IPF-market basket are publically available. The Medicare cost reports used to develop the major cost weights are publically available on the CMS Web site (http://www.cms.gov/​Research-Statistics-Data-and-Systems/​Downloadable-Public-Use-Files/​Cost-Reports/​Cost-Reports-by-Fiscal-Year.html under facility type “Hospital-2010”). The Bureau of Labor Statistics (BLS) Occupational Employment Statistics (http://www.bls.gov/​oes/​#data) and BLS price indices (http://www.bls.gov/​cpi/​#data, http://www.bls.gov/​ppi/​#data, and http://www.bls.gov/​ncs/​ect/​#data) are publically available. The last data source used was the Bureau of Economic Analysis 2007 Benchmark Input-Output (I-O) data which is also publically available (http://www.bea.gov/​industry/​io_​annual.htm under “ `Use Tables/Before Redefinitions/Purchaser Value' for North American Industry Classification System (NAICS) 622000 Hospitals”).

In addition, we also provided in the proposed rule a detailed description of the methodologies (including items such as Medicare Cost Report line items or BLS series codes) used to produce the proposed 2012-based IPF market basket using the aforementioned data. We believe these methodology descriptions allowed for informed public comments and evaluation of the materiality of the “consolidation effect” (which we interpret to be the inclusion of freestanding and hospital-based IPF Medicare cost report data). We did receive several comments on our detailed methodology, which we used to further evaluate our methodology. In fact, in this final rule, we are adopting changes to the Wages and Salaries and Employee Benefits costs methodologies based on these detailed public comments. A more thorough description of the methodological changes is provided below.

After consideration of the public comments, we are finalizing the creation and adoption of a 2012-based IPF market basket with a modification to the Wages and Salaries and Employee Benefits cost methodologies based on public comments. We believe that the use of the 2012-based IPF market basket to update IPF PPS payments is a technical improvement as it is based on Medicare Cost Report data from both freestanding and hospital-based IPFs. Furthermore, the 2012-based IPF market basket does not include costs from either IRF or LTCH providers, which are included in the current 2008-based RPL market basket.

In the following discussion, we provide an overview of the market basket and describe the methodologies used to determine the operating and capital portions of the 2012-based IPF market basket. For each proposed methodology, we indicate whether we received any public comments. We include responses for each comment. We then provide the methodology we are finalizing for the 2012-based IPF market basket.

2. Overview of the 2012-Based IPF Market Basket

The 2012-based IPF market basket is a fixed-weight, Laspeyres-type price index. A Laspeyres price index measures the change in price, over time, of the same mix of goods and services purchased in the base period. Any changes in the quantity or mix of goods and services (that is, intensity) purchased over time relative to a base period are not measured.

The index itself is constructed in 3 steps. First, a base period is selected (in this final rule, the base period is FY 2012) and total base period expenditures are estimated for a set of mutually exclusive and exhaustive spending categories with the proportion of total costs that each category represents being calculated. 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 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. 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 timeframe.

As noted above, the market basket is described as a fixed-weight index because it represents the change in price over time of a constant mix (quantity and intensity) of goods and services needed to furnish IPF services. The effects on total expenditures resulting from changes in the mix of goods and services purchased subsequent to the base period are not measured. For example, an IPF hiring more nurses to accommodate the needs of patients will increase the volume of goods and services purchased by the IPF, but would not be factored into the price change measured by a fixed-weight IPF market basket. Only when the index is rebased will changes in the quantity and intensity be captured, with those changes being reflected in the cost weights. Therefore, we rebase the market basket periodically so that the cost weights reflect recent changes in the mix of goods and services that IPFs purchase (facility inputs) to furnish inpatient care between base periods.

3. Creating an IPF-Specific Market Basket

As discussed in section III.A.1. of this final rule, over the last several years we have been exploring the possibility of creating a stand-alone, or IPF-specific, market basket that reflects the cost structures of only IPF providers. The major cost weights for the 2008-based RPL market basket were calculated using Medicare cost report data for freestanding facilities only. We used freestanding facilities due to concerns regarding our ability to incorporate Medicare cost report data for hospital-based providers. In the FY 2015 IPF PPS final rule (79 FR 45941), we presented Start Printed Page 46658several of these concerns (as stated below) but explained that we would continue to research the possibility of creating an IPF-specific market basket to update IPF PPS payments.

Since the FY 2015 IPF PPS final rule, we have performed additional research on the Medicare cost report data available for hospital-based IPFs and evaluated these concerns. We subsequently concluded from this research that Medicare cost report data for both hospital-based IPFs and freestanding IPFs can be used to calculate the major market basket cost weights for a stand-alone IPF market basket. We developed a detailed methodology to derive market basket cost weights that are representative of the universe of IPF providers. We believe the use of this final IPF market basket is a technical improvement over the RPL market basket that is currently used to update IPF PPS payments. As a result, in this FY 2016 IPF PPS final rule, we are finalizing a 2012-based IPF market basket that reflects data for both freestanding and hospital-based IPFs. Below we discuss our prior concerns and provide reasons for why we now feel it is appropriate to create a stand-alone IPF market basket using Medicare cost report data for both hospital-based and freestanding IPFs.

One concern we discussed in the FY 2015 IPF PPS final rule (79 FR 45941) about using the hospital-based IPF Medicare cost report data was the cost level differences for hospital-based IPFs relative to freestanding IPFs were not readily explained by the specific characteristics of the individual providers and the patients that they serve (for example, characteristics related to case mix, urban/rural status, teaching status, or presence of a qualified emergency department). To address this concern, we used regression analysis to evaluate the effect of including hospital-based IPF Medicare cost report data in the calculation of cost distributions. A more detailed description of these regression models can be found in the FY 2015 IPF final rule (79 FR 45941). Based on this analysis, we concluded that the inclusion of those IPF providers with unexplained variability in costs did not significantly impact the cost weights and, therefore, should not be a major cause of concern.

Another concern regarding the incorporation of hospital-based IPF data into the calculation of the market basket cost weights was the complexity of the Medicare cost report data for these providers. The freestanding IPFs independently submit a Medicare cost report for their facilities, making it relatively straightforward to obtain the cost categories necessary to determine the major market basket cost weights. However, Medicare cost report data submitted for a hospital-based IPF are embedded in the Medicare cost report submitted for the entire hospital facility in which the IPF is located. In order to use Medicare cost report data from these providers, we needed to determine the appropriate adjustments to apply to the data to ensure that the cost weights we obtained would represent only the hospital-based IPF (not the hospital as a whole). Over the past year, we worked to develop detailed methodologies to calculate the major cost weights for both freestanding and hospital-based IPFs. We also evaluated the differences in cost weights for hospital-based and freestanding IPFs and found the most significant differences occurred for wages and salaries and pharmaceutical costs. Specifically, the hospital-based IPF wages and salaries cost weights tend to be lower than those of freestanding IPFs while hospital-based IPF pharmaceutical cost weights tend to be higher than those of freestanding IPFs. Our methodology for deriving costs for each of these categories can be found in section III.A.3.a.i. of this final rule. We will continue to monitor these cost shares during our on-going research to ensure that the differences are explainable.

In summary, our research over the past year allowed us to evaluate the appropriateness of including hospital-based IPF data in the calculation of the major cost weights for an IPF market basket. In the proposed rule, we proposed methodologies to create a stand-alone IPF market basket that reflects the cost structure of the universe of IPF providers. We described our methodologies and the resulting cost weights in section III.A.3.a.i. of the FY 2016 IPF proposed rule (80 FR 25017) and solicited public comments on these proposals. In the sections below, we summarize and respond to comments we received on these proposed methodologies.

a. Development of Cost Categories and Weights

i. Medicare Cost Reports

We proposed a 2012-based IPF market basket that consisted of seven major cost categories derived from the FY 2012 Medicare cost reports (CMS Form 2552-10) for freestanding and hospital-based IPFs. These categories were Wages and Salaries, Employee Benefits, Contract Labor, Pharmaceuticals, Professional Liability Insurance (PLI), Capital, and a residual. The residual reflects all remaining costs that are not captured in the other six cost categories. The FY 2012 cost reports include providers whose cost report begin date is on or between October 1, 2011, and September 30, 2012. We choose to use FY 2012 as the base year because we believe that the Medicare cost reports for this year represent the most recent, complete set of Medicare cost report data available for IPFs at the time of rulemaking.

Prior Medicare cost report data used to develop the RPL market basket showed large differences between some providers' Medicare length of stay (LOS) and total facility LOS. Since our goal is to measure cost weights that are reflective of case mix and practice patterns associated with providing services to Medicare beneficiaries, we proposed to limit our selection of Medicare cost reports used in the 2012-based IPF market basket to those facilities that had a Medicare LOS that was within a comparable range of their total facility average LOS. For freestanding IPFs, we proposed to use the Medicare days and discharges from line 14, columns 6 and 13, Worksheet S-3, Part I to determine the Medicare LOS and the total facility days and discharges from line 14, columns 8 and 15, to determine the facility LOS (consistent with the RPL market basket method). For hospital-based IPFs, we proposed to use the Medicare days and discharges from line 16, columns 6 and 13, of Worksheet S-3, Part I to determine the Medicare LOS and the total facility days and discharges from line 16, columns 8 and 15, to determine the facility LOS. To derive the 2012-based IPF market basket, for those IPFs with an average facility LOS of greater than or equal to 15 days, we proposed to include IPFs where the Medicare LOS is within 50 percent (higher or lower) of the average facility LOS. For those IPFs whose average facility LOS is less than 15 days, we proposed to include IPFs where the Medicare LOS is within 95 percent (higher or lower) of the facility LOS.

Applying these trims resulted in IPF Medicare cost reports with an average Medicare LOS of 12 days, average facility LOS of 10 days, and Medicare utilization (as measured by Medicare inpatient IPF days as a percentage of total facility days) of 30 percent. Those providers that were excluded from the 2012-based IPF market basket have an average Medicare LOS of 22 days, average facility LOS of 49 days, and a Medicare utilization of 5 percent. Of those Medicare cost reports excluded from the proposed 2012-based IPF market basket, about 70 percent were Start Printed Page 46659freestanding providers whereas freestanding providers represent about 30 percent of all IPFs.

We did not receive any specific comments on our proposed LOS edit methodology.

Final Decision: We are finalizing the LOS edit methodology as proposed.

We applied this LOS trim to first obtain a set of cost reports for facilities that have a Medicare LOS within a comparable range of their total facility LOS. Using the resulting set of FY 2012 Medicare cost reports for freestanding IPFs and hospital-based IPFs, we calculated costs for the six major cost categories (Wages and Salaries, Employee Benefits, Contract Labor, Professional Liability Insurance, Pharmaceuticals, and Capital).

Similar to the 2008-based RPL market basket major cost weights, the 2012-based IPF market basket cost weights reflect Medicare allowable costs (routine, ancillary and capital costs) that are eligible for inclusion under the IPF PPS payments. We proposed to define Medicare allowable costs for freestanding facilities as cost centers (CMS Form 2552-10): 30 through 35, 50 through 76 (excluding 52 and 75), 90 through 91, and 93. We proposed to define Medicare allowable costs for hospital-based facilities as cost centers (CMS Form 2552-10): 40, 50 through 76 (excluding 52 and 75), 90 through 91, and 93. For freestanding IPFs, we proposed that total Medicare allowable costs would be equal to the total costs as reported on Worksheet B, part I, column 26. For hospital-based IPFs, we proposed that total Medicare allowable costs would be equal to total costs for the IPF inpatient unit after the allocation of overhead costs (Worksheet B, part I, column 26, line 40) and a portion of total ancillary costs. We also proposed to calculate the portion of ancillary costs attributable to the hospital-based IPF for a given ancillary cost center by multiplying total facility ancillary costs for the specific cost center (as reported on Worksheet B, Part I, column 26) by the ratio of IPF Medicare ancillary costs for the cost center (as reported on Worksheet D-3, column 3 for IPF subproviders) to total Medicare ancillary costs for the cost center (equal to the sum of Worksheet D-3, column 3 for all relevant PPS (that is, Inpatient Prospective Payment System (IPPS), IRF, IPF and Skilled Nursing Facility (SNF))).

We did not receive any specific comments on our methodology for calculating total costs.

Final Decision: We are finalizing our methodology for calculating total costs as proposed.

Below we provide a description of the methodologies used to derive costs for the six major cost categories.

Wages and Salaries Costs

For freestanding IPFs, we proposed to derive Wages and Salaries costs as the sum of routine inpatient salaries, ancillary salaries, and a proportion of overhead (or general service cost center) salaries as reported on Worksheet A, column 1. Since overhead salary costs are attributable to the entire IPF, we proposed to only include the proportion attributable to the Medicare allowable cost centers. We estimated the proportion of overhead salaries that are attributed to Medicare allowable costs centers by multiplying the ratio of Medicare allowable salaries to total salaries (Worksheet A, column 1, line 200) times total overhead salaries. A similar methodology was used to derive Wages and Salaries costs in the 2008-based RPL market basket.

For hospital-based IPFs, we proposed to derive Wages and Salaries costs as the sum of routine inpatient wages and salaries (Worksheet A, column 1, line 40) and a portion of salary costs attributable to total facility ancillary and overhead cost centers as these cost centers are shared with the entire facility. We proposed to calculate the portion of ancillary salaries attributable to the hospital-based IPF for a given ancillary cost center by multiplying total facility ancillary salary costs for the specific cost center (as reported on Worksheet A, column 1) by the ratio of IPF Medicare ancillary costs for the cost center (as reported on Worksheet D-3, column 3 for IPF subproviders) to total Medicare ancillary costs for the cost center (equal to the sum of Worksheet D-3, column 3 for all relevant PPS units (that is, IPPS, IRF, IPF and SNF)). For example, if hospital-based IPF Medicare laboratory costs represent 10 percent of the total Medicare laboratory costs for the entire facility, then 10 percent of total facility laboratory salaries (as reported in Worksheet A, column 1, line 60) would be attributable to the hospital-based IPF. We believe it is appropriate to use only a portion of the ancillary costs in the market basket cost weight calculations since the hospital-based IPF only utilizes a portion of the facility's ancillary services. We believe the ratio of reported IPF Medicare costs to reported total Medicare costs provides a reasonable estimate of the ancillary services utilized, and costs incurred, by the hospital-based IPF.

We proposed to calculate the portion of overhead salary costs attributable to hospital-based IPFs by multiplying the total overhead costs attributable to the hospital-based IPF (sum of columns 4 through18 on Worksheet B, part I, line 40) by the ratio of total facility overhead salaries (as reported on Worksheet A, column 1, lines 4 through 18) to total facility overhead costs (as reported on Worksheet A, column 7, lines 4 through 18). This methodology assumes the proportion of total costs related to salaries for the overhead cost center is similar for all inpatient units (that is, acute inpatient or inpatient psychiatric). Since the 2008-based RPL market basket did not include hospital-based providers, this proposed methodology cannot be compared to the derivation of Wages and Salaries costs in the 2008-based RPL market basket.

We received several comments on our methodology for deriving Wages and Salaries costs. These comments led to changes to our proposed methodology. We discuss these changes below.

Comment: Several commenters questioned the methodology we used to calculate the Wages and Salaries cost weight stating there was a risk of overstating the labor-related share. They encouraged CMS to utilize a more accurate calculation for the ancillary cost centers in order to mitigate the risk of overstating labor-related share costs.

One commenter stated that our methodology for deriving hospital-based IPF ancillary salary costs for a specific cost center using salary costs from Worksheet A, column 1 multiplied by the ratio of IPF Medicare ancillary costs for the cost center (as reported on Worksheet D-3, column 3 for IPF subproviders) to total Medicare ancillary costs for the cost center (equal to the sum of Worksheet D-3, column 3 for all relevant PPS units (that is, IPPS, IRF, IPF and SNF)) results in an overstatement of ancillary salary costs. Specifically, the commenter stated that the most accurate calculation would be to divide costs on Worksheet D-3, column 3 for the IPF subprovider by total costs on Worksheet C, column 5 for the hospital, and to apply this percentage to salary costs from Worksheet A, column 1. The commenter requested that we clarify how this ancillary salary calculation is used in determining the 74.9 percent labor-related share of the payment, and correct it as needed.

Response: The proposed labor-related share of 74.9 percent is equal to the sum of the relative importance of moving averages of the Wages and Salaries, Employee Benefits, Contract Labor, Labor-Related Services cost categories, and a portion of the relative importance moving average of the Capital-Related cost category. For a detailed description of how these cost categories were Start Printed Page 46660derived, please see the IPF proposed rule (80 FR 25017).

Based on the commenter's request, we reviewed our proposed methodology for calculating Wages and Salaries costs for hospital-based IPFs (including the ancillary wages and salaries costs mentioned by the commenter). As stated in the proposed rule, the Wages and Salaries costs for hospital-based IPFs are derived by summing routine inpatient salary costs for the hospital-based IPF (from Worksheet A, column 1, line 40), ancillary salaries, and overhead salaries. The methodology for calculating ancillary salaries (as the commenter noted) is calculated as ancillary salary costs for a specific cost center using salary costs from Worksheet A, column 1 multiplied by the ratio of IPF Medicare ancillary costs for the cost center (as reported on Worksheet D-3, column 3 for IPF subproviders) to total Medicare ancillary costs for the cost center (equal to the sum of Worksheet D-3, column 3 for all relevant PPS units (that is, IPPS, IRF, IPF and SNF)).

We respectfully disagree with the commenter's suggestion to use total costs on Worksheet C, column 5 as the denominator in the ratio above. We note that Worksheet D-3 represents Medicare IPF costs for ancillary services while Worksheet C, column 5 represents total ancillary costs for all payers. Our methodology for deriving all cost weights (for both freestanding and hospital-based providers) is based on Medicare-allowable costs (that is total costs for all patients for those cost centers that are Medicare-allowable under the IPF PPS). For example, the Contract Labor cost weight is based on contract labor costs reported on Worksheet S3, part V, for all hospital-based IPF patients; it is not specific to Medicare patients as that data is not reported on the Medicare cost report. The commenter's suggestion to use Worksheet C, column 5, would be inappropriate as the numerator would be based on Medicare patients (Worksheet D-3) and the denominator would be for all patients (Worksheet C), which would understate the proportion of ancillary salary costs that are attributable to all hospital-based IPF patients. Since the ancillary salary cost weight, in aggregate, is lower than the hospital-based IPF routine inpatient salary cost weight, this would lead to a higher Wages and Salaries cost weight relative to the proposed rule, and it would be calculated inconsistently with the other market basket cost weights (such as the Contract Labor cost weight). We believe using Medicare costs (Worksheet D-3) to determine the proportion of ancillary wages and salaries (and also total ancillary costs) that are attributable to the hospital-based IPF is a reasonable approach.

Comment: Several commenters stated that they had not conducted their own analysis of the CMS proposed 2012-based IPF market basket, but they were aware of an analysis of the proposed IRF market basket. That analysis, prepared by Dobson DaVanzo,[1] was submitted to CMS as part of the FY 2016 IRF PPS rulemaking record. These commenters encouraged CMS to review Dobson DaVanzo findings to determine if CMS needs to take corrective measures before finalizing the IPF-specific market basket, as the same methodologies in the IRF market basket methodology could exist in the IPF methodology.

Response: We appreciate the commenters' request to review the consultants' report on the methodology used to develop the IRF-specific market basket. As the commenter stated, the methodology used to develop the IPF major cost weights using the Medicare cost report data for the 2012-based IPF market basket is similar to the methodology used in the proposed 2012-based IRF market basket. The only difference is the use of IPF-specific Medicare cost report data to calculate the major cost weights.

Based on these comments, we reviewed the Dobson DaVanzo IRF report submitted by commenters on the IRF proposed rule. This report stated on page four that our proposed methodology for calculating hospital-based IRF wages and salaries was flawed as it disregards overhead wages and salaries associated with the ancillary departments. Our proposed methodology for the 2012-based IRF market basket was identical to our proposed methodology for the 2012-based IPF market basket. Our proposed methodology for the 2012-based IPF market basket included overhead wages and salaries attributable to the hospital-based IPF routine inpatient unit only. Therefore, we are revising our methodology for calculating the Wages and Salaries costs for hospital-based IPFs to account for the omission of the overhead wages and salaries attributable to the ancillary departments.

For this final rule, we calculated the overhead salaries attributable to each ancillary department by first calculating total noncapital overhead costs attributable to the specific ancillary department (Worksheet B, part I, columns 4-18 less Worksheet B, part II, columns 4-18). We then identified the portion of the total noncapital overhead costs for each ancillary cost center that is attributable to the hospital-based IPF by multiplying by the ratio of IPF Medicare ancillary costs for the cost center (as reported on Worksheet D-3, column 3 for hospital-based IPFs) to total Medicare ancillary costs for the cost center (equal to the sum of Worksheet D-3, column 3 for all relevant PPS units (that is, IPPS, IRF, IPF and SNF)). Finally, we identified the portion of these noncapital overhead costs attributable to Wages and Salaries by multiplying these costs by an “overhead ratio”, which is defined as the ratio of total facility overhead salaries (as reported on Worksheet A, column 1, lines 4-18) to total noncapital overhead costs (as reported on Worksheet A, column 1 & 2, lines 4-18) for all ancillary departments. This methodology is almost identical to the methodology suggested in the Dobson DaVanzo report with slight modifications, which are further discussed below.

Therefore, based on public comment, we are finalizing our methodology for calculating Wages and Salaries costs for hospital-based IPFs as the sum of routine inpatient salary costs for the hospital-based IPF (from Worksheet A, column 1, line 40), ancillary salaries, and overhead salaries attributable to the routine inpatient unit for the hospital-based IPF and ancillary departments.

During our review of the methodology to derive Wages and Salaries costs and the inclusion of overhead wages and salaries attributable to the ancillary department, we also found that the overhead ratios (used in the calculation of overhead wages and salaries attributable to the routine inpatient unit for the hospital-based IPF) (Worksheet A, column 1 divided by Worksheet A, column 7) by cost center showed that many providers reported data for these columns that resulted in a ratio that exceeded 100 percent. One possible explanation for the overhead ratio exceeding 100 percent is that Worksheet A, column 7 reflects reclassifications and adjustments while column 1 does not. However, when we calculated an alternative overhead ratio by defining overhead salaries using Worksheet S-3, part II column 4, which reflects reclassifications, and total facility noncapital overhead costs using Worksheet A, column 7, we also found that many providers still had overhead ratios that exceeded 100 percent. An overhead ratio exceeding 100 percent Start Printed Page 46661would suggest that wages and salaries costs are greater than total costs, which shows that the data we originally proposed to use results in an indisputable error to the allocation of overhead costs to wages and salaries. When we instead used an overhead ratio equal to the ratio of total facility overhead salaries (as reported on Worksheet A, column 1, lines 4-18) to total facility noncapital overhead costs (as reported on Worksheet A, column 1 and 2, lines 4-18), the impacts of any potential misreporting is minimized.

Therefore, based on the comment, and in order to address the error, we are revising the overhead ratio used to determine the proportion of overhead salaries attributable to the hospital-based IPF routine inpatient department. The revised overhead ratio is equal to the ratio of total facility overhead salaries (as reported on Worksheet A, column 1, lines 4-18) to total facility noncapital overhead costs (as reported on Worksheet A, column 1 and 2, lines 4-18). This is now consistent with the overhead ratio we are using to determine overhead wages and salaries attributable to ancillary departments as described above.

In addition, our review of the methodology for Wages and Salaries costs also found that our proposed methodology for calculating overhead wages and salaries attributable to the hospital-based IPF routine inpatient department were calculated using total (operating and capital) overhead costs attributable to the hospital-based IPF (sum of columns 4-18 on Worksheet B, part I, line 40). The proposed methodology resulted in a portion of overhead capital costs to be allocated to wages and salaries costs which is incorrect and inconsistent with the Medicare cost report instructions.

The Medicare cost report instructions define capital-related costs as “depreciation, leases and rentals for the use of facilities and/or equipment, and interest incurred in acquiring land or depreciable assets used for patient care, insurance on depreciable assets used for patient care and taxes on land or depreciable assets used for patient care.” [2] The instructions also state that providers should exclude the following from capital-related costs: “costs incurred for the repair or maintenance of equipment or facilities, amounts included in rentals or lease payments for repair and/or maintenance agreements. * * *” Based on this definition of capital costs as reported on the Medicare cost report, we concluded that capital costs do not include direct wages and salaries costs and that it would be erroneous to allocate a portion of capital costs to overhead wages and salaries.

Therefore, we are revising the methodology to reflect operating costs (that is the sum of Worksheet B, part I, line 40, columns 4-18 less Worksheet B, part II, line 40, columns 4-18).

We are finalizing our methodology for calculating hospital-based IPF Wages and Salaries costs as described above. We discuss the effect of the changes to the proposed methodology on the market basket cost weight in section III.A.3.i. of this final rule.

We did not receive any comments on our proposed methodology for calculating the freestanding IPF Wages and Salaries costs and therefore, we are finalizing the methodology for calculating the freestanding IPF Wages and Salaries costs as proposed.

Employee Benefits Costs

Effective with our implementation of CMS Form 2552-10, we began collecting Employee Benefits and Contract Labor data on Worksheet S-3, Part V. Previously, with CMS Form 2540-96, Employee Benefits and Contract Labor data were reported on Worksheet S-3, part II, which was applicable to only IPPS providers and, therefore, these data were not available for the derivation of the RPL market basket. Due to the lack of such data, the Employee Benefits cost weight for the 2008-based RPL market basket was derived by multiplying the 2008-based RPL market basket Wages and Salaries cost weight by the ratio of the IPPS hospital market basket Employee Benefits cost weight to the IPPS hospital market basket Wages and Salaries cost weight. Similarly, the Contract Labor cost weight for the 2008-based RPL market basket was derived by multiplying the 2008-based RPL market basket Wages and Salaries cost weight by the ratio of the IPPS hospital market basket Contract Labor cost weight to the IPPS hospital market basket Wages and Salaries cost weight.

For FY 2012 Medicare cost report data, while there were providers that did report data on Worksheet S-3, part V, many providers did not complete this worksheet. However, we believe we had a large enough sample to enable us to produce reasonable Employee Benefits cost weights. We continue to encourage all providers to report these data on the Medicare cost report.

For freestanding IPFs, Employee Benefits costs are equal to the data reported on Worksheet S-3, Part V, line 2, column 2.

For hospital-based IPFs, we calculate total benefits as the sum of benefit costs reported on Worksheet S-3 Part V, line 3, column 2, and a portion of ancillary benefits and overhead benefits for the total facility. We proposed that ancillary benefits attributable to the hospital-based IPF would be calculated by multiplying ancillary wages and salaries for the hospital-based IPF as determined in the derivation of Wages and Salaries for the hospital-based IPF by the ratio of total facility benefits to total facility wages and salaries. Similarly, we proposed that overhead benefits attributable to the hospital-based IPF would be calculated by multiplying overhead wages and salaries for the hospital-based IPF as determined in the derivation of Wages and Salaries for the hospital-based IPF by the ratio of total facility benefits to total facility wages and salaries.

Based on the comment above regarding the omission of overhead Wages and Salaries attributable to the ancillary departments, we are revising our methodology for calculating Employee Benefits costs for hospital-based IPFs to include overhead employee benefits attributable to the ancillary departments. Our proposed methodology included Employee Benefits attributable to hospital-based IPF routine inpatient unit only. We are estimating overhead employee benefits attributable to the ancillary departments using the same general methodology used to calculate routine inpatient overhead benefits and ancillary employee benefits attributable to the hospital-based IPF unit.

Overhead employee benefits attributable to the ancillary departments are calculated by multiplying overhead wages and salaries attributable to the ancillary departments by the ratio of total facility benefits to total facility wages and salaries. Therefore, based on public comments, total employee benefits for hospital-based IPFs are now equal to the sum of benefit costs reported on Worksheet S-3 Part V, line 3, column 2; a portion of ancillary benefits; and a portion of overhead benefits attributable to the routine inpatient unit and ancillary departments.

In addition, our methodology to calculate overhead benefits attributable to the hospital-based IPF is to multiply overhead wages and salaries for the hospital-based IPF routine inpatient unit (as determined in the derivation of Wages and Salaries for the hospital-based IPF) by the ratio of total facility benefits to total facility wages and Start Printed Page 46662salaries. Therefore, our changes to the overhead wages and salaries for the hospital-based IPF routine inpatient unit discussed above would result in changes to the overhead employee benefits attributable to the hospital-based IPF routine inpatient unit. The effect of these methodology changes on the Employee Benefits cost weight are discussed in more detail in section III.A.3.a.ii below.

We received one comment specific to our proposed methodology for calculating Employee Benefits costs.

Comment: Two commenters encouraged CMS to review the Dobson/DaVanzo report (referenced above), which noted our proposal to change the methodology for determining Employee Benefits costs from the methodology used to determine the Employee Benefits cost weight for the 2008-based RPL market basket. As discussed in the proposed rule, under the RPL methodology, we used data from IPPS hospitals as a proxy for determining these costs for RPL facilities. The Dobson DaVanzo report noted the low reporting of data on Worksheet S3, part V, used in the Employee Benefit and Contract Labor cost weight calculations. They stated that CMS should consider using IPPS data as a proxy for these specific data elements as is done for the RPL market basket.

Response: In the proposed rule (80 FR 25019), we noted that many providers did not report Worksheet S-3, part V data but that we believed we had a large enough sample to produce a reasonable Employee Benefits cost weight. Specifically, we found that when we recalculated the cost weight, after weighting to reflect the characteristics of the universe of IPF providers (freestanding and hospital-based), it did not have a material effect on the resulting cost weight. We understand the commenters' concern for the methodology change. However, we believe that the use of employee benefit costs reported by IPFs is a technical improvement from the methodology used for the 2008-based RPL market basket. Specifically, this methodology calculated the Employee Benefit cost weight by multiplying the RPL market basket Wages and Salaries cost weight by the IPPS employee benefit ratio. The IPPS employee benefit ratio was equal to the 2006-based IPPS market basket Employee Benefit cost weight divided by the 2006-based IPPS market basket Wages and Salaries cost weight. Using the rebased and revised 2010- based IPPS market basket, we calculate an employee benefit ratio of 28 percent compared to the 2012-based IPF market basket with 26 percent. Much of this two-percentage-point difference is attributable to the characteristics of the IPF facilities as compared to the IPPS hospitals. Approximately 20 percent of total costs for IPFs are attributable to for-profit facilities (80 percent are attributable to nonprofit and government facilities) while approximately 10 percent of total costs for IPPS hospitals are attributable to for-profit facilities (90 percent are attributable to nonprofit and government facilities). Both the IPF and IPPS hospital data show that the employee benefit ratio for for-profit facilities is lower than the employee benefit ratio for nonprofit/government facilities (in the range of 6-7 percentage points lower), thus IPFs' higher proportion of for-profit facilities compared to IPPS hospitals leads to a lower employee benefit ratio.

Final Decision: In conclusion, we believe the use of Worksheet S-3, part V data for IPFs is a technical improvement from the methodology used for the 2008-based RPL market basket as we believe it better reflects the cost structures of IPFs. We encourage IPF providers to continue to report Worksheet S-3, part V data and we will continue to monitor the data as the reporting improves. Therefore, after consideration of public comments, we are finalizing our proposed methodology for calculating the freestanding Employee benefit costs for the 2012-based IPF market basket using the Worksheet S-3, part V data as proposed.

Also, as discussed above, we are now capturing the proportion of overhead employee benefits attributable to ancillary departments in the hospital-based IPF employee benefit costs, based on public comments. Therefore, total employee benefits for hospital-based IPFs is equal to the sum of benefit costs reported on Worksheet S-3 Part V, line 3, column 2; a portion of ancillary benefits; and a portion of overhead benefits attributable to both the routine inpatient unit and ancillary departments.

Contract Labor Costs

Similar to the RPL and IPPS market baskets, Contract Labor costs are primarily associated with direct patient care services. Contract Labor costs for other services such as accounting, billing, and legal are calculated separately using other government data sources as described in section III.A.3.a.i. of this final rule. As discussed in this final rule in the Employee Benefits section, we now have data reported on Worksheet S-3, Part V that we can use to derive the Contract Labor cost weight for the 2012-based IPF market basket. For freestanding IPFs, we proposed Contract Labor costs would be based on data reported on Worksheet S-3, part V, column 1, line 2, and for hospital-based IPFs Contract Labor costs are based on line 3 of this same worksheet. As previously noted, for FY 2012 Medicare cost report data, while there were providers that did report data on Worksheet S-3, part V, many providers did not complete this worksheet. However, we believe we had a large enough sample to enable us to produce a reasonable Contract Labor cost weight. We continue to encourage all providers to report these data on the Medicare cost report.

We received one comment on our methodology for calculating Contract Labor costs that was similar to the comments we received regarding Employee Benefits.

Comment: Two commenters encouraged CMS to review the Dobson/DaVanzo report (noted above), which noted CMS' proposal to change the methodology for determining Contract Labor cost weight from the methodology used to derive the 2008-based RPL market basket. Under the RPL methodology, CMS used data from IPPS hospitals as a proxy for determining these costs for RPL facilities. The report expressed concern for the low response rate and its potential impact on the contract labor cost weight.

Response: We appreciate and understand the commenters' concern for the methodology change from the RPL market basket. The RPL market basket contract labor costs were calculated by multiplying the RPL market basket Wages and Salaries cost weight by the IPPS contract labor ratio. The IPPS contract labor ratio was equal to the 2006-based IPPS market basket Contract Labor cost weight divided by the 2006-based IPPS market basket Wages and Salaries cost weight. We implemented this methodology as the Medicare cost report available at that time did not capture contract labor costs for IPFs while CMS Form 2552-10, used for the 2012-based IPF market basket, collects contract labor costs data for freestanding and hospital-based IPFs. As stated in the proposed rule (80 FR 25019), we believed we had a large enough sample to produce a reasonable Contract Labor cost weight as we found that when we recalculated the cost weight after weighting to reflect the characteristics (by urban/rural and ownership type) of the universe of IPF providers (freestanding and hospital-based), it did not have a material effect on the resulting cost weight (less than 0.2 Start Printed Page 46663percentage point). In addition, we would note that the 2012-based IPF cost report data produces a contract labor ratio that is similar to the contract labor ratio using the 2010-based IPPS market basket with a contract labor ratio of 4 percent.

Final Decision: We are finalizing our methodology for calculating Contract Labor costs as proposed.

Pharmaceuticals Costs

For freestanding IPFs, we proposed to calculate pharmaceuticals costs using non-salary costs reported on Worksheet A, column 7 less Worksheet A, column 1 for the pharmacy cost center (line 15) and drugs charged to patients cost center (line 73).

For hospital-based IPFs, we proposed to calculate pharmaceuticals costs causing a portion of the non-salary pharmacy costs and a portion of the non-salary drugs charged to patient costs reported for the total facility. Non-salary pharmacy costs attributable to the hospital-based IPF are calculated by multiplying total pharmacy costs attributable to the hospital-based IPF (as reported on Worksheet B, column 15, line 40) by the ratio of total non-salary pharmacy costs (Worksheet A, column 2, line 15) to total pharmacy costs (sum of Worksheet A, column 1 and 2 for line 15) for the total facility. Non-salary drugs charged to patient costs attributable to the hospital-based IPF are calculated by multiplying total non-salary drugs charged to patient costs (Worksheet B, part I, column 0, line 73 plus Worksheet B, part I, column 15, line 73 less Worksheet A, column 1, line 73) for the total facility by the ratio of Medicare drugs charged to patient ancillary costs for the IPF unit (as reported on Worksheet D-3 for IPF subproviders, line 73, column 3) to total Medicare drugs charged to patients ancillary costs for the total facility (equal to the sum of Worksheet D-3, line 73, column 3, for all relevant PPS (that is, IPPS, IRF, IPF and SNF)). We did not receive any specific comments on our proposed methodology for calculating Pharmaceuticals costs for freestanding and hospital-based IPFs.

Final Decision: We are finalizing our methodology for calculating Pharmaceuticals costs as proposed.

Professional Liability Insurance (PLI) Costs

For freestanding IPFs, we proposed that PLI costs (often referred to as malpractice costs) are equal to premiums, paid losses and self-insurance costs reported on Worksheet S-2, line 118, columns 1 through 3.

For hospital-based IPFs, we proposed to assume that the PLI weight for the total facility is similar to the hospital-based IPF unit since the only data reported on this worksheet is for the entire facility. Therefore, hospital-based IPF PLI costs are equal to total facility PLI (as reported on Worksheet S-2, line 118, columns 1 through 3) divided by total facility costs (as reported on Worksheet A, line 200) times hospital-based IPF Medicare allowable total costs. We did not receive any specific comments on our proposed methodology for calculating PLI costs for freestanding and hospital-based IPFs.

Final Decision: We are finalizing our methodology for calculating PLI costs as proposed.

Capital Costs

For freestanding IPFs, capital costs are equal to Medicare allowable capital costs as reported on Worksheet B, Part II, column 26.

For hospital-based IPFs, capital costs are equal to IPF routine inpatient capital costs (as reported on Worksheet B, part II, column 26, line 40) and a portion of IPF ancillary capital costs. We calculate the portion of ancillary capital costs attributable to the hospital-based IPF for a given cost center by multiplying total facility ancillary capital costs for the specific ancillary cost center (as reported on Worksheet B, Part II, column 26) by the ratio of IPF Medicare ancillary costs for the cost center (as reported on Worksheet D-3, column 3 for IPF subproviders) to total Medicare ancillary costs for the cost center (equal to the sum of Worksheet D-3, column 3 for all relevant PPS (that is, IPPS, IRF, IPF and SNF)). We did not receive any specific comments on our proposed methodology for calculating Capital-related costs for freestanding and hospital-based IPFs.

Final Decision: We are finalizing our methodology for calculating Capital-related costs as proposed.

ii. Final Major Cost Category Computation

After we derive costs for the six major cost categories for each provider using the Medicare cost report data as described above, we proposed to trim the data for outliers based on the following steps. First, we divide the costs for each of the six categories by total Medicare allowable costs calculated for the provider to obtain cost weights for the universe of IPF providers. Next, we apply a mutually exclusive top and bottom 5 percent trim for each cost weight to remove outliers. After the outliers have been removed, we sum the costs for each category across all remaining providers. We then divide this by the sum of total Medicare allowable costs across all remaining providers to obtain a cost weight for the proposed 2012-based IPF market basket for the given category. Finally, we calculate the residual “All Other” cost weight that reflects all remaining costs that are not captured in the six cost categories listed above. See Table 1 for the resulting cost weights for these major cost categories that we obtain from the Medicare cost reports. In Table 1, we provide the proposed cost weights, as well as the final major cost weights after implementing the methodological changes to the calculation of the Wages and Salaries and Employee Benefits costs as described above.

Table 1—Major Cost Categories as Derived From Medicare Cost Reports

Major cost categoriesProposed 2012-based IPF (percent)Final 2012- based IPF (percent)2008-Based RPL (percent)
Wages and Salaries50.851.047.4
Employee Benefits 113.013.112.3
Contract Labor 11.41.42.6
Professional Liability Insurance (Malpractice)1.11.10.8
Pharmaceuticals4.84.86.5
Capital7.07.08.4
All Other22.021.622.0
Note: Total may not sum to 100 due to rounding.
1 Due to the lack of Medicare cost report data, the Employee Benefits and Contract Labor cost weights in the 2008-based RPL market basket were based on the IPPS market basket.
Start Printed Page 46664

As discussed in section III.A.3.i of this final rule, we made revisions to our proposed methodology for calculating Wages and Salaries costs for the IPF market basket based on public comments. The total effect of this methodology change on the 2012-based IPF market basket Wages and Salaries aggregate cost weight (which reflects freestanding and hospital-based IPFs) is an increase of 0.2 percentage point from the proposed 2012-based IPF market basket Wages and Salaries cost weight of 51.0 percent. This net overall effect can be broken down into two components including: (1) The inclusion of overhead wages and salaries attributable to the ancillary departments for hospital-based IPFs (resulting in an increase of 2.2 percentage points to the aggregate Wages and Salaries cost weight) and (2) our change in methodology for deriving the overhead wages and salaries attributable to the hospital-based IPF routine inpatient unit (resulting in a decrease of 1.9 percentage points to the Wages and Salaries cost weight). The Wages and Salaries cost weight obtained directly from the Medicare cost reports for the final 2012-based IPF market basket is approximately 3 percentage points higher than the Wages and Salaries cost weight for the 2008-based RPL market basket. This is the result of freestanding IPFs having a larger percentage of costs attributable to labor than freestanding IRF and long-term care hospitals. These latter facilities were included in the 2008-based RPL market basket.

Also as discussed in section III.A.3.a.i. of this final rule, we made revisions to our calculation of Employee Benefits costs based on public comment. The total effect of this methodology change on the 2012-based IPF market basket Employee Benefits aggregate cost weight (which reflects freestanding and hospital-based IPFs) is an increase of about 0.1 percentage point from the proposed 2012-based IPF market basket Employee Benefits cost weight of 13.1 percent. This net overall effect can be broken down into two components including: (1) The inclusion of overhead employee benefits attributable to the ancillary departments (resulting in an increase of 0.8 percentage point to the aggregate Employee Benefits cost weight) and (2) changes to the overhead employee benefits attributable to the hospital-based IPF routine inpatient unit as a result of changes to the routine overhead wages and salaries for the hospital-based IPF (resulting in a decrease of 0.7 percentage point to the Employee Benefits cost weight).

As we did for the 2008-based RPL market basket, we proposed to allocate the Contract Labor cost weight to the Wages and Salaries and Employee Benefits cost weights based on their relative proportions under the assumption that contract labor costs are comprised of both wages and salaries and employee benefits. The Contract Labor allocation proportion for Wages and Salaries is equal to the Wages and Salaries cost weight as a percent of the sum of the Wages and Salaries cost weight and the Employee Benefits cost weight. For the proposed rule, this rounded percentage was 80 percent; therefore, we proposed to allocate 80 percent of the Contract Labor cost weight to the Wages and Salaries cost weight and 20 percent to the Employee Benefits cost weight. Table 2 shows the Wages and Salaries and Employee Benefit cost weights after Contract Labor cost weight allocation for both the proposed 2012-based IPF market basket and 2008-based RPL market basket. We did not receive any public comments on our methodology for allocating Contract Labor to the Wages and Salaries and Employee Benefits cost weights.

Final Decision: We are finalizing our methodology for allocating Contract Labor as proposed. For the final rule, after making changes to the Wages and Salaries and Employee Benefits cost weights, the rounded percentage remains 80 percent. Therefore, we are finalizing our methodology as proposed and allocating 80 percent of the Contract Labor cost weight to the Wages and Salaries cost weight and 20 percent to the Employee Benefits cost weight.

Table 2—Wages and Salaries and Employee Benefits Cost Weights After Contract Labor Allocation

Major cost categoriesProposed 2012-based IPFFinal 2012-based IPF2008-Based RPL
Wages and Salaries51.952.149.4
Employee Benefits13.313.412.8

iii. Derivation of the Detailed Operating Cost Weights

To further divide the “All Other” residual cost weight estimated from the FY 2012 Medicare Cost Report data into more detailed cost categories, we proposed to use the 2007 Benchmark Input-Output (I-O) “Use Tables/Before Redefinitions/Purchaser Value” for North American Industry Classification System (NAICS) 622000 Hospitals, published by the Bureau of Economic Analysis (BEA). These data are publicly available at http://www.bea.gov/​industry/​io_​annual.htm.

The BEA Benchmark I-O data are scheduled for publication every 5 years with the most recent data available for 2007. The 2007 Benchmark I-O data are derived from the 2007 Economic Census and are the building blocks for BEA's economic accounts. Thus, they represent the most comprehensive and complete set of data on the economic processes or mechanisms by which output is produced and distributed.[3] BEA also produces Annual I-O estimates; however, while based on a similar methodology, these estimates reflect less comprehensive and less detailed data sources and are subject to revision when benchmark data becomes available. Instead of using the less detailed Annual I-O data, we proposed to inflate the 2007 Benchmark I-O data forward to 2012 by applying the annual price changes from the respective price proxies to the appropriate market basket cost categories that are obtained from the 2007 Benchmark I-O data. We repeat this practice for each year. We then calculated the cost shares that each cost category represents of the inflated 2012 data. These resulting 2012 cost shares are applied to the All Other residual cost weight to obtain the detailed cost weights for the 2012-based IPF market basket. For example, the cost for Food: Direct Purchases represents 6.5 percent of the sum of the “All Other” 2007 Benchmark I-O Hospital Expenditures inflated to 2012; therefore, the Food: Direct Purchases cost weight represents 6.5 percent of the 2012-based IPF market basket's “All Other” cost category (21.6 percent), yielding a “final” Food: Direct Purchases cost weight of 1.4 percent in the proposed 2012-based IPF market basket (0.065 * 21.6 percent = 1.4 percent).

Using this methodology, we proposed to derive eighteen detailed IPF market basket cost category weights from the Start Printed Page 466652012-based IPF market basket residual cost weight (21.6 percent). These categories are: (1) Electricity, (2) Fuel, Oil, and Gasoline (3) Water & Sewerage (4) Food: Direct Purchases, (5) Food: Contract Services, (6) Chemicals, (7) Medical Instruments, (8) Rubber & Plastics, (9) Paper and Printing Products, (10) Miscellaneous Products, (11) Professional Fees: Labor-related, (12) Administrative and Facilities Support Services, (13) Installation, Maintenance, and Repair, (14) All Other Labor-related Services, (15) Professional Fees: Nonlabor-related, (16) Financial Services, (17) Telephone Services, and (18) All Other Nonlabor-related Services. We did not receive any specific comments on our proposed methodology of deriving detailed market basket cost category weights using the BEA Benchmark I-O data.

Final Decision: We are finalizing our methodology for deriving the detailed market basket cost weights as proposed. However, since the methodological change to the derivation of Wages and Salaries and Employee Benefits results in a compensation cost weight that is slightly higher than proposed, the residual cost share weight is slightly lower than proposed. Therefore, we are finalizing the residual cost share weight of 21.6 percent rather than the proposed 22.0 percent. We would note that the residual All-Other cost weight was calculated using three decimal places and then rounded to a tenth of a percentage point for presentation purposes. Since this residual is used to calculate the detailed cost category weights using the BEA I-O data, these detailed cost category weights would also have slight revisions. These revisions round to no more than 0.1 percentage point.

iv. Derivation of the Detailed Capital Cost Weights

As described in section III.A.3.a.i. of the proposed rule, we proposed a Capital-Related cost weight of 7.0 percent as obtained from the FY 2012 Medicare cost reports for freestanding and hospital-based IPF providers. We proposed to separate this total Capital-Related cost weight into more detailed cost categories.

Using FY 2012 Medicare cost reports, we are able to group Capital-Related costs into the following categories: Depreciation, Interest, Lease, and Other Capital-Related costs. For each of these categories, we proposed to determine separately for hospital-based IPFs and freestanding IPFs what proportion of total capital-related costs the category represent.

For freestanding IPFs, we proposed to derive the proportions for Depreciation, Interest, Lease, and Other Capital-related costs using the data reported by the IPF on Worksheet A-7, which is similar to the methodology used for the 2008-based RPL market basket.

For hospital-based IPFs, data for these four categories are not reported separately for the subprovider; therefore, we proposed to derive these proportions using data reported on Worksheet A-7 for the total facility. We are assuming the cost shares for the overall hospital are representative for the hospital-based subprovider IPF unit. For example, if depreciation costs make up 60 percent of total capital costs for the entire facility, we believe it is reasonable to assume that the hospital-based IPF will also have a 60 percent proportion because it is a subprovider unit contained within the total facility.

In order to combine each detailed capital cost weight for freestanding and hospital-based IPFs into a single capital cost weight for the 2012-based IPF market basket, we proposed to weight together the shares for each of the categories (Depreciation, Interest, Lease, and Other Capital-related costs) based on the share of total capital costs each provider type represents of the total capital costs for all IPFs for 2012. Applying this methodology results in proportions of total capital-related costs for Depreciation, Interest, Lease and Other Capital-related costs that are representative of the universe of IPF providers.

Next, we proposed to allocate lease costs across each of the remaining detailed capital-related cost categories as was done in the 2008-based RPL market basket. This will result in 3 primary capital-related cost categories in the 2012-based IPF market basket: Depreciation, Interest, and Other Capital-Related costs. Lease costs are unique in that they are not broken out as a separate cost category in the 2012-based IPF market basket, but rather we proposed to proportionally distribute these costs among the cost categories of Depreciation, Interest, and Other Capital-Related, reflecting the assumption that the underlying cost structure of leases is similar to that of capital-related costs in general. As was done under the 2008-based RPL market basket, we proposed to assume that 10 percent of the lease costs as a proportion of total capital-related costs represents overhead and assign those costs to the Other Capital-Related cost category accordingly. We distributed the remaining lease costs proportionally across the 3 cost categories (Depreciation, Interest, and Other Capital-Related) based on the proportion that these categories comprise of the sum of the Depreciation, Interest, and Other Capital-related cost categories (excluding lease expenses). This is the same methodology used for the 2008-based RPL market basket. The allocation of these lease expenses are shown in Table 3 below.

Finally, we proposed to further divide the Depreciation and Interest cost categories. We proposed to separate Depreciation into the following two categories: (1) Building and Fixed Equipment; and (2) Movable Equipment; and proposing to separate Interest into the following two categories: (1) Government/Nonprofit; and (2) For-profit.

To disaggregate the Depreciation cost weight, we need to determine the percent of total Depreciation costs for IPFs that is attributable to Building and Fixed Equipment, which we hereafter refer to as the “fixed percentage.” For the 2012-based IPF market basket, we proposed to use slightly different methods to obtain the fixed percentages for hospital-based IPFs compared to freestanding IPFs.

For freestanding IPFs, we proposed to use depreciation data from Worksheet A-7 of the FY 2012 Medicare cost reports, similar to the methodology used for the 2008-based RPL market basket. However, for hospital-based IPFs, we determined that the fixed percentage for the entire facility may not be representative of the IPF subprovider unit due to the entire facility likely employing more sophisticated movable assets that are not utilized by the hospital-based IPF. Therefore, for hospital-based IPFs, we proposed to calculate a fixed percentage using: (1) Building and fixture capital costs allocated to the subprovider unit as reported on Worksheet B, part I line 40; and (2) building and fixture capital costs for the top five ancillary cost centers utilized by hospital-based IPFs. We proposed to then weight these two fixed percentages (routine inpatient and ancillary) using the proportion that each capital cost type represents of total capital costs in the proposed 2012-based IPF market basket. We then proposed to weight the fixed percentages for hospital-based and freestanding IPFs together using the proportion of total capital costs each provider type represents.

To disaggregate the Interest cost weight, we need to determine the percent of total interest costs for IPFs that are attributable to government and nonprofit facilities, which we hereafter refer to as the “nonprofit percentage.” For the IPF market basket, we proposed Start Printed Page 46666to use interest costs data from Worksheet A-7 of the FY 2012 Medicare cost reports for both freestanding and hospital-based IPFs, similar to the methodology used for the 2008-based RPL market basket. We determined the percent of total interest costs that are attributed to government and nonprofit IPFs separately for hospital-based and freestanding IPFs. We then proposed to weight the nonprofit percentages for hospital-based and freestanding IPFs together using the proportion of total capital costs each provider type represents.

Table 3 provides the detailed capital cost shares obtained from the Medicare cost reports. Ultimately, these detailed capital cost shares were applied to the total Capital-Related cost weight determined in section III.A.3.a.i. of the proposed rule to split out the total weight of 7.0 percent into more detailed cost categories and weights. We did not receive any specific comments on our proposed methodology for calculating the detailed capital cost weights for the 2012-based IPF market basket.

Final Decision: We are finalizing our methodology for deriving the detailed capital cost weights as proposed.

Therefore, the detailed capital cost weights for the final 2012-based IPF market basket contained in Table 3 are unchanged from the proposed rule.

Table 3—Detailed Capital Cost Weights for the Proposed 2012-Based IPF Market Basket

Cost shares obtained from Medicare cost reports (percent)Proposed detailed capital cost shares after allocation of lease expenses (percent)
Depreciation6475
Building and Fixed Equipment4653
Movable Equipment1922
Interest1517
Government/Nonprofit1214
For Profit23
Lease15n/a
Other68

v. 2012-Based IPF Market Basket Cost Categories and Weights

As stated in section III.A.3.i of this final rule, we are revising our methodology for deriving Wages and Salaries and Employee Benefit cost weights based on public comments. The methodological changes results in an increase of the Wages and Salaries and Employee Benefit cost weights of 0.2 percentage point and 0.1 percentage point, respectively. As a result of these methodology changes, the residual All-Other cost category was revised down 0.3 percentage point. Since this residual is used to calculate the detailed cost category weights using the BEA I-O data, these cost category weights would also have slight revisions. These revisions round to no more than 0.1 percentage point.

Table 4 shows the cost categories and weights for the proposed 2012-based IPF market basket, final 2012-based IPF market based on public comments, and the 2008-based RPL market basket.

Table 4—2012-Based IPF Cost Weights Compared to 2008-Based RPL Cost Weights

Cost categoryProposed 2012-based IPF cost weightFinal 2012-based IPF cost weight2008-Based RPL cost weight
Total100.0100.0100.0
Compensation65.265.562.3
Wages and Salaries51.952.149.4
Employee Benefits13.313.412.8
Utilities1.81.71.6
Electricity0.80.81.1
Fuel, Oil, and Gasoline0.90.90.4
Water & Sewerage0.10.10.1
Professional Liability Insurance1.11.10.8
Malpractice1.11.10.8
All Other Products and Services25.024.627.0
All Other Products11.711.515.6
Pharmaceuticals4.84.86.5
Food: Direct Purchases1.41.43.0
Food: Contract Services0.90.90.4
Chemicals0.60.61.1
Medical Instruments1.91.91.8
Rubber & Plastics0.50.51.1
Paper and Printing Products1.00.91.0
Appareln/an/a0.2
Machinery and Equipmentn/an/a0.1
Miscellaneous Products0.70.60.3
All Other Services13.313.111.4
Labor-Related Services6.76.64.7
Professional Fees: Labor-related2.92.92.1
Administrative and Facilities Support Services0.70.70.4
Installation, Maintenance, and Repair1.61.6-
Start Printed Page 46667
All Other: Labor-related Services1.51.52.1
Nonlabor-Related Services6.66.56.7
Professional Fees: Nonlabor-related2.62.64.2
Financial services2.32.30.9
Telephone Services0.60.60.4
Postagen/an/a0.6
All Other: Nonlabor-related Services1.11.10.6
Capital-Related Costs7.07.08.4
Depreciation5.25.25.5
Fixed Assets3.73.73.3
Movable Equipment1.51.52.2
Interest Costs1.21.22.0
Government/Nonprofit1.01.00.7
For Profit0.20.21.3
Other Capital-Related Costs0.60.60.9
Other Capital-Related Costs0.60.60.9
Note: Totals may not sum due to rounding.

We proposed that the 2012-based IPF market basket does not include separate cost categories for Apparel, Machinery & Equipment, and Postage. Due to the small weights associated with these detailed categories and relatively stable price growth in the applicable price proxy, we proposed to include Apparel and Machinery & Equipment in the Miscellaneous Products cost category and Postage in the All-Other Nonlabor-related Services. We note that these Machinery & Equipment expenses are for equipment that is paid for in a given year and not depreciated over the assets' useful life. Depreciation expenses for movable equipment are reflected in the Capital-related costs of the 2012-based IPF market basket. For the 2012-based IPF market basket, we also proposed to include a separate cost category for Installation, Maintenance, and Repair. We did not receive any public comments on our proposed list of detailed cost categories for the 2012-based IPF market basket.

Final Decision: We are finalizing our list of detailed cost categories as proposed.

b. Selection of Price Proxies

After developing the cost weights for the 2012-based IPF market basket, we proposed to select the most appropriate wage and price proxies currently available to represent the rate of price change for each expenditure category. For the majority of the cost weights, we base the price proxies on Bureau of Labor Statistics (BLS) data and grouped them into one of the following BLS categories:

  • Employment Cost Indexes. Employment Cost Indexes (ECIs) measure the rate of change in employment wage rates and employer costs for employee benefits per hour worked. These indexes are fixed-weight indexes and strictly measure the change in wage rates and employee benefits per hour. ECIs are superior to Average Hourly Earnings (AHE) as price proxies for input price indexes because they are not affected by shifts in occupation or industry mix, and because they measure pure price change and are available by both occupational group and by industry. The industry ECIs are based on the North American Classification System (NAICS) and the occupational ECIs are based on the Standard Occupational Classification System (SOC).
  • Producer Price Indexes. Producer Price Indexes (PPIs) measure price changes for goods sold in other than retail markets. PPIs are used when the purchases of goods or services are made at the wholesale level.
  • Consumer Price Indexes. Consumer Price Indexes (CPIs) measure change in the prices of final goods and services bought by consumers. CPIs are only used when the purchases are similar to those of retail consumers rather than purchases at the wholesale level, or if no appropriate PPIs are available.

We evaluated the price proxies using the criteria of reliability, timeliness, availability, and relevance:

  • Reliability. Reliability indicates that the index is based on valid statistical methods and has low sampling variability. Widely accepted statistical methods ensure that the data were collected and aggregated in a way that can be replicated. Low sampling variability is desirable because it indicates that the sample reflects the typical members of the population. (Sampling variability is variation that occurs by chance because only a sample was surveyed rather than the entire population.)
  • Timeliness. Timeliness implies that the proxy is published regularly, preferably at least once a quarter. The market baskets are updated quarterly and, therefore, it is important for the underlying price proxies to be up-to-date, reflecting the most recent data available. We believe that using proxies that are published regularly (at least quarterly, whenever possible) helps to ensure that we are using the most recent data available to update the market basket. We strive to use publications that are disseminated frequently, because we believe that this is an optimal way to stay abreast of the most current data available.
  • Availability. Availability means that the proxy is publicly available. We prefer that our proxies are publicly available because this will help ensure that our market basket updates are as transparent to the public as possible. In addition, this enables the public to be able to obtain the price proxy data on a regular basis.
  • Relevance. Relevance means that the proxy is applicable and representative of the cost category weight to which it is applied. The CPIs, PPIs, and ECIs that we selected meet these criteria. Therefore, we believe that they continue to be the best measure of price changes for the cost categories to which they would be applied.

Table 6 lists all price proxies that we proposed to use for the 2012-based IPF market basket. Below is a detailed explanation of the price proxies we are finalizing for each cost category weight.Start Printed Page 46668

i. Price Proxies for the Operating Portion of the 2012-Based IPF Market Basket

Wages and Salaries

To measure wage price growth in the proposed 2012-based IPF market basket, we proposed to apply a proxy blend based on six occupational subcategories within the Wages and Salaries category, which would reflect the IPF occupational mix. There is not a published wage proxy for IPF workers. The 2008-based RPL market basket uses the ECI for Wages and Salaries for All Civilian workers in Hospitals (BLS series code #CIU1026220000000I) to proxy these expenses.

We proposed to use the National Industry-Specific Occupational Employment and Wage estimates for North American Industrial Classification System (NAICS) 622200, Psychiatric & Substance Abuse Hospitals, published by the BLS Office of Occupational Employment Statistics (OES), as the data source for the wage cost shares in the wage proxy blend. We used OES' May 2012 data. Detailed information on the methodology for the national industry-specific occupational employment and wage estimates survey can be found at http://www.bls.gov/​oes/​current/​oes_​tec.htm.

Based on the OES data, there are six wage subcategories: Management; NonHealth Professional and Technical; Health Professional and Technical; Health Service; NonHealth Service; and Clerical. Table 5 lists the 2012 occupational assignments for the six wage subcategories.

Table 5—2012 Occupational Assignments for IPF Wage Blend

2012 Occupational groupings
Group 1Management.
11-0000Management Occupations.
Group 2NonHealth Professional & Technical.
13-0000Business and Financial Operations Occupations.
15-0000Computer and Mathematical Science Occupations.
17-0000Architecture and Engineering Occupations.
19-0000Life, Physical, and Social Science Occupations.
23-0000Legal Occupations.
25-0000Education, Training, and Library Occupations.
27-0000Arts, Design, Entertainment, Sports, and Media Occupations.
Group 3Health Professional & Technical.
29-1021Dentists, General.
29-1031Dietitians and Nutritionists.
29-1051Pharmacists.
29-1062Family and General Practitioners.
29-1063Internists, General.
29-1069Physicians and Surgeons, All Other.
29-1071Physician Assistants.
29-1111Registered Nurses.
29-1122Occupational Therapists.
29-1123Physical Therapists.
29-1125Recreational Therapists.
29-1126Respiratory Therapists.
29-1127Speech-Language Pathologists.
29-1129Therapists, All Other.
29-1199Health Diagnosing and Treating Practitioners, All Other.
Group 4Health Service.
21-0000Community and Social Services Occupations.
29-2011Medical and Clinical Laboratory Technologists.
29-2012Medical and Clinical Laboratory Technicians.
29-2021Dental Hygienists.
29-2032Diagnostic Medical Sonographers.
29-2034Radiologic Technologists and Technicians.
29-2041Emergency Medical Technicians and Paramedics.
29-2051Dietetic Technicians.
29-2052Pharmacy Technicians.
29-2054Respiratory Therapy Technicians.
29-2061Licensed Practical and Licensed Vocational Nurses.
29-2071Medical Records and Health Information Technicians.
29-2099Health Technologists and Technicians, All Other.
29-9012Occupational Health and Safety Technicians.
29-9099Healthcare Practitioner and Technical Workers, All Other.
31-0000Healthcare Support Occupations.
Group 5NonHealth Service.
33-0000Protective Service Occupations.
35-0000Food Preparation and Serving Related Occupations.
37-0000Building and Grounds Cleaning and Maintenance Occupations.
39-0000Personal Care and Service Occupations.
41-0000Sales and Related Occupations.
47-0000Construction and Extraction Occupations.
49-0000Installation, Maintenance, and Repair Occupations.
51-0000Production Occupations.
53-0000Transportation and Material Moving Occupations.
Group 6Clerical.
43-0000Office and Administrative Support Occupations.
Start Printed Page 46669

Total expenditures by occupation (that is, occupational assignment) were calculated by taking the OES number of employees multiplied by the OES annual average salary. These expenditures were aggregated based on the six groups in Table 6. We next calculated the proportion of each group's expenditures relative to the total expenditures of all six groups. These proportions, listed in Table 5, represent the weights used in the wage proxy blend. We then proposed to use the published wage proxies in Table 6 for each of the six groups (that is, wage subcategories) as we believe these six price proxies are the most technically appropriate indices available to measure the price growth of the Wages and Salaries cost category in the proposed 2012-based IPF market basket.

Table 6—2012-Based IPF Market Basket Wage Proxy Blend

Wage subcategoryWage blend weightPrice proxyBLS Series ID
Health Service36.2ECI for Wages and Salaries for All Civilian workers in Healthcare and Social AssistanceCIU1026200000000I
Health Professional and Technical33.5ECI for Wages and Salaries for All Civilian workers in HospitalsCIU1026220000000I
NonHealth Service9.2ECI for Wages and Salaries for Private Industry workers in Service OccupationsCIU2020000300000I
NonHealth Professional and Technical7.3ECI for Wages and Salaries for Private Industry workers in Professional, Scientific, and Technical ServicesCIU2025400000000I
Management7.1ECI for Wages and Salaries for Private Industry workers in Management, Business, and FinancialCIU2020000110000I
Clerical6.7ECI for Wages and Salaries for Private Industry workers in Office and Administrative SupportCIU2020000220000I
Total100.0

A comparison of the yearly changes from FY 2012 to FY 2015 for the 2012-based IPF wage blend and the 2008-based RPL wage proxy is shown in Table 7. The average annual increase in the two price proxies is similar, and in no year is the difference greater than 0.4 percentage point.

Table 7—Fiscal Year Growth in the 2012-Based IPF Wage Proxy Blend and 2008-Based RPL Wage Proxy

2012201320142015Average 2012-2015
2012-based IPF Proposed Wage Proxy Blend1.61.61.62.11.7
2008-based RPL Wage Proxy1.51.51.51.71.6
Source: IHS Global Insight, Inc., 2nd Quarter 2015 forecast with historical data through 4th Quarter 2014.

We did not receive any comments on our proposed Wages and Salaries price proxy methodology.

Final Decision: We are finalizing the use a blended Wages and Salaries price proxy as proposed.

Benefits

For measuring benefits price growth in the 2012-based IPF market basket, we proposed to apply a benefits proxy blend based on the same six subcategories and the same six blend weights used in the wage proxy blend. These subcategories and blend weights are listed in Table 8.

We proposed that the applicable benefit ECIs be identical in industry definition to the wage blend ECIs selected for each of the six subcategories. These benefit ECIs, listed in Table 8, are not publically available. Therefore, we calculated “ECIs for Total Benefits” using publically available “ECIs for Total Compensation” for each subcategory and the relative importance of wages within that subcategory's total compensation. This is the same benefits ECI methodology we implemented in our IPPS, SNF, HHA, RPL, LTCH, and ESRD market baskets. We believe the six price proxies listed in Table 8 are the most technically appropriate indices to measure the price growth of the Benefits cost category in the 2012-based IPF market basket.

The current 2008-based RPL market basket uses the ECI for Benefits for All Civilian Workers in Hospitals to proxy Benefit expenses.

Table 8—2012-Based IPF Market Basket Benefits Proxy Blend

Wage subcategoryWage blend weightPrice proxy
Health Service36.2ECI for Total Benefits for All Civilian workers in Healthcare and Social Assistance.
Health Professional and Technical33.5ECI for Total Benefits for All Civilian workers in Hospitals.
NonHealth Service9.2ECI for Total Benefits for Private Industry workers in Service Occupations.
NonHealth Professional and Technical7.3ECI for Total Benefits for Private Industry workers in Professional, Scientific, and Technical Services.
Management7.1ECI for Total Benefits for Private Industry workers in Management, Business, and Financial.
Start Printed Page 46670
Clerical6.7ECI for Total Benefits for Private Industry workers in Office and Administrative Support.
Total100.0

A comparison of the yearly changes from FY 2012 to FY 2015 for the 2012-based IPF benefit proxy blend and the 2008-based RPL benefit proxy is shown in Table 9. The average annual increase in the two price proxies is similar, and in no year is the difference greater than 0.4 percentage point.

Table 9—Fiscal Year Growth in the 2012-Based IPF Benefit Proxy Blend and 2008-Based RPL Benefit Proxy

2012201320142015Average 2012-2015
2012-based IPF Proposed Benefit Proxy Blend2.51.92.02.02.1
2008-based RPL Benefit Proxy2.11.82.12.02.0
Source: IHS Global Insight, Inc., 2nd Quarter 2015 forecast with historical data through 1st Quarter 2015

We did not receive any comments on our proposed methodology and use of a blended wage proxy index.

Final Decision: We are finalizing our proposal to use a blended wage proxy.

Electricity

We proposed to use the PPI for Commercial Electric Power (BLS series code #WPU0542) to measure the price growth of this cost category. This is the same price proxy used in the 2008-based RPL market basket.

Fuel, Oil, and Gasoline

We proposed to change the proxy used for the Fuel, Oil, and Gasoline cost category. The 2008-based RPL market basket uses the PPI for Petroleum Refineries (BLS series code #PCU32411-32411) to proxy these expenses.

For the 2012-based IPF market basket, we proposed to use a blend of the PPI for Petroleum Refineries and the PPI Commodity for Natural Gas (BLS series code #WPU0531). Our analysis of the Bureau of Economic Analysis' 2007 Benchmark Input-Output data (use table before redefinitions, purchaser's value for NAICS 622000 [Hospitals]), shows that Petroleum Refineries expenses accounts for approximately 70 percent and Natural Gas accounts for approximately 30 percent of the Fuel, Oil, and Gasoline expenses. Therefore, we proposed to blend using 70 percent of the PPI for Petroleum Refineries (BLS series code #PCU32411-32411) and 30 percent of the PPI Commodity for Natural Gas (BLS series code #WPU0531). We believe that these 2 price proxies are the most technically appropriate indices available to measure the price growth of the Fuel, Oil, and Gasoline cost category in the 2012-based IPF market basket.

Water and Sewerage

We proposed to use the CPI for Water and Sewerage Maintenance (BLS series code #CUUR0000SEHG01) to measure the price growth of this cost category. This is the same proxy used in the 2008-based RPL market basket.

Professional Liability Insurance

We proposed to use the CMS Hospital Professional Liability Index to measure changes in professional liability insurance (PLI) premiums. To generate this index, we collect commercial insurance premiums for a fixed level of coverage while holding non-price factors constant (such as a change in the level of coverage). This is the same proxy used in the 2008-based RPL market basket.

Pharmaceuticals

We proposed to use the PPI for Pharmaceuticals for Human Use, Prescription (BLS series code #WPUSI07003) to measure the price growth of this cost category. This is the same proxy used in the 2008-based RPL market basket.

Food: Direct Purchases

We proposed to use the PPI for Processed Foods and Feeds (BLS series code #WPU02) to measure the price growth of this cost category. This is the same proxy used in the 2008-based RPL market basket.

Food: Contract Purchases

We proposed to use the CPI for Food Away From Home (BLS series code #CUUR0000SEFV) to measure the price growth of this cost category. This is the same proxy used in the 2008-based RPL market basket.

Chemicals

We proposed to use a four part blended PPI composed of the PPI for Industrial Gas Manufacturing (BLS series code PCU325120325120P), the PPI for Other Basic Inorganic Chemical Manufacturing (BLS series code #PCU32518-32518), the PPI for Other Basic Organic Chemical Manufacturing (BLS series code #PCU32519-32519), and the PPI for Soap and Cleaning Compound Manufacturing (BLS series code #PCU32561-32561). We updated the blend weights using 2007 Benchmark I-O data which, compared to 2002 Benchmark I-O data, is weighted more toward organic chemical products and weighted less toward inorganic chemical products.

Table 10 shows the weights for each of the four PPIs used to create the blended PPI. These are the same four proxies used in the 2008-based RPL market basket; however, the blended PPI weights in the 2008-based RPL market baskets were based on 2002 Benchmark I-O data.Start Printed Page 46671

Table 10—Blended Chemical PPI Weights

NameProposed 2012-based IPF weights (percent)2008-Based RPL weights (percent)NAICS
PPI for Industrial Gas Manufacturing3235325120
PPI for Other Basic Inorganic Chemical Manufacturing1725325180
PPI for Other Basic Organic Chemical Manufacturing4530325190
PPI for Soap and Cleaning Compound Manufacturing610325610

Medical Instruments

We proposed to use a blend for the Medical Instruments cost category. The 2007 Benchmark Input-Output data shows an approximate 50/50 split between Surgical and Medical Instruments and Medical and Surgical Appliances and Supplies for this cost category. Therefore, we blended composed of 50 percent of the commodity-based PPI for Surgical and Medical Instruments (BLS code #WPU1562) and 50 percent of the commodity-based PPI for Medical and Surgical Appliances and Supplies (BLS code #WPU1563). The 2008-based RPL market basket uses the single, higher level PPI for Medical, Surgical, and Personal Aid Devices (BLS series code #WPU156).

Rubber and Plastics

We proposed to use the PPI for Rubber and Plastic Products (BLS series code #WPU07) to measure price growth of this cost category. This is the same proxy used in the 2008-based RPL market basket.

Paper and Printing Products

We proposed to use the PPI for Converted Paper and Paperboard Products (BLS series code #WPU0915) to measure the price growth of this cost category. This is the same proxy used in the 2008-based RPL market basket.

Miscellaneous Products

We proposed to use the PPI for Finished Goods Less Food and Energy (BLS series code #WPUSOP3500) to measure the price growth of this cost category. This is the same proxy used in the 2008-based RPL market basket.

Professional Fees: Labor-Related

We proposed to use the ECI for Total Compensation for Private Industry workers in Professional and Related (BLS series code #CIU2010000120000I) to measure the price growth of this category. This is the same proxy used in the 2008-based RPL market basket.

Administrative and Facilities Support Services

We proposed to use the ECI for Total Compensation for Private Industry workers in Office and Administrative Support (BLS series code #CIU2010000220000I) to measure the price growth of this category. This is the same proxy used in the 2008-based RPL market basket.

Installation, Maintenance, and Repair

We proposed to use the ECI for Total Compensation for Civilian workers in Installation, Maintenance, and Repair (BLS series code #CIU1010000430000I) to measure the price growth of this new cost category. Previously these costs were included in the All Other: Labor-related Services category and were proxied by the ECI for Total Compensation for Private Industry workers in Service Occupations (BLS series code #CIU2010000300000I). We believe that this index better reflects the price changes of labor associated with maintenance-related services and its incorporation represents a technical improvement to the market basket.

All Other: Labor-Related Services

We proposed to use the ECI for Total Compensation for Private Industry workers in Service Occupations (BLS series code #CIU2010000300000I) to measure the price growth of this cost category. This is the same proxy used in the 2008-based RPL market basket.

Professional Fees: Nonlabor-Related

We proposed to use the ECI for Total Compensation for Private Industry workers in Professional and Related (BLS series code #CIU2010000120000I) to measure the price growth of this category. This is the same proxy used in the 2008-based RPL market basket.

Financial Services

We proposed to use the ECI for Total Compensation for Private Industry workers in Financial Activities (BLS series code #CIU201520A000000I) to measure the price growth of this cost category. This is the same proxy used in the 2008-based RPL market basket.

Telephone Services

We proposed to use the CPI for Telephone Services (BLS series code #CUUR0000SEED) to measure the price growth of this cost category. This is the same proxy used in the 2008-based RPL market basket.

All Other: Nonlabor-Related Services

We proposed to use the CPI for All Items Less Food and Energy (BLS series code #CUUR0000SA0L1E) to measure the price growth of this cost category. This is the same proxy used in the 2008-based RPL market basket.

We did not receive any public comments on our proposed selection of price proxies.

Final Decision: We are finalizing our selection of price proxies as proposed.

ii. Price Proxies for the Capital Portion of the 2012-Based IPF Market Basket

Capital Price Proxies Prior to Vintage Weighting

We proposed to apply the same price proxies to the detailed capital-related cost categories as were applied in the 2008-based RPL market basket, which are provided in Table 12 and described below. We also proposed to continue to vintage weight the capital price proxies for Depreciation and Interest in order to capture the long-term consumption of capital. This vintage weighting method is similar to the method used for the 2008-based RPL market basket and is described below.

We proposed to proxy the Depreciation: Building and Fixed Equipment cost category by BEA's Chained Price Index for Nonresidential Construction for Hospitals and Special Care Facilities (BEA Table 5.4.4. Price Indexes for Private Fixed Investment in Structures by Type). We proposed to proxy the Depreciation: Movable Equipment cost category by the PPI for Machinery and Equipment (BLS series code #WPU11). We proposed to proxy the Nonprofit Interest cost category by the average yield on domestic municipal bonds (Bond Buyer 20-bond index). We proposed to proxy for the For-profit Interest cost category by the average yield on Moody's Aaa bonds (Federal Start Printed Page 46672Reserve). We proposed to proxy the Other Capital-Related cost category by the CPI-U for Rent of Primary Residence (BLS series code #CUUS0000SEHA). We believe these are the most appropriate proxies for IPF capital-related costs that meet our selection criteria of relevance, timeliness, availability, and reliability.

We did not receive any public comments on our proposed selection of price proxies for the capital-related portion of the market basket.

Final Decision: We are finalizing our selection of price proxies for the capital-related portion of the market basket as proposed.

Vintage Weights for Price Proxies

Because capital is acquired and paid for over time, capital-related expenses in any given year are determined by both past and present purchases of physical and financial capital. The vintage-weighted capital-related portion of the 2012-based IPF market basket 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 proportion of capital-related purchases attributable to each year of the expected life of building and fixed equipment, movable equipment, and interest. We proposed to use vintage weights to compute vintage-weighted price changes associated with depreciation and interest expenses.

Capital-related costs are inherently complicated and are determined by complex capital-related 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. By accounting for the vintage nature of capital, we are able to provide an accurate and 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 IPF capital-related costs. The capital-related component of the 2012-based IPF market basket reflects the underlying stability of the capital-related acquisition process.

To calculate the vintage weights for depreciation and interest expenses, we first need a time series of capital-related purchases for building and fixed equipment and movable equipment. We found no single source that provides an appropriate time series of capital-related purchases by hospitals for all of the above components of capital purchases. The early Medicare cost reports did not have sufficient capital-related data to meet this need. Data we obtained from the American Hospital Association (AHA) do not include annual capital-related purchases. However, the AHA does provide a consistent database of total expenses back to 1963. Consequently, we proposed to use data from the AHA Panel Survey and the AHA Annual Survey to obtain a time series of total expenses for hospitals. We then proposed to use data from the AHA Panel Survey supplemented with the ratio of depreciation to total hospital expenses obtained from the Medicare cost reports to derive a trend of annual depreciation expenses for 1963 through 2012. We proposed to separate these depreciation expenses into annual amounts of building and fixed equipment depreciation and movable equipment depreciation as determined above. From these annual depreciation amounts we derive annual end-of-year book values for building and fixed equipment and movable equipment using the expected life for each type of asset category. While data are not available that are specific to IPFs, we believe this information for all hospitals serves as a reasonable alternative for the pattern of depreciation for IPFs.

To continue to calculate the vintage weights for depreciation and interest expenses, we also need the expected lives for Building and Fixed Equipment, Movable Equipment, and Interest for the 2012-based IPF market basket. We proposed to calculate the expected lives using Medicare cost report data from freestanding and hospital-based IPFs. The expected life of any asset 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 expected life of an asset if the rates of depreciation were to continue at current year levels, assuming straight-line depreciation. We proposed to determine the expected life of building and fixed equipment separately for hospital-based IPFs and freestanding IPFs and weight these expected lives using the percent of total capital costs each provider type represents. We proposed to apply a similar method for movable equipment. Using these methods, we determined the average expected life of building and fixed equipment to be equal to 23 years, and the average expected life of movable equipment to be equal to 11 years. For the expected life of interest, we believe vintage weights for interest should represent the average expected life of building and fixed equipment because, based on previous research described in the FY 1997 IPPS final rule (61 FR 46198), the expected life of hospital debt instruments and the expected life of buildings and fixed equipment are similar. We note that for the 2008-based RPL market basket, we used FY 2008 Medicare cost reports for IPPS hospitals to determine the expected life of building and fixed equipment and movable equipment (76 FR 51763). The 2008-based RPL market basket was based on an expected average life of building and fixed equipment of 26 years and an expected average life of movable equipment of 11 years, which were both calculated using data for IPPS hospitals.

Multiplying these expected lives by the annual depreciation amounts results in annual year-end asset costs for building and fixed equipment and movable equipment. We then calculate a time series, beginning in 1964, of annual capital purchases by subtracting the previous year's asset costs from the current year's asset costs.

For the building and fixed equipment and movable equipment vintage weights, we proposed to use the real annual capital-related purchase amounts for each asset type to capture the actual amount of the physical acquisition, net of the effect of price inflation. These real annual capital-related purchase amounts are produced by deflating the nominal annual purchase amount by the associated price proxy as provided above. For the interest vintage weights, we proposed to use the total nominal annual capital-related purchase amounts to capture the value of the debt instrument (including, but not limited to, mortgages and bonds). Using these capital-related purchase time series specific to each asset type, we proposed to calculate the vintage weights for building and fixed equipment, for movable equipment, and for interest.

The vintage weights for each asset type are deemed to represent the average purchase pattern of the asset over its expected life (in the case of building and fixed equipment and interest, 23 years, and in the case of movable equipment, 11 years). For each asset type, we used the time series of annual capital-related purchase amounts available from 2012 back to 1964. These data allow us to derive twenty-seven 23-year periods of capital-related purchases for building and fixed equipment and interest, and thirty-nine 11-year periods of capital-related purchases for movable equipment. For each 23-year period for building and fixed equipment and interest, or 11-year period for movable equipment, we calculate annual vintage weights by Start Printed Page 46673dividing the capital-related purchase amount in any given year by the total amount of purchases over the entire 23-year or 11-year period. This calculation is done for each year in the 23-year or 11-year period and for each of the periods for which we have data. We then calculate the average vintage weight for a given year of the expected life by taking the average of these vintage weights across the multiple periods of data.

We did not receive any public comments on the proposed methodology for calculating the vintage weights for the 2012-based IPF market basket.

Final Decision: We are finalizing the vintage weights as proposed.

The vintage weights for the capital-related portion of the 2008-based RPL market basket and the 2012-based IPF market basket are presented in Table 11 below.

Table 11—2008-Based RPL Market Basket and 2012-Based IPF Market Basket Vintage Weights for Capital-Related Price Proxies

YearBuilding and fixed equipmentMovable equipmentInterest
2012-Based 23 years2008-Based 26 years2012-Based 11 years2008-Based 11 years2012-Based 23 years2008-Based 26 years
10.0290.0210.0690.0710.0170.010
20.0310.0230.0730.0750.0190.012
30.0340.0250.0770.0800.0220.014
40.0360.0270.0830.0830.0240.016
50.0370.0280.0870.0850.0260.018
60.0390.0300.0910.0890.0280.020
70.0400.0310.0960.0920.0300.021
80.0410.0330.1000.0980.0320.024
90.0420.0350.1030.1030.0350.026
100.0440.0370.1070.1090.0380.029
110.0450.0390.1140.1160.0400.033
120.0450.0410.0420.035
130.0450.0420.0440.038
140.0460.0430.0460.041
150.0460.0440.0480.043
160.0480.0450.0530.046
170.0490.0460.0570.049
180.0500.0470.0600.052
190.0510.0470.0630.053
200.0510.0450.0660.053
210.0510.0450.0670.055
220.0500.0450.0690.056
230.0520.0460.0730.060
240.0460.063
250.0450.064
260.0460.068
Total1.0001.0001.0001.0001.0001.000
Note: Numbers may not add to total due to rounding.

The process of creating vintage-weighted price proxies requires applying the vintage weights to the price proxy index where the last applied vintage weight in Table 11 is applied to the most recent data point. We have provided on the CMS Web site an example of how the vintage weighting price proxies are calculated, using example vintage weights and example price indices. The example can be found at the following link: http://www.cms.gov/​Research-Statistics-Data-and-Systems/​Statistics-Trends-and-Reports/​MedicareProgramRatesStats/​MarketBasketResearch.html in the zip file titled “Weight Calculations as described in the IPPS FY 2010 Proposed Rule.”

iii. Summary of Price Proxies of the 2012-Based IPF Market Basket

As stated above, we did not receive any public comments on our proposed list of operating or capital price proxies.

Final Decision: We are finalizing the list of operating and capital price proxies as proposed.

Table 12 shows both the operating and capital price proxies for the 2012-based IPF Market Basket.

Table 12—Price Proxies for the 2012-Based IPF Market Basket

Cost descriptionPrice proxiesWeight (percent)
Total100.0
Compensation65.5
Wages and SalariesBlended Wages and Salaries Price Proxy52.1
Employee BenefitsBlended Benefits Price Proxy13.4
Utilities1.7
ElectricityPPI for Commercial Electric Power0.8
Fuel, Oil, and GasolineBlend of the PPI for Petroleum Refineries and PPI for Natural Gas0.9
Start Printed Page 46674
Water & SewerageCPI-U for Water and Sewerage Maintenance0.1
Professional Liability Insurance1.1
MalpracticeCMS Hospital Professional Liability Insurance Premium Index1.1
All Other Products and Services24.6
All Other Products11.5
PharmaceuticalsPPI for Pharmaceuticals for human use, prescription4.8
Food: Direct PurchasesPPI for Processed Foods and Feeds1.4
Food: Contract ServicesCPI-U for Food Away From Home0.9
ChemicalsBlend of Chemical PPIs0.6
Medical InstrumentsBlend of the PPI for Surgical and medical instruments and PPI for Medical and surgical appliances and supplies1.9
Rubber & PlasticsPPI for Rubber and Plastic Products0.5
Paper and Printing ProductsPPI for Converted Paper and Paperboard Products0.9
Miscellaneous ProductsPPI for Finished Goods Less Food and Energy0.6
All Other Services13.1
Labor-Related Services6.6
Professional Fees: Labor-relatedECI for Total compensation for Private industry workers in Professional and related2.9
Administrative and Facilities Support ServicesECI for Total compensation for Private industry workers in Office and administrative support0.7
Installation, Maintenance, and RepairECI for Total compensation for Civilian workers in Installation, maintenance, and repair1.6
All Other: Labor-related ServicesECI for Total compensation for Private industry workers in Service occupations1.5
Nonlabor-Related Services6.5
Professional Fees: Nonlabor-relatedECI for Total compensation for Private industry workers in Professional and related2.6
Financial servicesECI for Total compensation for Private industry workers in Financial activities2.3
Telephone ServicesCPI-U for Telephone Services0.6
All Other: Nonlabor-related ServicesCPI-U for All Items Less Food and Energy1.1
Capital-Related Costs7.0
Depreciation5.2
Fixed AssetsBEA chained price index for nonresidential construction for hospitals and special care facilities—vintage weighted (23 years)3.7
Movable EquipmentPPI for machinery and equipment—vintage weighted (11 years)1.5
Interest Costs1.2
Government/NonprofitAverage yield on domestic municipal bonds (Bond Buyer 20 bonds)—vintage weighted (23 years)1.0
For ProfitAverage yield on Moody's Aaa bonds—vintage weighted (23 years)0.2
Other Capital-Related CostsCPI-U for Rent of primary residence0.6
Note: Totals may not sum to 100.0 percent due to rounding.

4. FY 2016 Market Basket Update

For FY 2016 (that is, beginning October 1, 2015 and ending September 30, 2016), we proposed to use an estimate of the 2012-based IPF market basket increase factor to update the IPF PPS base payment rate. Consistent with historical practice, we estimate the market basket update for the IPF PPS based on IHS Global Insight's forecast. IHS Global Insight (IGI), Inc. is a nationally recognized economic and financial forecasting firm that contracts with CMS to forecast the components of the market baskets and multifactor productivity (MFP).

In the FY 2016 proposed rule, using IGI's first quarter 2015 forecast with historical data through the fourth quarter of 2014, the projected proposed 2012-based IPF market basket increase factor for FY 2016 was 2.7 percent. We also proposed that if more recent data are subsequently available (for example, a more recent estimate of the market basket) we would use such data, to determine the FY 2016 update in the final rule.

For this final rule, we are estimating the market basket update for the IPF PPS using the most recent available data. Based on IGI's second quarter 2015 forecast with historical data through the first quarter of 2015, the final 2012-based IPF market basket increase factor for FY 2016 is 2.4 percent. For comparison, the current 2008-based RPL market basket is projected to increase by 2.4 percent in FY 2016 based on IGI's second quarter 2015 forecast and the proposed 2012-based IPF market basket is projected to increase 2.4 percent in FY 2016 based on IGI's second quarter 2015 forecast.

Final Decision: We are finalizing our methodology for determining the market basket increase as proposed. Therefore, consistent with our historical practice of estimating market basket increases based on the best available data, we are finalizing a market basket increase factor of 2.4 percent for FY 2016. Table 13 compares the final 2012-based IPF market basket and the 2008-based RPL market basket percent changes.Start Printed Page 46675

Table 13—2012-Based IPF Market Basket and 2008-Based RPL Market Basket Percent Changes, FY 2010 Through FY 2018

Fiscal Year (FY)Final 2012-based IPF market basket index percent change2008-Based RPL market basket index percent change
Historical data:
FY 20102.02.2
FY 20112.22.5
FY 20121.92.2
FY 20132.02.1
FY 20141.91.8
Average 2010-20142.02.2
Forecast:
FY 20151.92.0
FY 20162.42.4
FY 20172.92.9
FY 20183.03.1
Average 2015-20182.62.6
Note: These market basket percent changes do not include any further adjustments as may be statutorily required.
Source: IHS Global Insight, Inc. 2nd quarter 2015 forecast.

For FY 2016, the 2012-based IPF market basket update (2.4 percent) is the same as the 2008-based RPL market basket (2.4 percent).

5. Productivity Adjustment

Section 1886(s)(2)(A)(i) of the Act requires the application of the productivity adjustment described in section 1886(b)(3)(B)(xi)(II) of the Act to the IPF PPS for the RY beginning in 2012 (that is, a RY that coincides with a FY) and each subsequent RY. The statute defines the productivity adjustment to be equal to the 10-year moving average of changes in annual economy-wide private nonfarm business multifactor productivity (MFP) (as projected by the Secretary for the 10-year period ending with the applicable FY, year, cost reporting period, or other annual period) (the “MFP adjustment”). The Bureau of Labor Statistics (BLS) publishes the official measure of private non-farm business MFP. We refer readers to the BLS Web site at http://www.bls.gov/​mfp for the BLS historical published MFP data.

MFP is derived by subtracting the contribution of labor and capital inputs growth from output growth. The projections of the components of MFP are currently produced by IGI, a nationally recognized economic forecasting firm with which CMS contracts to forecast the components of the market baskets and MFP. As described in the FY 2012 IPPS/LTCH final rule (76 FR 51690 through 51692), in order to generate a forecast of MFP, IGI replicated the MFP measure calculated by the BLS using a series of proxy variables derived from IGI's U.S. macroeconomic models. In the FY 2012 rule, we identified each of the major MFP component series employed by the BLS to measure MFP as well as provided the corresponding concepts determined to be the best available proxies for the BLS series.

Beginning with the FY 2016 rulemaking cycle, the MFP adjustment is calculated using a revised series developed by IGI to proxy the aggregate capital inputs. Specifically, IGI has replaced the Real Effective Capital Stock used for Full Employment GDP with a forecast of BLS aggregate capital inputs recently developed by IGI using a regression model. This series provides a better fit to the BLS capital inputs, as measured by the differences between the actual BLS capital input growth rates and the estimated model growth rates over the historical time period. Therefore, we are using IGI's most recent forecast of the BLS capital inputs series in the MFP calculations beginning with the FY 2016 rulemaking cycle. A complete description of the MFP projection methodology is available on our Web site at http://www.cms.gov/​Research-Statistics-Data-and-Systems/​Statistics-Trends-and-Reports/​MedicareProgramRatesStats/​MarketBasketResearch.html. Although we discuss the IGI changes to the MFP proxy series in this final rule, in the future, when IGI makes changes to the MFP methodology, we will announce them on our Web site rather than in the annual rulemaking.

In the FY 2016 proposed rule, using IGI's first quarter 2015 forecast, the MFP adjustment for FY 2016 (the 10-year moving average of MFP for the period ending FY 2016) was projected to be 0.6 percent. Furthermore, we also proposed that if more recent data are subsequently available (for example, a more recent estimate of the market basket and MFP adjustment), we would use such data to determine the FY 2016 market basket update and MFP adjustment in the final rule. For this final rule, based on IGI's second quarter 2015 forecast with historical data through the first quarter of 2015, the MFP adjustment for FY 2016 (the 10-year moving average of MFP for the period ending FY 2016) is projected to be 0.5 percent.

Thus, in accordance with section 1886(s)(2)(A)(i) of the Act, we are finalizing our proposal to base the FY 2016 market basket update, which is used to determine the applicable percentage increase for the IPF payments, on the most recent estimate of the final 2012-based IPF market basket (estimated to be 2.4 percent based on IGI's second quarter 2015 forecast). We then reduced this percentage increase by the current estimate of the MFP adjustment for FY 2016 of 0.5 percentage point (the 10-year moving average of MFP for the period ending FY 2016 based on IGI's second quarter 2015 forecast).

Section 1886(s)(2)(A)(ii) of the Act requires the application of an “other adjustment” that reduces any update to an IPF PPS base rate by percentages specified in section 1886(s)(3) of the Act for the RY beginning in 2010 through the RY beginning in 2019. For the RY beginning in 2015 (that is, FY 2016), section 1886(s)(3)(D) of the Act requires the reduction to be 0.2 percentage point. We are implementing the productivity adjustment and “other adjustment” in this final rule.

6. Labor-Related Share

Due to variations in geographic wage levels and other labor-related costs, we Start Printed Page 46676believe that payment rates under the IPF PPS should continue to be adjusted by a geographic wage index, which would apply to the labor-related portion of the Federal per diem base rate (hereafter referred to as the labor-related share). The labor-related share is determined by identifying the national average proportion of total costs that are related to, influenced by, or vary with the local labor market. We continue to classify a cost category as labor-related if the costs are labor-intensive and vary with the local labor market. As stated in the FY 2015 IPF PPS final rule (79 FR 45943), the labor-related share was defined as the sum of the relative importance of Wages and Salaries, Employee Benefits, Professional Fees: Labor- Related Services, Administrative and Facilities Support Services, All Other: Labor-related Services, and a portion of the Capital Costs from the 2008-based RPL market basket.

Based on our definition of the labor-related share and the cost categories in the 2012-based IPF market basket, we proposed to include in the labor-related share the sum of the relative importance of Wages and Salaries, Employee Benefits, Professional Fees: Labor- Related, Administrative and Facilities Support Services, Installation, Maintenance, and Repair, All Other: Labor-related Services, and a portion of the Capital-Related cost weight from the proposed 2012-based IPF market basket.

Comment: Several commenters expressed concerns over the accuracy of the labor-related share using the proposed 2012-based IPF market basket, particularly given the proposed increase in the labor-related share of six percentage points over the FY 2015 labor-related share using the 2008-based RPL market basket. One commenter stated that they anticipated that the IPF labor costs would be higher than possibly rehabilitation or long-term care hospitals; however, a labor share of this magnitude was not anticipated. They further stated that CMS acknowledged in the proposed rule that approximately 69 percent of the IPFs have a wage index value less than 1.00 and would face permanent payment reductions, while the remaining IPFs in high-cost areas will receive payment increases due to the budget neutrality and cost-shifting that will occur if the proposed labor-related share and proposed wage indices are adopted.

Several other commenters stated there is a potential to overstate the labor-related share by multiplying the ancillary salary cost reported on worksheet A “by the ratio of IPF Medicare ancillary costs for the cost center.” They urged CMS to utilize a more accurate calculation for the ancillary cost centers in order to mitigate the risk of overstating labor- related share costs.

Response: We appreciate the commenters' concern over the increase in the FY 2016 labor-related share using the proposed 2012-based IPF market basket compared to the FY 2015 labor-related share using the 2008-based RPL market basket. As stated in the FY 2016 proposed rule (80 FR 25032), of the six percentage-point difference in the labor-related shares, three percentage points are attributable to the higher Wages and Salaries and Employee Benefits cost weights in the 2012-based IPF market basket compared to the 2008-based RPL market basket, while two percentage points are attributable to the higher weight associated with the labor-related services cost categories. Further, we stated that the higher Wages and Salaries cost weight in the 2012-based IPF market basket relative to the 2008-based RPL market basket is the result of freestanding IPFs having a larger percentage of costs attributable to labor than freestanding IRFs and long-term care hospitals. These latter facilities were included in the 2008-based RPL market basket.

The freestanding IPF Wages and Salaries cost weight is approximately 10 percentage points higher than the hospital-based IPF Wages and Salaries cost weight. It is also about six percentage points higher than the freestanding IRF Wages and Salaries cost weight, and 13 percentage points higher than the LTCH Wages and Salaries cost weight, all of which were included in the 2008-based RPL market basket. The methodology used to develop the freestanding IPF Wages and Salaries cost weight is similar to that used in the 2008-based RPL market basket, and we did not receive any comments on our proposed methodology outlined in the FY 2016 IPF PPS rule.

As stated in section III.A.3.a.i of this final rule, we evaluated our methodology for Wages and Salaries cost weight, including that of ancillary wages and salaries. Based on the comments received, we are revising our methodology for calculating the Wages and Salaries cost weight and Employee Benefits cost weight, resulting in an increase in the cost weights of 0.2 and 0.1 percentage point, respectively.

Comment: One commenter stated they had major reservations about the new inclusion of the Installation, Maintenance and Repair cost category in the labor-related share, stating that it adds an additional 1.6 percentage points in non-health related labor costs to the IPF labor-related share. They further stated that it is unclear why CMS considers this additional category a technical improvement to the IPF market basket since CMS has never recognized this cost category in its RPL market basket computations in prior years nor has CMS shown how this additional cost category improves the labor-related share computation. They urged CMS not to adopt this change to the labor-related share.

Response: We disagree with the commenter's claim that the Installation, Maintenance and Repair category is a new cost category in the labor-related share. As stated in the proposed rule (80 FR 25027 and 25032), Installation, Maintenance and Repair services costs were previously included in the “All Other” Labor-related Services cost category in the 2008-based RPL market basket, along with other services, including but not limited to janitorial, waste management, security, and dry cleaning/laundry services. Also, as stated in the proposed rule (80 FR 20527), we chose to create a separate cost category for Installation, Maintenance and Repair services in order to proxy these costs by the ECI for Total Compensation for Civilian workers in Installation, Maintenance, and Repair services. We believe this price proxy better reflects the price changes of labor associated with maintenance-related services. In the 2008-based RPL market basket, these services are proxied by the ECI for total Compensation for Private Industry in Service Occupations, which reflects price growth associated with general service occupations.

During our development of the 2012-based IPF market basket using 2007 Benchmark I-O data, we decided to aggregate detailed I-O NAICS data to create a cost category specific to Installation, Maintenance and Repair services and to proxy these costs by a more specific price index. A comparison of the average historical growth rate over the last 10 years showed that the ECI for Total Compensation for Civilian workers in Installation, Maintenance, and Repair outpaced the ECI for total Compensation for Private Industry in Service Occupations by approximately 0.4 percentage point. We continue to believe that the inclusion of this cost category is a technical improvement to the 2012-based IPF market basket as we are able to proxy Installation, Maintenance, and Repair services with a price proxy that better reflects the price changes of labor associated with maintenance-related services. Because Installation, Maintenance and Repair services tend to be labor-intensive and Start Printed Page 46677are mostly performed at the facility (and, therefore, unlikely to be purchased in the national market), we continue to believe that they meet our definition of labor-related services and thus, should be included in the labor-related share.

Similar to the 2008-based RPL market basket, the 2012-based IPF market basket includes two cost categories for non-medical professional fees (including but not limited to expenses for legal, accounting, and engineering services). These are Professional Fees: Labor-related and Professional Fees: Nonlabor-related. For the proposed 2012-based IPF market basket, we estimated the labor-related percentage of non-medical professional fees (and assign these expenses to the Professional Fees: Labor-related services cost category) based on the same method that was used to determine the labor-related percentage of professional fees in the 2008-based RPL market basket.

To summarize, the professional services survey found that hospitals purchase the following proportion of these four services outside of their local labor market:

  • 34 percent of accounting and auditing services.
  • 30 percent of engineering services.
  • 33 percent of legal services.
  • 42 percent of management consulting services.

We proposed to apply each of these percentages to the respective Benchmark I-O cost category underlying the professional fees cost category to determine the Professional Fees: Nonlabor-related costs. The Professional Fees: Labor-related costs were determined to be the difference between the total costs for each Benchmark I-O category and the Professional Fees: Nonlabor-related costs. This is the same methodology that we used to separate the 2008-based RPL market basket professional fees category into Professional Fees: Labor-related and Professional Fees: Nonlabor-related cost categories. For more detail regarding this methodology see the FY 2012 IPF final rule (76 FR 26445).

In addition to the professional services listed above, we also proposed to classify expenses under NAICS 55, Management of Companies and Enterprises, into the Professional Fees cost category as was done in the 2008-based RPL market basket. The NAICS 55 data are mostly comprised of corporate, subsidiary, and regional managing offices, or otherwise referred to as home offices. Since many facilities are not located in the same geographic area as their home office, we analyzed data from a variety of sources in order to determine what proportion of these costs should be appropriately included in the labor-related share. For the 2012-based IPF market basket, we derived the home office percentages using data for both freestanding IPF providers and hospital-based IPF providers. In the 2008-based RPL market basket, we used the home office percentages based on the data reported by freestanding IRFs, IPFs, and LTCHs.

Using data primarily from the Medicare cost reports and the Home Office Medicare Records (HOMER) database that provides the address (including city and state) for home offices, we were able to determine that 36 percent of the total number of freestanding and hospital-based IPFs that had home offices had those home offices located in their respective local labor markets—defined as being in the same Metropolitan Statistical Area (MSA).

The Medicare cost report requires hospitals to report their home office provider numbers. Using the HOMER database to determine the home office location for each home office provider number, we compared the location of the provider with the location of the hospital's home office. We then placed providers into one of the following 2 groups:

  • Group 1—Provider and home office are located in different MSAs.
  • Group 2—Provider and home office are located in the same MSA.

We found that 64 percent of the providers with home offices were classified into Group 1 (that is, different MSA) and, thus, these providers were determined to not be located in the same local labor market as their home office. We found that 36 percent of all providers with home offices were classified into Group 2 (that is, the same MSA). Given these results, we proposed to classify 36 percent of these Professional Fees costs into the Professional Fees: Labor-related cost category and the remaining 64 percent into the Professional Fees: Nonlabor-related Services cost category. This methodology for apportioning the Professional Fee expenses between labor-related and nonlabor-related categories is similar to the method used in the 2008-based RPL market basket (see 76 FR 26445).

We received one comment on our methodology for determining the Professional Fees: Labor-related and Professional Fees: Nonlabor-related cost weights.

Comment: One commenter pointed out that CMS's proposed FY 2016 labor-related share of 74.9 percent is an 8.1 percent increase compared to the FY 2015 labor-related share of 69.294 percent, and disagreed with the logic used to support this increase, stating that CMS disproportionately emphasizes professional fees and home office costs in the calculations of the labor-related share. The commenter stated that of the 1,617 psychiatric hospitals/units, 69.4 percent are IPF units. The commenter then stated that the majority of IPF unit salaries relate to direct patient care (RNs, LPNs, Aides, etc.) and are consistent with salaries in the hospital acute care areas. The commenter noted that the FY 2016 IPPS proposed rule for acute care hospitals indicates no changes to the labor-related share for wage indexes less than 1.000 or wage indexes greater than 1.000 (the labor-related share for IPPS hospitals is 69.6 percent). The commenter stated that yet, in the FY 2016 IPF proposed rule, CMS believes an 8.1 percent increase is justified and indicative of salary changes to almost 70 percent of psychiatric providers. The commenter stated that this change also negatively impacts 64.4 percent of psychiatric providers, all located in CMS' Central/South Atlantic Regions. The commenter disagreed that East and West coast provider costs have increased significantly compared to the Midwest and thus should bear the brunt of this change.

The commenter further proposed that CMS consider calculating labor-related share percentages similar to those calculated for IPPS, where CMS uses a percentage for providers with a wage index less than 1.00 and a percentage for providers with a wage index greater than 1.00.

Response: We respectfully disagree with the commenter's statement that we are disproportionately emphasizing professional fees and home office costs in the calculations of the labor-related share. The components of the labor-related share are identical to those used in the IPPS labor-related share, including the inclusion of professional fees and home office costs in the IPPS labor-related share. (As stated above, we note that the Installation, Maintenance, and Repair services costs are included in the All Other: Labor-related Services in both the FY 2016 IPPS labor-related share and FY 2015 IPF labor-related share using the 2008-based RPL market basket).

The differences in the IPF labor-related share and IPPS labor-related share are primarily attributable to the Wages and Salaries, Employee Benefits, and Contract Labor cost weights (the sum of which is the Compensation cost weight) which are based on IPF PPS and IPPS Medicare cost report data, Start Printed Page 46678respectively. We note that the 2010-based IPPS market basket cost weights are based on costs as a percent of total operating costs while the 2012-based IPF market basket cost weights are based on a percent of total costs (the sum of operating costs and capital costs). The 2012-based IPF Compensation cost weight as a percent of total operating costs (after removing the capital cost weight) is about 10 percentage points higher than the 2010-based IPPS Compensation cost weight whereas the 2012-based IPF market basket Professional Fees: Labor-related share cost weight as a percent of total operating costs (after removing the capital cost weight) is about two percentage points lower than the 2010-based IPPS market basket Professional Fees: Labor-related share cost weight. In addition, the 2012-based IPF Professional Fees: Labor-related share cost weight is about four percent of the 2012-based IPF Compensation cost weight whereas the 2010-based IPPS Professional Fees: Labor-related share cost weight is about nine percent of the 2012-based IPPS Compensation cost weight.

As the commenter stated, the Professional Fees: Labor-related share includes home office costs. As described above, we determine the proportion of the home office costs that are labor-related by comparing the IPF provider's location (that is, MSA) to the location of its home office (also, MSA). This is the same methodology used in the 2008-based RPL market basket and 2010-based IPPS market basket. The 2012 IPF Medicare cost report and Medicare HOMER data found that 36 percent were located in the same MSA (and thus were allocated to the Professional Fees: Labor-related share cost weight) whereas the same analysis using 2010 IPPS Medicare cost report data and Medicare HOMER data found this percentage to be much higher with 62 percent.

We would further note that the approximately three percentage point difference between the IPF labor-related share of 74.9 percent and the IPPS labor-related share of 69.6 percent is attributable to the IPF labor-related share including a portion of capital-related costs. The IPPS labor-related share applies to the operating base payment rate and therefore, does not include a portion of capital-related costs. IPPS has a separate capital base payment rate and geographic adjustment factor. The IPF PPS base payment rate reflects both operating and capital costs (similar to the IRF and SNF PPS); therefore, the labor-related share also reflects both costs.

We acknowledge the commenter's concern regarding an IPPS labor-related share of 62 percent for wage indexes less than 1.000 but there is no such provision for IPFs. The 62 percent rule is mandated by Section 403 of Public Law 108-173, which amended section 1886(d)(3)(E) of the Act and is applicable to IPPS hospitals operating base payment rate only.

We would also note that the FY 2016 IPPS proposed rule did not include a revision to the IPPS labor-related share. The IPPS labor-related share was last revised effective for FY 2014 when CMS finalized their proposal to rebase and revise the IPPS market basket as is now being done for the FY 2016 IPF PPS proposed rule.

Therefore, we disagree with the commenters' claim that we are overemphasizing professional fees and home office costs in the IPF labor-related share and we continue to believe a labor-related share based on the 2012-based IPF market basket is appropriate.

Final Decision: We are finalizing our methodology for determining the IPF labor-related share based on the final 2012-based IPF market basket (reflecting methodological revisions to the Wages and Salaries and Employee Benefit cost weights based on public comments as described in section III.A.3.a.i in this final rule).

Using this method and the IHS Global Insight, Inc. 2nd quarter 2015 forecast for the final 2012-based IPF market basket, the IPF labor-related share for FY 2016 is the sum of the FY 2016 relative importance of each labor-related cost category. The relative importance reflects the different rates of price change for these cost categories between the base year (FY 2012) and FY 2016. Table 14 shows the FY 2016 labor-related share using the final 2012-based IPF market basket relative importance and the FY 2015 labor-related share using the 2008-based RPL market basket.

The sum of the relative importance for FY 2016 operating costs (Wages and Salaries, Employee Benefits, Professional Fees: Labor-related, Administrative and Facilities Support Services, Installation Maintenance & Repair Services, and All Other: Labor-related Services) is 72.1 percent, as shown in Table 14. We specified the labor-related share to one decimal place, which is consistent with the IPPS labor-related share (currently the Labor-related share from the RPL market basket is specified to 3 decimal places).

The portion of Capital that is influenced by the local labor market is estimated to be 46 percent, which is the same percentage applied to the 2008-based RPL market basket. Since the relative importance for Capital-Related Costs is 6.8 percent of the 2012-based IPF market basket in FY 2016, we took 46 percent of 6.8 percent to determine the labor-related share of Capital for 2016. The result will be 3.1 percent, which we added to 72.1 percent for the operating cost amount to determine the total labor-related share for FY 2016.

The FY 2016 labor-related share using the 2012-based IPF market basket is about five percentage points higher than the FY 2015 labor-related share using the 2008-based RPL market basket. Of the 5 percentage point difference in the labor-related shares, three percentage points are attributable to the higher Wages and Salaries and Employee Benefits cost weights in the 2012-based IPF market basket compared to the 2008-based RPL market basket, while two percentage points are attributable to the higher weight associated with the labor-related services cost categories. Further, we stated that the higher Wages and Salaries cost weight in the 2012-based IPF market basket relative to the 2008-based RPL market basket is the result of freestanding IPFs having a larger percentage of costs attributable to labor than freestanding IRFs and long-term care hospitals both of which were included in the 2008-based RPL market basket.

Table 14—2016 IPF Labor-Related Share

FY 2016 Labor-related share based on 2012-based IPF market basket 1FY 2015 Final labor-related share 2
Wages and Salaries51.948.271
Employee Benefits13.512.936
Start Printed Page 46679
Professional Fees: Labor-related2.92.058
Administrative and Facilities Support Services0.70.415
Installation, Maintenance and Repair1.6
All Other: Labor-related Services1.52.061
Subtotal72.165.741
Labor-related portion of capital (46%)3.13.553
Total LRS75.269.294
1 IHS Global Insight, Inc. 2nd quarter 2015 forecast.
2Federal Register 79 FR 45943.

In weighing the effects of the change in the LRS, we considered whether to recommend a 2-year transitional implementation of the increase in the LRS. We recognize that IPFs with wage index values of less than one would be adversely affected by an increased LRS, as a larger share of the base rate will be adjusted by the wage index value. About 69 percent of IPFs will have wage index values of less than one using FY2015 CBSA data, and 30 percent of these providers are rural. While the LRS will be updated in a budget neutral manner so that the overall impact on payments is zero, there will still be distributional effects on specific categories of IPFs. We considered the distributional effects of the multiple updates made in this final rule, including the update to the full LRS in FY 2016, and we found that the negative impact of updating the LRS in a single year, without a transition, was relatively small, as shown in Table 28 in section VIII. of this final rule. Additionally, we made two other adjustments to benefit providers: A transitional wage index and a phase-out of the 17 percent rural adjustment for the 37 IPFs that will change from rural to urban status due to the new CBSA delineations. As presented in section III.A.6. of this final rule, we used the 2012-based IPF market basket relative importance's to determine the FY 2016 IPF LRS. We believe this is appropriate as it is based on more recent, provider-specific data for IPFs. For all of these reasons, we implemented the full LRS in FY 2016.

Comment: We received three comments, which asked that we phase in the updated LRS over 2 years rather than implementing it in a single year. Commenters were concerned about the effect of the increase in the LRS on providers.

Response: We thank the commenters for their suggestion, but we are not providing a transition to the updated LRS. The 2012-based IPF market basket improves the accuracy of the IPF PPS, and the updated LRS is a more accurate reflection of the IPF labor-related share. Although in two other instances we are providing a transition that will benefit providers—a 1-year transitional wage index and the 3-year transition of the rural adjustment—in this case, we believe the impact on those providers that will be negatively affected by the updated LRS is relatively small. Furthermore, we have not typically provided a transition in the IPF PPS when the LRS has changed. For example, in the May 6, 2011 IPF PPS final rule, we rebased the RPL market basket, and the LRS changed from 75.400 to 70.317. Although this decrease in the LRS would have benefitted IPFs with wage index values less than one, but would have had a negative payment effect on IPFs with wage index values greater than one, we did not provide a transition to this lower LRS. For all of these reasons, we are implementing the updated IPF-specific LRS of 75.2 in full in FY 2016.

B. Updates to the IPF PPS for FY 2016 (Beginning October 1, 2015)

The IPF PPS is based on a standardized Federal per diem base rate calculated from the IPF average per diem costs and adjusted for budget-neutrality in the implementation year. The Federal per diem base rate is used as the standard payment per day under the IPF PPS and is adjusted by the patient-level and facility-level adjustments that are applicable to the IPF stay. A detailed explanation of how we calculated the average per diem cost appears in the November 2004 IPF PPS final rule (69 FR 66926).

1. Determining the Standardized Budget-Neutral Federal Per Diem Base Rate

Section 124(a)(1) of the BBRA required that we implement the IPF PPS in a budget-neutral manner. In other words, the amount of total payments under the IPF PPS, including any payment adjustments, must be projected to be equal to the amount of total payments that would have been made if the IPF PPS were not implemented. Therefore, we calculated the budget-neutrality factor by setting the total estimated IPF PPS payments to be equal to the total estimated payments that would have been made under the Tax Equity and Fiscal Responsibility Act of 1982 (TEFRA) (Pub. L. 97-248) methodology had the IPF PPS not been implemented. A step-by-step description of the methodology used to estimate payments under the TEFRA payment system appears in the November 2004 IPF PPS final rule (69 FR 66926).

Under the IPF PPS methodology, we calculated the final Federal per diem base rate to be budget-neutral during the IPF PPS implementation period (that is, the 18-month period from January 1, 2005 through June 30, 2006) using a July 1 update cycle. We updated the average cost per day to the midpoint of the IPF PPS implementation period (that is, October 1, 2005), and this amount was used in the payment model to establish the budget-neutrality adjustment.

Next, we standardized the IPF PPS Federal per diem base rate to account for the overall positive effects of the IPF PPS payment adjustment factors by dividing total estimated payments under the TEFRA payment system by estimated payments under the IPF PPS. Additional information concerning this standardization can be found in the November 2004 IPF PPS final rule (69 Start Printed Page 46680FR 66932) and the RY 2006 IPF PPS final rule (71 FR 27045). We then reduced the standardized Federal per diem base rate to account for the outlier policy, the stop loss provision, and anticipated behavioral changes. A complete discussion of how we calculated each component of the budget-neutrality adjustment appears in the November 2004 IPF PPS final rule (69 FR 66932 through 66933) and in the May 2006 IPF PPS final rule (71 FR 27044 through 27046). The final standardized budget-neutral Federal per diem base rate established for cost reporting periods beginning on or after January 1, 2005 was calculated to be $575.95.

The Federal per diem base rate has been updated in accordance with applicable statutory requirements and § 412.428 through publication of annual notices or proposed and final rules. A detailed discussion on the standardized budget-neutral Federal per diem base rate and the electroconvulsive therapy (ECT) payment per treatment appears in the August 2013 IPF PPS update notice (78 FR 46738 through 46739). These documents are available on the CMS Web site at http://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientPsychFacilPPS/​index.html.

2. FY 2016 Update of the Federal Per Diem Base Rate and Electroconvulsive Therapy (ECT) Payment Per Treatment

The current (that is, FY 2015) Federal per diem base rate is $728.31 and the ECT payment per treatment is $313.55. For FY 2016, we applied an update of 1.7 percent (that is, the 2012-based IPF market basket increase for FY 2016 of 2.4 percent less the productivity adjustment of 0.5 percentage point, and further reduced by the 0.2 percentage point required under section1886(s)(3)(D) of the Act), and the wage index budget-neutrality factor of 1.0041 (as discussed in section III.D.1.e. of this final rule) to the FY 2015 Federal per diem base rate of $728.31, yielding a Federal per diem base rate of $743.73 for FY 2016. Similarly, we applied the 1.7 percent payment update and the 1.0041 wage index budget-neutrality factor to the FY 2015 ECT payment per treatment, yielding an ECT payment per treatment of $320.19 for FY 2016.

As noted above, section 1886(s)(4) of the Act requires the establishment of a quality data reporting program for the IPF PPS beginning in RY 2015. We refer readers to section V. of this final rule for a discussion of the IPF Quality Reporting Program. Section 1886(s)(4)(A)(i) of the Act requires that, for RY 2014 and each subsequent rate year, the Secretary shall reduce any annual update to a standard Federal rate for discharges occurring during the rate year by 2.0 percentage points for any IPF that does not comply with the quality data submission requirements with respect to an applicable year. Therefore, we will apply a 2.0 percentage point reduction to the Federal per diem base rate and the ECT payment per treatment as follows:

For IPFs that failed to submit quality reporting data under the IPFQR program, we will apply a −0.3 percent annual update (that is, 1.7 percent reduced by 2 percentage points, in accordance with section 1886(s)(4)(A)(ii) of the Act) and the wage index budget-neutrality factor of 1.0041 to the FY 2015 Federal per diem base rate of $728.31, yielding a Federal per diem base rate of $729.10 for FY 2016.

Similarly, we will apply the −0.3 percent annual update and the 1.0041 wage index budget-neutrality factor to the FY 2015 ECT payment per treatment of $313.55, yielding an ECT payment per treatment of $313.89 for FY 2016.

C. Updates to the IPF PPS Patient-Level Adjustment Factors

1. Overview of the IPF PPS Adjustment Factors

The IPF PPS payment adjustments were derived from a regression analysis of 100 percent of the FY 2002 MedPAR data file, which contained 483,038 cases. For a more detailed description of the data file used for the regression analysis, see the November 2004 IPF PPS final rule (69 FR 66935 through 66936). While we have since used more recent claims data to simulate payments to set the fixed dollar loss threshold amount for the outlier policy and to assess the impact of the IPF PPS updates, we continue to use the regression-derived adjustment factors established in 2005 for FY 2016.

2. IPF PPS Patient-Level Adjustments

The IPF PPS includes payment adjustments for the following patient-level characteristics: Medicare Severity Diagnosis Related Groups (MS-DRGs) assignment of the patient's principal diagnosis, selected comorbidities, patient age, and the variable per diem adjustments. We did not propose any changes to the IPF PPS Patient-level Adjustments.

a. MS-DRG Assignment

We believe it is important to maintain the same diagnostic coding and DRG classification for IPFs that are used under the IPPS for providing psychiatric care. For this reason, when the IPF PPS was implemented for cost reporting periods beginning on or after January 1, 2005, we adopted the same diagnostic code set (ICD-9-CM) and DRG patient classification system (that is, the CMS DRGs) that were utilized at the time under the IPPS. In the May 2008 IPF PPS notice (73 FR 25709), we discussed CMS' effort to better recognize resource use and the severity of illness among patients. CMS adopted the new MS-DRGs for the IPPS in the FY 2008 IPPS final rule with comment period (72 FR 47130). In the 2008 IPF PPS notice (73 FR 25716), we provided a crosswalk to reflect changes that were made under the IPF PPS to adopt the new MS-DRGs. For a detailed description of the mapping changes from the original DRG adjustment categories to the current MS-DRG adjustment categories, we refer readers to the May 2008 IPF PPS notice (73 FR 25714).

The IPF PPS includes payment adjustments for designated psychiatric DRGs assigned to the claim based on the patient's principal diagnosis. The DRG adjustment factors were expressed relative to the most frequently reported psychiatric DRG in FY 2002, that is, DRG 430 (psychoses). The coefficient values and adjustment factors were derived from the regression analysis. Mapping the DRGs to the MS-DRGs resulted in the current 17 IPF-MS-DRGs, instead of the original 15 DRGs, for which the IPF PPS provides an adjustment.

For the FY 2016 update, we are not making any changes to the IPF MS-DRG adjustment factors. In FY 2015 rulemaking (79 FR 45945 through 45947), we proposed and finalized conversions of the ICD-9-CM-based MS-DRGs to ICD-10-CM/PCS-based MS-DRGs, which will be implemented on October 1, 2015. Further information for the ICD-10-CM/PCS MS-DRG conversion project can be found on the CMS ICD-10-CM Web site at http://www.cms.hhs.gov/​Medicare/​Coding/​ICD10/​ICD-10-MS-DRG-Conversion-Project.html.

For FY 2016, we will continue to make a payment adjustment for psychiatric diagnoses that group to one of the existing 17 IPF-MS-DRGs listed in the Addendum. Psychiatric principal diagnoses that do not group to one of the 17 designated DRGs will still receive the Federal per diem base rate and all other applicable adjustments, but the payment would not include a DRG adjustment.

As noted above, the diagnoses for each IPF-MS-DRG will be updated on October 1, 2015, using the ICD-10-CM/PCS code sets.Start Printed Page 46681

b. Payment for Comorbid Conditions

The intent of the comorbidity adjustments is to recognize the increased costs associated with comorbid conditions by providing additional payments for certain concurrent medical or psychiatric conditions that are expensive to treat. In the May 2011 IPF PPS final rule (76 FR 26451 through 26452), we explained that the IPF PPS includes 17 comorbidity categories and identified the new, revised, and deleted ICD-9-CM diagnosis codes that generate a comorbid condition payment adjustment under the IPF PPS for RY 2012 (76 FR 26451).

Comorbidities are specific patient conditions that are secondary to the patient's principal diagnosis and that require treatment during the stay. Diagnoses that relate to an earlier episode of care and have no bearing on the current hospital stay are excluded and must not be reported on IPF claims. Comorbid conditions must exist at the time of admission or develop subsequently, and affect the treatment received, length of stay (LOS), or both treatment and LOS.

For each claim, an IPF may receive only one comorbidity adjustment within a comorbidity category, but it may receive an adjustment for more than one comorbidity category. Current billing instructions for claims for discharges on or after October 1, 2015 require IPFs to enter the complete ICD-10-CM codes for up to 24 additional diagnoses if they co-exist at the time of admission, or develop subsequently and impact the treatment provided.

The comorbidity adjustments were determined based on the regression analysis using the diagnoses reported by IPFs in FY 2002. The principal diagnoses were used to establish the DRG adjustments and were not accounted for in establishing the comorbidity category adjustments, except where ICD-9-CM “code first” instructions apply. As we explained in the May 2011 IPF PPS final rule (76 FR 265451), the “code first” rule applies when a condition has both an underlying etiology and a manifestation due to the underlying etiology. For these conditions, ICD-9-CM has a coding convention that requires the underlying conditions to be sequenced first followed by the manifestation. Whenever a combination exists, there is a “use additional code” note at the etiology code and a “code first” note at the manifestation code.

The same principle holds for ICD-10-CM as for ICD-9-CM. Whenever a combination exists, there is a “use additional code” note in the ICD-10-CM codebook pertaining to the etiology code, and a “code first” code pertaining to the manifestation code. In the FY 2015 IPF PPS final rule, we provided a “code first” table for reference that highlights the same or similar manifestation codes where the “code first” instructions apply in ICD-10-CM that were present in ICD-9-CM (79 FR 46009).

As noted previously, it is our policy to maintain the same diagnostic coding set for IPFs that is used under the IPPS for providing the same psychiatric care. The 17 comorbidity categories formerly defined using ICD-9-CM codes were converted to ICD-10-CM/PCS in the FY 2015 IPF PPS final rule (79 FR 45947 to 45955). The goal for converting the comorbidity categories is referred to as replication, meaning that the payment adjustment for a given patient encounter is the same after ICD-10-CM implementation as it would be if the same record had been coded in ICD-9-CM and submitted prior to ICD-10-CM/PCS implementation on October 1, 2015. All conversion efforts were made with the intent of achieving this goal.

We did not propose any refinements to the comorbidity adjustments, and will continue to use the existing adjustments in effect in FY 2015. The FY 2016 comorbidity adjustments are found in the Addendum to this final rule.

Comment: We received one comment suggesting that we change the comorbidity adjustment to add a number of infectious diseases which the commenters felt increased IPF costs. The commenter provided a listing of ICD-10-CM codes for these conditions.

Response: Changes to the comorbidity adjustment would occur as part of a larger IPF PPS refinement, as the comorbidity adjustment factors are derived through a regression analysis, which also includes other IPF PPS adjustments (for example, the age adjustment). We did not propose to refine the IPF PPS in the FY 2016 IPF PPS proposed rule, and therefore, this comment is outside the scope of this rule. However, we will consider the comment when we undertake future refinements.

3. Patient Age Adjustments

As explained in the November 2004 IPF PPS final rule (69 FR 66922), we analyzed the impact of age on per diem cost by examining the age variable (that is, the range of ages) for payment adjustments. In general, we found that the cost per day increases with age. The older age groups are more costly than the under 45 age group, the differences in per diem cost increase for each successive age group, and the differences are statistically significant.

We did not propose any changes to the patient age adjustments; for FY 2016, we will continue to use the patient age adjustments currently in effect in FY 2015, as shown in the Addendum to this final rule.

4. Variable Per Diem Adjustments

We explained in the November 2004 IPF PPS final rule (69 FR 66946) that the regression analysis indicated that per diem cost declines as the LOS increases. The variable per diem adjustments to the Federal per diem base rate account for ancillary and administrative costs that occur disproportionately in the first days after admission to an IPF.

We used a regression analysis to estimate the average differences in per diem cost among stays of different lengths. As a result of this analysis, we established variable per diem adjustments that begin on day 1 and decline gradually until day 21 of a patient's stay. For day 22 and thereafter, the variable per diem adjustment remains the same each day for the remainder of the stay. However, the adjustment applied to day 1 depends upon whether the IPF has a qualifying emergency department (ED). If an IPF has a qualifying ED, it receives a 1.31 adjustment factor for day 1 of each stay. If an IPF does not have a qualifying ED, it receives a 1.19 adjustment factor for day 1 of the stay. The ED adjustment is explained in more detail in section III.D.4. of this final rule.

We did not propose any changes to the variable per diem adjustment factors; for FY 2016, we will continue to use the variable per diem adjustment factors currently in effect as shown in the Addendum to this final rule. A complete discussion of the variable per diem adjustments appears in the November 2004 IPF PPS final rule (69 FR 66946).

D. Updates to the IPF PPS Facility-Level Adjustments

The IPF PPS includes facility-level adjustments for the wage index, IPFs located in rural areas, teaching IPFs, cost of living adjustments for IPFs located in Alaska and Hawaii, and IPFs with a qualifying ED.

1. Wage Index Adjustment

a. Background

As discussed in the May 2006 IPF PPS final rule (71 FR 27061) and in the May 2008 (73 FR 25719) and May 2009 IPF PPS notices (74 FR 20373), in order to provide an adjustment for geographic wage levels, the labor-related portion of Start Printed Page 46682an IPF's payment is adjusted using an appropriate wage index. Currently, an IPF's geographic wage index value is determined based on the actual location of the IPF in an urban or rural area as defined in § 412.64(b)(1)(ii)(A) and (C).

b. Wage Index for FY 2016

Since the inception of the IPF PPS, we have used the pre-floor, pre-reclassified acute care hospital wage index in developing a wage index to be applied to IPFs because there is not an IPF-specific wage index available. We believe that IPFs generally compete in the same labor markets as acute care hospitals, so the pre-floor, pre-reclassified hospital wage index should reflect IPF labor costs. As discussed in the May 2006 IPF PPS final rule for FY 2007 (71 FR 27061 through 27067), under the IPF PPS, the wage index is calculated using the IPPS wage index for the labor market area in which the IPF is located, without taking into account geographic reclassifications, floors, and other adjustments made to the wage index under the IPPS. For a complete description of these IPPS wage index adjustments, please see the CY 2013 IPPS/LTCH PPS final rule (77 FR 53365 through 53374). For FY 2016, we will continue to apply the most recent hospital wage index (that is, the FY 2015 pre-floor, pre-reclassified hospital wage index, which is the most appropriate index as it best reflects the variation in local labor costs of IPFs in the various geographic areas) using the most recent hospital wage data (that is, data from hospital cost reports for the cost reporting period beginning during FY 2011) without any geographic reclassifications, floors, or other adjustments. We apply the FY 2016 IPF PPS wage index to payments beginning October 1, 2015.

We apply the wage index adjustment to the labor-related portion of the federal rate, which we changed from 69.294 percent to 75.2 percent in FY 2016. This percentage reflects the labor-related share of the 2012-based IPF market basket for FY 2016 (see section III.A.6. of this final rule).

c. OMB Bulletins and Transitional Wage Index

OMB publishes bulletins regarding CBSA changes, including changes to CBSA numbers and titles. In the May 2006 IPF PPS final rule for RY 2007 (71 FR 27061 through 27067), we adopted the changes discussed in the Office of Management and Budget (OMB) Bulletin No. 03-04 (June 6, 2003), which announced revised definitions for Metropolitan Statistical Areas (MSAs), and the creation of Micropolitan Statistical Areas and Combined Statistical Areas. In adopting the OMB CBSA geographic designations in RY 2007, we did not provide a separate transition for the CBSA-based wage index since the IPF PPS was already in a transition period from TEFRA payments to PPS payments.

In the May 2008 IPF PPS notice, we incorporated the CBSA nomenclature changes published in the most recent OMB bulletin that applies to the hospital wage index used to determine the current IPF PPS wage index and stated that we expect to continue to do the same for all the OMB CBSA nomenclature changes in future IPF PPS rules and notices, as necessary (73 FR 25721). The OMB bulletins may be accessed online at http://www.whitehouse.gov/​omb/​bulletins_​default/​.

In accordance with our established methodology, we have historically adopted any CBSA changes that are published in the OMB bulletin that corresponds with the hospital wage index used to determine the IPF PPS wage index. For the FY 2015 IPF wage index, we used the FY 2014 pre-floor, pre-reclassified hospital wage index to adjust the IPF PPS payments. On February 28, 2013, OMB issued OMB Bulletin No. 13-01, which established revised delineations for Metropolitan Statistical Areas, Micropolitan Statistical Areas, and Combined Statistical Areas, and provided guidance on the use of the delineations of these statistical areas. A copy of this bulletin may be obtained at http://www.whitehouse.gov/​omb/​bulletins_​default/​. Because the FY 2014 pre-floor, pre-reclassified hospital wage index was finalized prior to the issuance of this Bulletin, the FY 2015 IPF PPS wage index, which was based on the FY 2014 pre-floor, pre-reclassified hospital wage index, did not reflect OMB's new area delineations based on the 2010 Census. According to OMB, “[t]his bulletin provides the delineations of all Metropolitan Statistical Areas, Metropolitan Divisions, Micropolitan Statistical Areas, Combined Statistical Areas, and New England City and Town Areas in the United States and Puerto Rico based on the standards published on June 28, 2010, in the Federal Register (75 FR 37246 through 37252) and Census Bureau data.” These OMB Bulletin changes are reflected in the FY 2015 pre-floor, pre-reclassified hospital wage index, upon which the FY 2016 IPPS PPS wage index is based. We have adopted these new OMB CBSA delineations in the FY 2016 IPF PPS wage index.

We believe that the most current CBSA delineations accurately reflect the local economies and wage levels of the areas where IPFs are located, and we believe that it is important for the IPF PPS to use the latest CBSA delineations available in order to maintain an up-to-date payment system that accurately reflects the reality of population shifts and labor market conditions.

In adopting these changes for the IPF PPS, it was necessary to identify the new labor market area delineation for each county and facility in the country. For example, there will be new CBSAs, urban counties that would become rural, rural counties that would become urban, and existing CBSAs that would be split apart. Because the wage index of urban areas is typically higher than that of rural areas, IPF facilities currently located in rural counties that will become urban, beginning October 1, 2015, will generally experience an increase in their wage index values. We identified 105 counties and 37 IPFs that will move from rural to urban status due to the new CBSA delineations beginning in FY 2016, shown in Table 15.

Table 15—FY 2016 Rural to Urban CBSA Crosswalk

County nameFY 2014 CBSA Delineations/FY 2015 dataFY 2015 CBSA Delineations/FY 2015 dataChange in value (percent)
CBSAUrban/RuralWage indexCBSAUrban/RuralWage index
Baldwin County, Alabama1RURAL0.696319300URBAN0.72484.09
Pickens County, Alabama1RURAL0.696346220URBAN0.833719.73
Cochise County, Arizona3RURAL0.912543420URBAN0.8937−2.06
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Little River County, Arkansas4RURAL0.731145500URBAN0.73620.70
Windham County, Connecticut7RURAL1.125149340URBAN1.14932.15
Sussex County, Delaware8RURAL1.026141540URBAN0.9289−9.47
Citrus County, Florida10RURAL0.800626140URBAN0.7625−4.76
Gulf County, Florida10RURAL0.800637460URBAN0.7906−1.25
Highlands County, Florida10RURAL0.800642700URBAN0.7982−0.30
Sumter County, Florida10RURAL0.800645540URBAN0.80951.11
Walton County, Florida10RURAL0.800618880URBAN0.81561.87
Lincoln County, Georgia11RURAL0.742512260URBAN0.922524.24
Morgan County, Georgia11RURAL0.742512060URBAN0.936926.18
Peach County, Georgia11RURAL0.742547580URBAN0.75421.58
Pulaski County, Georgia11RURAL0.742547580URBAN0.75421.58
Kalawao County, Hawaii12RURAL1.074127980URBAN1.0561−1.68
Maui County, Hawaii12RURAL1.074127980URBAN1.0561−1.68
Butte County, Idaho13RURAL0.739826820URBAN0.893320.75
De Witt County, Illinois14RURAL0.836214010URBAN0.91659.60
Jackson County, Illinois14RURAL0.836216060URBAN0.8324−0.45
Williamson County, Illinois14RURAL0.836216060URBAN0.8324−0.45
Scott County, Indiana15RURAL0.841631140URBAN0.86052.25
Union County, Indiana15RURAL0.841617140URBAN0.947312.56
Plymouth County, Iowa16RURAL0.845143580URBAN0.89155.49
Kingman County, Kansas17RURAL0.780648620URBAN0.84728.53
Allen County, Kentucky18RURAL0.774414540URBAN0.84108.60
Butler County, Kentucky18RURAL0.774414540URBAN0.84108.60
Acadia Parish, Louisiana19RURAL0.758029180URBAN0.78693.81
Iberia Parish, Louisiana19RURAL0.758029180URBAN0.78693.81
St. James Parish, Louisiana19RURAL0.758035380URBAN0.882116.37
Tangipahoa Parish, Louisiana19RURAL0.758025220URBAN0.945224.70
Vermilion Parish, Louisiana19RURAL0.758029180URBAN0.78693.81
Webster Parish, Louisiana19RURAL0.758043340URBAN0.83259.83
St. Marys County, Maryland21RURAL0.855415680URBAN0.85930.46
Worcester County, Maryland21RURAL0.855441540URBAN0.92898.59
Midland County, Michigan23RURAL0.820733220URBAN0.7935−3.31
Montcalm County, Michigan23RURAL0.820724340URBAN0.87997.21
Fillmore County, Minnesota24RURAL0.912440340URBAN1.139824.92
Le Sueur County, Minnesota24RURAL0.912433460URBAN1.119622.71
Mille Lacs County, Minnesota24RURAL0.912433460URBAN1.119622.71
Sibley County, Minnesota24RURAL0.912433460URBAN1.119622.71
Benton County, Mississippi25RURAL0.758932820URBAN0.899118.47
Yazoo County, Mississippi25RURAL0.758927140URBAN0.78913.98
Golden Valley County, Montana27RURAL0.902413740URBAN0.8686−3.75
Hall County, Nebraska28RURAL0.892424260URBAN0.92193.31
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Hamilton County, Nebraska28RURAL0.892424260URBAN0.92193.31
Howard County, Nebraska28RURAL0.892424260URBAN0.92193.31
Merrick County, Nebraska28RURAL0.892424260URBAN0.92193.31
Jefferson County, New York33RURAL0.820848060URBAN0.83862.17
Yates County, New York33RURAL0.820840380URBAN0.87506.60
Craven County, North Carolina34RURAL0.799535100URBAN0.899412.50
Davidson County, North Carolina34RURAL0.799549180URBAN0.86798.56
Gates County, North Carolina34RURAL0.799547260URBAN0.922315.36
Iredell County, North Carolina34RURAL0.799516740URBAN0.907313.48
Jones County, North Carolina34RURAL0.799535100URBAN0.899412.50
Lincoln County, North Carolina34RURAL0.799516740URBAN0.907313.48
Pamlico County, North Carolina34RURAL0.799535100URBAN0.899412.50
Rowan County, North Carolina34RURAL0.799516740URBAN0.907313.48
Oliver County, North Dakota35RURAL0.709913900URBAN0.72161.65
Sioux County, North Dakota35RURAL0.709913900URBAN0.72161.65
Hocking County, Ohio36RURAL0.832918140URBAN0.953914.53
Perry County, Ohio36RURAL0.832918140URBAN0.953914.53
Cotton County, Oklahoma37RURAL0.779930020URBAN0.79181.53
Josephine County, Oregon38RURAL1.008324420URBAN1.00860.03
Linn County, Oregon38RURAL1.008310540URBAN1.08797.89
Adams County, Pennsylvania39RURAL0.871923900URBAN1.010415.88
Columbia County, Pennsylvania39RURAL0.871914100URBAN0.93477.20
Franklin County, Pennsylvania39RURAL0.871916540URBAN1.095725.67
Monroe County, Pennsylvania39RURAL0.871920700URBAN0.93727.49
Montour County, Pennsylvania39RURAL0.871914100URBAN0.93477.20
Utuado Municipio, Puerto Rico40RURAL0.404710380URBAN0.3586−11.39
Beaufort County, South Carolina42RURAL0.837425940URBAN0.87083.99
Chester County, South Carolina42RURAL0.837416740URBAN0.90738.35
Jasper County, South Carolina42RURAL0.837425940URBAN0.87083.99
Lancaster County, South Carolina42RURAL0.837416740URBAN0.90738.35
Union County, South Carolina42RURAL0.837443900URBAN0.8277−1.16
Custer County, South Dakota43RURAL0.831239660URBAN0.89898.14
Campbell County, Tennessee44RURAL0.736528940URBAN0.7015−4.75
Crockett County, Tennessee44RURAL0.736527180URBAN0.77475.19
Maury County, Tennessee44RURAL0.736534980URBAN0.896921.78
Morgan County, Tennessee44RURAL0.736528940URBAN0.7015−4.75
Start Printed Page 46685
Roane County, Tennessee44RURAL0.736528940URBAN0.7015−4.75
Falls County, Texas45RURAL0.785547380URBAN0.81373.59
Hood County, Texas45RURAL0.785523104URBAN0.938619.49
Hudspeth County, Texas45RURAL0.785521340URBAN0.81393.62
Lynn County, Texas45RURAL0.785531180URBAN0.883012.41
Martin County, Texas45RURAL0.785533260URBAN0.894013.81
Newton County, Texas45RURAL0.785513140URBAN0.85088.31
Oldham County, Texas45RURAL0.785511100URBAN0.82775.37
Somervell County, Texas45RURAL0.785523104URBAN0.938619.49
Box Elder County, Utah46RURAL0.889136260URBAN0.92253.76
Augusta County, Virginia49RURAL0.767444420URBAN0.83268.50
Buckingham County, Virginia49RURAL0.767416820URBAN0.905317.97
Culpeper County, Virginia49RURAL0.767447894URBAN1.040335.56
Floyd County, Virginia49RURAL0.767413980URBAN0.847310.41
Rappahannock County, Virginia49RURAL0.767447894URBAN1.040335.56
Staunton City County, Virginia49RURAL0.767444420URBAN0.83268.50
Waynesboro City County, Virginia49RURAL0.767444420URBAN0.83268.50
Columbia County, Washington50RURAL1.089247460URBAN1.09340.39
Pend Oreille County, Washington50RURAL1.089244060URBAN1.14254.89
Stevens County, Washington50RURAL1.089244060URBAN1.14254.89
Walla Walla County, Washington50RURAL1.089247460URBAN1.09340.39
Fayette County, West Virginia51RURAL0.741013220URBAN0.80248.29
Raleigh County, West Virginia51RURAL0.741013220URBAN0.80248.29
Green County, Wisconsin52RURAL0.904131540URBAN1.113023.11

The wage index values of rural areas are typically lower than that of urban areas. Therefore, IPFs located in a county that is currently designated as urban under the IPF PPS wage index that will become rural when we adopt the new CBSA delineations may experience a decrease in their wage index values. We identified 38 counties and four IPFs that will move from urban to rural status due to the new CBSA delineations beginning in FY 2016. Our use of updated data for this final rule increased the number of counties and the number of IPFs that changed status from urban to rural from 37 to 38, and three to four, respectively. Table 16 shows the CBSA delineations and the urban wage index values for FY 2015 based on existing CBSA delineations, compared with the proposed CBSA delineations and wage index values for FY 2016 based on the new OMB CBSA delineations. Table 16 also shows the percentage change in these values for those counties that will change from urban to rural, beginning in FY 2016, when we adopt the new CBSA delineations.

Table 16—FY 2016 Urban to Rural CBSA Crosswalk

County nameFY 2014 CBSA Delineations/FY 2015 dataFY 2015 CBSA Delineations/FY 2015 dataChange in value (percent)
CBSAUrban/RuralWage indexCBSAUrban/RuralWage index
Greene County, Alabama46220URBAN0.83871RURAL0.6914−17.56
Franklin County, Arkansas22900URBAN0.75934RURAL0.7311−3.71
Power County, Idaho38540URBAN0.967213RURAL0.7398−23.51
Franklin County, Indiana17140URBAN0.947315RURAL0.8416−11.16
Gibson County, Indiana21780URBAN0.853715RURAL0.8416−1.42
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Greene County, Indiana14020URBAN0.906215RURAL0.8416−7.13
Tipton County, Indiana29020URBAN0.899015RURAL0.8416−6.38
Franklin County, Kansas28140URBAN0.941917RURAL0.7779−17.41
Geary County, Kansas31740URBAN0.840617RURAL0.7779−7.46
Nelson County, Kentucky31140URBAN0.859318RURAL0.7748−9.83
Webster County, Kentucky21780URBAN0.853718RURAL0.7748−9.24
Franklin County, Massachusetts44140URBAN1.027122RURAL1.155312.48
Ionia County, Michigan24340URBAN0.896523RURAL0.8288−7.55
Newaygo County, Michigan24340URBAN0.896523RURAL0.8288−7.55
George County, Mississippi37700URBAN0.739625RURAL0.75702.35
Stone County, Mississippi25060URBAN0.817925RURAL0.7570−7.45
Crawford County, Missouri41180URBAN0.936626RURAL0.7725−17.52
Howard County, Missouri17860URBAN0.831926RURAL0.7725−7.14
Washington County, Missouri41180URBAN0.936626RURAL0.7725−17.52
Anson County, North Carolina16740URBAN0.923034RURAL0.7899−14.42
Greene County, North Carolina24780URBAN0.937134RURAL0.7899−15.71
Erie County, Ohio41780URBAN0.778436RURAL0.83487.25
Ottawa County, Ohio45780URBAN0.912936RURAL0.8348−8.56
Preble County, Ohio19380URBAN0.893836RURAL0.8348−6.60
Washington County, Ohio37620URBAN0.818636RURAL0.83481.98
Stewart County, Tennessee17300URBAN0.752644RURAL0.7277−3.31
Calhoun County, Texas47020URBAN0.847345RURAL0.7847−7.39
Delta County, Texas19124URBAN0.970345RURAL0.7847−19.13
San Jacinto County, Texas26420URBAN0.973445RURAL0.7847−19.39
Summit County, Utah41620URBAN0.951246RURAL0.9005−5.33
Cumberland County, Virginia40060URBAN0.962549RURAL0.7554−21.52
Danville City County, Virginia19260URBAN0.796349RURAL0.7554−5.14
King And Queen County, Virginia40060URBAN0.962549RURAL0.7554−21.52
Louisa County, Virginia40060URBAN0.962549RURAL0.7554−21.52
Pittsylvania County, Virginia19260URBAN0.796349RURAL0.7554−5.14
Surry County, Virginia47260URBAN0.922349RURAL0.7554−18.10
Morgan County, West Virginia25180URBAN0.908051RURAL0.7274−19.89
Pleasants County, West Virginia37620URBAN0.818651RURAL0.7274−11.14

We note that IPFs in some urban CBSAs will experience a change in their wage index values even though they remain urban because an urban CBSA's boundaries and/or the counties included in that CBSA can change. Table 17 shows those counties that would experience a change in their wage index value in FY 2016 due to the new OMB CBSAs. Table 17 shows the urban CBSA delineations and wage index values for FY 2015 based on existing CBSA delineations, compared with the urban CBSA delineations and wage index values for FY 2016 based on the new OMB delineations, and the percentage change in these values, for counties that will remain urban even though the CBSA boundaries and/or counties included in that CBSA will change.Start Printed Page 46687

Table 17—FY 2015 Urban to a Different FY 2016 Urban CBSA Crosswalk

County nameFY 2014 CBSA Delineations/FY 2015 dataFY 2015 CBSA Delineations/FY 2015 dataChange in value (percent)
CBSAUrban/RuralWage indexCBSAUrban/RuralWage index
Flagler County, Florida37380URBAN0.846219660URBAN0.8376−1.02
De Kalb County, Illinois16974URBAN1.041220994URBAN1.0299−1.09
Kane County, Illinois16974URBAN1.041220994URBAN1.0299−1.09
Madison County, Indiana11300URBAN1.007826900URBAN1.01330.55
Meade County, Kentucky31140URBAN0.859321060URBAN0.7701−10.38
Essex County, Massachusetts37764URBAN1.076915764URBAN1.11593.62
Ottawa County, Michigan26100URBAN0.813624340URBAN0.87998.15
Jackson County, Mississippi37700URBAN0.739625060URBAN0.78966.76
Bergen County, New Jersey35644URBAN1.311035614URBAN1.2837−2.08
Hudson County, New Jersey35644URBAN1.311035614URBAN1.2837−2.08
Middlesex County, New Jersey20764URBAN1.098935614URBAN1.283716.82
Monmouth County, New Jersey20764URBAN1.098935614URBAN1.283716.82
Ocean County, New Jersey20764URBAN1.098935614URBAN1.283716.82
Passaic County, New Jersey35644URBAN1.311035614URBAN1.2837−2.08
Somerset County, New Jersey20764URBAN1.098935084URBAN1.12332.22
Bronx County, New York35644URBAN1.311035614URBAN1.2837−2.08
Dutchess County, New York39100URBAN1.153320524URBAN1.1345−1.63
Kings County, New York35644URBAN1.311035614URBAN1.2837−2.08
New York County, New York35644URBAN1.311035614URBAN1.2837−2.08
Orange County, New York39100URBAN1.153335614URBAN1.283711.31
Putnam County, New York35644URBAN1.311020524URBAN1.1345−13.46
Queens County, New York35644URBAN1.311035614URBAN1.2837−2.08
Richmond County, New York35644URBAN1.311035614URBAN1.2837−2.08
Rockland County, New York35644URBAN1.311035614URBAN1.2837−2.08
Westchester County, New York35644URBAN1.311035614URBAN1.2837−2.08
Brunswick County, North Carolina48900URBAN0.886734820URBAN0.8620−2.79
Bucks County, Pennsylvania37964URBAN1.083733874URBAN1.0157−6.27
Chester County, Pennsylvania37964URBAN1.083733874URBAN1.0157−6.27
Montgomery County, Pennsylvania37964URBAN1.083733874URBAN1.0157−6.27
Arecibo Municipio, Puerto Rico41980URBAN0.444911640URBAN0.4213−5.30
Camuy Municipio, Puerto Rico41980URBAN0.444911640URBAN0.4213−5.30
Ceiba Municipio, Puerto Rico21940URBAN0.366941980URBAN0.443820.96
Fajardo Municipio, Puerto Rico21940URBAN0.366941980URBAN0.443820.96
Guanica Municipio, Puerto Rico49500URBAN0.337538660URBAN0.415423.08
Guayanilla Municipio, Puerto Rico49500URBAN0.337538660URBAN0.415423.08
Hatillo Municipio, Puerto Rico41980URBAN0.444911640URBAN0.4213−5.30
Start Printed Page 46688
Luquillo Municipio, Puerto Rico21940URBAN0.366941980URBAN0.443820.96
Penuelas Municipio, Puerto Rico49500URBAN0.337538660URBAN0.415423.08
Quebradillas Municipio, Puerto Rico41980URBAN0.444911640URBAN0.4213−5.30
Yauco Municipio, Puerto Rico49500URBAN0.337538660URBAN0.415423.08
Anderson County, South Carolina11340URBAN0.874424860URBAN0.91614.77
Grainger County, Tennessee34100URBAN0.698328940URBAN0.70150.46
Lincoln County, West Virginia16620URBAN0.798826580URBAN0.884610.74
Putnam County, West Virginia16620URBAN0.798826580URBAN0.884610.74

Likewise, IPFs currently located in a rural area may remain rural under the new CBSA delineations but experience a change in their rural wage index value due to implementation of the new CBSA delineations. Table 18 shows the FY 2015 CBSA delineations and rural statewide wage index values, compared with the FY 2016 CBSA delineations and rural statewide wage index values, and the percentage change in these values, for those rural areas that will change.

Table 18—FY 2016 Changes to the Statewide Rural Wage Index Crosswalk

County nameFY 2014 CBSA Delineations/FY 2015 dataFY 2015 CBSA Delineations/FY 2015 dataChange in value (percent)
CBSAUrban/RuralWage indexCBSAUrban/RuralWage index
ALABAMA1RURAL0.69631RURAL0.6914−0.70
ARIZONA3RURAL0.91253RURAL0.92191.03
CONNECTICUT7RURAL1.12517RURAL1.12950.39
FLORIDA10RURAL0.800610RURAL0.83714.56
GEORGIA11RURAL0.742511RURAL0.74390.19
HAWAII12RURAL1.074112RURAL1.08721.22
ILLINOIS14RURAL0.836214RURAL0.83690.08
KANSAS17RURAL0.780617RURAL0.7779−0.35
KENTUCKY18RURAL0.774418RURAL0.77480.05
LOUISIANA19RURAL0.758019RURAL0.7108−6.23
MARYLAND21RURAL0.855421RURAL0.87462.24
MASSACHUSETTS22RURAL1.392022RURAL1.1553−17.00
MICHIGAN23RURAL0.820723RURAL0.82880.99
MISSISSIPPI25RURAL0.758925RURAL0.7570−0.25
NEBRASKA28RURAL0.892428RURAL0.8877−0.53
NEW YORK33RURAL0.820833RURAL0.8192−0.19
NORTH CAROLINA34RURAL0.799534RURAL0.7899−1.20
OHIO36RURAL0.832936RURAL0.83480.23
OREGON38RURAL1.008338RURAL0.9949−1.33
PENNSYLVANIA39RURAL0.871939RURAL0.8083−7.29
SOUTH CAROLINA42RURAL0.837442RURAL0.8370−0.05
TENNESSEE44RURAL0.736544RURAL0.7277−1.19
TEXAS45RURAL0.785545RURAL0.7847−0.10
UTAH46RURAL0.889146RURAL0.90051.28
VIRGINIA49RURAL0.767449RURAL0.7554−1.56
WASHINGTON50RURAL1.089250RURAL1.0877−0.14
WEST VIRGINIA51RURAL0.741051RURAL0.7274−1.84
WISCONSIN52RURAL0.904152RURAL0.90870.51

While we believe that the new CBSA delineations will result in wage index values that are more representative of the actual costs of labor in a given area, we also recognize that use of the new CBSA delineations will result in reduced payments to some IPFs and increased payments to other IPFs, due to changes in wage index values. Approximately 23.3 percent of IPFs will experience a decrease in wage index values due to CBSA changes, while 12.3 percent of IPFs will experience an increase in wage index values due to CBSA changes. The remaining 64.4 percent of IPFs will experience no change in their wage index values. While the wage index CBSA changes will be implemented in a budget-neutral fashion, the distributional effects of these CBSA changes appear to affect Start Printed Page 46689rural IPFs in particular; column 5 in Table 29 in section VIII. of this final rule shows that rural providers overall are anticipated to experience payment reductions of 0.2 percent, with for-profit rural psychiatric hospitals anticipated to experience the greatest reduction of 0.5 percent.

We believe that it will be appropriate to provide for a transition period to mitigate any negative impacts on facilities that experience reduced payments as a result of our adopting the new OMB CBSA delineations. Therefore, we are implementing these CBSA changes using a 1-year transition with a blended wage index for all providers. For FY 2016, the wage index for each provider will consist of a blend of 50 percent of the FY 2016 IPF wage index using the current OMB delineations and 50 percent of the FY 2016 IPF wage index using the new OMB delineations. This results in an average of the two values. The FY 2017 IPF PPS wage index and subsequent IPF PPS wage indices will be based solely on the new OMB CBSA delineations. We believe a 1-year transition strikes an appropriate balance between ensuring that IPF PPS payments are as accurate and stable as possible while giving IPFs time to adjust to the new CBSA delineations. The final FY 2016 IPF PPS transitional wage index is located on the CMS Web site at http://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientPsychFacilPPS/​WageIndex.html.

Comment: We received one comment on the proposed transitional wage index, supporting the new OMB delineations, but stating that a 2-year transition was too short given the impact on providers. This commenter asked for 3-year transition instead of a 2-year transition.

Response: We appreciate the commenter's support for the new OMB delineations, but note that we proposed a 1-year transition, not a 2-year transition. We believe that our proposed 1-year transition is sufficient to allow providers to adjust to changes resulting from the new OMB delineations. A 1-year transition is also consistent with how the new OMB delineations have been handled in other Medicare benefits. Therefore, we are implementing the FY 2016 IPF PPS Wage Index as proposed, with a 1-year transition.

d. Adjustment for Rural Location and Phase Out the Rural Adjustment for IPFs Losing Their Rural Adjustment Due to CBSA Changes

In the November 2004 IPF PPS final rule, we provided a 17 percent payment adjustment for IPFs located in a rural area. This adjustment was based on the regression analysis, which indicated that the per diem cost of rural facilities was 17 percent higher than that of urban facilities after accounting for the influence of the other variables included in the regression. For FY 2016, we will continue to apply a 17 percent payment adjustment for IPFs located in a rural area as defined at § 412.64(b)(1)(ii)(C). A complete discussion of the adjustment for rural locations appears in the November 2004 IPF PPS final rule (69 FR 66954).

As noted in section III.D.1.c. of this final rule, we are adopting OMB updates to CBSA delineations. Adoption of the updated CBSAs will change the status of 37 IPF providers currently designated as “rural” to “urban” for FY 2016 and subsequent fiscal years. As such, these 37 newly urban providers will no longer receive the 17 percent rural adjustment.

While 34 of these 37 rural IPFs that will be designated as urban under the new CBSA delineations will experience an increase in their wage index value, all 37 of these IPFs will lose the 17 percent rural adjustment. Consistent with the transition policy adopted for Inpatient Rehabilitation Facilities (IRFs) in FY 2006 (70 FR 47923 through 47927), we considered the appropriateness of applying a 3-year phase-out of the rural adjustment for IPFs located in rural counties that will become urban under the new OMB delineations, given the potentially significant payment impacts for these IPFs. We believe that a phase-out of the rural adjustment transition period for these 37 IPFs specifically is appropriate because we expect these IPFs will experience a steeper and more abrupt reduction in their payments compared to other IPFs.

Therefore, in addition to the 1-year wage index transition policy noted above, we are finalizing a budget-neutral 3-year phase-out of the rural adjustment for existing FY 2015 rural IPFs that will become urban in FY 2016 and that experience a loss in payments due to changes from the new CBSA delineations. Accordingly, the incremental steps needed to reduce the impact of the loss of the FY 2015 rural adjustment of 17 percent will be taken over FYs 2016, 2017 and 2018. This policy will allow rural IPFs that will be classified as urban in FY 2016 to receive two-thirds of the 2015 rural adjustment for FY 2016, as well as the blended wage index. For FY 2017, these IPFs will receive the full FY 2017 wage index and one-third of the FY 2015 rural adjustment. For FY 2018, these IPFs will receive the full FY 2018 wage index without a rural adjustment. We believe a 3-year budget-neutral phase-out of the rural adjustment for IPFs that transition from rural to urban status under the new CBSA delineations will best accomplish the goals of mitigating the loss of the rural adjustment for existing FY 2015 rural IPFs. The purpose of the gradual phase-out of the rural adjustment for these providers is to alleviate the significant payment implications for existing rural IPFs that may need time to adjust to the loss of their FY 2015 rural payment adjustment or that experience a reduction in payments solely because of this re-designation. As stated, this policy is specifically for rural IPFs that become urban in FY 2016. We are not implementing a transition policy for urban IPFs that become rural in FY 2016 because these IPFs will receive the full rural adjustment of 17 percent beginning October 1, 2015.

For the reasons discussed, we are implementing a 3-year budget-neutral phase-out of the rural adjustment for the IPFs that during FY 2015 were designated as rural and for FY 2016 are designated as urban under the new CBSA system. This is in addition to our implementation of a 1-year blended wage index for all IPFs. We believe that the incremental reduction of the FY 2015 rural adjustment will be appropriate to mitigate a significant reduction in payment. We considered alternative timeframes for phasing out the rural adjustment for IPFs which will transition from rural to urban status in FY 2016, but believe that a 3-year budget-neutral phase-out of the rural adjustment will appropriately mitigate the adverse payment impacts for existing FY 2015 rural IPFs that will be designated as urban IPFs in FY 2016, while also ensuring that payment rates for these providers are set accurately and appropriately.

Comment: We received one comment asking that we phase out the rural adjustment for the 37 affected providers over 4 years rather than 3 years. This commenter was concerned that affected providers would be significantly impacted by the loss of the rural adjustment.

Response: We appreciate the commenter's request, but as noted above, we considered alternate timeframes for phasing out the rural adjustment. We believe that a 3-year phase-out balances the need for us to pay accurately and appropriately with sufficient time for providers to adjust to, and to mitigate the adverse payment effect. A 3-year phase-out is also consistent with the policy we followed in FY 2006 for Inpatient Rehabilitation Start Printed Page 46690Facilities. As such, we are finalizing the rural adjustment phase-out for these 37 IPFs as proposed, with a 3-year phase out.

e. Budget Neutrality Adjustment

Changes to the wage index are made in a budget-neutral manner so that updates do not increase expenditures. Therefore, for FY 2016, we will continue to apply a budget-neutrality adjustment in accordance with our existing budget-neutrality policy. This policy requires us to estimate the total amount of IPF PPS payments for FY 2016 using the labor-related share and the wage indices from FY 2015 divided by the total estimated IPF PPS payments for FY 2016 using the labor-related share and wage indices from FY 2016. The estimated payments are based on FY 2014 IPF claims, inflated to the appropriate FY. This quotient is the wage index budget-neutrality factor, and it is applied in the update of the Federal per diem base rate for FY 2016 in addition to the market basket described in section III.A. of this final rule. The final wage index budget-neutrality factor for FY 2016 is 1.0041. We received no comments on the wage index budget-neutrality factor for FY 2016.

2. Teaching Adjustment

In the November 2004 IPF PPS final rule, we implemented regulations at § 412.424(d)(1)(iii) to establish a facility-level adjustment for IPFs that are, or are part of, teaching hospitals. The teaching adjustment accounts for the higher indirect operating costs experienced by hospitals that participate in graduate medical education (GME) programs. The payment adjustments are made based on the ratio of the number of full-time equivalent (FTE) interns and residents training in the IPF and the IPF's average daily census (ADC).

Medicare makes direct 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 a PPS, and those paid under the TEFRA rate-of-increase limits. These direct GME payments are made separately from payments for hospital operating costs and are not part of the IPF PPS. The direct GME payments do not address the estimated higher indirect operating costs teaching hospitals may face.

The results of the regression analysis of FY 2002 IPF data established the basis for the payment adjustments included in the November 2004 IPF PPS final rule. The results showed that the indirect teaching cost variable is significant in explaining the higher costs of IPFs that have teaching programs. We calculated the teaching adjustment based on the IPF's “teaching variable,” which is one plus the ratio of the number of FTE residents training in the IPF (subject to limitations described below) to the IPF's ADC.

We established the teaching adjustment in a manner that limited the incentives for IPFs to add FTE residents for the purpose of increasing their teaching adjustment. We imposed a cap on the number of FTE residents that may be counted for purposes of calculating the teaching adjustment. The cap limits the number of FTE residents that teaching IPFs may count for the purpose of calculating the IPF PPS teaching adjustment, not the number of residents teaching institutions can hire or train. We calculated the number of FTE residents that trained in the IPF during a “base year” and used that FTE resident number as the cap. An IPF's FTE resident cap is ultimately determined based on the final settlement of the IPF's most recent cost report filed before November 15, 2004 (that is, the publication date of the IPF PPS final rule). A complete discussion on the temporary adjustment to the FTE cap to reflect residents added due to hospital closure and by residency program appears in the January 27, 2011 IPF PPS proposed rule (76 FR 5018 through 5020) and the May 6, 2011 IPF PPS final rule (76 FR 26453 through 26456).

In the regression analysis, the logarithm of the teaching variable had a coefficient value of 0.5150. We converted this cost effect to a teaching payment adjustment by treating the regression coefficient as an exponent and raising the teaching variable to a power equal to the coefficient value. We note that the coefficient value of 0.5150 was based on the regression analysis holding all other components of the payment system constant. A complete discussion of how the teaching adjustment was calculated appears in the November 2004 IPF PPS final rule (69 FR 66954 through 66957) and the May 2008 IPF PPS notice (73 FR 25721). As with other adjustment factors derived through the regression analysis, we do not plan to rerun the teaching adjustment factors in the regression analysis until we more fully analyze IPF PPS data. Therefore, in this final rule, for FY 2016, we will continue to retain the coefficient value of 0.5150 for the teaching adjustment to the Federal per diem base rate.

3. Cost of Living Adjustment for IPFs Located in Alaska and Hawaii

The IPF PPS includes a payment adjustment for IPFs located in Alaska and Hawaii based upon the county in which the IPF is located. As we explained in the November 2004 IPF PPS final rule, the FY 2002 data demonstrated that IPFs in Alaska and Hawaii had per diem costs that were disproportionately higher than other IPFs. Other Medicare PPSs (for example, the IPPS and LTCH PPS) adopted a cost of living adjustment (COLA) to account for the cost differential of care furnished in Alaska and Hawaii.

We analyzed the effect of applying a COLA to payments for IPFs located in Alaska and Hawaii. The results of our analysis demonstrated that a COLA for IPFs located in Alaska and Hawaii would improve payment equity for these facilities. As a result of this analysis, we provided a COLA in the November 2004 IPF PPS final rule.

A COLA for IPFs located in Alaska and Hawaii is made by multiplying the nonlabor-related portion of the Federal per diem base rate by the applicable COLA factor based on the COLA area in which the IPF is located.

The COLA factors are published on the Office of Personnel Management (OPM) Web site (http://www.opm.gov/​oca/​cola/​rates.asp).

We note that the COLA areas for Alaska are not defined by county as are the COLA areas for Hawaii. In 5 CFR 591.207, the OPM established the following COLA areas:

  • City of Anchorage, and 80-kilometer (50-mile) radius by road, as measured from the Federal courthouse;
  • City of Fairbanks, and 80-kilometer (50-mile) radius by road, as measured from the Federal courthouse;
  • City of Juneau, and 80-kilometer (50-mile) radius by road, as measured from the Federal courthouse;
  • Rest of the State of Alaska.

As stated in the November 2004 IPF PPS final rule, we update the COLA factors according to updates established by the OPM. However, sections 1911 through 1919 of the Nonforeign Area Retirement Equity Assurance Act, as contained in subtitle B of title XIX of the National Defense Authorization Act (NDAA) for Fiscal Year 2010 (Pub. L. 111-84, October 28, 2009), transitions the Alaska and Hawaii COLAs to locality pay. Under section 1914 of NDAA, locality pay is being phased in over a 3-year period beginning in January 2010, with COLA rates frozen as of the date of enactment, October 28, 2009, and then proportionately reduced to reflect the phase-in of locality pay.Start Printed Page 46691

When we published the proposed COLA factors in the January 2011 IPF PPS proposed rule (76 FR 4998), we inadvertently selected the FY 2010 COLA rates which had been reduced to account for the phase-in of locality pay. We did not intend to propose the reduced COLA rates because that would have understated the adjustment. Since the 2009 COLA rates did not reflect the phase-in of locality pay, we finalized the FY 2009 COLA rates for RY 2010 through RY 2014.

In the FY 2013 IPPS/LTCH final rule (77 FR 53700 through 53701), we established a methodology for FY 2014 to update the COLA factors for Alaska and Hawaii. Under that methodology, we use a comparison of the growth in the Consumer Price Indices (CPIs) in Anchorage, Alaska and Honolulu, Hawaii relative to the growth in the overall CPI as published by the Bureau of Labor Statistics (BLS) to update the COLA factors for all areas in Alaska and Hawaii, respectively. As discussed in the FY 2013 IPPS/LTCH proposed rule (77 FR 28145), because BLS publishes CPI data for only Anchorage, Alaska and Honolulu, Hawaii, our methodology for updating the COLA factors uses a comparison of the growth in the CPIs for those cities relative to the growth in the overall CPI to update the COLA factors for all areas in Alaska and Hawaii, respectively. We believe that the relative price differences between these cities and the United States (as measured by the CPIs mentioned above) are generally appropriate proxies for the relative price differences between the “other areas” of Alaska and Hawaii and the United States.

The CPIs for “All Items” that BLS publishes for Anchorage, Alaska, Honolulu, Hawaii, and for the average U.S. city are based on a different mix of commodities and services than is reflected in the nonlabor-related share of the IPPS market basket. As such, under the methodology we established to update the COLA factors, we calculated a “reweighted CPI” using the CPI for commodities and the CPI for services for each of the geographic areas to mirror the composition of the IPPS market basket nonlabor-related share. The current composition of BLS' CPI for “All Items” for all of the respective areas is approximately 40 percent commodities and 60 percent services. However, the nonlabor-related share of the IPPS market basket is comprised of 60 percent commodities and 40 percent services. Therefore, under the methodology established for FY 2014 in the FY 2013 IPPS/LTCH PPS final rule, we created reweighted indexes for Anchorage, Alaska, Honolulu, Hawaii, and the average U.S. city using the respective CPI commodities index and CPI services index and applying the approximate 60/40 weights from the IPPS market basket. This approach is appropriate because we would continue to make a COLA for hospitals located in Alaska and Hawaii by multiplying the nonlabor-related portion of the standardized amount by a COLA factor.

Under the COLA factor update methodology established in the FY 2014 IPPS/LTCH final rule, we adjust payments made to hospitals located in Alaska and Hawaii by incorporating a 25-percent cap on the CPI-updated COLA factors. We note that OPM's COLA factors were calculated with a statutorily mandated cap of 25 percent, and since at least 1984, we have exercised our discretionary authority to adjust Alaska and Hawaii payments by incorporating this cap. In keeping with this historical policy, we continue to use such a cap because our CPI-updated COLA factors use the 2009 OPM COLA factors as a basis.

In FY 2015 IPF PPS rulemaking, we adopted the same methodology for the COLA factors applied under the IPPS because IPFs are hospitals with a similar mix of commodities and services. We think it is appropriate to have a consistent policy approach with that of other hospitals in Alaska and Hawaii. Therefore, in the FY 2015 IPF PPS final rule, we adopted the cost of living adjustment factors shown in the Addendum for IPFs located in Alaska and Hawaii. Under IPPS COLA policy, the COLA updates are determined every four years, when the IPPS market basket is rebased. Since the IPPS COLA factors were last updated in FY 2014, they are not scheduled to be updated again until FY 2018. As such, we will continue using the existing IPF PPS COLA factors in effect in FY 2015 for FY 2016. The IPF PPS COLA factors for FY 2016 are shown in the Addendum of this final rule.

4. Adjustment for IPFs With a Qualifying Emergency Department (ED)

The IPF PPS includes a facility-level adjustment for IPFs with qualifying EDs. We provide an adjustment to the Federal per diem base rate to account for the costs associated with maintaining a full-service ED. The adjustment is intended to account for ED costs incurred by a freestanding psychiatric hospital with a qualifying ED or a distinct part psychiatric unit of an acute care hospital or a CAH, for preadmission services otherwise payable under the Medicare Outpatient Prospective Payment System (OPPS), furnished to a beneficiary on the date of the beneficiary's admission to the hospital and during the day immediately preceding the date of admission to the IPF (see § 413.40(c)(2)), and the overhead cost of maintaining the ED. This payment is a facility-level adjustment that applies to all IPF admissions (with one exception described below), regardless of whether a particular patient receives preadmission services in the hospital's ED.

The ED adjustment is incorporated into the variable per diem adjustment for the first day of each stay for IPFs with a qualifying ED. That is, IPFs with a qualifying ED receive an adjustment factor of 1.31 as the variable per diem adjustment for day 1 of each stay. If an IPF does not have a qualifying ED, it receives an adjustment factor of 1.19 as the variable per diem adjustment for day 1 of each patient stay.

The ED adjustment is made on every qualifying claim except as described below. As specified in § 412.424(d)(1)(v)(B), the ED adjustment is not made when a patient is discharged from an acute care hospital or CAH and admitted to the same hospital's or CAH's psychiatric unit. We clarified in the November 2004 IPF PPS final rule (69 FR 66960) that an ED adjustment is not made in this case because the costs associated with ED services are reflected in the DRG payment to the acute care hospital or through the reasonable cost payment made to the CAH.

Therefore, when patients are discharged from an acute care hospital or CAH and admitted to the same hospital or CAH's psychiatric unit, the IPF receives the 1.19 adjustment factor as the variable per diem adjustment for the first day of the patient's stay in the IPF.

We did not propose any changes to the ED adjustment. For FY 2016, we will continue to retain the 1.31 adjustment factor for IPFs with qualifying EDs. A complete discussion of the steps involved in the calculation of the ED adjustment factor appears in the November 2004 IPF PPS final rule (69 FR 66959 through 66960) and the May 2006 IPF PPS final rule (71 FR 27070 through 27072).

E. Other Payment Adjustments and Policies

1. Outlier Payment Overview

The IPF PPS includes an outlier adjustment to promote access to IPF care for those patients who require expensive care and to limit the financial risk of IPFs treating unusually costly patients. In the November 2004 IPF PPS Start Printed Page 46692final rule, we implemented regulations at § 412.424(d)(3)(i) to provide a per-case payment for IPF stays that are extraordinarily costly. Providing additional payments to IPFs for extremely costly cases strongly improves the accuracy of the IPF PPS in determining resource costs at the patient and facility level. These additional payments reduce the financial losses that would otherwise be incurred in treating patients who require more costly care and, therefore, reduce the incentives for IPFs to under-serve these patients.

We make outlier payments for discharges in which an IPF's estimated total cost for a case exceeds a fixed dollar loss threshold amount (multiplied by the IPF's facility-level adjustments) plus the Federal per diem payment amount for the case.

In instances when the case qualifies for an outlier payment, we pay 80 percent of the difference between the estimated cost for the case and the adjusted threshold amount for days 1 through 9 of the stay (consistent with the median LOS for IPFs in FY 2002), and 60 percent of the difference for day 10 and thereafter. We established the 80 percent and 60 percent loss sharing ratios because we were concerned that a single ratio established at 80 percent (like other Medicare PPSs) might provide an incentive under the IPF per diem payment system to increase LOS in order to receive additional payments.

After establishing the loss sharing ratios, we determined the current FY 2015 fixed dollar loss threshold amount through payment simulations designed to compute a dollar loss beyond which payments are estimated to meet the 2 percent outlier spending target. Each year when we update the IPF PPS, we simulate payments using the latest available data to compute the fixed dollar loss threshold so that outlier payments represent 2 percent of total projected IPF PPS payments.

2. Update to the Outlier Fixed Dollar Loss Threshold Amount

In accordance with the update methodology described in § 412.428(d), we are updating the fixed dollar loss threshold amount used under the IPF PPS outlier policy. Based on the regression analysis and payment simulations used to develop the IPF PPS, we established a 2 percent outlier policy which strikes an appropriate balance between protecting IPFs from extraordinarily costly cases while ensuring the adequacy of the Federal per diem base rate for all other cases that are not outlier cases.

Based on an analysis of the latest available data (that is, the March 2015 update of FY 2014 IPF claims) and rate increases, we believe it is necessary to update the fixed dollar loss threshold amount in order to maintain an outlier percentage that equals 2 percent of total estimated IPF PPS payments. To update the IPF outlier threshold amount for FY 2016, we used FY 2014 claims data and the same methodology that we used to set the initial outlier threshold amount in the May 2006 IPF PPS final rule (71 FR 27072 and 27073), which is also the same methodology that we used to update the outlier threshold amounts for years 2008 through 2015. Based on an analysis of these updated data, we estimate that IPF outlier payments as a percentage of total estimated payments are approximately 2.2 percent in FY 2015. Therefore, we will update the outlier threshold amount to $9,580 to maintain estimated outlier payments at 2 percent of total estimated aggregate IPF payments for FY 2016.

Comment: One commenter wrote that the increase in the outlier threshold would result in significant losses for hospitals with a high percentage of outlier cases, and suggested that CMS transition to the higher threshold over 2 years.

Response: Our longstanding policy is to maintain a 2 percent outlier threshold, which would not be possible if we transitioned to the FY 2016 outlier threshold. We note that when we reanalyzed the outlier data for this final rule using the March 2015 update of the 2014 MedPAR claims, the final outlier threshold was lower than the proposed outlier threshold ($9,825).

3. Update to IPF Cost-to-Charge Ratio Ceilings

Under the IPF PPS, an outlier payment is made if an IPF's cost for a stay exceeds a fixed dollar loss threshold amount plus the IPF PPS amount. In order to establish an IPF's cost for a particular case, we multiply the IPF's reported charges on the discharge bill by its overall cost-to-charge ratio (CCR). This approach to determining an IPF's cost is consistent with the approach used under the IPPS and other PPSs. In the June 2003 IPPS final rule (68 FR 34494), we implemented changes to the IPPS policy used to determine CCRs for acute care hospitals because we became aware that payment vulnerabilities resulted in inappropriate outlier payments. Under the IPPS, we established a statistical measure of accuracy for CCRs in order to ensure that aberrant CCR data did not result in inappropriate outlier payments.

As we indicated in the November 2004 IPF PPS final rule (69 FR 66961), because we believe that the IPF outlier policy is susceptible to the same payment vulnerabilities as the IPPS, we adopted a method to ensure the statistical accuracy of CCRs under the IPF PPS. Specifically, we adopted the following procedure in the November 2004 IPF PPS final rule: We calculated 2 national ceilings, one for IPFs located in rural areas and one for IPFs located in urban areas. We computed the ceilings by first calculating the national average and the standard deviation of the CCR for both urban and rural IPFs using the most recent CCRs entered in the CY 2015 Provider Specific File.

To determine the rural and urban ceilings, we multiplied each of the standard deviations by 3 and added the result to the appropriate national CCR average (either rural or urban). The upper threshold CCR for IPFs in FY 2016 is 1.9041 for rural IPFs, and 1.7339 for urban IPFs, based on CBSA-based geographic designations. If an IPF's CCR is above the applicable ceiling, the ratio is considered statistically inaccurate, and we assign the appropriate national (either rural or urban) median CCR to the IPF.

We apply the national CCRs to the following situations:

  • New IPFs that have not yet submitted their first Medicare cost report. We continue to use these national CCRs until the facility's actual CCR can be computed using the first tentatively or final settled cost report.
  • IPFs whose overall CCR is in excess of 3 standard deviations above the corresponding national geometric mean (that is, above the ceiling).
  • Other IPFs for which the MAC obtains inaccurate or incomplete data with which to calculate a CCR.

We did not propose any changes to the application of the national CCRs or to the procedures for updating the CCR ceilings in FY 2016. However, we are updating the FY 2016 national median and ceiling CCRs for urban and rural IPFs based on the CCRs entered in the latest available IPF PPS Provider Specific File. Specifically, for FY 2016, and to be used in each of the 3 situations listed above, using the most recent CCRs entered in the CY 2015 Provider Specific File we estimate the national median CCR of 0.6220 for rural IPFs and the national median CCR of 0.4650 for urban IPFs. These calculations are based on the IPF's location (either urban or rural) using the CBSA-based geographic designations.

A complete discussion regarding the national median CCRs appears in the Start Printed Page 46693November 2004 IPF PPS final rule (69 FR 66961 through 66964).

IV. Other Payment Policy Issues

A. ICD-10-CM and ICD-10-PCS Implementation

We remind IPF providers that we are implementing the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) as the HIPAA designated code set for reporting diseases, injuries, impairments, other health related problems, their manifestations, and causes of injury as of October 1, 2015. Below is a brief history of key activities leading to the October 1, 2015 implementation date.

In the Standards for Electronic Transactions final rule, published in the Federal Register on August 17, 2000 (65 FR 50312), the Department adopted the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) as the HIPAA designated code set for reporting diseases, injuries, impairments, other health related problems, their manifestations, and causes of injury. Therefore, on January 1, 2005 when the IPF PPS began, we used ICD-9-CM as the designated code set for the IPF PPS. IPF claims with a principal diagnosis included in Chapter Five of the ICD-9-CM are paid the Federal per diem base rate and all other applicable adjustments, including any applicable DRG adjustment.

Together with the rest of the healthcare industry, we were scheduled to implement the 10th revision of the ICD coding scheme, that is, ICD-10-CM, on October 1, 2014. Hence, in the FY 2014 IPF PPS final rule (78 FR 46741-46742), we finalized a policy that ICD-10-CM codes will be used in IPF PPS.

On April 1, 2014, the Protecting Access to Medicare Act of 2014 (PAMA) (Pub. L. 113-93) was enacted. Section 212 of PAMA, titled “Delay in Transition from ICD-9 to ICD-10 Code Sets,” provided that “[t]he Secretary of Health and Human Services may not, prior to October 1, 2015, adopt ICD-10 code sets as the standard for code sets under section 1173(c) of the Social Security Act (42 U.S.C. 1320d-2(c)) and section 162.1002 of title 45, Code of Federal Regulations.” On May 1, 2014, the Secretary announced that HHS expected to issue an interim final rule that would require use of ICD-10-CM beginning October 1, 2015 and would continue to require use of ICD-9-CM through September 30, 2015. This announcement is available on the CMS Web site at http://cms.gov/​Medicare/​Coding/​ICD10/​index.html. HHS finalized the new compliance date of October 1, 2015 for ICD-10-CM and ICD-10-PCS in an August 4, 2014 final rule titled “Administrative Simplification: Change to the Compliance Date for the International Classification of Diseases, 10th Revision (ICD-10-CM and ICD-10-PCS)” (79 FR 45128). This rule also requires HIPAA covered entities to continue to use the ICD-9-CM code set through September 30, 2015. Therefore, beginning October 1, 2015, we require use of the ICD-10-CM and ICD-10-PCS codes for reporting the MS-DRG and comorbidity adjustment factors for IPF services.

Every year, changes to the ICD-10-CM and the ICD-10-PCS coding system will be addressed in the IPPS proposed and final rules. The changes to the codes are effective October 1 of each year and must be used by acute care hospitals as well as other providers to report diagnostic and procedure information. The IPF PPS has always incorporated ICD-9-CM coding changes made in the annual IPPS update and will continue to do so for the ICD-10-CM and ICD-10-PCS coding changes. We will continue to publish coding changes in a Transmittal/Change Request, similar to how coding changes are announced by the IPPS and LTCH PPS. The coding changes relevant to the IPF PPS are also published in the IPF PPS proposed and final rules, or in IPF PPS update notices.

In § 412.428(e), we indicate that we will publish information pertaining to the annual update for the IPF PPS, which includes describing the ICD-9-CM coding changes and DRG classification changes discussed in the annual update to the hospital IPPS regulations. Because ICD-10-CM will be implemented on October 1, 2015, we need to update the regulation language at § 412.428(e) to refer to ICD-10-CM, rather than ICD-9-CM. Therefore, we are revising § 412.428(e) to state that the information we will publish annually in the Federal Register to describe IPF PPS updates would describe the ICD-10-CM coding changes and DRG classification changes discussed in the annual update to the hospital inpatient prospective payment system regulations.

In the FY 2015 IPF PPS final rule (79 FR 45945 through 46946), the MS-DRGs were converted so that the MS-DRG assignment logic uses ICD-10-CM/PCS codes directly. When an IPF submits a claim for discharges, the ICD-10-CM/PCS diagnosis and procedure codes will be assigned to the correct MS-DRG. In the FY 2015 IPF PPS final rule, we also identified the ICD-10-CM/PCS codes that are eligible for comorbidity payment adjustments under the IPF PPS (79 FR 45947 through 45955).

The ICD-10-CM guidelines are updated each year along with the ICD-10-CM code set. To find the annual coding guidelines, go to CDC's Web site at http://www.cdc.gov/​nchs/​icd/​icd10cm.htm or the annual ICD-10-CM updates posted on the CMS ICD-10 Web site at http://www.cms.gov/​Medicare/​Coding/​ICD10/​index.html.

We received no comments on the proposed revision to the regulation text at § 412.428(e), and are implementing it as proposed. We received 2 comments on ICD-10-CM/PCS issues.

Comment: One commenter asked that CMS remain receptive to comments related to ICD-10-CM/PCS and conversion issues as health care staff become more familiar with the new coding. The other commenter was pleased that CMS had provided end-to-end testing, but noted that while claims submission was fairly seamless, receiving a remittance was less consistent. This commenter suggested that CMS allow IPFs to submit a larger number of varied claims and that we complete additional testing on the Medicare Administrative Contractor's ability to issue remittances timely.

Response: We thank the commenters for their thoughts and suggestions. While these comments are outside the scope of this rule, we have shared them with the areas within CMS that handle ICD-10-CM/PCS conversion and end-to-end testing.

B. Status of Future IPF PPS Refinements

For RY 2012, we identified several areas of concern for future refinement, and we invited comments on these issues in our RY 2012 proposed and final rules. For further discussion of these issues and to review the public comments, we refer readers to the RY 2012 IPF PPS proposed rule (76 FR 4998) and final rule (76 FR 26432).

We have delayed making refinements to the IPF PPS until we have completed a thorough analysis of IPF PPS data on which to base those refinements. Specifically, we will delay updating the adjustment factors derived from the regression analysis until we have IPF PPS data that include as much information as possible regarding the patient-level characteristics of the population that each IPF serves. We have begun the necessary analysis to better understand IPF industry practices so that we may refine the IPF PPS in the future, as appropriate.

IPF Covered Services

The IPF PPS established the Federal per diem base rate for each patient day in an IPF from the national average routine operating, ancillary, and capital Start Printed Page 46694costs. Preliminary analysis reveals that in 2012 to 2013, over 20 percent of IPF stays show no reported ancillary costs, such as laboratory and drug costs, in cost reports or charges on claims. The majority of these stays with zero ancillary costs or charges were in for-profit, free-standing IPF hospitals. We would expect that patients admitted to an IPF would undergo laboratory testing as part of the admission history and physical. We would also expect that most patients requiring hospitalization for active psychiatric treatment would need drugs. Therefore, we were surprised when the analysis showed such a large number of stays reporting no laboratory services and no drugs were provided throughout the hospitalization. Until further analysis is completed, we can only surmise that the stays did not require ancillaries and therefore, were not provided, or that the ancillary services were separately billed.

We remind the industry that we pay only the inpatient psychiatric facility for services furnished to a Medicare beneficiary who is an inpatient of that inpatient psychiatric facility, except for certain professional services, and that payments made under this subpart are payments in full for all inpatient hospital services, provided directly or under arrangement (see 42 CFR 412.404(d)), as specified in 42 CFR 409.10.

The covered services specified in § 409.10(a), which apply to IPFs, include the following: bed and board; nursing services and other related services; use of hospital or CAH facilities; medical social services; drugs, biologicals, supplies, appliances, and equipment; certain other diagnostic or therapeutic services; medical or surgical services provided by certain interns or residents-in-training; and transportation services, including transport by ambulance.

Only the professional services listed in § 409.10(b) can be separately billed for a Medicare beneficiary who is an inpatient at an IPF, including services of physicians, physician assistants, nurse practitioners, clinical nurse specialists, certified nurse mid-wives, anesthetists, and qualified psychologists. (See § 409.10(b) for specifics on how these professions and services are defined. These regulations are available online at the electronic Code of Federal Regulations, at http://www.ecfr.gov/​cgi-bin/​text-idx?​c=​ecfr&​tpl=​%2Findex.tpl.)

Ancillary costs such as laboratory costs and drugs are already included in the Medicare IPF PPS per diem payment and should not be unbundled and billed separately to Medicare. We expect that the IPF would be recording the cost of all drugs provided to its Medicare patients on its Medicare cost reports, and reporting charges for those drugs on its Medicare claims. We expect that when an IPF contracts with an outside laboratory to provide services to its Medicare inpatients, the IPF would instruct the laboratory to bill the IPF and not to bill Medicare.

Similarly, drugs provided to IPF Medicare inpatients where Medicare is the primary payer should not be billed to Part D or to other insurers.

We are continuing to analyze claims and cost report data that do not include ancillary charges or costs, and will be sharing our findings with the Center for Program Integrity and the Office of Financial Management for further investigation, as the results warrant. Our refinement analysis is dependent on recent precise data for costs, including ancillary costs. We will continue to collect these data until an accurate refinement analysis can be performed. Therefore, we are not making refinements in this final rule. Once we have gathered timely and accurate data, we will analyze that data with the expectation of a refinement update in future rulemaking. We invite comments on this issue of zero ancillary costs to better understand industry practices.

Comment: We received two comments on this section, with one commenter asking that CMS engage stakeholders in the policy development process for refinements, and that CMS consider any changes carefully, to preserve access to IPF services for vulnerable beneficiaries. A second commenter was concerned that CMS lacks accurate cost data for refinements, particularly if unbundling is occurring with ancillary costs. This commenter also cited findings by the Medicare Payment Advisory Commission which also noted concerns about limited IPF data, and which suggested CMS consider using an assessment tool with IPF patients for future refinements. This commenter suggested that CMS examine the tools already in use in IPFs to gauge their effectiveness in explaining differences in patient needs and their ability to add data collection at minimal cost to providers.

Response: We thank the commenters for their comments, and will consider them as we undertake IPF refinements in future rulemaking.

V. Inpatient Psychiatric Facilities Quality Reporting (IPFQR) Program

A. Background

1. Statutory Authority

Section 1886(s)(4) of the Act, as added and amended by sections 3401(f) and 10322(a) of the Affordable Care Act, requires the Secretary to implement a quality reporting program for inpatient psychiatric hospitals and psychiatric units. Section 1886(s)(4)(A)(i) of the Act requires that, for FY 2014 [4] and each subsequent fiscal year, the Secretary must reduce any annual update to a standard federal rate for discharges occurring during the fiscal year by 2.0 percentage points for any inpatient psychiatric hospital or psychiatric unit that does not comply with quality data submission requirements with respect to an applicable fiscal year.

As provided in section 1886(s)(4)(A)(ii) of the Act, the application of the reduction for failure to report under section 1886(s)(4)(A)(i) of the Act may result in an annual update of less than 0.0 percent for a fiscal year, and may result in payment rates under section 1886(s)(1) of the Act being less than the payment rates for the preceding year. In addition, section 1886(s)(4)(B) of the Act requires that the application of the reduction to a standard Federal rate update be noncumulative across fiscal years. Thus, any reduction applied under section 1886(s)(4)(A) of the Act will apply only with respect to the fiscal year rate involved and the Secretary may not take into account the reduction in computing the payment amount under the system described in section 1886(s)(1) of the Act for subsequent years.

Section 1886(s)(4)(C) of the Act requires that, for FY 2014 (October 1, 2013, through September 30, 2014) and each subsequent year, each psychiatric hospital and psychiatric unit must submit to the Secretary data on quality measures as specified by the Secretary. The data must be submitted in a form and manner and at a time specified by the Secretary. Under section 1886(s)(4)(D)(i) of the Act, unless the Start Printed Page 46695exception of subclause (ii) applies, measures selected for the quality reporting program must have been endorsed by the entity with a contract under section 1890(a) of the Act. The National Quality Forum (NQF) currently holds this contract.

Section 1886(s)(4)(D)(ii) of the Act provides an exception to the requirement for NQF endorsement of measures: In the case of a specified area or medical topic determined appropriate by the Secretary for which a feasible and practical measure has not been endorsed by the entity with a contract under section 1890(a) of the Act, the Secretary may specify a measure that is not so endorsed as long as due consideration is given to measures that have been endorsed or adopted by a consensus organization identified by the Secretary. Pursuant to section 1886(s)(4)(D)(iii) of the Act, the Secretary must publish the measures applicable to the FY 2014 IPFQR Program no later than October 1, 2012.

Section 1886(s)(4)(E) of the Act requires the Secretary to establish procedures for making public the data submitted by inpatient psychiatric hospitals and psychiatric units under the IPFQR Program. These procedures must ensure that a facility has the opportunity to review its data prior to the data being made public. The Secretary must report quality measures that relate to services furnished by the psychiatric hospitals and units on the CMS Web site.

2. Covered Entities

In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53645), we established that the IPFQR Program's quality reporting requirements cover those psychiatric hospitals and psychiatric units paid under Medicare's IPF PPS (42 CFR 412.404(b)). Generally, psychiatric hospitals and psychiatric units within acute care and critical access hospitals that treat Medicare patients are paid under the IPF PPS. Consistent with prior rules, we continue to use the term “inpatient psychiatric facility” (IPF) to refer to both inpatient psychiatric hospitals and psychiatric units. This usage follows the terminology in our IPF PPS regulations at § 412.402. For more information on covered entities, we refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 53645).

3. Considerations in Selecting Quality Measures

Our objective in selecting quality measures is to balance the need for information on the full spectrum of care delivery and the need to minimize the burden of data collection and reporting. We have focused on measures that evaluate critical processes of care that have significant impact on patient outcomes and support CMS and HHS priorities for improved quality and efficiency of care provided by IPFs. We refer readers to section 4.a. of the FY 2013 IPPS/LTCH PPS final rule (77 FR 53645 through 53646) for a detailed discussion of the considerations taken into account in selecting quality measures.

Before being proposed for inclusion in the IPFQR Program, measures are placed on a list of measures under consideration, which is published annually by December 1 on behalf of CMS by the NQF. In compliance with section 1890A(a)(2) of the Act, measures proposed for the IPFQR Program were included in 2 publicly available documents: “List of Measures under Consideration for December 1, 2013,” and “List of Measures under Consideration for December 1, 2014” (http://www.qualityforum.org/​Setting_​Priorities/​Partnership/​Measure_​Applications_​Partnership.aspx). The Measure Applications Partnership (MAP), a multi-stakeholder group convened by the NQF, reviews the measures under consideration for the IPFQR Program, among other Federal programs, and provides input on those measures to the Secretary. The MAP's 2014 and 2015 recommendations for quality measures under consideration are captured in the following documents: “MAP Pre-Rulemaking Report: 2014 Recommendations on Measures for More than 20 Federal Programs” (http://www.qualityforum.org/​Publications/​2014/​01/​MAP_​Pre-Rulemaking_​Report_​_​2014_​Recommendations_​on_​Measures_​for_​More_​than_​20_​Federal_​Programs.aspx) and “Process and Approach for MAP Pre-Rulemaking Deliberations 2015” (http://www.qualityforum.org/​Publications/​2015/​01/​Process_​and_​Approach_​for_​MAP_​Pre-Rulemaking_​Deliberations_​2015.aspx.) We considered the input and recommendations provided by the MAP in selecting all measures for the IPFQR Program, including those discussed below.

B. Retention of IPFQR Program Measures Adopted in Previous Payment Determinations

Since the inception of the IPFQR Program in FY 2013, we have adopted a total of 14 mandatory measures. In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53646 through 53652), we adopted six chart-abstracted IPF quality measures for the FY 2014 payment determination and subsequent years. In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50889 through 50895), we added 2 measures for the FY 2016 payment determination and subsequent years. In the FY 2015 IPF PPS final rule (79 FR 45963 through 45974), we finalized the addition of 2 new measures to the IPFQR Program to those already adopted for the FY 2016 payment determination and subsequent years, and finalized four quality measures for the FY 2017 payment determination and subsequent years.

C. Removal of HBIPS-4 From the IPFQR Program Measure Set for the FY 2017 Payment Determination and Subsequent Years

We first adopted HBIPS-4 Patients Discharged on Multiple Antipsychotic Medications in the FY 2013 IPPS/LTCH PPS final rule (77 FR 53649 through 53650). We refer readers to that rule for a detailed discussion of the measure. At the time we adopted the measure, it was NQF-endorsed and intended for use in conjunction with HBIPS-5 Patients Discharged on Multiple Antipsychotic Medications with Appropriate Justification. However, the NQF removed its endorsement of HBIPS-4 in January 2014. The NQF's Behavioral Health Steering Committee, in its May 2014 Technical Expert Panel Report, found that current evidence indicated that HBIPS-4 “does not allow for the distinction of differences in providers . . . .” [5] Moreover, the Steering Committee noted that HBIPS-4 “is not a measure of quality of patient care . . . and there is insufficient evidence to warrant the endorsement of this measure given the use of HBIPS-5, which addresses patients discharged on multiple antipsychotic medications with appropriate justification.” [6] For these reasons, the Steering Committee did not re-endorse HBIPS-4.

As we stated in the FY 2013 IPPS/LTCH PPS final rule, we originally proposed HBIPS-4, in part, because HBIPS-4 and HBIPS-5 were intended to be reported as a set (77 FR 53649). However, as discussed above, the NQF no longer believes HBIPS-4 is necessary in that set, and we agree. As we stated in the proposed rule, we have the authority to maintain measures that are not NQF-endorsed under section 1886(s)(4)(D)(ii) of the Act. However, based on the loss of NQF endorsement and because providers must still submit data for HBIPS-5, which we believe Start Printed Page 46696sufficiently includes the information HBIPS-4 was intended to collect, we stated our belief that removal of HBIPS-4 from the IPFQR Program is warranted. We noted that the data collection period for FY 2016 has ended and providers are required to submit this data. Therefore, we stated that FY 2017 is the first year that we will be able to remove this measure from the program, and we proposed to remove HBIPS-4 beginning with the FY 2017 payment determination.

We welcomed public comments on this proposal. The comments received and our responses are outlined below.

Comment: Many commenters supported the removal of HBIPS-4, noting that it is no longer NQF-endorsed and is not risk-adjusted, the use of a measure for the sake of documentation does not lead to improved care or provide actionable information and only increases burden, and HBIPS-5 details the quality of care for those receiving multiple antipsychotic medications. A few commenters, however, did not support CMS' removal of HBIPS-4, stating that the practice of prescribing more than one antipsychotic medication is a major contributor to high-dose prescribing, which increases the potential of adverse side effects and healthcare costs, and HBIPS-4 and HBIPS-5 are paired and, therefore, HBIPS-5 is less meaningful without HBIPS-4.

Response: As stated above, although HBIPS-4 and HBIPS-5 were originally paired, the NQF no longer believes that HBIPS-4 is necessary to that set and has removed endorsement of HBIPS-4, stating that HBIPS-4 “does not allow for the distinction of differences in providers . . . .” [7] Moreover, the Steering Committee noted that HBIPS-4 “is not a measure of quality of patient care . . . and there is insufficient evidence to warrant the endorsement of this measure given the use of HBIPS-5. . . .” [8] We agree and believe that HBIPS-5 is sufficient without HBIPS-4 and that HBIPS-4 should be removed from the IPFQR Program measure set as it increases burden without concomitant benefit.

Comment: Some commenters supported CMS' removal of HBIPS-4 but contended that problems remain with HBIPS-5 because IPFs are not always able to obtain a thorough history about patients and do not know, therefore, whether there is adequate justification for patients to be on more than one antipsychotic. Commenters recommended that CMS work with the measure developer and other stakeholders to determine if HBIPS-5 should include additional exclusions, such as patients for whom an IPF was unable to obtain records due to an inability to contact previous or current providers or patients for whom a caregiver wishes to be on multiple antipsychotics.

Response: We have not proposed to change HBIPS-5, and, therefore, will not be altering it in the final rule (77 FR 53650). We will, however, continue to monitor these issues in future years of the IPFQR Program.

For the reasons stated above, and as displayed in Table 19, we are finalizing our proposal to remove HBIPS-4: Patients Discharged on Multiple Antipsychotic Medications beginning with the FY 2017 payment determination.

Table 19—IPFQR Program Measure To Be Removed for the FY 2017 Payment Determination and Subsequent Years

NQF #Measure IDMeasure
N/AHBIPS-4Patients Discharged on Multiple Antipsychotic Medications.

D. New Quality Measures for the FY 2018 Payment Determination and Subsequent Years

In the FY 2016 IPF PPS proposed rule, we proposed to add five new measures to the IPFQR Program for the FY 2018 payment determination and subsequent years (80 FR 25047). The sections below outline our rationale for proposing these measures.

1. TOB-3 Tobacco Use Treatment Provided or Offered at Discharge and the Subset Measure TOB-3a Tobacco Use Treatment at Discharge (NQF #1656)

Tobacco use is one of the greatest contributors of morbidity and mortality in the United States, accounting for more than 435,000 deaths annually.[9] Smoking is a known cause of multiple cancers, heart disease, stroke, complications of pregnancy, chronic obstructive pulmonary disease, other respiratory problems, poorer wound healing, and many other diseases.[10] This health issue has significant implications for persons with mental illness and substance use disorders. Tobacco use is much higher among people with co-existing mental health conditions than for the general population.[11] One study has estimated that these individuals are twice as likely to smoke as the rest of the population.[12] Tobacco use also creates a heavy financial cost to both individuals and society. Smoking-attributable health care expenditures are estimated at $96 billion per year in direct medical expenses and $97 billion in lost productivity.[13]

Strong and consistent evidence demonstrates that timely tobacco dependence interventions for patients using tobacco can significantly reduce the risk of developing a tobacco-related disease, as well as provide improved health outcomes for those already suffering from a tobacco-related Start Printed Page 46697disease.[14] Even a minimal intervention has been shown to result in cessation.[15] Research discloses that tobacco users hospitalized with psychiatric illnesses who enter into smoking-cessation treatment can successfully overcome their tobacco dependence; [16] however, “studies show that many hospitals do not consistently provide cessation services to their patients.” [17] Evidence also suggests that tobacco cessation treatment does not increase, and may even decrease, the risk of re-hospitalization for tobacco users hospitalized with psychiatric illnesses.[18] Research further demonstrates that effective tobacco cessation support across the care continuum can be provided with only minimal additional provider effort and without harm to the mental health recovery process.[19]

TOB-3 (NQF #1656) is a chart-abstracted measure that identifies those patients 18 years of age and older who have used tobacco products within 30 days of admission and who “were referred to or refused evidence-based outpatient counseling AND received or refused a prescription for FDA-approved cessation medication upon discharge.” [20] TOB-3a is a subset of TOB-3 and identifies those IPF “patients who were referred to evidence-based outpatient counseling AND received a prescription for FDA-approved cessation medication upon discharge as well as those who were referred to outpatient counseling and had reason for not receiving a prescription for medication.” [21] Providers must report this measure set as “an overall rate which includes all patients to whom tobacco treatment was provided, or offered and refused, at the time of hospital discharge (TOB-3), and a second rate, a subset of the first, which includes only those patients who received tobacco use treatment at discharge. (TOB-3a).” [22] For more information on the measure specifications, we refer readers to the Specifications Manual for National Hospital Inpatient Quality Measures at https://www.qualitynet.org/​dcs/​ContentServer?​c=​Page&​pagename=​QnetPublic%2FPage%2FQnetTier4&​cid=​1228773989482. Providing counseling and recommending cessation medication are core strategies of the Treating Tobacco Use and Dependence Guidelines.[23] For the reasons stated above, we stated that we believe that adoption of the TOB-3/TOB-3a measure set, which assesses IPFs' offering of these tobacco use cessation treatments to IPF patients, will result in better overall health outcomes for IPF patients.

Furthermore, we noted that the adoption of this measure set will strengthen related measures already in place in the IPFQR Program. Currently, the IPFQR Program includes 2 other tobacco cessation measures: (1) Tobacco Use Screening (TOB-1), a chart-abstracted measure that assesses hospitalized patients who are screened within the first 3 days of admission for tobacco use (cigarettes, smokeless tobacco, pipe, and cigar) within the previous 30 days; and (2) Tobacco Use Treatment Provided or Offered (TOB-2), which includes the subset, Tobacco Use Treatment (TOB-2a). TOB-2/TOB-2a is a chart-abstracted measure set reported as an overall rate that includes all patients to whom tobacco use treatment was provided, or offered and refused, and a second rate, a subset of the first, which includes only those patients who received tobacco use treatment. TOB-1 and TOB-2/TOB-2a provide a picture of care given during the hospital stay. In contrast, TOB-3/TOB-3a present the care given at discharge. Together, these 3 measures/measure sets present a broader picture of the entire episode of care. We noted that if the TOB-3/TOB-3a measure set is adopted, the IPFQR Program's measure set will showcase both the facility's practice of screening patients for tobacco use and the outcomes of a facility's practice of offering opportunities to stop during the course of the stay and upon discharge. Further, we stated that the adoption of TOB-3/TOB-3a could alert IPFs to gaps in treatment for smoking cessation intervention at discharge if rates for these measures are low. We noted our belief that this knowledge will support the development of quality improvement plans and better engage patients in treatment.

We also stated our belief that public reporting of this information will provide consumers and other stakeholders with useful information in choosing among different facilities for patients who use tobacco products. In addition, we observed that this measure set promotes the National Quality Strategy priority of Effective Prevention and Treatment, particularly with respect to the leading causes of mortality, starting with cardiovascular disease. As noted above, tobacco use is one of the greatest contributors of morbidity and mortality in the United States, [24] contributing to various forms of cardiovascular disease, among many other conditions. [25] “Tobacco use remains the chief preventable cause of illness and death in our society.” [26] Cessation interventions can significantly reduce the risk of developing tobacco-related disease, [27] leading to decreases in cardiovascular disease, among other diseases, and, ultimately, mortality. We noted our belief that encouraging intervention would promote effective treatment of tobacco use, and may contribute to prevention of the many Start Printed Page 46698diseases that are associated with tobacco use.

For these reasons, we included TOB-3/TOB-3a in our “List of Measures under Consideration for December 1, 2014.” The MAP provided input on the measure set and supported its inclusion in the IPFQR Program in its report “Process and Approach for MAP Pre-Rulemaking Deliberations 2015” available at http://www.qualityforum.org/​WorkArea/​linkit.aspx?​LinkIdentifier=​id&​ItemID=​78711. Moreover, this measure set is NQF-endorsed for the IPF setting in conformity with the statutory criteria for measure selection under section 1886(s)(4)(D)(i) of the Act.

For these reasons, we proposed to adopt TOB-3/3a for the FY 2018 payment determination and subsequent years. We welcomed public comments on this proposal. The comments we received and our responses are set forth below.

Comment: Comments submitted from a consumer perspective strongly recommended adopting TOB-3/3a given the prevalence of tobacco use among those with mental illness, noting that rates are 2 to 4 times higher than the overall adult population in the United States. These commenters noted that tobacco use is the leading cause of premature disease and death in the United States, is a primary driver of hospitalizations for cancers, stroke, cardiovascular and respiratory disease, causes complications in pregnancy and newborns, and interferes with recovery and healing. These commenters also noted that hospitalizations are an ideal time to initiate cessation because most hospitals are smoke-free or tobacco-free environments, patients may be more likely to quit if the reason for hospitalization is caused or made worse by smoking, and patients may be more likely to continue cessation medications if they are given them during hospitalizations with a positive effect. They also pointed out that HHS has stated that hospitalizations present an unequaled opportunity to promote tobacco cessation, urging evidence-based interventions. Despite these facts, commenters noted that most hospitals have not placed a high priority on cessation efforts, specifically at discharge, thus presenting an opportunity for incorporation of cessation strategies into discharge planning and sustained participation in cessation treatment after patients reenter communities. Supporters of the measure also noted that, together with TOB-1 and TOB-2/2a, TOB-3/3a provides a comprehensive picture of tobacco use treatment around all episodes of inpatient psychiatric care. Finally, these commenters stated that, although the measure is chart-abstracted, the abstraction can be done at the same time the facility is abstracting data for TOB-1 and TOB-2/2a, thereby not substantively increasing burden.

Response: We thank commenters for their support.

Comment: Many commenters recommended that CMS not adopt TOB-3/3a because, they said the measure is a population health measure not created for IPFs and, therefore, does not address quality of psychiatric care. In addition, commenters stated that tobacco cessation is not a primary treatment goal for the majority of patients and may even be contraindicated if a practitioner believes the patient should focus on modifying a different behavior. These commenters also asserted that, when needed, IPFs already use appropriate screening tools. Commenters underscored that measures should be directly related to the reasons that patients seek or require IPF services. One commenter stated that this measure should not be adopted because 5 measures in the area of tobacco cessation are excessive. Other commenters stated that the measure is redundant given TOB-1 and TOB-2/2a. One commenter contended that the measure will show no differentiation in providers, rendering it meaningless to consumers. Finally, one commenter suggested that it may be operationally difficult for IPFs to comply with TOB-3/3a because IPFs may have to modify discharge procedures in order to manage offering and providing medications or counseling for heavy smokers, and suggested, therefore, that the measure be delayed until the FY 2019 payment determination.

Response: As we stated in the FY 2014 IPPS/LTCH PPS final rule (79 FR 45972), we disagree with commenters that maintain that tobacco cessation measures do not provide meaningful information regarding quality of care at IPFs. We continue to believe that reporting this information will provide meaningful distinctions between IPFs and that tobacco cessation treatment is an essential step for IPF patients, specifically because of the prevalence of tobacco use in this community. Tobacco use is the leading preventable cause of premature morbidity and mortality in the United States,[28] affects people with co-existing mental health conditions at a much higher rate than for the general population,[29] and is associated with estimated costs of $96 billion per year in direct medical expenses and $97 billion in lost productivity.[30] These figures are supported by recent studies, including those provided by the U.S. Surgeon General.[31] Furthermore, we disagree that measures must be created for IPFs or specifically for the IPF population to be indicative of quality care. We believe that limiting the program to only measures or conditions that specifically apply to the psychiatric population creates a false demarcation between nonpsychiatric and psychiatric care. In our opinion, IPFs should be considering the overall health of the patient throughout the length of his/her episode of care, in addition to the patient's psychiatric condition. Finally, although some IPFs may currently use appropriate screening tools, as asserted by commenters, these rates may not be publicly reported; a major goal of the IPFQR Program is to provide the public with information upon which to choose providers. Since, as discussed above, tobacco use is high among the IPF-population, we believe that publicly reporting this data will facilitate patient choice.

Additionally, we do not believe that TOB-3/3a is redundant, excessive or unnecessary. TOB-3/3a rounds out the tobacco measures we have previously adopted by showcasing the facility's practice of screening patients for tobacco use and the outcomes of a facility's practice of offering opportunities to stop during the course Start Printed Page 46699of the stay (TOB -1/2/2a) and upon discharge (TOB-3/3a), thus encompassing the entire episode of care. Furthermore, we are unaware of a situation in which tobacco cessation measures, which could lead to a decrease in disease and even premature death, would be contraindicated. As we state above, we believe the provider should be considering the overall health of the patient.

Finally, we understand that the measure may require some facilities to change their existing discharge procedures for the purpose of improving their performance on the measure, and that such changes may take longer to accomplish than the time available before measure data is collected. However, because we already require TOB-1/2/2a, we believe these changes will be minimal. In addition, if facilities have low measure rates, these low measure rates help signal important quality improvement and operational gaps and encourage IPFs to close these gaps, with the goal of higher measure rates in the future.

Comment: Several commenters recommended changes to this measure. One commenter recommended that CMS change the measure specifications to include minors since these individuals would also benefit from smoking cessation. Another commenter noted that the current specification require an appointment made by the healthcare provider for ongoing evidence-based counseling with clinicians, and IPFs may not be able to arrange a specific date for outpatient appointments. This commenter asked CMS to modify the measure to allow hospitals to arrange a referral without a specific appointment date. Other commenters stated that the measure should exclude patients who were screened but later decided they did not wish to receive treatment, asserting that informed consent is a hallmark of medical delivery, and, as specified, the measure is a measure of patient cooperation rather than provider quality; one commenter suggested, instead, capturing a rate of “patient refusal after treatment was offered.”

Response: When feasible and practicable, we believe it is important to implement measures as they are specified, especially once such measures are NQF-endorsed. As such, we do not believe we should make the suggested modifications to the measure. We encourage commenters to suggest these changes to the measure's steward, The Joint Commission, so that the measure can be properly specified, tested, and endorsed for these changes. Furthermore, we believe that patient compliance is indicative of quality care. That is, we maintain that it is important that providers understand gaps in patient compliance so that they can modify their actions and policy to systematically encourage such compliance.

Comment: One commenter requested that the measure be refined so that “referral to evidence-based outpatient counseling” specifies that “referral to evidence-based tobacco cessation interventions” may include outpatient counseling, community resources, or telephonic counseling services. Another commenter maintained that the measure should be inclusive of behavioral healthcare treatment approaches that meet the intent of “outpatient counseling.” Another commenter expressed concern with the availability of outpatient counseling services, particularly in rural areas, noting that many patients may not feel comfortable having a referral made from a psychiatric facility.

Response: As specified, the measure does not state examples of what “referral to evidence-based outpatient counseling” should include. We believe it is important to give providers flexibility in prescribing interventions to best fit the needs of the patient; telephonic counseling services or other types of community resources may meet the requirements for the measure and provide additional opportunities for outpatient counseling in rural areas if they provide evidence-based tobacco cessation counseling on an outpatient basis. Finally, upon discharge, many patients are referred to outpatient providers; we do not believe this measure presents unique issues to discharge referrals and believe that providers should adhere to confidentiality laws and requirements in all of these situations.

Comment: One commenter stated that because of its limited resources as a community mental health center, it would likely face reduced payment as a result of this measure, and, therefore, urged us not to adopt it.

Response: As we stated above, the IPFQR Program does not penalize facilities for low measure rates; facilities are only penalized if they fail to report these data.

Comment: Many commenters recommended that CMS review the TOB measures to see if they are effective and appropriate in the IPF setting and should continue to be required for the IPFQR Program.

Response: We continuously evaluate whether our measures are effective and appropriate for the IPFQR Program. Furthermore, as stated above, this measure is endorsed for all inpatient settings, which is inclusive of the IPF-setting. We will continue to do so for the TOB measure set.

Comment: One commenter noted that several states do not provide financial support for prescription medication for tobacco use treatment, which may translate to high costs for the patient, and recommended that the measure track patients who are unable to accept treatment due to costs.

Response: We thank the commenter for this suggestion, and we will consider it for future years of the IPFQR Program.

For the reasons stated above, we are finalizing our proposal to adopt TOB-3 Tobacco Use Treatment Provided or Offered at Discharge and the subset measure TOB-3a Tobacco Use Treatment at Discharge (NQF #1656) for the FY 2018 payment determination and subsequent years.

2. SUB-2 Alcohol Use Brief Intervention Provided or Offered and SUB-2a Alcohol Use Brief Intervention (NQF #1663)

Individuals with mental health conditions experience substance use disorders (SUDs) at a much higher rate than the general population. Individuals with the most serious mental illnesses have the highest rates of SUDs. Co-occurring SUDs often go undiagnosed and, without treatment, contribute to a longer persistence of disorders, poorer treatment outcomes, lower rates of medication adherence, and greater impairments to functioning.

Substance abuse, particularly alcohol abuse, is a significant problem in the elderly. Alcohol use disorders are the most prevalent type of addictive disorder in individuals ages 65 and over.[32] Roughly 6 percent of the elderly are considered to be heavy users of alcohol.[33] Alcohol abuse is often associated with depression and contributes to the etiology of many serious medical conditions, including liver disease and cardiovascular disease. For these reasons, it is important to assess IPFs' efforts to offer alcohol abuse treatment to those patients who screen positive for alcohol abuse.

SUB-2 includes “[p]atients 18 years of age and older who screened positive for unhealthy alcohol use who received or refused a brief intervention during Start Printed Page 46700the hospital [34] stay.” [35] SUB-2a includes “[p]atients who received the brief intervention during the hospital stay.” [36] The measure set is chart-abstracted and “is reported as an overall rate which includes all patients to whom a brief intervention was provided, or offered and refused, and a second rate, a subset of the first, which includes only those patients who received a brief intervention.” [37] For more information on the measure specifications, we refer readers to the Specifications Manual for National Hospital Inpatient Quality Measures at https://www.qualitynet.org/​dcs/​ContentServer?​c=​Page&​pagename=​QnetPublic%2FPage%2FQnetTier4&​cid=​1228773989482.

We stated our belief that the addition of the SUB-2/SUB-2a measure set to the related existing substance abuse measure in the IPFQR Program will improve the overall quality of care that patients receive in IPF settings, as well as overall patient health outcomes. We previously adopted the SUB-1 measure (Alcohol Use Screening (SUB-1) (NQF #1661)) (78 FR 50890 through 50892). SUB-1 assesses “hospitalized patients 18 years of age and older who are screened during the hospital stay using a validated screening questionnaire for unhealthy alcohol use.” SUB-1 alone does not provide a full picture of an IPF's response to this screening. However, when linked to SUB-2/SUB-2a, the IPF measure set depicts the rate at which patients are screened for potential alcohol abuse and the rate at which those who screen positive accept the offered interventions. Further, the adoption of SUB-2/SUB 2a could alert IPFs to gaps in treatment for interventions if rates are low, which supports the development of quality improvement plans and better patient engagement in treatment. In addition, data for the SUB-2/SUB-2a measure set, in combination with the SUB-1 measure, would afford consumers useful information in choosing among different facilities, particularly for patients who may require assistance with unhealthy alcohol use.

Additionally, we stated our belief that this measure set promotes the National Quality Strategy priority of Effective Prevention and Treatment for the leading causes of mortality, starting with cardiovascular disease. As noted above, alcohol use disorders are the most prevalent type of addictive disorder in individuals ages 65 and over [38] and contribute to serious medical conditions, including cardiovascular disease and liver disease. We noted that encouraging interventions would promote treatment of unhealthy alcohol use and may contribute to prevention of the many diseases that are associated with alcohol abuse, including cardiovascular disease.

For these reasons, we included the SUB-2/SUB-2a measure set in our “List of Measures under Consideration for December 1, 2014.” The MAP provided input on the measure set and supported its inclusion in the IPFQR Program in its report “Process and Approach for MAP Pre-Rulemaking Deliberations 2015” available at http://www.qualityforum.org/​WorkArea/​linkit.aspx?​LinkIdentifier=​id&​ItemID=​78711. Moreover, this measure set is NQF-endorsed for the IPF setting, in conformity with the statutory criteria for measure selection under section 1886(s)(4)(D)(i) of the Act.

Therefore, we proposed to adopt SUB-2/2a for the FY 2018 payment determination and subsequent years. We welcomed public comments on this proposal. The comments we received and our responses are set forth below.

Comment: Comments submitted from a consumer perspective supported the measure since alcohol use may be a contributing factor to the mental health of patients. Commenters noted that mental health and substance abuse treatment have historically been provided separately and not in a coordinated fashion and the measure could serve as a catalyst for coordinated, integrated responses. Furthermore, these commenters stated that the addition of these measures will complement SUB-1.

Response: We thank commenters for their support.

Comment: Many commenters recommended that CMS not adopt SUB-2/2a because, they submitted, the measure is a population screening measure neither created for IPFs nor systematically tested in the IPF setting, and, therefore, does not address quality of psychiatric care. Specifically, commenters stated that this measure penalizes providers for a patient's refusal to receive treatment, and is therefore a measure of patient cooperation rather than provider quality. In addition, commenters asserted that measures should be directly related to reasons that patients seek or require IPF services to focus providers on optimal care and recommended measures specific to evidence-based practices. Finally, commenters noted that IPFs already perform an in-depth assessment of patients' alcohol and substance abuse history, and current use and patients with such disorders are treated through a multi-disciplinary and multi-model plan, so the measure is not necessary, and the measure will show no differentiation in providers, rendering it meaningless to consumers.

Response: As we stated in the FY 2014 IPPS/LTCH PPS final rule (78 FR 50891), although the SUB measures were developed using all hospitalizations in general acute care, we believe that SUB-2 is equally applicable to freestanding IPFs and psychiatric units within acute care facilities because risky alcohol use is an area of high comorbidity for populations hospitalized in all of these settings. Furthermore, we disagree that measures must be created for IPFs or specifically for the IPF population to be indicative of quality care. We believe that limiting the program to only measures or conditions that specifically apply to the psychiatric population creates a false demarcation between nonpsychiatric and psychiatric care. In our opinion, IPFs should be considering the overall health of the patient throughout the length of his/her episode of care, in addition to the patient's psychiatric condition. Furthermore, we believe that patient compliance is indicative of quality care. That is, we maintain that it is important that providers understand gaps in patient compliance so that they can modify their actions and policy to systematically encourage such compliance. Additionally, although we believe that the measure will differentiate between providers, we will monitor measure rates to assure the measure provides meaningful information to consumers by differentiating care among IPFs. Finally, although some IPFs may currently use appropriate screening tools and provide cessation treatment, as asserted by commenters, these rates may not be publicly reported; a major goal of the IPFQR Program is to provide the public with information upon which to choose providers. Since, as discussed above, Start Printed Page 46701alcohol use is high among the IPF-population, we believe that publicly reporting this data will facilitate patient choice.

Comment: Several commenters stated that the measure should not be adopted because it does not go far enough, stating the measure separates alcohol use from other substances when psychiatric patients are routinely screened for all substance use issues.

Response: As we stated in the FY 2014 IPPS/LTCH PPS final rule (78 FR 58092), we recognize that this measure only assesses alcohol use and that screening for risky use/abuse of other substances would also be desirable. We believe the SUB measure set to be an important first step in this area, and we intend to consider the incorporation of other substance use measures into the program in the future.

Comment: Many commenters urged CMS to modify this measure to include more than a “brief” intervention since patients who demonstrate behaviors sufficient to warrant involuntary inpatient commitment and are dually diagnosed with substance abuse or dependence require more intensive than “brief” substance use treatments. One commenter stated that “brief intervention” needs further definition and clarification to suggest or require brief intervention structures supported by evidence, such as the FRAMES (feedback, responsibility, advice, menu of options, empathy, and self-efficacy) structure. Other commenters submitted that there is no evidence supporting the efficacy of brief interventions for individuals that have alcohol or other substance use.

Response: We disagree with the commenters regarding the efficacy of brief interventions, specifically as they are defined by the measure. In 2014, during the measures maintenance process, the NQF's Behavioral Health Steering Committee stated that “in order to receive credit for the brief intervention there must be a bedside discussion with the patient focusing on increasing the patient's understanding of the impact of substance use on his or her health and motivating the patient to change risky behaviors. The intervention should include feedback concerning the quantity and frequency of alcohol consumed by the patient in comparison with national norms, a discussion of negative physical, emotional, and occupational consequences, and a discussion of the overall severity of the problem. The brief intervention may be given by a variety of healthcare professionals such as physician, nurse, certified addictions counselor, psychologist, social worker, or health educator with training in brief intervention.” [39] We understand that for heavy users of alcohol, brief intervention may not be enough, but these brief interventions, we believe, are an important first-step to cessation. Furthermore, if providers believe that additional cessation strategies are warranted, we highly encourage using them. In addition, as described, the FRAMES structure would satisfy the requirements for “brief intervention,” and we believe that the provider community could use this framework. We note, however, that such structure is not required as long as the provider meets the elements discussed above.

Comment: One commenter expressed concern that the measure set does not exclude cases when treatment was offered but refused. This commenter requested that CMS report the measure as the percentage of patients who were offered treatment and refused, or retitle the measure to “patients who were offered alcohol use intervention and accepted.” This commenter also requested that CMS allow clinicians to determine whether a patient's cognitive impairment in the first three days of admission prevented screening because some patients are alert and oriented but impaired cognitively so as to not allow screening for substance abuse.

Response: When feasible and practicable, we believe it is important to implement measures as they are specified, especially where, as here, the measure set is NQF-endorsed. As such, we do not believe we should make the suggested modifications to the measure. We encourage the commenter to suggest these changes to the measure's steward, The Joint Commission, so that the measure can be properly specified, tested, and endorsed for these changes. In addition, the measure set is bifurcated specifically to delineate patients that refuse or do not otherwise receive treatment. SUB-2 measures “[p]atients 18 years of age and older who screened positive for unhealthy alcohol use who received or refused a brief intervention during the hospital [40] stay,” [41] but SUB-2a only includes “[p]atients who received the brief intervention during the hospital stay.” [42] Thus, the measure rates that will be published on Hospital Compare will allow the public to derive rates of patient refusal. As stated above, however, we believe that patient compliance is indicative of quality care. That is, we maintain that it is important that providers understand gaps in patient compliance so that they can modify their actions and policy to systematically encourage such compliance.

Comment: One commenter stated that because of its limited resources as a community mental health center, it would likely face reduced payment as a result of this measure, and, therefore, urged us not to adopt it.

Response: As we stated above, the IPFQR Program does not penalize facilities for low measure rates; facilities are only penalized if they fail to report these data.

Comment: One commenter noted that individuals screening positive for alcohol dependency may need both brief interventions and further assessment or referral to specialty treatment and, therefore, suggested an additional quality measure that assesses patients who were defined as alcohol dependent and referred to a substance use disorder specialist for assessment. Another commenter urged CMS to adopt SUB-3/3a to complement SUB-1/2/2a, noting that co-occurring substance use disorders are prevalent in many patients with psychiatric diagnoses and SUB-3/3a will ensure that patients continue to receive treatment after discharge. Another commenter encouraged CMS to consider additional non-alcohol substance abuse disorder measures, specifically the use of opioids.

Response: We thank the commenters for these suggestions and will consider them for future years of the program.

For the reasons stated above, we are finalizing our proposal to adopt SUB-2 Alcohol Use Brief Intervention Provided or Offered and SUB-2a Alcohol Use Brief Intervention (NQF #1663) for the FY 2018 payment determination and subsequent years.

3. Transition Record With Specified Elements Received by Discharged Patients (Discharges From an Inpatient Facility to Home/Self Care or Any Other Site of Care) (NQF #0647) and Removal of HBIPS-6

Effective and timely communication of a patient's clinical status and other relevant information at the time of discharge from an inpatient facility is essential for supporting appropriate continuity of care. Establishment of an Start Printed Page 46702effective transition from one treatment setting to another is enhanced by providing patients and their caregivers with sufficient information regarding treatment during hospitalization. Receiving discharge instructions can assist the patient in understanding how to maintain and enhance his/her care when discharged to home or any other site, and studies have shown that readmissions can be prevented by providing detailed, personalized information to patients pre-discharge.[43]

The Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any other Site of Care) measure is a chart-abstracted measure that captures the “[p]ercentage of patients, regardless of age, discharged from an inpatient facility to home or other site of care, or their caregiver(s), who received a transition record (and with whom a review of all included information was documented) at the time of discharge.” [44] At a minimum, the transition record should include:

  • Reason for inpatient admission;
  • Major procedures and tests performed during inpatient stay and summary of results;
  • Principal diagnosis at discharge;
  • Current medication list;
  • Studies pending at discharge;
  • Patient instructions;
  • Advance directive or surrogate decision maker documented or reason for not providing advance care plan;
  • 24-hour/7-day contact information, including physician for emergencies related to inpatient stay;
  • Contact information for obtaining results of studies pending at discharge;
  • Plan for follow-up care; and
  • Primary physician, other health care professional, or site designated for follow-up care.[45]

The measure was developed by the American Medical Association-convened Physician Consortium for Performance Improvement (AMA-convened PCPI), “a national, physician-led initiative dedicated to improving patient health and safety.” [46] For more information on this measure, including its specifications, we refer the readers to the AMA-convened PCPI list of measures at http://www.qualityforum.org/​Qps/​0647.

The Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any other Site of Care) measure seeks to prevent gaps in care transitions caused by the patient receiving inadequate or insufficient information that lead to avoidable adverse events and cost CMS approximately $15 billion due to avoidable patient readmissions.[47]

We stated our belief that public reporting of this measure will afford patients and their families or caregivers useful information in choosing among different facilities and will promote the National Quality Strategy priority of Communication and Care Coordination. As articulated by HHS, “Care coordination is a conscious effort to ensure that all key information needed to make clinical decisions is available to patients and providers. It is defined as the deliberate organization of patient care activities between 2 or more participants involved in a patient's care to facilitate appropriate delivery of health care services.” [48] This measure will promote appropriate care coordination by specifying that patients discharged from an inpatient facility receive relevant and meaningful transition information. This measure also promotes Person and Family Engagement, “a set of behaviors by patients, family members, and health professionals and a set of organizational policies and procedures that foster both the inclusion of patients and family members as active members of the health care team and collaborative partnerships with providers and provider organizations.” [49] This measure will inform patients of their status at discharge, empowering them to become active members in their care. Additionally, the inclusion in this measure of an advance care plan will support open communication of the patient's, and his/her caregiver's/surrogate's, wishes, resulting in improved patient-provider communication.

For these reasons, we included this measure in our “List of Measures under Consideration for December 1, 2014.” The MAP provided input on the measure and supported its inclusion in the IPFQR Program in its report “Process and Approach for MAP Pre-Rulemaking Deliberations 2015” available at http://www.qualityforum.org/​WorkArea/​linkit.aspx?​LinkIdentifier=​id&​ItemID=​78711. In addition, the MAP had previously suggested this measure as one that could fill a gap in communication between the provider and patient at discharge [50] and recommended that the measure be used for dual eligible patients (that is, patients with both Medicare and Medicaid coverage), who comprise a significant beneficiary population served within IPFs.[51] Moreover, this measure set is NQF-endorsed for the IPF setting, in conformity with the statutory criteria for measure selection under section 1886(s)(4)(D)(i) of the Act.

We proposed that, if this measure is finalized, it would replace the existing HBIPS-6 Post-Discharge Continuing Care Plan measure.[52] We stated our belief that the Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure is a more effective and robust measure than HBIPS-6 for use in the IPF setting. Specifically, HBIPS-6 requires discharge plans to only have 4 components:

  • Reason for hospitalization;
  • Principal diagnosis;
  • Discharge medications; and
  • Next level of care recommendations.[53]

In contrast, the Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure requires additional elements, including those described below, which are intended to improve quality of care, Start Printed Page 46703decrease costs, and increase beneficiary engagement.

First, this measure requires the provider to communicate both studies pending at discharge as well as contact information so that patients or their families can obtain the results of those studies. Approximately 40 percent of discharged patients have test results that are pending and about a quarter of such test results require further action that, if not taken in a timely manner, could result in potentially avoidable negative outcomes.[54] HBIPS-6 does not require providers to specify studies pending at discharge.

Second, the transition record is also required to contain a list of major procedures and tests that were performed during the hospitalization and summary results. HBIPS-6 does not include this requirement. We believe it is important for a patient to understand which tests were performed on him/her and for what purpose, understanding the outcome and consequences of these tests. This knowledge may serve to empower patients to seek additional care or follow-up when necessary, reducing the risk of avoidable consequences and readmissions.

Third, the transition record in this measure is required to include patient instructions while HBIPS-6 has no such requirement. Without instructions, the patient may not take the necessary steps for recovery, leading to complications and/or readmissions.

Fourth, this measure requires both of the following: (1) 24-hour/7-day contact information including physicians for emergencies related to inpatient stay; and (2) the primary physician, other health care professional, or sites designated for follow-up care. HBIPS-6 does not have these requirements. Again, this information can lead to reduced complications and an increased likelihood of appropriate follow-up care, resulting in reduced readmissions.

Finally, the elements required for the transition record measure are far better aligned than HBIPS-6 with the elements required in the Summary of Care record required by the Electronic Health Record (EHR) Incentive Program for eligible hospitals and critical access hospitals and with the guidance on discharge planning provided by the Medicare Learning Network available at https://www.cms.gov/​Outreach-and-Education/​Medicare-Learning-Network-MLN/​MLNProducts/​Downloads/​Discharge-Planning-Booklet-ICN908184.pdf.

In summary, we stated our belief that the Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure is more robust than HBIPS-6 because it includes these and other elements that are currently absent from HBIPS-6. Therefore, we proposed to adopt the Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure for the FY 2018 payment determination and subsequent years, and to remove HBIPS-6. We welcomed public comments on these proposals. The comments we received and our responses are set forth below.

Comment: Many comments submitted from a consumer perspective supported the adoption of this measure, stating that the transition from inpatient to home/self-care or any other site is extremely critical; the measure supports patient engagement, and patient activation, and provides patients with necessary documentation for follow-up care. Commenters also stated that, unlike HBIPS-6, because this measure is not limited to the inpatient psychiatric setting, it decreases the separation between psychiatric and nonpsychiatric care.

Response: We thank the commenters for their support.

Comment: Many commenters recommended that CMS not replace HBIPS-6 with the Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure for several reasons. First, commenters asserted that HBIPS-6 is widely-used and fully operational, was developed with the input of IPFs, and fully tested in the IPF-setting, whereas the proposed measure does not appear to be widely used or have benchmarking data available. One commenter specifically submitted that the measure was developed for use at the individual-clinician level rather than at the facility-level. Commenters stated that most IPFs have been reporting HBIPS data for over eight years, allowing them to understand trends and performance gaps, and believed that removing HBIPS-6 could upset quality improvement efforts currently in place. Commenters also stated that continually revising the measures does not provide reliable data on which to base decisions about patient care and evaluate care improvement over time.

Second, commenters contended that HBIPS-6 better addresses the core elements of the proposed measure and requires more stringent documentation of medications, noting that, although the proposed measure requires more information, it is the practice of IPFs to include all relevant information in the continuing care plan, and, if needed, hospitals communicate additional elements to the next level care provider. Commenters further stated that the new elements required by this measure are not germane to the vast majority of psychiatric patients, commenting that the rule mainly cites articles that did not necessarily study psychiatric patients, and that the new elements are primarily based on medical models rather than psychiatric care.

Third, commenters contended that retiring HBIPS-6 will increase burden on IPFs because of the 7 additional elements required by the proposed measure and because IPFs will still be required to abstract data for HBIPS-6 for The Joint Commission.

Finally, some commenters stated that the measure is duplicative of, and sometimes misaligned with, the requirements of Medicare's Conditions of Participation. Commenters believed that the Conditions of Participation meet the goals of promoting care coordination by specifying that patients discharged from an inpatient facility receive relevant and meaningful transition information and the results are publicly reported.

Commenters suggested that, if CMS wishes to require transition elements in addition to HBIPS-6, CMS either allow hospitals more time to operationalize the measure, implementing the measure beginning with the FY 2019 payment determination, or that CMS work with The Joint Commission to revise HBIPS-6 to include additional elements.

Response: We agree with commenters that there may be some increase in burden due to the removal of HBIPS-6 and the adoption of the Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure, since HBIPS-6 requires 4 elements while the Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure requires 11 elements. However, we believe that this burden will be significantly mitigated by the overlap in the two measures; the 4 elements required by HBIPS-6 satisfy 4 of the 11 elements for the new measure. We clarify in this final rule that, if the IPF Start Printed Page 46704meets the documentation requirements of HBIPS-6, it also meets the documentation requirements for the following elements for the Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure: (1) Reason for hospitalization; (2) principal diagnosis; (3) discharge medications; and (4) next level of care recommendations. Therefore a hospital could abstract data for and comply with HBIPS-6 by also complying with and abstracting data for the Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure. Furthermore, if it is currently the practice of IPFs to include all relevant information in the continuing care plan, as some commenters assert, we do not understand how the measure would substantially increase burden. In addition, for the reasons stated above, we believe the additional elements in the new transition measure are indicative of quality care, leading to a decrease in re-hospitalizations and an increase in patient safety. We also do not agree that replacing this measure will upset quality improvement efforts begun by HBIPS-6. If IPFs have already begun quality improvement in this area, we believe it will continue and even surpass the current state because the proposed measure is even more robust, requiring 7 additional elements. Therefore, we believe that the benefit of the removal of HBIPS-6 and the adoption of the Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure outweighs any associated burden and furthers the goals of the IPFQR Program. In addition, the measure is endorsed at the facility-level, not the clinical-level, and was developed with a broad range of inpatient settings in mind that did not specifically exclude IPFs; the measure developer is considering explicitly including the IPF-setting in the next round of measure maintenance so that the measure is endorsed not only for all inpatient settings, but explicitly states that it is endorsed for the IPF-setting.

Furthermore, we disagree that the Conditions of Participation are duplicative of or misaligned with this measure. To the extent that the measure and Conditions of Participation overlap, they are aligned in their requirements. Furthermore, this measure requires elements in addition to those of the Conditions of Participation, increasing the quality of care delivered to patients.

To clarify, although HBIPS-6 requires documentation in the medical record of discharge medications, dosage, and indication for use or that no medications were prescribed at discharge, the new measure requires documentation of all medications to be taken by patient after discharge, including all continued and new medications. We believe that it is important that patients understand all medications that they should be taking, even those not specifically prescribed at discharge. Thus, we believe that this new measure is actually more robust than HBIPS-6.

Additionally, as we have stated previously, we disagree that measures must be created for IPFs or specifically for the IPF population to be indicative of quality care. Many issues concerning service quality are not specific to a particular setting. We believe that the content of transition records is one such issue. Further, we believe that limiting the program to only measures or conditions that specifically apply to the psychiatric population creates a false demarcation between nonpsychiatric and psychiatric care.

Finally, although we believe this measure to be a critical indicator of quality care, we understand that with the additional elements required it may take providers time to change their operations to begin collecting this data. Therefore, we will only require IPFs to report the last two quarters of data for this measure for the FY 2018 payment determination; that is, providers will only be required to report data for July 1, 2016-December 31, 2016. Beginning with the FY 2019 payment determination, IPFs will be required to report all four quarters of data or will face a payment reduction.

Comment: Some commenters asserted that patients have expressed frustration with the length of discharge instructions, and the number of elements required by this measure may overwhelm the patient, causing the patient or caregiver to lose interest and disregard the important information. Commenters also stated that some of this information could be misinterpreted if the patient reviews the information after discharge and not in the presence of a clinician. One commenter specifically contended that “patient instructions” should not be included in the record because they will become lost in the packet of information and many patients are discharged to places, such as a group home, residential care, or jail, where they are not able to keep such a large amount of information, putting their confidentiality at risk. Another commenter stated its belief that the requirements in the measure for patients to receive and understand their transition records is burdensome because the timeframe for collection does not allow enough time for hospitals to modify the language in their current systems to account for health literacy. Therefore, some commenters requested that the measure be limited to items necessary for the transition period to the next follow-up care visit and be tailored to psychiatric patient's ability to comprehend. Other commenters, however, specifically noted that the measure will enhance the likelihood that patients will have the information they need to effectively manage their own care (or for their caregiver to understand and assist with managing the patient's care).

Response: We agree that the measure will help, rather than harm, patients. We are committed to patient engagement and believe that the more that patients know about their condition and treatment, the more empowered they become in their care and their follow-up treatment. If facilities believe that certain items in the record need to be explained, we believe it is incumbent upon them to become partners in care with patients and sufficiently explain these details. Although such changes may present additional burden to facilities, we believe that this burden is far outweighed by the benefit of fostering an involved and empowered patient population. Additionally, we do not believe that this measure presents confidentiality issues for patients. Once a patient receives his or her record, the disposition of the information is up to the patient. Thus, as with all discharge records, a patients may choose to do with the information as they so choose without raising confidentiality concerns.

Comment: Some commenters supported the measure because it more closely aligns with existing summary of care document requirements for EHRs, but some commenters stated that, psychiatric hospitals are not eligible for the EHR Incentive Program and the majority of organizations to which IPFs discharge patients do not have electronic records. Other commenters stated their belief that this measure would require providers to modify their EHRs.

Response: Nothing in this measure requires a facility to use an EHR. While we recognize that psychiatric hospitals are not eligible for the EHR Incentive Program, we believe that, whenever Start Printed Page 46705possible, the goals of the agency should be aligned to foster streamlined processes and procedures across providers and care settings. Furthermore, we are not aware of any specific EHR changes that would need to be made to accommodate this measure, and, when the record is transmitted to a next-level provider per the measure discussed below, the “transition record may be transmitted to the facility or physician or other health care professional designated for follow-up care via fax, secure email, or mutual access to an electronic health record (EHR).” [55]

Comment: Some commenters maintained that CMS inappropriately compared HBIPS-6 with the proposed measure when the HBIPS-6 transition plan is not required to go to the patient.

Response: We believe comparing these measures was appropriate because both concern practices around documentation of the care provided during the inpatient stay. In fact, the requirements for patient communication in the measure is an important reason for choosing it to replace HBIPS-6, which does not require the documentation to go to the patient. As we discuss above, we believe it is vital to provide this information to enhance patient engagement.

Comment: Commenters expressed concern that the Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure is not stratified by age, which limits the usefulness of the data, given the variation across populations.

Response: As stated above, when feasible and practicable, we believe it is important to implement measures as they are specified especially where, as here, the measure is NQF-endorsed. As such, this measure is not specified to be reported by age. Furthermore, we believe that presenting the measure as an aggregate number rather than stratified by age will allow greater rather than less insight into these data because, as further explained in section V.F.1. of this final rule, the resultant number of cases is often too small to allow public reporting when data are stratified by age.

Comment: Comments submitted from a consumer perspective recommended that CMS consider adding the following additional elements to the existing transition measure: (1) Information on locations and contacts for community services and support group meetings; (2) recommendations for additional, non-medication mental health treatments; (3) recommendations for relevant physical health suggested appointments and clinical references; (4) patient surveys evaluating the quality of mental health care received; (5) information about side effects from medications and potential warning signs of adverse medication interactions; (6) information about follow-up care for alcohol or substance use treatment; and (7) documented coordination between inpatient and outpatient providers. Another commenter stated that the measure should exclude patients discharged in less than 24 hours because collecting the required information takes at least this amount of time. The same commenter also submitted that patients discharged to another acute facility should be excluded from the measure since such a discharge is always accompanied by an appropriate transition record. Another commenter stated that additional exclusions should be added, including patient refusal and unplanned discharges, noting that more than 6 percent of discharges fall in these categories. One commenter noted that “medication indications” is missing from the proposed measure, but appears in HBIPS-6, and questions why CMS believes this is no longer a necessary element, noting that such an omission is welcome because of the burden in documenting this information. Other commenters, however, stated that this more stringent documentation of medications is necessary.

Response: As stated above, when feasible and practicable, we believe it is important to implement measures as they are specified, especially once such measures are NQF-endorsed. As such, we do not believe we should make the suggested modifications to the measure. We encourage the commenters to suggest these changes to the measure's steward, the AMA-convened PCPI, so that the measure can be properly specified, tested, and endorsed for these changes.

Comment: Some commenters stated that this measure was either the same as or similar to a measure previously adopted by the Hospital OQR Program that was subsequently removed because hospitals raised concerns about potential privacy issues related to releasing certain elements of the record to family members or caregivers. Commenters asked if the measure had been revised to address these issues and if IPFs will be constrained by state laws, and, if so, since state laws differ from state-to-state, how the measure can be implemented nationwide.

Response: We believe the commenters stating that the measure is the same as a measure adopted by the Hospital OQR Program are incorrect. The Hospital OQR Program adopted and finalized NQF #0649 Transition Record with Specified Elements Received by Discharged Patients (Emergency Department Discharges to Ambulatory Care [Home/Self Care] or Home Health Care). Although this measure is also stewarded by the AMA-PCPI and requires a transition record, it is not the same as NQF #0647, which we proposed. The measures differ in regards to the location from which the patient is discharged; specifically, NQF #0649 measures discharges from the emergency department, while NQF #0647 measures discharges from an inpatient facility. We believe that this difference is critical because the circumstances surrounding discharge from an emergency department are typically not planned; that is, a patient is discharged the same day he/she arrives with the individual that brought him/her to the emergency room, whom a patient may or may not feel comfortable sharing information. Those discharged from an inpatient setting usually have advanced notice and can plan accordingly. Thus, we do not believe, and neither does the AMA-PCPI, that NQF #0647 raises any of the privacy concerns articulated by the Hospital OQR Program for #0649.

Comment: Commenters requested clarification on several elements of the discharge plan: (1) What needs to be transmitted to satisfy the advanced directive requirement and who is a “surrogate decision maker”; (2) what is defined as a “major procedure”; (3) which tests should be included in the transition record; and (4) what is “24 hour, 7-day a week contact information.” Another commenter requested that CMS clarify whether psychiatric patients undergo major procedures and tests during their stay, and, if so, the most common procedures and tests. Another commenter requested CMS to opine if Indiana's Physician Order for Scope Treatment document would satisfy the advance directive element. Another commenter stated that psychiatric patients are often not in the best position to formulate an advanced care plan.

Response: According to the measure steward, the AMA-convened PCPI, to satisfy the “advance directive or surrogate decision maker documented or reason for not providing advance care plan” element, the IPF need only document whether the patient has an Start Printed Page 46706advance directive or surrogate decision maker or a reason he/she does not have one. No additional documentation need be transmitted and a patient need not create an advance directive to satisfy the measure. A “surrogate decision maker” is an individual that the patient has designated to make decisions for him/her. Again, per the measure specifications, the patient need not necessarily have a surrogate decision maker, but the IPF should document why he or she does not in the absence of one.

The AMA-PCPI has also clarified that “major procedure” and “tests” are intentionally not defined to allow flexibility for providers; therefore, we cannot quantify which procedures or tests are major. If a provider believes a procedure to be “major” or a test important enough to be included, it should be included in the transition record.

Regarding the “24 hour, 7-day a week contact information,” IPFs need only provide a number where a patient can contact the facility with questions. This number need not connect the patient to his/her specific doctor, although it may do so.

For the reasons stated above, we are finalizing our proposal to adopt Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) and remove HPIBS-6: Post-Discharge Continuing Care Plan for the FY 2018 payment determination and subsequent years with one modification. For the FY 2018 payment determination, we will only require IPFs to report data on this measure for the last two quarters of the reporting period (July 1, 2016-December 1, 2016). Beginning with the FY 2019 payment determination, IPFs will be required to report all four quarters of data.

4. Timely Transmission of Transition Record (Discharges From an Inpatient Facility to Home/Self Care or Any Other Site of Care) (NQF #0648) and Removal of HBIPS-7

The literature shows infrequent communication between hospital physicians and primary care practitioners and that the availability of discharge summaries at the patient's first post-discharge visit with the primary care practitioner is low, which affects the quality of care provided to patients.[56] The Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure (NQF #0648) is a chart-abstracted measure developed by AMA-convened PCPI to narrow gaps in care transition that result in adverse health outcomes for patients and cost CMS about $15 billion due to readmissions,[57] as discussed above. This measure captures the “[p]ercentage of patients, regardless of age, discharged from an inpatient facility to home or any other site of care for whom a transition record was transmitted to the facility or primary physician or other health care professional designated for follow-up care within 24 hours of discharge.” [58] For more information on this measure, including its specifications, we refer the readers to http://www.qualityforum.org/​Qps/​0648.

We stated our belief that public reporting of this measure will afford consumers, and their families or caregivers, useful information in choosing among different facilities because it communicates how quickly a summary of the patient's record will be transmitted to his or her other treating facilities and physicians, improving care, as outlined above. We further believe that this measure will promote the National Quality Strategy priority of Communication and Care Coordination. As discussed above, according to HHS, “Care coordination is a conscious effort to ensure that all key information needed to make clinical decisions is available to patients and providers. It is defined as the deliberate organization of patient care activities between 2 or more participants involved in a patient's care to facilitate appropriate delivery of health care services.” [59] This measure enables a patient's primary care physician or other healthcare practitioner to timely receive a transition record of the inpatient hospitalization.

For these reasons, we included this measure in our “List of Measures under Consideration for December 1, 2014.” The MAP provided input on the measure and supported its inclusion in the IPFQR Program (http://www.qualityforum.org/​WorkArea/​linkit.aspx?​LinkIdentifier=​id&​ItemID=​78711). In addition, the MAP had previously suggested this measure as one that could fill a gap in communication [60] and recommended that the measure be used for dual eligible patients (that is, patients with both Medicare and Medicaid coverage), who comprise a significant beneficiary population served within IPFs.[61] Moreover, this measure set is NQF-endorsed for the IPF setting, in conformity with the statutory criteria for measure selection under section 1886(s)(4)(D)(i) of the Act.

We proposed that if we finalized this measure, it would replace the existing HBIPS-7: Post Discharge Continuing Care Plan Transmitted to the Next Level of Care Provider Upon Discharge measure.[62] HBIPS-7 requires that the continuing care plan be transmitted to the next care provider no later than the fifth day post discharge.[63] The Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure requires transmission to the next level of care within 24 hours of discharge. More timely communication of vital information regarding the inpatient hospitalization results in better care, reduction of systemic medical errors, and improved patient outcomes. Studies show that the risks of re-hospitalization are lower when primary care providers have access to patients' post-discharge records at the first post-discharge visit,[64 65] which may be within a day (or days) of discharge. Critically, the availability of the discharge record to the next level provider within 24 hours after discharge supports more effective care coordination and patient safety, since a delay in communication can result in medication or treatment errors. Thus, we stated our belief that replacing HBIPS-7 with the Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care Start Printed Page 46707or Any Other Site of Care) measure would increase the quality of care provided to patients, reduce avoidable readmissions, and increase patient safety.

Therefore we proposed to replace HBIPS-7 with the Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure beginning with the FY 2018 payment determination. We welcomed public comments on these proposals. The comments we received and our responses are set forth below.

Comment: Comments submitted from a consumer perspective strongly supported the adoption of this measure, specifically the 24-hour requirement, since lack of coordinated care has led to high rates of re-hospitalization, arrests, homelessness, and other negative consequences, and the measure will ensure that there is only a potential 24-hour gap between discharge and the next level of care. Commenters maintained that the measure would promote safe and effective care and communication and care coordination efforts of the National Quality Strategy. Commenters also stated that the measure more closely aligns with existing summary of care document requirements for EHRs, and is applicable to more settings than HBIPS-7, decreasing the separation between psychiatric and nonpsychiatric care.

Response: We thank the commenters for their support, and agree that psychiatric and nonpsychiatric care should be considered as a whole in treating a patient.

Comment: Many commenters recommended that CMS not replace HBIPS-7 with the Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure for several reasons. First, commenters submitted that HBIPS-7 is widely-used and fully operational, was developed with the input of IPFs, and fully tested in the IPF setting, whereas the proposed measure does not appear to be widely used or have benchmarking data available. One commenter specifically maintained that the measure was developed for use at the individual clinician level rather than at the facility level. Other commenters stated that most IPFs have been reporting HBIPS data for over 8 years, allowing them to understand trends and performance gaps, and believed that removing HBIPS-7 could upset quality improvement efforts currently in place. Commenters also stated that any comparative data may not be meaningful since national comparative rates would include settings other than IPFs. Many commenters specifically noted that room for improvement in HBIPS-7 remains, with a compliance rate of only 44 percent for the two-thirds of psychiatric facilities that began using this measure as a result of the IPFQR Program. Commenters recommended that CMS refrain from changing measures in the same domain to allow time for providers to change and stabilize their procedures.

Second, commenters expressed concern that the 24-hour window for transmission does not improve the quality of data submitted to the next level of care provider, is in conflict with other documentation requirements, such as the allowable time for the discharge summary to be completed, focuses on how quickly the documentation is completed rather than the quality of data transmitted, and is nearly impossible for providers to meet. Some commenters noted that the 24-hour timeframe is not necessary because most patients are not seen by an outpatient provider within 24 hours of discharge and most communication is done through fax, necessitating a longer timeframe to ensure control over who receives the data and compliance with confidentiality requirements.

Third, commenters contended that HBIPS-7 better addresses the core elements of the proposed measure and requires more stringent documentation of medications, noting that, although the proposed measure requires more information, it is the practice of IPFs to include all relevant information in the continuing care plan. In addition, commenters stated that the new elements are primarily based on medical models rather than psychiatric care and focus on areas not important in the psychiatric population.

Finally, commenters asserted that removing HBIPS-7 will increase burden on IPFs because IPFs will still be required to abstract data for this measure for The Joint Commission.

Commenters suggested that, if we wish to require transition elements in addition to HBIPS-7, we either allow hospitals more time to operationalize the measure, implementing it beginning with the FY 2019 payment determination, or that CMS work with The Joint Commission to revise HBIPS-7 to include additional elements.

Response: Although we agree that there may be some increase in burden due to the removal of HBIPS-7 and the adoption of the Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure, we note that the primary difference between the two measures is in the timing of transmission; HBIPS-7 requires transmission to the next-level care provider within 5 days of discharge, while the Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure requires the same within 24-hours of discharge. Thus, by transmitting the transition record within 24 hours, the provider satisfies both the Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure and HBIPS-7. Therefore a hospital could abstract data for and comply with HBIPS-7 by also complying with and abstracting data for the Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure. Furthermore, although we believe that high-quality data is important, we note that the point of this measure is timeliness. As we explain above, studies show that the risks of re-hospitalization are lower when primary care providers have access to patients' post-discharge records at the first post-discharge visit,[66 67] which may be within a day (or days) of discharge. Additionally, the AMA-PCPI maintains, and we agree, that studies have documented the prevalence of communication gaps and discontinuities in care for patients after discharge and the significant effect of these lapses on hospital readmissions and other indicators of the quality of transitional care.[68] Therefore, we believe that the 24-hour window is critical to quality improvement and that the benefit of the removal of HBIPS-7 and the adoption of the Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure outweighs any associated burden and further the goals of the IPFQR Program. Furthermore, we do not agree with commenters that it is “impossible” for providers to meet the 24-hour transmission requirement; the NQF specifically reviews a measure for feasibility and has endorsed this measure. Thus, we believe this measure Start Printed Page 46708can be implemented. In addition, although some patients are not seen in 24-hours, some are, and we believe that their records should be available to the next-level provider. Finally, as explained below, we do not believe this measure presents any confidentiality issues.

Additionally, we note that the additional elements that commenters state are required by this measure are actually required by the measure we are adopting above, NQF #0647. In addition, the need for “more stringent documentation of medications,” is found in the measure we are removing above, HBIPS-6. We discuss any issues associated with the measures in that section. We believe the only additional burden when comparing this measure to HBIPS-7 is the decreased timeline. In addition, the measure was developed with a broad range of inpatient settings in mind and did not specifically exclude IPFs; the measure developer is considering explicitly including the IPF-setting in the next round of measure maintenance so that the measure is endorsed not only for all inpatient settings, but explicitly states that it is endorsed for the IPF-setting.

We do not agree that replacing this measure will upset quality improvement efforts begun by HBIPS-7. If IPFs have already begun quality improvement in this area, we believe it will continue and even surpass the current state because the proposed measure is even more robust. We also disagree that the data may not be meaningful because, when posted on Hospital Compare, the data will include all IPFs participating in the IPFQR Program, thus allowing consumers to meaningfully compare the quality of care provided by each IPF participating in the program.

Finally, although we believe this measure to be a critical indicator of quality care, we understand that the change from requiring the document within 5 days of discharge to within 24 hours may initially prove operationally difficult for providers. Therefore, we will only require IPFs to report the last two quarters of data for this measure for the FY 2018 payment determination; that is, providers will only be required to report data for July 1, 2016-December 31, 2016. Beginning with the FY 2019 payment determination, IPFs will be required to report all four quarters of data or will face a payment reduction.

Comment: Some commenters noted that it could be problematic to implement this measure if a patient is discharged on a weekend. Commenters noted that some of the discharge planning resources such as social workers and case managers are not present to support the inpatient discharge process and many offices are closed on Saturday and Sunday. One commenter noted that some providers turn off their fax machines on weekends. Other commenters stated that 24 hours is not realistic even on weekdays because EHRs across systems are not yet a reality, and the measure may require providers to modify their EHRs. One commenter also noted that some community mental health clinics may not be able to receive the transition document, noting that quality care may not be improved if the next-level care provider is overloaded or unable to provide the necessary care. Commenters requested that CMS amend the measure to allow more time for transmission, with one commenter urging that 3 days is a more reasonable timeline.

Response: As stated above, we believe that the 24-hour window is critical to this measure. Furthermore, we note that the measure only requires transmission of the record, not receipt of the record. The “transition record may be transmitted to the facility or physician or other health care professional designated for follow-up care via fax, secure email, or mutual access to an electronic health record (EHR).” [69] Thus, the measure can be satisfied even if an office is closed. Finally, we are not aware of any specific EHR changes that would need to be made to accommodate this measure, because the measure need not be transmitted as an EHR.

Comment: Commenters expressed concern that the Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure is not stratified by age, which limits the usefulness of the data, given the variation across populations.

Response: As stated above, when feasible and practicable, we believe it is important to implement measures as they are specified, especially where, as here, such measures are NQF-endorsed. This measure is not specified to be reported by age. Furthermore, we believe that presenting the measure as an aggregate number rather than stratified by age will allow greater rather than less insight into these data because, as further explained in section V.F.1. of this final rule, the resultant number of cases is often too small to allow public reporting when data are stratified by age.

Comment: One commenter stated that this measure violates HIPAA because patients have no control over how the next-level provider will use the discharge record and noted that the same measure was suspended from the Hospital OQR Program for privacy concerns.

Response: Neither we nor the measure developer are aware of any provision of HIPAA that this measure would violate. Furthermore, we believe the commenter is incorrect. The Hospital OQR Program adopted and finalized NQF #0649 Transition Record with Specified Elements Received by Discharged Patients (Emergency Department Discharges to Ambulatory Care [Home/Self Care] or Home Health Care). Although this measure, NQF #0648, is also stewarded by the AMA-PCPI and requires a transition record, it is not the same as NQF #0649. The measures differ in regards to the location from which the patient is discharged; specifically, NQF #0649 measures discharges from the emergency department, while NQF #0648 measures discharges from an inpatient facility. We believe that this difference is critical because the circumstances surrounding discharge from an emergency department are typically not planned; that is, a patient is discharged the same day he/she arrives with the individual that brought him/her to the emergency room, whom a patient may or may not feel comfortable sharing information. Those discharged from an inpatient setting usually have advanced notice and can plan accordingly. Thus, we do not believe, and neither does the AMA-PCPI, that NQF #0648 raises any of the privacy concerns articulated by the Hospital OQR Program for #0649.

Comment: One commenter stated that many patients do not have follow-up care, and, therefore, suggested that the measure should specify that the record be provided to family members or other caregivers when appropriate.

Response: We note that we are adopting the Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure above, which requires transmission of the transition record to the patient. We believe this measure will allow family members and caregivers the opportunity to understand the discharge information if the patient wishes to share such information.

For the reasons stated above, we are finalizing our proposal to adopt the Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure and remove HBIPS-7: Post Discharge Continuing Start Printed Page 46709Care Plan Transmitted to the Next Level of Care Provider Upon Discharge for the FY 2018 payment determination and subsequent years with one modification. For the FY 2018 payment determination, we will only require IPFs to report data for this measure for the last two quarters of the reporting period (July 1, 2016-December 1, 2016). Beginning with the FY 2019 payment determination, IPFs will be required to report all four quarters of data.

5. Screening for Metabolic Disorders

Studies show that both second generation antipsychotics (SGAs) and antipsychotics increase the risk of metabolic syndrome.[70] Metabolic syndrome involves a cluster of conditions that occur together, including excess body fat around the waist, high blood sugar, high cholesterol, and high blood pressure, and increases the risk of coronary artery disease, stroke, and type 2 diabetes. Recognizing this problem, in February 2004, the American Diabetes Association (ADA), the American Psychiatric Association (APA), the American Association of Clinical Endocrinologists, and the North American Association for the Study of Obesity released a consensus statement finding that the use of SGAs “have been associated with reports of dramatic weight gain, diabetes (even acute metabolic decompensation, for example, diabetic ketoacidosis [DKA]), and an atherogenic lipid profile (increased LDL cholesterol and triglyceride levels and decreased HDL cholesterol) . . . [and] [s]ubsequent drug surveillance and retrospective database analyses suggest that there is an association between specific SGAs and both diabetes and obesity.” [71] SGAs also have an effect on serum lipids and could result in dyslipidemia.[72] Given these concerns, the group recommended that “baseline screening measures be obtained before, or as soon as clinically feasible after, the initiation of any antipsychotic medication,” including body mass index (BMI), blood pressure, fasting plasma glucose, and fasting lipid profile.[73] Although the consensus statement specifically discussed the issues with SGAs, the ADA also emphasized that “all patients receiving antipsychotic medications [should] be screened” [74] and subsequent studies have found that “[i]n schizophrenic patients, the level of lipid profile had been increased in both atypical and conventional antipsychotic users” [75]

Numerous other organizations have also made similar recommendations.[76] For example, the National Association of State Mental Health Program Directors Medical Directors Council notes, “the second generation antipsychotic medications have become more highly associated with weight gain, diabetes, dyslipidemia, insulin resistance, and the metabolic syndrome.” They recommend the same screening as the consensus statement (BMI, blood pressure, fasting plasma glucose, and fasting lipid profile) and emphasize that this screening is “the standard of care for the general population.” [77] Likewise, the Mount Sinai Conference,[78] convened in 2002, recommended that, for every patient with schizophrenia, “regardless of the antipsychotic prescribed,” mental health providers should, among other things: (1) Monitor and chart BMI; (2) measure plasma glucose levels (fasting or HbA1c); and (3) obtain a lipid profile.[79]

Despite these consensus statements and guidelines, many of which are over a decade old, screening for metabolic syndrome remains low and there appears to be disagreement regarding where the responsibility for this screening lies.[80] Studies show a systematic lack of metabolic risk monitoring of patients who have been prescribed antipsychotics.[81] Screening for metabolic syndrome may reduce the risk of preventable adverse events and improve the physical health status of the patient. Therefore, we stated our belief that it is necessary to include a measure of metabolic syndrome screening in the IPFQR Program.

The Screening for Metabolic Disorders measure is a chart-abstracted measure developed by CMS and defined as a percentage of discharges from an IPF for which a structured metabolic screening for 4 elements was completed in the past year. The denominator includes IPF patients discharged with one or more routinely scheduled antipsychotic medications during the measurement period. The numerator is the total number of patients who received a metabolic screening either prior to, or during, the index IPF stay. The screening must contain four tests: (1) BMI; (2) blood pressure; (3) glucose or HbA1c; and (4) a lipid panel—which includes total cholesterol (TC), triglycerides (TG), high density lipoprotein (HDL), and low density lipoprotein (LDL-C) levels. The screening must have been completed at least once in the 12 months prior to the patient's date of discharge. Screenings can be conducted either at the reporting facility or another facility for which records are available to the reporting facility. The following patients are excluded from the measure: (1) Patients for whom a screening could not be completed within the stay due to the patient's enduring unstable medical or Start Printed Page 46710psychological condition; and (2) patients with a length of stay equal to or greater than 365 days, or less than 3 days. In section V.F.3. of this final rule, we finalize a sampling methodology for this and certain other measures.

Testing of this measure demonstrated that performance on the metabolic screening measure was low, on average, across the tested IPFs. The measure's average performance rate of 42 percent signals a strong opportunity for improvement. During testing, the metabolic screening measure also demonstrated nontrivial variation in performance among IPFs (6.2-98.6 percent). In addition, it demonstrated near-perfect agreement between chart abstractors (kappa of 0.93 for the measure numerator).[82]

We included the Screening for Metabolic Disorders measure (then titled “IPF Metabolic Screening”) in our “Measures Under Consideration List” in December 2013. The MAP did not recommend this measure, noting, “a different NQF-endorsed measure better addresses the needs of the program.” [83] However, the different NQF-endorsed measure was not identified by the MAP, and we stated that we are unaware of any screening measures for metabolic syndrome that are NQF-endorsed. We noted that, when presented to the MAP, the denominator for this measure was the “total number of psychiatric inpatients admitted during the measurement period.” Based on testing and further feedback on the measure, we revised the measure by reducing its application to only those patients on antipsychotic medication; the denominator for the measure is now “IPF patients discharged with one or more routinely scheduled antipsychotic medications during the measurement period.” We stated our belief that this change was appropriate because, as discussed above, the patients most at risk for metabolic syndrome are those receiving antipsychotics, and the APA and other consensus organizations recommend this screening for patients on antipsychotics. Furthermore, we stated our belief that we, by limiting the application of the measure only to those receiving antipsychotics, have reduced provider burden, both in terms of possible changes in practice that might result from the measure, as well as the direct burden resulting from its collection and reporting.

We also stated our belief that this measure promotes the National Quality Strategy priority of Making Care Safer, which seeks to reduce risk that is caused by the delivery of healthcare. As discussed above, antipsychotics have been shown to be related to metabolic syndrome. The Screening for Metabolic Disorders measure is aimed at the prevention and treatment of serious side effects of these drugs.

Section 1886(s)(4)(D)(ii) of the Act authorizes the Secretary to specify a measure that is not endorsed by NQF as long as due consideration is given to measures that have been endorsed or adopted by a consensus organization identified by the Secretary. We have been unable to identify any measures addressing screening for metabolic syndrome for the IPF setting that have been endorsed by the NQF or adopted by any other consensus organization. We stated our belief that the proposed measure for the Screening for Metabolic Disorders meets the measure selection exception requirement under section 1886(s)(4)(D)(ii) of the Act.

For the reasons stated above, we proposed to adopt the Screening for Metabolic Disorders measure beginning with the FY 2018 payment determination. We welcomed public comments on this proposal. The comments we received and our responses are set forth below.

Comment: Comments submitted from a consumer perspective supported this measure, noting that it is imperative to treat co-occurring conditions. Furthermore, these commenters noted that this measure has some potential to connect the “physical health care provider to the psychiatric services provider”, and metabolic screening is an important area of follow-up that will improve patient outcomes. These commenters also made the following recommendations: (1) The measure should also include reviewing the results of the screening with the patient; (2) the measure should require further cardiovascular disease testing be performed if the screening indicates that it is warranted; (3) the measure should refer patients to the appropriate cardiovascular specialist, if needed; (4) the measure should include all patients receiving mental health treatment; (5) individuals for whom a screening cannot be completed within the stay “due to the patient's enduring unstable medical or psychological condition” should not be discharged until such a screening can occur since these individuals are arguably at greatest risk and their conditions should be stabilized before discharged; (6) for individuals excluded because of a length of stay of less than 3 days, the need for screening should be clearly identified as part of the discharge planning record so that this takes place on an outpatient basis; and (7) the rationale for excluding individuals who are hospitalized for 365 days or more be explained or removed.

Response: We thank commenters for their support and will address each of these recommendations in turn. First, we agree with the importance of the processes of care described by the commenters (that is, recommendations 1-4). However, the current measure, as specified and tested, addresses only the screening for metabolic abnormalities. We believe that this measure is an important first step in metabolic screening, and we will consider additional measures that address any necessary follow-up care in future years. Furthermore, we believe that other measures we are adopting, Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) and Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care), address the communication of specific information to the next care provider, such as major procedures and tests performed during inpatient stay and summary of results.

The exclusion “due to the patient's enduring unstable medical or psychological condition” is harmonized with other screening measures developed by the Joint Commission for the IPF setting. This exclusion was reviewed and supported by a Technical Expert Panel and an Expert Workgroup.[84] Additionally, during the testing of this measure, the exclusion applied to only one patient (0.2% of sample) indicating that the exclusion would be rare and only applied in the most severe cases where screening could not be conducted. Therefore, we will retain the exclusion and further evaluate the frequency of the exclusion with data from implementation.

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Patients with stays of fewer than 3 days were excluded from the metabolic screening measure based on the rationale that IPFs could not be expected to complete all metabolic screening tests (or verify that they were completed elsewhere within the previous 12 months) within that short time period. Therefore, we believe that we should retain this exclusion as specified.

Finally, as noted above, the screening must have been completed at least once in the 12 months prior to the patient's date of discharge. Thus, an IPF need only consider the past 12 months of records for a patient after that patient is discharged. Since this lookback is one year, we do not believe we should include patients who have been at the facility for more than one year. Furthermore, based on our testing of this measure, we believe this exclusion will be negligible, applying to less than 1.5 percent of the population. Therefore, we will retain the exclusion and further evaluate the frequency of the exclusion with data from implementation.

Comment: One commenter suggested that the ADA Consensus guidelines recommended a lipid profile every 5 years while the Screening for Metabolic Disorders measure requires a lipid profile every year, creating unnecessary costs. This commenter recommended that the measure be changed to require lipid panels every 5 years.

Response: The ADA Consensus guidelines from 2004 recommended that “in those with normal lipid profile, repeat testing should be performed at 5-year intervals or more frequently if clinically indicated.[85] More recent recommendations, however, indicate yearly monitoring is preferred throughout treatment.[86 87 88] Therefore, to ensure appropriate screening and monitoring for patients on routinely scheduled antipsychotic medication(s), we believe that IPFs need to obtain either documentation of metabolic screening performed in the past 12 months or conduct the lipid panel testing prior to a patient's discharge from the facility.

Comment: Some commenters stated that the purpose of the ADA Consensus guidelines is to ensure long-term monitoring rather than annual screening and suggested that, as such, monitoring should be done in an outpatient rather than inpatient setting. One commenter suggested that the measure should be modified so that IPFs are required to communicate any baseline or ongoing screening tests with the outpatient provider who is assuming the management of medications at discharge.

Response: Although we agree that long-term metabolic monitoring of psychiatric patients is important, studies indicate that 40 percent to 80 percent of patients fail to find outpatient treatment after discharge from the inpatient setting.[89] In addition, studies find consistently low adherence rates to metabolic screening guidelines.[90 91] These studies are confirmed by empirical analysis of calendar year 2012 and 2013 Medicare claims data, which indicated that only 53.8 percent of patients discharged from an IPF with at least two prescription claims for antipsychotic medications had at least one lipid panel annually in the outpatient setting.[92] Therefore, although we agree that the long-term monitoring for individuals is appropriate in the outpatient setting, we believe that the inpatient setting represents a clear opportunity to screen patients. We do believe it is important to convey test results to the next-level care provider, and we believe that the additional measures that we are adopting, Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) and Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care), should facilitate the communication of such information.

Comment: Many commenters recommended that CMS not adopt the Screening for Metabolic Disorders measure at the present time, but, instead suggested that CMS propose the measure after it has been tested and NQF-endorsed with full specifications available. Some commenters questioned why CMS did not take the measure through the NQF-endorsement process, arguing that premature adoption may cause discrepancies between what the IPFQR Program implements and what NQF ultimately endorses. One commenter urged us to share the measure with the IPF TEP and other stakeholders. One commenter stated that the TEP convened to evaluate the measure made several important recommendations to amend the measure and recommended that, if the measure is adopted, it should include these recommendations. Another commenter noted that the measure was only tested among six facilities.

Response: The measure has been finalized for NQF submission and will be submitted during the next call for behavioral health measures, which is expected in calendar year 2016. The measure specifications were evaluated by two separate Technical Expert Panels and an Expert Workgroup. The recommendations from these experts have been incorporated into the measure definitions. Although we agree that NQF endorsement of a measure is preferred, we are permitted to include a measure that has not been NQF-endorsed under section 1886(s)(4)(D)(ii) of the Act. Under that section, the Secretary is authorized to specify a measure that is not endorsed by the NQF as long as due consideration is given to measures that have been endorsed or adopted by a consensus organization identified by the Secretary. We attempted to find available measures that had been endorsed or adopted by a consensus organization and found no other feasible and practical measures on the topic of metabolic screening for patients taking antipsychotics in the IPF setting. We believe that this area is important, specifically because of the gaps in treatment, and we believe it is important to implement a measure of metabolic screening as soon as possible.

We acknowledge that testing for this measure occurred in six facilities; however the facilities selected represent a variety of facility types from across the Start Printed Page 46712country. These facilities are diverse in both structure and size. Three of the IPFs selected are private psychiatric units with fewer than 50 patient beds, two are public freestanding facilities with over 100 beds, and one is a private freestanding facility with 400 beds. In addition, the six IPFs were geographically distributed by region including Mid-Atlantic, Northeast, Midwest, South, and West.[93] Therefore, we believe this testing was adequate to evaluate the measure.

Comment: Many commenters expressed concern that the measure adds significant burden for providers. Specifically, they suggested that IPFs involved in measure testing verified that chart-abstraction of this measure was more intensive than the other screening measures; they also expressed concern that the additional lab tests required by this measure may not be fully reimbursed by CMS, stating that most lab tests cost between $30 and $50. One commenter noted that, because the measure allows screenings at another facility, the measures may increase burden not only to the immediate facility, but potentially to other facilities.

Response: In testing the measure, the abstraction time for this measure did not exceed 20 minutes for any given discharge, which is only slightly more time (5 minutes more) than the measures previously adopted by this program (79 FR 45979). Furthermore, the CMS-convened Screening of Metabolic Disorders Measure Workgroup reviewed this measure and the majority of members indicated that the costs of any duplicate testing would have minimal unintended consequences.[94] Finally, we believe that transmitting records between providers for the purpose of improving patient care is an essential component of effective care coordination and communication of previously delivered care, and, therefore, the benefits of such communication outweigh any associated burden.

Comment: Many commenters stated that they could not comment on the measure without full specifications, noting that many issues remained unclear, including: (1) If the measure allows for patient refusal of a screening; (2) how the measure addresses “fasting” bloodwork protocols; (3) how the measure addresses patients with changes in antipsychotic medication; (4) how the measure avoids unnecessary testing requirements for patients previously screened but whose records are unobtainable within a reasonable period of time; (5) how screening records “available to the reporting facility” from another facility is defined; (6) if the measure identified all appropriate patient exclusions; (7) if there are potential medical necessity issues that need to be addressed; (8) the actionability of the measure during a short-term hospitalization; (9) if the public reporting of a screening measure rate a measure of quality that will help the public differentiate among facilities; and (10) if the measure reflects an appropriate application of various practice guidelines from the perspective of the guideline developers.

Response: We agree with commenters that elements in the measure need to be clarified. We will take each of these issues in turn.

First, as stated above, we believe that patient compliance is indicative of quality care. That is, we maintain that it is important that providers understand gaps in patient compliance so that they can modify their actions and policy to systematically encourage patients to receive appropriate tests. We encourage providers to educate patients about the importance of these screenings, and we, therefore, will not exclude patients who refuse the screening.

Second, the emphasis in this measure is on the screening itself rather than the associated measure values. Clinical judgments about the best methods for conducting and interpreting the testing, including whether to use fasting glucose or an HbA1c test, are left to the facility.

Third, since all antipsychotic medication regimens require regular monitoring,[95 96] we will not distinguish between patients whose antipsychotic regimens have changed during the inpatient stay.

Fourth, we agree that avoiding unnecessary testing requirements is an important consideration. But, as stated above, 40 percent to 80 percent of psychiatric patients fail to receive outpatient treatment,[97] and an analysis conducted of calendar year 2012 and 2013 claims data indicated that a little over half of patients taking antipsychotics had a lipid panel conducted annually in the outpatient setting.[98] Therefore, we believe it is important to conduct this testing in the inpatient setting, even if some duplication may result because the testing conducted in another setting was not obtainable.

Fifth, we believe that there are potentially multiple sources available to facilities to obtain testing results conducted by other providers and the phrase “available to the reporting facility” is not meant to limit the method of obtaining numerical lab results within the previous 12 months of the index discharge for evidence of screening. To fulfill the measure requirements, evidence of screening includes presence/absence of each screening element, based on the chart review and documentation of lab results (numeric values) in the medical record.

Sixth, we believe the measure incorporates all appropriate patient exclusions taking into consideration the comments provided by the TEPs and Screening of Metabolic Disorders Measure Workgroup.

Seventh, we believe it is important to treat the whole patient by addressing both the mental and the physical needs of patients in the IPF and guideline recommendations indicate yearly monitoring is preferred throughout treatment for patients taking antipsychotic medications.[99 100 101]

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Eighth, we believe that even short-term hospitalizations provide an opportunity for providing the best quality care for patients. As we state above, the inpatient setting represents a clear opportunity to screen patients and may be the only opportunity some patients have for this screening. We recognize, however, that obtaining the records or conducting the screening of very short-stay patients might be too difficult for the IPF, and therefore, patients with lengths of stay of less than 3 days is an exclusion in the measure.

Ninth, we believe a vital component of the CMS quality reporting programs is the public reporting of the information to inform patients and caregivers of differences in quality across providers. We believe that this measure will inform patients and caregivers of the quality of care in IPFs in terms of the screening for metabolic disorders among patients taking antipsychotic medications. Among the six test facilities, there was an average performance score of 41.5 percent, with a wide range of performance from 6.2 percent to 98.6 percent.[102]

Tenth, the measure is aligned with clinical practice guidelines for patients taking antipsychotic medications.[103 104 105] .

We recognize it may take time for providers to review and understand these clarifications and changes to the measure. Therefore, we will only require IPFs to report the last two quarters of data for this measure for the FY 2018 payment determination; that is, providers will only be required to report data for this measure for July 1, 2016-December 31, 2016. Beginning with the FY 2019 payment determination, IPFs will be required to report all four quarters of data or will face a payment reduction.

Comment: Many commenters noted that, although the measure allows IPFs to obtain data from outside sources, because of the cost of doing so, most would complete the testing themselves, unnecessarily increasing costs and leading to an overutilization of tests. One commenter stated its belief that it will be difficult to determine the patients that were on one antipsychotic medication in the past year and suggested, instead, that the measure be limited to the four antipsychotic medications that contribute to metabolic disorders, Clozaril, Seroquel, Zyprexa, and Risperdal, indicating that these medications should have a metabolic screening every 3 months, which would be easier to monitor.

Response: The Screening of Metabolic Disorders Measure Workgroup reviewed this measure and the majority of members indicated that the costs of any duplicate testing would have minimal unintended consequences based on data that only about half of the patients discharged from an IPF had at least one annual screening.[106] Furthermore, studies suggest that antipsychotic-induced weight gain occurs in all diagnostic groups and is common in both first and second generation antipsychotics.[107 108 109 110] Generally, guidelines recommending monitoring do not distinguish their recommendations based on first or second generation antipsychotics.[111 112 113] Therefore, although it may be less burdensome to monitor the four antipsychotics the commenter suggested above, based on the heightened risk of metabolic disorders in this population, we believe this measure should apply to all patients on any antipsychotic regimen.

For the reasons stated above, we are finalizing our proposal to adopt the Screening for Metabolic Disorders measure for the FY 2018 payment determination and subsequent years with one modification. For the FY 2018 payment determination, we will only require IPFs to report data for this measure for the last two quarters of the reporting period (July 1, 2016-December 1, 2016). Beginning with the FY 2019 payment determination, IPFs will be required to report all four quarters of data.

6. Summary of Measures for the FY 2018 Payment Determination and Subsequent Years

The measures that we are adopting for the IPFQR Program for the FY 2018 payment determination and subsequent years are set forth in Table 20.

Table 20—New IPFQR Program Measures for the FY 2018 Payment Determination and Subsequent Years

National Quality Strategy PriorityNQF #Measure IDMeasure
Effective Prevention and Treatment1656TOB-3 and TOB-3aTobacco Use Treatment Provided or Offered at Discharge and the subset measure Tobacco Use Treatment at Discharge.
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Effective Prevention and Treatment1663SUB-2 and SUB-2aAlcohol Use Brief Intervention Provided or Offered and SUB-2a Alcohol Use Brief Intervention.
Communication and Care Coordination; Person and Family Engagement0647N/ATransition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care).
Communication and Care Coordination0648N/ATimely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care).
Making Care SaferN/AN/AScreening for Metabolic Disorders.

The measures that we are removing beginning with the FY 2018 payment determination are set forth in Table 21.

Table 21—IPFQR Program Measures To Be Removed for the FY 2018 Payment Determination and Subsequent Years

NQF #Measure IDMeasure
0557HBIPS-6Post-Discharge Continuing Care Plan.
0558HBIPS-7Post Discharge Continuing Care Plan Transmitted to the Next Level of Care Provider Upon Discharge.

Therefore, the number of measures for the FY 2018 IPFQR Program and subsequent years will total 16, as set forth in Table 22.

Table 22—Measures for FY 2018 Payment Determination and Subsequent Years

NQF #Measure IDMeasure
0640HBIPS-2Hours of Physical Restraint Use.
0641HBIPS-3Hours of Seclusion Use.
0560HBIPS-5Patients Discharged on Multiple Antipsychotic Medications with Appropriate Justification.
0576FUHFollow-up After Hospitalization for Mental Illness.
1661SUB-1Alcohol Use Screening.
1663SUB-2 and SUB-2aAlcohol Use Brief Intervention Provided or Offered and SUB-2a Alcohol Use Brief Intervention.*
1651TOB-1Tobacco Use Screening.
1654TOB-2 TOB-2aTobacco Use Treatment Provided or Offered and Tobacco Use Treatment.
1656TOB-3 and TOB-3aTobacco Use Treatment Provided or Offered at Discharge and the subset measure Tobacco Use Treatment at Discharge.*
1659IMM-2Influenza Immunization.
0647N/ATransition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care).*
0648N/ATimely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care).*
N/AN/AScreening for Metabolic Disorders.*
N/AN/AInfluenza Vaccination Coverage Among Healthcare Personnel.
N/AN/AAssessment of Patient Experience of Care.
N/AN/AUse of an Electronic Health Record.
* New measures finalized for the FY 2018 payment determination and future years.

E. Possible IPFQR Program Measures and Topics for Future Consideration

As we have previously indicated (79 FR 45974 through 45975), we seek to develop a comprehensive set of quality measures to be available for widespread use for informed decision-making and quality improvement in the IPF setting. Therefore, through future rulemaking, we intend to propose new measures for development or adoption that will help further our goals of achieving better health care and improved health for Medicare beneficiaries who obtain inpatient psychiatric services through the widespread dissemination and use of quality information.

We are developing a 30-day psychiatric readmission measure that is similar to the readmission measures Start Printed Page 46715currently in use in other CMS quality reporting programs, such as the Hospital Inpatient Quality Reporting Program. In the future, we intend to develop a measure set that effectively assesses IPF quality across the range of services and diagnoses, encompasses all of the goals of the CMS quality strategy, addresses measure gaps identified by the MAP and others, and minimizes collection and reporting burden. We may also propose the removal of some measures in the future.

We welcomed public comments on possible new measures. The comments we received and our responses are set forth below.

Comment: One commenter expressed concern that CMS proposed time-intensive, chart-abstracted measures without discussing a future goal of working toward electronic submission of these measures.

Response: We agree that moving to electronic clinical quality measures is important and will ultimately reduce burden. At this time, we are not operationally able to implement electronic clinical quality measure reporting and not all of our measures are electronically specified. However, we continue to work toward transitioning to electronic clinical quality measures in the future.

Comment: Commenters urged the program not to burden providers with too many process measures and to move toward the use of outcome measures since these measures are more meaningful to patients and can have a greater impact on provider behavior. Some commenters specifically supported a readmissions measure, noting that such measure should focus on readmissions that are clinically related to the index admission and potentially preventable by the IPF. Commenters expressed concern that the IPF population is complex, with patients often having multiple comorbid mental health, substance abuse, and other medical conditions, and outpatient compliance is challenging. Therefore, commenters suggested that CMS adjust the measure for sociodemographic variables and work to ensure that the readmissions measure is adequately adjusted for case mix and provider type in order to more accurately capture and report readmission rates in an unbiased way, particularly for those hospitals that treat the most vulnerable patients. One commenter cautioned that a readmission measure can be gamed if it does not include all readmissions to the acute care system within a specified window. Another commenter noted that to accurately risk adjust a readmissions measure, the program may need to collect patient assessment data. Commenters also encouraged us to adopt a readmission measure only if it is NQF-endorsed for the IPF setting and has broad stakeholder support that considers important components of measures, including reliability, validity, feasibility of implementation, and stakeholders' and clinicians' input. Several commenters questioned whether the measure could be adequately risk-adjusted using claims and suggested a thorough NQF review to determine if claims-based measures can be accurately risk-adjusted for mental health patients. Another commenter encouraged us to ensure the measure does not incentivize facilities to deny admissions to meet the quality measurement.

Response: When appropriate, we strive to move toward measures of outcome and will consider these measures for future years of the program. Specifically, we believe a measure of readmissions to be important and will consider these important issues raised by commenters as we move forward with developing such a measure.

Comment: One commenter recommended including psychiatric patients in the HCAHPS survey rather than creating a survey just for the IPF population, noting that the HCAHPS survey is applicable to IPF patients, these patients can answer the questions in the HCAHPS survey, and creating a new survey would be overly burdensome. Other commenters, however, recommended developing a patient experience of care measure specified for psychiatric patients.

Response: We thank the commenters for their recommendations. We believe that patient and family engagement measures are important, and we will consider this suggestion in the future.

Comment: Commenters recommended the following measures for future consideration: (1) Number of hours before the individual was seen by a psychiatrist; (2) number of hours before the individual was transferred to a facility where he/she would receive appropriate treatment; (3) readmission to the same IPF within 30 days of discharge; (4) improved functioning or stabilization of functioning as measures through clinical assessment, patient self-assessment, or discharge to lower level of care; (5) receiving best practices specific to the conditions noted in the treatment plan as well as acuity of illness; (6) scheduled appointment for aftercare within 7 days of discharge, controlling for urban/rural area and type of provider, at minimum; (7) documentation of follow-up mental health services in the community within 14 days of discharge; (8) reduced payment rates for readmissions to psychiatric hospitals after discharge; (9) a change score on a standardized measure of psychiatric functioning to demonstrate the impact of hospitalization on a patient admitted to the IPF; and (10) length of stay.

Response: We thank the commenters for their recommendations and will consider them in the future.

Comment: One commenter encouraged CMS to consider adding staff-level related measures, specifically NQF #0205: Nursing Hours per Patient Day, since nursing and staff time contribute to a large amount of IPF costs and freestanding locations have a larger percentage of labor costs than IRFs or LTCHs.

Response: We thank the commenter for its recommendation and will consider such measures in the future.

Comment: Some commenters recommended CMS include HBIPS-1 in future years of the program since the measure will increase compliance with admission screening and will not increase burden to providers that report data to The Joint Commission.

Response: We thank the commenters for their recommendation and will consider it in the future.

F. Changes to Reporting Requirements

We are making the following changes to our reporting requirements for FY 2017 and subsequent years:

  • Requiring that measures be reported as a single yearly count rather than by quarter and age; and
  • Requiring that aggregate population counts be reported as a single yearly number rather than by quarter.

For FY 2018 and subsequent years we are also making one change, allowing uniform sampling requirements for certain measures.

1. Changes to Reporting by Age and Quarter for the FY 2017 Payment Determination and Subsequent Years

In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53655 through 53656), we finalized our policy that IPFs must submit data for chart-abstracted measures to the Web-Based Measures Tool on an annual basis aggregated by quarter. We also finalized our policy that IPFs must submit data as required by The Joint Commission, which calls for IPFs to submit data for measures by age group. Since then, we have learned that obtaining data for each quarter and by age is burdensome to providers and the resultant number of cases is often too small to allow public reporting. That Start Printed Page 46716is, we do not report data on Hospital Compare for measures with fewer than 11 cases; reporting by age and quarter often causes the number of cases to fall below 11. For example, for HBIPS-5, in Quarter 2 of 2013, only 5.75 percent of the data were reportable. Likewise, in Quarter 3 and Quarter 4 of 2013, for HBIPS-5, only 5.5 percent of the data were reportable.

Therefore, beginning with the FY 2017 payment determination, we proposed to require facilities to report data for chart-abstracted measures to the Web-Based Measures Tool on an aggregate basis by year, rather than by quarter, and to discontinue the requirement for reporting by age group. We proposed to require IPFs to report a single aggregate measure rate for each measure annually for each payment determination.

We stated our belief that this change will reduce provider burden because IPFs would report a single rate for each measure. In addition, we stated that we do not believe that quarterly data or data stratified by age are necessary for quality improvement activities. We are able to differentiate, and the public is able to view on Hospital Compare, those IPFs that perform well on measures from those for which quality improvement activities may be necessary based on an annual aggregate rate submission. We noted, however, that in the future, if our evolving measures set, quality improvement goals, and experience with the program indicate a change is needed, we may reevaluate and reinstate the requirement for quarterly reporting.

We welcomed public comments on this proposal. The comments we received and our responses are set forth below.

Comment: Many commenters supported this proposal, noting that IPFs will more easily be able to comply with reporting aggregate population as a single yearly count rather than by quarter and by age, and the proposal will improve the usability of the public display data.

Response: We thank commenters for their support.

Comment: Many commenters did not support the proposal, stating that submitting data by year rather than quarter will not decrease burden since it requires the same number of abstractions, is contrary to the national desire to have more current data, would reduce the ability of consumers to know if there are lower measure rates for certain age groups, and would decrease the ability to monitor trends over the year and by age. Other commenters suggested that we continue to work to improve the report format for consumers and consider allowing providers to report on a quarterly basis without segregating the measure by age so that we can publicly report data closer to real time. Many commenters requested that we convene TEPs to identify the best ways to reduce reporting burden.

Response: We believe that reporting data yearly and no longer reporting by age will be easier for IPFs because it will decrease the number of values reported from 16 numbers (that is, four age groups multiplied by four quarters) to 1 number for every measure, leading to an aggregate decrease of 210 values per year. Furthermore, although the public will no longer be able to view data by age, we believe that submitting and reporting data as an aggregate number will increase rather than decrease the ability to monitor trends, since, as we explain above, doing so will increase the number of cases that are reported and that we are, therefore, able to report on Hospital Compare. Finally, although we are not operationally able to implement them at this time, we will continue to consider commenters' suggestions to modify our reporting structures to allow more consumer-friendly interfaces and real-time data entry and viewing. We will also consider the suggestion that we convene TEPs to identify ways to reduce provider burden.

Comment: Some commenters contended that this change in methodology will only affect HBIPS-5, and stated that changing a methodology to improve reporting on one measure is ineffective, specifically because the change will not reduce provider burden since providers will still be required to submit this data to The Joint Commission by age and quarter. These commenters stated that it may be more effective and efficient to report HBIPS-5 by year rather than changing the data collection methodology.

Response: We do not agree that the reporting change is limited to HBIPS-5. Although the example provided in the proposed rule only includes HBIPS-5, we believe that, as we collect more data, specifically data on measures that we adopted last year and for which we will be collecting data this summer, values that do not meet minimum reporting thresholds as a result of age and quarter stratification will exist across measures. Additionally, although we acknowledge that many IPFs may report data to The Joint Commission by age and quarter, we believe the burden required to aggregate these numbers is minimal.

For the reasons stated above, we are finalizing our proposal to require facilities to report data for chart-abstracted measures to the Web-Based Measures Tool on an aggregate basis by year, rather than by quarter, and to discontinue the requirement for reporting by age group beginning with the FY 2017 payment determination. In Table 23, we set forth the quality reporting and submission timelines for the FY 2017 payment determination and subsequent years for all the measures except FUH and the Influenza Vaccination Coverage among Healthcare Personnel measures.

Table 23—Quality Reporting Periods and Timeframes for the FY 2017 Payment Determination and Subsequent Years

Payment determination (FY)Reporting period for services providedData submission timeframe
2017January 1, 2015-December 31, 2015July 1, 2016-August 15, 2016.

In Table 24, we set forth the quality reporting and submission timelines for the FY 2018 payment determination and subsequent years for all the measures except FUH and the Influenza Vaccination Coverage among Healthcare Personnel measures. We note that FUH is claims-based, and therefore does not require additional data submission. The Influenza Vaccination Coverage among Healthcare Personnel measure is reported to the Centers for Disease Control and Prevention's National Healthcare Safety Network, and we refer readers to the FY 2015 IPF PPS final rule for more information on the reporting timeline for this measure (79 FR 45969). In addition, we note that, as finalized above, for the Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care), Timely Transmission of Start Printed Page 46717Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care), and Screening for Metabolic Disorders measures, we are only requiring facilities to report data for July 1, 2016-December 31, 2016 for the FY 2018 payment determination.

Table 24—Quality Reporting Periods and Timeframes for the FY 2018 Payment Determination and Subsequent Years

Payment determination (FY)Reporting period for services providedData submission timeframe
2018For All Measures Except NQF #0647, NQF #0648, and Screening for Metabolic DisordersJanuary 1, 2016-December 31, 2016July 1, 2017-August 15, 2017.
For NQF #0647, NQF #0648, and Screening for Metabolic DisordersJuly 1, 2016-December 31, 2016

2. Changes to Aggregate Population Count Reporting for the FY 2017 Payment Determination and Subsequent Years

In the FY 2015 IPF PPS final rule (79 FR 45973), we finalized our policy that IPFs must submit aggregate population counts for Medicare and non-Medicare discharges by age group, diagnostic group, and quarter, and sample size counts for measures for which sampling is performed. In section V.F.1. of this final rule, we finalized our proposal to only require measure reporting as an annual aggregate rate, rather than by quarter. Likewise, beginning with the FY 2017 payment determination, we proposed to require non-measure data to be reported as an aggregate, yearly count rather than by quarter. We welcomed public comments on this proposal. The comments we received and our responses are set forth below.

Comment: Some commenters supported this proposal.

Response: We thank commenters for their support.

Comment: Some commenters stated that aggregating data increases the possibility of human error and suggested that we allow patient-level reporting in the same way it is submitted to The Joint Commission. Commenter suggested that CMS convene TEPs to identify the best ways to reduce reporting burden in the future.

Response: To our knowledge, The Joint Commission does not require reporting non-measure data as required by the IPFQR Program. Thus, it is unclear to us what commenters mean in suggesting that we allow patient-level reporting in the same way as The Joint Commission. Additionally, we do not agree that adding together 4 numbers rather than reporting these numbers separately will increase human error by any noticeable margin, specifically since facilities were already required to manually submit these data. Furthermore, as stated above, we are finalizing our proposal to require facilities to report data for chart-abstracted measures to the Web-Based Measures Tool on an aggregate basis by year, rather than by quarter, and to discontinue the requirement for reporting by age group beginning with the FY 2017 payment determination. We believe it is important to collect non-measure data similarly to how measure data is collected. Finally, we will consider convening TEPs to identify ways to reduce provider burden in the future.

For the reasons stated above, we are finalizing our proposal to require facilities to report non-measure data as an aggregate, yearly count rather than by quarter beginning with the FY 2017 payment determination.

3. Changes to Sampling Requirements for the FY 2018 Payment Determination and Subsequent Years

Measure specifications for the measures that we have adopted allow sampling for some measures; however, for other measures, IPFs must report data for all discharges/patients. In addition, the sampling requirements sometimes vary by measure. In response to these policies, in the FY 2014 IPPS/LTCH PPS final rule, some commenters noted that different sampling requirements in the measures could increase burden on facilities because these differences will require IPFs to have varying policies and procedures in place for each measure (78 FR 50901). Although we stated our belief that the importance of these measures and of gathering information for all discharges/patients outweighs the burden of various sampling requirements, we now believe that the additional measures in this final rule tip the balance of benefit and burden. Therefore, and for the reasons provided below, we proposed to allow a uniform sampling methodology both for measures that require sampling and for certain other measures. Specifically, we proposed to allow The Joint Commission/CMS Global Initial Patient Population sampling in Section 2.9_Global Initial Patient Population found at https://www.qualitynet.org/​dcs/​ContentServer?​c=​Page&​pagename=​QnetPublic%2FPage%2FQnetTier4&​cid=​1228773989482. We stated our belief that this will allow IPFs to take one, global sample for all measures specified in Table 25, thereby decreasing burden on these facilities and streamlining policies and procedures.

In our current measure set, the measures for which we proposed to allow The Joint Commission/CMS Global sampling included those outlined in Table 25.

Table 25—Measures to Which Sampling Applies

NQF #Measure IDMeasure
0560HBIPS-5Patients Discharged on Multiple Antipsychotic Medications with Appropriate Justification.
1661SUB-1Alcohol Use Screening.
1663SUB-2 and SUB-2aAlcohol Use Brief Intervention Provided or Offered and SUB-2a Alcohol Use Brief Intervention.
1651TOB-1Tobacco Use Screening.
1654TOB-2 TOB-2aTobacco Use Treatment Provided or Offered and Tobacco Use Treatment.
Start Printed Page 46718
1656TOB-3 and TOB-3aTobacco Use Treatment Provided or Offered at Discharge and the subset measure Tobacco Use Treatment at Discharge.
1659IMM-2Influenza Immunization.
0647N/ATransition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care).
0648N/ATimely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care).
N/AN/AScreening for Metabolic Disorders.

In section V.F.1. of this final rule, we are finalizing our proposal to require reporting on measures as a yearly count rather than by quarter. Because The Joint Commission/CMS Global sampling guidelines specify sampling by quarter, we proposed to modify their sampling guidelines by multiplying the “number of cases in the initial patient population” and the “number of cases to be sampled” by 4. In addition, since we require all IPFs to report data on all chart-abstracted measures even when the population size for a given measure is small or zero (78 FR 50901), we have modified the table to require reporting regardless of the number of cases. Thus, we proposed the following sampling guidelines for the measures above:

Table 26—Number of Records Required To Be Sampled

Number of cases in initial patient populationNumber of records to be sampled
≥6,117.1,224.
3,057-6,11620% of initial patient population.
609-3,056609.
0-608All cases.

We stated our belief that this will simplify processes and procedures for IPFs because uniform requirements will promote streamlined procedures and reporting. We also stated our belief that the proposal will decrease burden by allowing IPFs to identify a single, initial patient population for all of the measures specified in Table 25 from which to calculate the sample size. Furthermore, we stated that we do not believe this approach will reduce quality improvement. Sampling calculations ensure that enough data are represented in the sample to determine accurate measure rates. Therefore, even with sampling, we stated that we believe that CMS, IPFs, and the public would be able to differentiate those IPFs who perform well on measures from those who do not.

Therefore, we proposed to allow The Joint Commission/CMS Global Initial Patient Population sampling, with limited methodology changes as described above, for the measures in Table 25 beginning with the FY 2018 payment determination. We welcomed public comments on this proposal. The comments we received and our responses are set forth below.

Comment: Many commenters supported this proposal, stating that it would make the abstraction process less burdensome for providers.

Response: We thank commenters for their support.

Comment: Some commenters suggested that changing the sampling requirements for HBIPS measures increases burden for providers since IPFs are required to submit HBIPS data to The Joint Commission using the HBIPS sampling methodology and suggested aligning the sampling methodology with the HBIPS methodology. These commenters also noted that misalignment between CMS and The Joint Commission may result in consumer confusion since both publicly report data.

Response: We do not agree that this proposal increases burden. Most of our measures (IMM-2, TOB-1, TOB-2/2a, and SUB-1) currently require sampling per The Joint Commission/CMS Global Initial Patient Population guidelines. Only HBIPS-5 is required to be reported to The Joint Commission using a different sampling methodology. Therefore, we believe that, overall, allowing uniform sampling for the measures discussed in Table 25 will greatly decrease burden, specifically because some of these measures (the transition and metabolic screening measures) currently do not allow sampling at all. In addition, we note that, if providers believe using this optional sampling is too burdensome, we are not requiring them to do so.

We appreciate the comment that the public may be confused if numbers are reported differently in different programs. We note, however, that this confusion would be limited to HBIPS-5, the only measure that uses a different sampling methodology from The Joint Commission/CMS Global Initial Patient Population sampling, and we believe, even in this case, the public can understand that reporting requirements, and their results, vary by program and organization.

Comment: Commenters stated that the sampling tables were developed by The Joint Commission to ensure that most healthcare organizations would be able to obtain a sample size large enough to distinguish meaningful differences from the national average, and adopting a uniform methodology could cause over-sampling for measures with large populations and under-sampling for those with small populations, affecting the ability of providers to monitor measures where their patient populations are heterogeneous.

Response: We will monitor the results of this proposal to see if it causes the inability to distinguish meaningful differences between providers and will make appropriate adjustments if we believe this is the case.

Comment: One commenter noted that the HBIPS measure set and the SUB and TOB measure sets use different population criteria for sampling and asked CMS to clarify its proposal.

Response: As we explained in the proposed rule (80 FR 25056), we proposed to allow IPFs to use The Joint Commission/CMS Global Initial Patient Population guidelines for the measures in Table 25, which includes these measures. Thus, for both sampling and population purposes, IPFs may use The Joint Commission/CMS Global Initial Patient Population guidelines found at https://www.qualitynet.org/​dcs/​ContentServer?​c=​Page&​pagename=​QnetPublic%2FPage%2FQnetTier4&​cid=​1228773989482.

Comment: Many commenters suggested that CMS convene TEPs to identify the best ways to reduce reporting burden.

Response: We will also consider convening a TEP to discuss ways to diminish provider burden in the future.Start Printed Page 46719

For the reasons stated above, we are finalizing our proposal to allow The Joint Commission/CMS Global Initial Patient Population sampling for the measures in Table 25 beginning with the FY 2018 payment determination.

G. Public Display and Review Requirements

We did not propose any changes to the public display and review requirements for the FY 2018 payment determination and subsequent years and refer readers to the FY 2014 IPPS/LTCH PPS final rule (78 FR 50897 through 50898) for more information.

H. Form, Manner, and Timing of Quality Data Submission

1. Procedural and Submission Requirements

We did not propose any changes to the procedural and submission requirements for the FY 2018 payment determination and subsequent years and refer readers to the FY 2014 IPPS/LTCH PPS final rule (77 FR 50898 through 50899) for more information on these previously finalized requirements.

2. Change to the Reporting Periods and Submission Timeframes

In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50901), we finalized requirements for reporting periods and submission timeframes for the IPFQR Program measures. We are making one change to these requirements, as discussed above in section V.F.1. of this final rule. Specifically, we are no longer requiring that measure rates be reported quarterly and by age; we will only require an aggregate, yearly number beginning with the FY 2017 payment determination.

3. Population and Sampling

In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53657 through 53658) and FY 2014 IPPS/LTCH PPS final rule (78 FR 58901 through 58902), we finalized policies for population, sampling, and minimum case thresholds. We are making one change to these policies, as discussed above in section V.F.3. of this final rule. Specifically, we will allow uniform sampling on certain measures beginning with the FY 2018 payment determination.

4. Data Accuracy and Completeness Acknowledgement (DACA) Requirements

We did not propose any changes to the DACA requirements and refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 53658) for more information on these requirements.

I. Reconsideration and Appeals Procedures

In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53658 through 53660), we adopted a reconsideration process, later codified at § 412.434, by which IPFs can request a reconsideration of their payment update reduction if an IPF believes that its annual payment update has been incorrectly reduced for failure to meet all IPFQR Program requirements. We did not propose any changes to the Reconsideration and Appeals Procedure and refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 53658 through 53660) and the FY 2014 IPPS/LTCH PPS final rule (78 FR 50953) for further details on the reconsideration process.

J. Exceptions to Quality Reporting Requirements

We did not propose any changes to the exceptions to quality reporting requirements and refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 53659 through 53660), where we initially finalized the policy as “Waivers from Quality Reporting,” and the FY 2015 IPF PPS final rule (79 FR 45978), where we re-named the policy as “Exceptions to Quality Reporting Requirements” for more information.

VI. Provisions of the Final Regulations

For the most part, this final rule incorporates the provisions of the proposed rule. Those provisions of this final rule that differ from the proposed rule are as follows:

  • Effective for FY 2016 IPF PPS update, we adopted a 2012-based IPF-market basket. However, we revised the proposed 2012-based IPF market basket based on public comments. Specifically, we revised the methodology for calculating the Wages and Salaries and the Employee Benefits cost weights.
  • We adopted an updated FY 2016 LRS of 75.2 percent, which increased from the proposed LRS of 74.9 percent largely due to the methodological changes made to the 2012-based IPF market basket based on public comments. We are implementing the LRS as proposed, in full in FY 2016.
  • Effective for FY 2016 IPF PPS update, we adopted a 2012-based IPF market basket. We adjusted the 2012-based IPF market basket update for FY 2016 (currently estimated to be 2.4 percent) by a reduction for economy-wide productivity (currently estimated to be 0.5 percentage point) as required by section 1886(s)(2)(A)(i) of the Social Security Act (the Act), and further reduced by 0.2 percentage point as required by section 1886(s)(2)(A)(ii) of the Act, resulting in a final estimated market basket update of 1.7 percent.
  • We updated the IPF per diem rate from $728.31 to $743.73. Providers that failed to report quality data for FY 2016 payment will receive a final FY 2016 per diem rate of $729.10.
  • We updated the electroconvulsive therapy (ECT) payment per treatment from $313.55 to $320.19. Providers that failed to report quality data for FY 2016 payment would receive a FY 2016 ECT payment per treatment of $313.89.
  • We updated the fixed dollar loss threshold amount from $8,755 to $9,580 in order to maintain outlier payments that are 2 percent of total estimated IPF PPS payments.
  • We finalized that the national urban and rural cost-to-charge ratio (CCR) ceilings for FY 2016 will be 1.7339 and 1.9041, respectively, and the national median CCR will be 0.4650 for urban IPFs and 0.6220 for rural IPFs.

All other payment policy proposals are being implemented as proposed. We are implementing the IPF Quality Reporting Program proposals as proposed, except for the following changes: Due to concerns with the timeline required to operationalize the Transition Record with Specified Elements Received by Discharged Patients, Timely Transmission of Transition Record, and Screening for Metabolic Disorders measures, we are only requiring that facilities report the last two quarters of data for the first year of public reporting. That is, for the FY 2018 payment determination, facilities must only report data from July 1, 2016-December 1, 2016 for these measures. Beginning with the FY 2019 payment determination, IPFs must report all four quarters of data or face a payment reduction.

VII. Collection of Information Requirements

Under the Paperwork Reduction Act of 1995 (PRA), we are required to publish a 60-day notice in the Federal Register and solicit public comment before a collection of information requirement is submitted to the Office of Management and Budget (OMB) for review and approval.

To fairly evaluate whether an information collection should be approved by OMB, PRA section 3506(c)(2)(A) requires that we solicit comment on the following issues:

  • The need for the information collection and its usefulness in carrying out the proper functions of our agency.
  • The accuracy of our burden estimates.
  • The quality, utility, and clarity of the information to be collected.Start Printed Page 46720
  • Our effort to minimize the information collection burden on the affected public, including the use of automated collection techniques.

In our May 1, 2015, proposed rule, we solicited public comment on each of the section 3506(c)(2)(A)-required issues for the following information collection requirements (ICRs). While comments were received on the proposed rule, none of those comments were related to the PRA or to the ICRs. All of this final rule's information collection requirements and burden estimates are unchanged from what was set out in the proposed rule.

A. Wage Estimates

We estimate that reporting data for the IPFQR Program measures can be accomplished by staff with a mean hourly wage of $16.42 per hour.[114] Under OMB Circular A-76, in calculating direct labor, agencies should not only include salaries and wages, but also “other entitlements” such as fringe benefits.[115] This Circular provides that the civilian position full fringe benefit cost factor is 36.25 percent. Therefore, using these assumptions, we estimate an hourly labor cost of $22.37 ($16.42 base salary + $5.95 fringe). The following table presents the mean hourly wage, the cost of fringe benefits (calculated at 36.25 percent of salary), and the adjusted hourly wage.

Table 27—Occupational Employment and Wage Estimates

Occupation titleOccupation codeMean hourly wage ($/hour)Fringe benefit (at 36.25% in $/hour)Adjusted hourly wage ($/hour)
Medical Records and Health Information Technician29-207116.425.9522.37

The BLS is “the principal Federal agency responsible for measuring labor market activity, working conditions, and price changes in the economy.” [116] Acting as an independent agency, the Bureau provides objective information for not only the government, but also for the public. The Bureau's National Occupational Employment and Wage Estimates describes Medical Records and Health Information Technicians as those responsible for organizing and managing health information data. Therefore, we believe it is reasonable to assume that these individuals would be tasked with abstracting clinical data for these measures. In addition, the Hospital IQR Program uses this wage to calculate its burden estimates.

B. ICRs Regarding the Inpatient Psychiatric Facility Quality Reporting (IPFQR) Program

We refer readers to the FY 2015 IPF PPS final rule (79 FR 45978 through 45980) for a detailed discussion of the burden for the program requirements that we have previously adopted. Below, we discuss only the changes in burden resulting from the provisions in this final rule. Although we are finalizing provisions that impact both the FY 2017 and FY 2018 payment determinations, all of these new elements begin to apply to facilities in FY 2016. For example, data collection for the measures begins in FY 2016, and the changes to the reporting requirements take effect beginning with reporting that is required in the summer of FY 2016. For purposes of calculating burden, we will attribute the costs to the year in which these costs begin; for the purposes of all of the provisions in this final rule, that year is FY 2016.

1. Changes in Time Required To Chart-Abstract Data Based on Reporting Requirements

As discussed in section V.F. of this final rule, we are finalizing the following 3 changes regarding how facilities should report data for IPFQR Program measures: (1) Beginning with the FY 2017 payment determination, measures must be reported as a single yearly count rather than by quarter and age; (2) beginning with the FY 2017 payment determination, aggregate population counts must be reported as a single yearly number rather than by quarter; and (3) beginning with the FY 2018 payment determination, uniform sampling is allowed for certain measures.

We believe that these changes will lead to a decrease in burden since facilities are required to enter one aggregate number for both the numerator and denominator for each measure and will be allowed to pull one sample used to calculate the measures specified in Table 25 of this final rule. Consequently, we believe that the time required to chart-abstract data for these measures would be reduced by 20 percent. Previously, we estimated 15 minutes to chart-abstract data for each case (79 FR 45979). Because of our proposed changes to sampling and reporting data, we are revising the figure and now estimate 12 minutes (0.20 × 15 minutes), a change of −3 minutes or −0.05 hour.

2. Estimated Burden of IPFQR Program

In section V. of this final rule, we are finalizing our proposal to adopt the following 5 measures:

  • TOB-3—Tobacco Use Treatment Provided or Offered at Discharge and the subset measure TOB-3a Tobacco Use Treatment at Discharge (National Quality Forum (NQF) #1656);
  • SUB-2—Alcohol Use Brief Intervention Provided or Offered and the subset measure SUB-2a Alcohol Use Brief Intervention (NQF #1663);
  • Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) (NQF #0647);
  • Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) (NQF #0648); and
  • Screening for Metabolic Disorders.

In the same section, we are also finalizing our proposal to remove the following 3 measures:

  • HBIPS-4: Patients Discharged on Multiple Antipsychotic Medications;
  • HBIPS-6: Post-Discharge Continuing Care Plan (NQF #0557); and
  • HBIPS-7: Post-Discharge Continuing Care Plan Transmitted to the Next Level of Care Provider Upon Discharge (NQF #0558).

We believe that approximately 1,617 [117] IPFs will participate in the IPFQR Program for requirements occurring in FY 2016 and subsequent years. Based on data from CY 2013, we believe that each facility will submit measure data on approximately 431 [118] cases per year. Although we note that, Start Printed Page 46721as finalized in section V. of this final rule, for the Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care), Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care), and the Screening for Metabolic Disorders measures, we are only requiring facilities to report data for two quarters for the FY 2018 payment determination, we believe it is best to estimate the burden for the full year of reporting as this will be the requirement going forward. Therefore, we estimate that adopting 5 measures and removing 3 measures (for a net result of 2 measures) will result in an increase in burden of 172.4 hours per facility (2 measures × (431 cases/measure × 0.20 hours/case)) or 278,770.80 hours across all IPFs (172.4 hours/facility × 1,617 facilities). The increase in costs is approximately $3,856.59 per IPF ($22.37/hour × 172.4 hours) or $6,236,102.80 across all IPFs (278,770.80 hours × $22.37/hour).

Consistent with our estimates in the FY 2015 IPF PPS final rule (79 FR 45979), we believe the estimated burden for training personnel on this final rule's revised data collection and submission requirements is 2 hours per facility or 3,234 hours (2 hours/facility × 1,617 facilities) across all IPFs. Therefore, the cost for this training is $44.74 ($22.37/hour × 2 hours) for each IPF or $72,344.58 ($22.37/hour × 3,234 hours) for all facilities.

Finally, IPFs must submit to CMS aggregate population counts for Medicare and non-Medicare discharges by age group, and diagnostic group, and sample size counts for measures for which sampling is performed. As noted above, we are adopting 5 new measures beginning with the FY 2018 payment determination. However, because, as further described above, we are eliminating reporting this non-measure data by quarter for all measures, we believe that the addition of 5 measures leads to a net negligible change in burden associated with non-measure data collection.

C. Summary of Annual Burden Estimates

Table 28—Annual Recordkeeping and Reporting Requirements Under OMB Control Number 0938-1171

[CMS-10432]

Preamble section(s)Proposed actionRespondentsResponses (per respondent)Burden per response (hours)*Total annual burden (hours)Labor cost of reporting ($/hour)Total cost ($)
V.C.Remove HBIPS-41,617862 (431 cases/yr x 2 measures)0.20278,770.8022.376,236,102.80
V.Remove HBIPS-6 and HBIPS-7
V.Add NQF #1656, #1663, #0647, #0648, and Screening for Metabolic Disorders
Training123,23472,344.58
Total1,6178632.2282,004.822.376,308,447.38

D. ICRs Regarding the Hospital and Health Care Complex Cost Report (CMS-2552-10)

This rule would not impose any new or revised collection of information requirements associated with CMS-2552-10 (as discussed under preamble section III.A.3.a.i.). Consequently, the cost report does not require additional OMB review under the authority of the Paperwork Reduction Act of 1995 (44 U.S.C. 3501 et seq.). The report's information collection requirements and burden estimates are approved by OMB under control number 0938-0052.

E. Submission of PRA-Related Comments

We submitted a copy of this final rule to OMB for its review of the rule's information collection and recordkeeping requirements. The requirements are not effective until they have been approved by the OMB.

To obtain copies of the supporting statement and any related forms for the proposed collections discussed above, please visit CMS' Web site at www.cms.hhs.gov/​Paperwork@cms.hhs.gov, or call the Reports Clearance Office at 410-786-1326.

We invite public comments on these potential information collection requirements. If you wish to comment, please identify the rule (CMS-1627-F) and submit your comments to the OMB desk officer via one of the following transmissions:

Mail: OMB, Office of Information and Regulatory Affairs, Attention: CMS Desk Officer, Fax Number: 202-395-5806 or, Email: OIRA_submission@omb.eop.gov, ICR-related comments are due August 31, 2015.

VIII. Regulatory Impact Analysis

A. Statement of Need

This final rule updates the prospective payment rates for Medicare inpatient hospital services provided by IPFs for discharges occurring during FY 2016 (October 1, 2015, through September 30, 2016). We are applying the final 2012-based IPF market basket increase of 2.4 percent, less the productivity adjustment of 0.5 percentage point as required by 1886(s)(2)(A)(i) of the Act, and further reduced by 0.2 percentage point as required by sections 1886(s)(2)(A)(ii) and 1886(s)(3)(D) of the Act. In this final rule, we are adopting a 2012-based IPF market basket and updating the IPF labor-related share; adopting new OMB CBSA delineations for the FY 2016 IPF Wage Index; and phasing out the rural adjustment for 37 rural providers which will become urban providers as a result of the new CBSA delineations. Additionally, this rule reminds providers of the October 1, 2015 implementation of the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM/PCS) for the IPF prospective payment system, updates providers on the status of IPF PPS refinements, and Start Printed Page 46722finalizes new quality reporting requirements for the IPFQR Program.

B. Overall Impact

We have examined the impact of this final rule as required by Executive Order 12866 on Regulatory Planning and Review (September 30, 1993), Executive Order 13563 on Improving Regulation and Regulatory Review (January 18, 2011), the Regulatory Flexibility Act (RFA) (September 19, 1980, Pub. L. 96-354), section 1102(b) of the Social Security Act, section 202 of the Unfunded Mandates Reform Act of 1995 (March 22, 1995; Pub. L. 104-4), Executive Order 13132 on Federalism (August 4, 1999) and the Congressional Review Act (5 U.S.C. 804(2)).

Executive Orders 12866 and 13563 direct 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 (RIA) must be prepared for a major rules with economically significant effects ($100 million or more in any 1 year). This final rule is not designated as economically “significant” under section 3(f)(1) of Executive Order 12866.

We estimate that the total impact of these changes for FY 2016 payments compared to FY 2015 payments will be a net increase of approximately $75 million. This reflects an $85 million increase from the update to the payment rates, as well as a $10 million decrease as a result of the update to the outlier threshold amount. Outlier payments are estimated to decrease from 2.2 percent in FY 2015 to 2.0 percent of total estimated IPF payments in FY 2016.

The RFA requires agencies to analyze options for regulatory relief of small entities if a rule has a significant impact on a substantial number of small entities. For purposes of the RFA, small entities include small businesses, nonprofit organizations, and small governmental jurisdictions. Most IPFs and most other providers and suppliers are small entities, either by nonprofit status or having revenues of $7.5 million to $38.5 million or less in any 1 year, depending on industry classification (for details, refer to the SBA Small Business Size Standards found at http://www.sba.gov/​sites/​default/​files/​files/​Size_​Standards_​Table.pdf), or being nonprofit organizations that are not dominant in their markets.

Because we lack data on individual hospital receipts, we cannot determine the number of small proprietary IPFs or the proportion of IPFs' revenue derived from Medicare payments. Therefore, we assume that all IPFs are considered small entities. The Department of Health and Human Services generally uses a revenue impact of 3 to 5 percent as a significance threshold under the RFA.

As shown in Table 29, we estimate that the overall revenue impact of this final rule on all IPFs is to increase Medicare payments by approximately 1.5 percent. As a result, since the estimated impact of this final rule is a net increase in revenue across almost all categories of IPFs, the Secretary has determined that this final rule will have a positive revenue impact on a substantial number of small entities. MACs are not considered to be small entities. Individuals and States are not included in the definition of a small entity.

In addition, section 1102(b) of the Social Security Act requires us to prepare a regulatory impact analysis if a rule 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 604 of the RFA. For purposes of section 1102(b) of the Act, we define a small rural hospital as a hospital that is located outside of a metropolitan statistical area and has fewer than 100 beds. As discussed in detail below, the rates and policies set forth in this final rule would not have an adverse impact on the rural hospitals based on the data of the 277 rural units and 65 rural hospitals in our database of 1,617 IPFs for which data were available. Therefore, the Secretary has determined that this final rule would not have a significant impact on the operations of a substantial number of small rural hospitals.

Section 202 of the Unfunded Mandates Reform Act of 1995 (UMRA) also requires that agencies assess anticipated costs and benefits before issuing any rule whose mandates require spending in any 1 year of $100 million in 1995 dollars, updated annually for inflation. In 2015, that threshold is approximately $144 million. This final rule will not impose spending costs on state, local, or tribal governments in the aggregate, or by the private sector, of $144 million or more.

Executive Order 13132 establishes certain requirements that an agency must meet when it promulgates a proposed rule (and subsequent final rule) that imposes substantial direct requirement costs on state and local governments, preempts state law, or otherwise has Federalism implications. As stated above, this final rule would not have a substantial effect on state and local governments.

C. Anticipated Effects

We discuss the historical background of the IPF PPS and the impact of this final rule on the Federal Medicare budget and on IPFs.

1. Budgetary Impact

As discussed in the November 2004 and May 2006 IPF PPS final rules, we applied a budget neutrality factor to the Federal per diem base rate and ECT payment per treatment to ensure that total estimated payments under the IPF PPS in the implementation period would equal the amount that would have been paid if the IPF PPS had not been implemented. The budget neutrality factor includes the following components: Outlier adjustment, stop-loss adjustment, and the behavioral offset. As discussed in the May 2008 IPF PPS notice (73 FR 25711), the stop-loss adjustment is no longer applicable under the IPF PPS.

As discussed in section III.D.1.e. of this final rule, we are using the wage index and labor-related share in a budget neutral manner by applying a wage index budget neutrality factor to the Federal per diem base rate and ECT payment per treatment. Therefore, the budgetary impact to the Medicare program of this final rule will be due to the final market basket update for FY 2016 of 2.4 percent (see section III.A.4. of this final rule) less the productivity adjustment of 0.5 percentage point required by section 1886(s)(2)(A)(i) of the Act; further reduced by the “other adjustment” of 0.2 percentage point under sections 1886(s)(2)(A)(ii) and 1886(s)(3)(D) of the Act; and the update to the outlier fixed dollar loss threshold amount.

We estimate that the FY 2016 impact will be a net increase of $75 million in payments to IPF providers. This reflects an estimated $85 million increase from the update to the payment rates and a $10 million decrease due to the update to the outlier threshold amount to set total estimated outlier payments at 2.0 percent of total estimated payments in FY 2016. This estimate does not include the implementation of the required 2 percentage point reduction of the market basket increase factor for any IPF that fails to meet the IPF quality reporting requirements (as discussed in section VIII.C.4. below).

2. Impact on Providers

To understand the impact of the changes to the IPF PPS on providers, discussed in this final rule, it is necessary to compare estimated Start Printed Page 46723payments under the IPF PPS rates and factors for FY 2016 versus those under FY 2015. We determined the percent change of estimated FY 2016 IPF PPS payments to FY 2015 IPF PPS payments for each category of IPFs. In addition, for each category of IPFs, we have included the estimated percent change in payments resulting from the update to the outlier fixed dollar loss threshold amount; the updated wage index data; the changes to wage index CBSAs; the changes to rural adjustment payments resulting from changes in rural or urban status, due to CBSA changes; the final labor-related share; and the final market basket update for FY 2016, as adjusted by the productivity adjustment according to section 1886(s)(2)(A)(i), and the “other adjustment” according to sections 1886(s)(2)(A)(ii) and 1886(s)(3)(D) of the Act.

To illustrate the impacts of the FY 2016 changes in this final rule, our analysis begins with a FY 2015 baseline simulation model based on FY 2014 IPF payments inflated to the midpoint of FY 2015 using IHS Global Insight Inc.'s most recent forecast of the market basket update (see section III.A.4. of this final rule); the estimated outlier payments in FY 2015; the CBSA delineations for IPFs based on OMB's MSA definitions after June 2003; the FY 2014 pre-floor, pre-reclassified hospital wage index; the FY 2015 labor-related share; and the FY 2015 percentage amount of the rural adjustment. During the simulation, total outlier payments are maintained at 2 percent of total estimated IPF PPS payments.

Each of the following changes is added incrementally to this baseline model in order for us to isolate the effects of each change:

  • The update to the outlier fixed dollar loss threshold amount;
  • The FY 2015 pre-floor, pre-reclassified hospital wage index without the revised OMB delineations;
  • The FY 2015 updated CBSA delineations, based on OMB's February 28, 2013 Bulletin No. 13-01, as described in section III.D.1.c. of this final rule, with the final blended FY 2016 IPF wage index;
  • The FY 2016 rural adjustment, accounting for changes to rural or urban status due to the updated CBSA delineations, including the phase-out of the rural adjustment for the IPFs changing from rural to urban status, as described in section III.D.1.d;
  • The final FY 2016 labor-related share;
  • The final market basket update for FY 2016 of 2.4 percent less the productivity adjustment of 0.5 percentage point reduction in accordance with section 1886(s)(2)(A)(i) of the Act and further reduced by the “other adjustment” of 0.2 percentage point in accordance with sections 1886(s)(2)(A)(ii) and 1886(s)(3)(D) of the Act.

Our final comparison illustrates the percent change in payments from FY 2015 (that is, October 1, 2014, to September 30, 2015) to FY 2016 (that is, October 1, 2015, to September 30, 2016) including all the changes in this final rule.

Table 29—IPF Impact for FY 2016

[Percent change in columns 3-9]

Facility by typeNumber of IPFsOutlierWage index 1CBSA 2Change in rural adjustment 3Labor- related share (75.2) 4IPF market basket update 5Total percent change 6
(1)(2)(3)(4)(5)(6)(7)(8)(9)
All Facilities1,617−0.20.00.00.00.01.71.5
Total Urban1,275−0.20.00.00.00.21.71.7
Total Rural342−0.20.1−0.20.2−1.11.70.4
Urban unit845−0.30.00.00.00.21.71.6
Urban hospital430−0.10.00.10.00.11.71.8
Rural unit277−0.20.1−0.20.2−1.11.70.3
Rural hospital65−0.10.1−0.30.2−1.01.70.5
CBSA Change:
Urban to Urban1,238−0.20.00.00.10.21.71.7
Rural to Rural338−0.20.0−0.20.1−1.11.70.2
Urban to Rural4−0.72.4−0.213.2−0.91.715.7
Rural to Urban37−0.10.12.8−4.1−0.91.7−0.7
By Type of Ownership:
Freestanding IPFs:
Urban Psychiatric Hospitals:
Government125−0.20.10.00.00.11.71.7
Non-Profit102−0.10.40.10.00.41.72.5
For-Profit2030.0−0.30.10.00.01.71.4
Rural Psychiatric Hospitals:
Government35−0.10.2−0.10.4−0.81.71.2
Non-Profit11−0.4−0.60.00.1−0.31.70.4
For-Profit190.00.1−0.50.1−1.31.7−0.1
IPF Units:
Urban:
Government128−0.5−0.2−0.10.00.31.71.3
Non-Profit547−0.30.20.0−0.10.31.71.8
For-Profit170−0.2−0.30.00.00.01.71.3
Rural:
Government70−0.2−0.1−0.30.0−1.41.7−0.3
Non-Profit143−0.20.2−0.20.3−1.01.70.7
For-Profit64−0.30.0−0.20.2−1.31.70.2
By Teaching Status:
Non-teaching1,427−0.20.00.00.0−0.11.71.4
Less than 10% interns and residents to beds103−0.30.2−0.10.00.51.72.0
Start Printed Page 46724
10% to 30% interns and residents to beds61−0.50.4−0.10.10.51.72.1
More than 30% interns and residents to beds26−0.50.50.00.10.91.72.7
By Region:
New England108−0.30.80.00.00.81.73.1
Mid-Atlantic242−0.20.2−0.10.00.61.72.2
South Atlantic240−0.1−0.30.0−0.1−0.41.70.7
East North Central259−0.20.00.00.1−0.21.71.4
East South Central160−0.2−0.60.0−0.1−1.11.7−0.2
West North Central140−0.30.00.00.0−0.41.71.2
West South Central243−0.2−0.50.0−0.1−0.81.70.2
Mountain102−0.20.40.00.10.21.72.2
Pacific123−0.30.50.00.11.41.73.4
By Bed Size:
Psychiatric Hospitals:
Beds: 0-2481−0.10.00.2−0.3−0.71.70.7
Beds: 25-4974−0.1−0.30.3−0.1−0.11.71.4
Beds: 50-7587−0.10.00.00.10.01.71.6
Beds: 76+2530.00.00.00.00.11.71.8
Psychiatric Units:
Beds: 0-24667−0.30.00.00.0−0.31.71.0
Beds: 25-49294−0.30.00.10.00.01.71.5
Beds: 50-75105−0.20.10.00.00.21.71.8
Beds: 76+56−0.3−0.1−0.20.10.51.71.7
1 Includes a FY 2016 IPF wage index, current CBSA delineations, and a labor-related share of 0.69294.
2 Includes a 50/50 FY 2016 blended IPF wage index, new CBSA delineations, and a labor-related share of 0.69294.
3 Includes a 50/50 FY 2016 blended IPF wage index, new CBSA delineations, a labor-related share of 0.69294, and a rural adjustment. Providers changing from urban to rural status will receive a 17 percent rural adjustment, and providers changing from rural to urban status will receive 2/3 of the 17 percent rural adjustment in FY 2016. For those changing from urban to rural status, the total impact shown is affected by outlier threshold increasing, which results in smaller outlier payments as part of total payments. For those changing from rural to urban status, the outlier threshold is being lowered by 2/3 of 17 percent, which results in more providers being eligible for outlier payments, increasing the outlier portion of their total payments.
4 Includes a 50/50 FY 2016 blended IPF wage index, new CBSA delineations, a labor-related share of 0.752, and a rural adjustment.
5 This column reflects the payment update impact of the 2012-based IPF market basket update of 2.4 percent, a 0.5 percentage point reduction for the productivity adjustment as required by section 1886(s)(2)(A)(i) of the Act, and a 0.2 percentage point reduction in accordance with sections 1886(s)(2)(A)(ii) and 1886(s)(3)(D) of the Act.
6 Percent changes in estimated payments from FY 2015 to FY 2016 include all of the changes presented in this final rule. The products of these impacts may be different from the percentage changes shown due to rounding effects.

3. Results

Table 29 displays the results of our analysis. The table groups IPFs into the categories listed below based on characteristics provided in the Provider of Services (POS) file, the IPF provider specific file, and cost report data from HCRIS:

  • Facility Type
  • Location
  • Teaching Status Adjustment
  • Census Region
  • Size

The top row of the table shows the overall impact on the 1,617 IPFs included in this analysis.

In column 3, we present the effects of the update to the outlier fixed dollar loss threshold amount. We estimate that IPF outlier payments as a percentage of total IPF payments are 2.2 percent in FY 2015. Thus, we are adjusting the outlier threshold amount in this final rule to set total estimated outlier payments equal to 2 percent of total payments in FY 2016. The estimated change in total IPF payments for FY 2016, therefore, includes an approximate 0.2 percent decrease in payments because the outlier portion of total payments is expected to decrease from approximately 2.2 percent to 2.0 percent.

The overall impact of this outlier adjustment update (as shown in column 3 of Table 26), across all hospital groups, is to decrease total estimated payments to IPFs by 0.2 percent. The largest decrease in payments is estimated to reflect a 0.7 percent decrease in payments for IPFs that change from urban to rural status under the new CBSA delineations.

In column 4, we present the effects of the budget-neutral final update to the IPF wage index. This represents the effect of using the most recent wage data available without taking into account the revised OMB delineations, which are presented separately in the next column. That is, the impact represented in this column is solely that of updating from the FY 2015 IPF wage index to the FY 2016 IPF wage index without any changes to the OMB delineations. We note that there is no projected change in aggregate payments to IPFs, as indicated in the first row of column 4. However, there will be distributional effects among different categories of IPFs. For example, we estimate the largest increase in payments to be 2.4 percent for IPFs changing from urban to rural status, and the largest decrease in payments to be 0.6 percent for rural non-profit freestanding IPFs and IPFs in the East South Central region.Start Printed Page 46725

In column 5, we present the effects of the new OMB delineations and the finalized transition to the new delineations using the transitional IPF wage index. The FY 2016 IPF final transitional wage index is a blended wage index using 50 percent of the IPF's FY 2016 wage index based on the new OMB delineations and 50 percent of the IPF's FY 2016 wage index based on the OMB delineations used in FY 2015. In the aggregate, since these final updates to the wage index are applied in a budget-neutral manner, we do not estimate that these final updates would affect overall estimated payments to IPFs. However, we estimate that these final updates would have distributional effects. We estimate the largest increase in payments would be 2.8 percent for IPFs changing from rural to urban status and the largest decrease in payments would be 0.5 percent for rural for-profit freestanding IPFs.

In column 6, we present the effects of the changes to the rural adjustment under the new CBSA delineations. Four urban IPFs would be newly designated as rural IPFs and would now receive a full 17 percent rural adjustment. We estimate that the largest increase in payments would be to these four newly rural IPFs. Note that each column's simulations include both regular and outlier payments; as regular payments increase, outlier payments decrease to maintain outlier payments at 2 percent of total payments. As such, the increase to total IPF payments is estimated to be 13.2 percent. There are also 37 rural IPFs which would be newly designated as urban IPFs, where we finalized a phase-out of their rural adjustment over 3 years. These 37 newly urban providers will receive 2/3 of the 17 percent rural adjustment in FY 2016, 1/3 of the 17 percent rural adjustment in FY 2017, and no rural adjustment for FY 2018 and subsequent years. As the regular payments for these 37 providers decrease, their outlier payments increase to maintain outlier payments at 2 percent of total payments. We estimate that the largest decrease in payments would be 4.1 percent for these 37 newly urban providers.

In column 7, we present the estimated effects of the final labor-related share. The final update to the IPF labor-related share is made in a budget-neutral manner and therefore will not affect total estimated IPF PPS payments. However, it will affect the estimated distribution of payments among providers. For example, we estimate the largest increase in payments will be 1.4 percent to IPFs in the Pacific region. We estimate the largest decrease in payments will be 1.4 percent to rural IPF governmental units.

In column 8, we present the estimated effects of the update to the IPF PPS payment rates of 1.7 percent, which are based on the 2012-based IPF market basket update of 2.4 percent, less the productivity adjustment of 0.5 percentage point in accordance with section 1886(s)(2)(A)(i), and further reduced by 0.2 percentage point in accordance with section 1886(s)(2)(A)(ii) and 1886(s)(3)(D).

Finally, column 9 compares our estimates of the total changes reflected in this final rule for FY 2016 to the payments for FY 2015 (without these changes). This column reflects all finalized FY 2016 changes relative to FY 2015. The average estimated increase for all IPFs is approximately 1.5 percent. This estimated net increase includes the effects of the final 2.4 percent market basket update reduced by the productivity adjustment of 0.5 percentage point, as required by section 1886(s)(2)(A)(i)of the Act and further reduced by the “other adjustment” of 0.2 percentage point, as required by sections 1886(s)(2)(A)(ii) and 1886(s)(3)(D) of the Act. It also includes the overall estimated 0.2 percent decrease in estimated IPF outlier payments as a percent of total payments from the update to the outlier fixed dollar loss threshold amount. Since we are making the updates noted in columns 4 through 7 in a budget-neutral manner, they will not affect total estimated IPF payments in the aggregate. However, they will affect the estimated distribution of payments among providers.

Overall, urban IPFs are estimated to experience a 1.7 percent increase in payments in FY 2016 and rural IPFs are estimated to experience a 0.4 percent increase in payments in FY 2016. The largest estimated decrease in payments is 0.7 percent for rural IPFs that transition to urban status as a result of the new OMB delineations. As noted previously, we are finalizing our proposal to mitigate the effects of the loss of the rural adjustment to these 37 providers by phasing the adjustment out over 3 years. The largest payment increase is estimated at 15.7 percent for IPFs that transition from urban to rural status (thereby gaining the 17 percent rural adjustment), followed by a 3.4 percent increase for IPFs in the Pacific region.

4. Effects of Updates to the IPFQR Program

As discussed in section V. of this final rule and in accordance with section 1886(s)(4)(A)(i) of the Act, we will implement a 2 percentage point reduction in the FY 2018 market basket update for IPFs that have failed to comply with the IPFQR Program requirements for FY 2018, including reporting on the required measures. In section V. of this final rule, we discuss how the 2 percentage point reduction will be applied. For FY 2015, of the 1,725 IPFs eligible for the IPFQR Program, 31 IPFs (1.8 percent) did not receive the full market basket update because of the IPFQR Program; 10 of these IPFs chose not to participate and 21 did not meet the requirements of the program. We anticipate that even fewer IPFs would receive the reduction for FY 2016 as IPFs become more familiar with the requirements. Thus, we estimate that this policy will have a negligible impact on overall IPF payments for FY 2016.

Based on the proposals we finalized in this rule, we estimate a total increase in burden of 174.4 hours per IPF or 282,004.80 hours across all IPFs, resulting in a total increase in financial burden of $3,901.33 per IPF or $6,308,447.38 across all IPFs. As discussed in section VII. of this final rule, we will attribute the costs associated with the finalized proposals to the year in which these costs begin; for the purposes of all the changes made in this final rule, that year is FY 2016. Further information on these estimates can be found in section VII. of this final rule.

We intend to closely monitor the effects of this quality reporting program on IPFs and help facilitate successful reporting outcomes through ongoing stakeholder education, national trainings, and a technical help desk.

5. Effect on Beneficiaries

Under the IPF PPS, IPFs will receive payment based on the average resources consumed by patients for each day. We do not expect changes in the quality of care or access to services for Medicare beneficiaries under the FY 2016 IPF PPS, but we continue to expect that paying prospectively for IPF services would enhance the efficiency of the Medicare program.

D. Alternatives Considered

The statute does not specify an update strategy for the IPF PPS and is broadly written to give the Secretary discretion in establishing an update methodology. Therefore, we are updating the IPF PPS using the methodology published in the November 2004 IPF PPS final rule, but implementing a 2012-based IPF market basket with some methodological changes to the calculations of Wages and Salaries and Employee Benefit Start Printed Page 46726costs, based on public comments; finalizing the updated labor-related share as proposed; finalizing a transitional wage index to implement new OMB CBSA designations as proposed; and implementing a phase-out of the rural adjustment as proposed for the 37 providers changing from rural to urban status as a result of the updated OMB CBSA delineations used in the FY 2016 IPF PPS transitional wage index. We considered implementing the new OMB designations for the FY 2016 IPF PPS wage index without a blend, but wanted to mitigate any negative effects of CBSA changes on IPFs. Additionally, we considered abruptly ending the rural adjustment for the 37 IPF providers which changed from rural to urban status as a result of the OMB CBSA changes. However, we wanted to provide relief from the effects of OMB's new CBSA delineations to the 37 providers which changed from rural to urban status. We also considered whether to allow a phase-in of the updated LRS, but decided that the impact of full implementation did not warrant a phase-in, especially given that we are also implementing a transitional wage index and a phase-out of the rural adjustment for those IPFs which changed status from rural to urban under the new CBSAs. Additionally, for the IPFQR program, alternatives were not considered because the program, as designed, best achieves quality reporting goals for the inpatient psychiatric care setting, while minimizing associated reporting burdens on IPFs. Section V. of this final rule discusses other benefits and objectives of the program.

E. Accounting Statement

As required by OMB Circular A-4 (available at http://www.whitehouse.gov/​omb/​circulars_​a004_​a-4), in Table 30 below, we have prepared an accounting statement showing the classification of the expenditures associated with the provisions implemented in this final rule. The costs for data submission presented in Table 30 are calculated in section VI, which also discusses the benefits of data collection. This table provides our best estimate of the increase in Medicare payments under the IPF PPS as a result of the changes presented in this final rule and based on the data for 1,617 IPFs in our database. Furthermore, we present the estimated costs associated with updating the IPFQR program. The increases in Medicare payments are classified as Federal transfers to IPF Medicare providers.

Table 30—Accounting Statement: Classification of Estimated Expenditures

Change in Estimated Transfers from FY 2015 IPF PPS to FY 2016 IPF PPS:
CategoryTransfers
Annualized Monetized Transfers$75 million.
From Whom to Whom?Federal Government to IPF Medicare Providers.
FY 2016 Costs to Updating the Quality Reporting Program for IPFs:
CategoryCosts
Annualized Monetized Costs for IPFs to Submit Data (Quality Reporting Program)$6.31 million.

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

Start List of Subjects

List of Subjects in 42 CFR Part 412

  • Administrative practice and procedure
  • Health facilities
  • Medicare
  • Puerto Rico
  • Reporting and recordkeeping requirements
End List of Subjects

For the reasons set forth in the preamble, the Centers for Medicare and Medicaid Services amends 42 CFR chapter IV as set forth below:

Start Part

PART 412—PROSPECTIVE PAYMENT SYSTEMS FOR INPATIENT HOSPITAL SERVICES

End Part Start Amendment Part

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

End Amendment Part Start Authority

Authority: Secs. 1102 and 1871 of the Social Security Act (42 U.S.C. 1302 and 1395hh), sec. 124 of Pub. L. 106-113 (113 Stat. 1501A-332), sec. 1206 of Pub. L. 113-67, and sec. 112 of Pub. L. 113-93.

End Authority Start Amendment Part

2. Section 412.428 is amended by revising paragraph (e) to read as follows:

End Amendment Part
Publication of Updates to the inpatient psychiatric facility prospective payment system.
* * * * *

(e) Describe the ICD-10-CM coding changes and DRG classification changes discussed in the annual update to the hospital inpatient prospective payment system regulations.

* * * * *
Start Signature

Dated: July 27, 2015.

Andrew M. Slavitt,

Acting Administrator, Centers for Medicare & Medicaid Services.

Dated: July 27, 2015.

Sylvia M. Burwell,

Secretary, Department of Health & Human Services.

End Signature

Note: The following addendum will not publish in the Code of Federal Regulations.

Addendum—FY 2016 Final Rates and Adjustment Factors

Per Diem Rate

Federal Per Diem Base Rate$743.73
Labor Share (0.752)559.28
Non-Labor Share (0.248)184.45

Per Diem Rate Applying the 2 Percentage Point Reduction

Federal Per Diem Base Rate$729.10
Labor Share (0.752)548.28
Non-Labor Share (0.248)180.82

Fixed Dollar Loss Threshold Amount: $9,580.

Wage Index Budget-Neutrality Factor: 1.0041.Start Printed Page 46727

Facility Adjustments

Rural Adjustment Factor1.17.
Teaching Adjustment Factor0.5150.
Wage IndexPre-reclass Hospital Wage Index (FY2015).

Cost of Living Adjustments (COLAs)

AreaCost of living adjustment factor
Alaska:
City of Anchorage and 80-kilometer (50-mile) radius by road1.23
City of Fairbanks and 80-kilometer (50-mile) radius by road1.23
City of Juneau and 80-kilometer (50-mile) radius by road1.23
Rest of Alaska1.25
Hawaii:
City and County of Honolulu1.25
County of Hawaii1.19
County of Kauai1.25
County of Maui and County of Kalawao1.25

Patient Adjustments

ECT—Per Treatment$320.19
ECT—Per Treatment Applying the 2 Percentage Point Reduction313.89

Variable Per Diem Adjustments

Adjustment factor
Day 1—Facility Without a Qualifying Emergency Department1.19
Day 1—Facility With a Qualifying Emergency Department1.31
Day 21.12
Day 31.08
Day 41.05
Day 51.04
Day 61.02
Day 71.01
Day 81.01
Day 91.00
Day 101.00
Day 110.99
Day 120.99
Day 130.99
Day 140.99
Day 150.98
Day 160.97
Day 170.97
Day 180.96
Day 190.95
Day 200.95
Day 210.95
After Day 210.92

Age Adjustments

Age (in years)Adjustment factor
Under 451.00
45 and under 501.01
50 and under 551.02
55 and under 601.04
60 and under 651.07
65 and under 701.10
70 and under 751.13
75 and under 801.15
80 and over1.17

DRG Adjustments

MS-DRGMS-DRG DescriptionsAdjustment factor
056 057Degenerative nervous system disorders w MCC Degenerative nervous system disorders w/o MCC1.05
080 081Nontraumatic stupor & coma w MCC Nontraumatic stupor & coma w/o MCC1.07
876O.R. procedure w principal diagnoses of mental illness1.22
880Acute adjustment reaction & psychosocial dysfunction1.05
881Depressive neuroses0.99
882Neuroses except depressive1.02
883Disorders of personality & impulse control1.02
884Organic disturbances & mental retardation1.03
885Psychoses1.00
886Behavioral & developmental disorders0.99
887Other mental disorder diagnoses0.92
894Alcohol/drug abuse or dependence, left AMA0.97
895Alcohol/drug abuse or dependence w rehabilitation therapy1.02
896 897Alcohol/drug abuse or dependence w/o rehabilitation therapy w MCC Alcohol/drug abuse or dependence w/o rehabilitation therapy w/o MCC0.88

Comorbidity Adjustments

ComorbidityAdjustment factor
Developmental Disabilities1.04
Coagulation Factor Deficit1.13
Tracheostomy1.06
Eating and Conduct Disorders1.12
Infectious Diseases1.07
Renal Failure, Acute1.11
Renal Failure, Chronic1.11
Oncology Treatment1.07
Uncontrolled Diabetes Mellitus1.05
Severe Protein Malnutrition1.13
Drug/Alcohol Induced Mental Disorders1.03
Cardiac Conditions1.11
Gangrene1.10
Chronic Obstructive Pulmonary Disease1.12
Artificial Openings—Digestive & Urinary1.08
Severe Musculoskeletal & Connective Tissue Diseases1.09
Start Printed Page 46728
Poisoning1.11
End Supplemental Information

Footnotes

1.  “Analysis of CMS Proposed Inpatient Rehabilitation Facility Specific Market Basket”, submitted to HealthSouth Corporation by Dobson DaVanzo, May 22, 2015. The public reference for this comment letter is: CMS-2015-0053-0004, and can be retrieved from the following link: http://www.regulations.gov/​#!documentDetail;​D=​CMS-2015-0053-0004.

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2.  See the Medicare cost report instructions at https://www.cms.gov/​Regulations-and-Guidance/​Guidance/​Manuals/​Paper-Based-Manuals-Items/​CMS021935.html, Chapter, 40, Page 40-259 to 40-260..

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4.  The statute uses the term “rate year” (RY). However, beginning with the annual update of the inpatient psychiatric facility prospective payment system (IPF PPS) that took effect on July 1, 2011 (RY 2012), we aligned the IPF PPS update with the annual update of the ICD-9-CM codes, effective on October 1 of each year. This change allowed for annual payment updates and the ICD-9-CM coding update to occur on the same schedule and appear in the same Federal Register document, promoting administrative efficiency. To reflect the change to the annual payment rate update cycle, we revised the regulations at 42 CFR 412.402 to specify that, beginning October 1, 2012, the RY update period would be the 12-month period from October 1 through September 30, which we refer to as a “fiscal year” (FY) (76 FR 26435). Therefore, with respect to the IPFQR Program, the terms “rate year”, as used in the statute, and “fiscal year” as used in the regulation, both refer to the period from October 1 through September 30. For more information regarding this terminology change, we refer readers to section III. of the RY 2012 IPF PPS final rule (76 FR 26434 through 26435).

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5.  Behavioral Health Endorsement Maintenance 2014, Phase 2, Technical Report, 67, (May 9, 2014). Available at http://www.qualityforum.org/​Publications/​2014/​05/​Behavioral_​Health_​Endorsement_​Maintenance_​2014_​-_​Phase_​II.aspx.

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6.  Ibid.

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7.  Behavioral Health Endorsement Maintenance 2014, Phase 2, Technical Report, 67, (May 9, 2014). Available at http://www.qualityforum.org/​Publications/​2014/​05/​Behavioral_​Health_​Endorsement_​Maintenance_​2014_​-_​Phase_​II.aspx.

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8.  Ibid.

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9.  Centers for Disease Control and Prevention. Annual Smoking-Attributable Mortality, Years of Potential Life Lost, and Productivity Losses—United States, 2000-2004.” Morb Mortal Wkly Rep. 2008. 57(45): 1226-1228. Available at: http://www.cdc.gov/​mmwr/​preview/​mmwrhtml/​mm5745a3.htm.

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10.  U.S. Department of Health and Human Services. “The health consequences of smoking: A report of the Surgeon General.” Atlanta, GA, U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, 2004.

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11.  Fiore, Michael C., Goplerud, Eric, Shroeder, Steven A. (2010). The Joint Commission's New Tobacco Cessation Measures—Will Hospitals Do the Right Thing? N Engl J Med 2012; 366:1172-1174. Available at http://www.nejm.org/​doi/​full/​10.1056/​nejmp1115176.

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12.  Lasser K., Boyd J.W., Woolhandler S., Himmelstein, D.U., McCormick D., Bor D.H.. Smoking and mental illness: A population-based prevalence study. JAMA. 2000; 284(20):2606-2610.

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13.  Centers for Disease Control and Prevention. “Best Practices for Comprehensive Tobacco Control Programs—2007.” Atlanta, GA, Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, 2007.

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14.  U.S. Department of Health and Human Services. “The health consequences of smoking: a report of the Surgeon General.” Atlanta, GA, U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, 2004.

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15.  Fiore M.C., Jaén C.R., Baker T.B., et al. Treating Tobacco Use and Dependence: 2008 Update. Clinical Practice Guideline. Rockville, MD: U.S. Department of Health and Human Services. Public Health Service. May 2008, available at http://www.ncbi.nlm.nih.gov/​books/​NBK63952.

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16.  Prochaska, J.J., et al. “Efficacy of Initiating Tobacco Dependence Treatment in Inpatient Psychiatry: A Randomized Controlled Trial.” Am. J. Pub. Health. 2013 August 15; e1-e9.

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17.  Fiore, Michael C., Goplerud, Eric, Shroeder, Steven A. (2010). The Joint Commission's New Tobacco Cessation Measures—Will Hospitals Do the Right Thing? N Engl J Med 2012; 366:1172-1174, available at http://www.nejm.org/​doi/​full/​10.1056/​nejmp1115176.

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18.  Prochaska, JJ, et al. “Efficacy of Initiating Tobacco Dependence Treatment in Inpatient Psychiatry: A Randomized Controlled Trial.” Am. J. Pub. Health. 2013 August 15; e1-e9.

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19.  Ibid.

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21.  Ibid.

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23.  See Fiore MC, Jaén CR, Baker TB, et al. Treating Tobacco Use and Dependence: 2008 Update. Clinical Practice Guideline. Rockville, MD: U.S. Department of Health and Human Services. Public Health Service. May 2008. Available at http://www.ncbi.nlm.nih.gov/​books/​NBK63952. The specific strategy is further specified in Strategy 4A.

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24.  Centers for Disease Control and Prevention. Annual Smoking-Attributable Mortality, Years of Potential Life Lost, and Productivity Losses—United States, 2000-2004.” Morb Mortal Wkly Rep. 2008. 57(45): 1226-1228. Available at: http://www.cdc.gov/​mmwr/​preview/​mmwrhtml/​mm5745a3.htm.

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25.  U.S. Department of Health and Human Services. “The health consequences of smoking: A report of the Surgeon General.” Atlanta, GA, U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, 2004.

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26.  Fiore, Michael C., Goplerud, Eric, Shroeder, Steven A. (2010). The Joint Commission's New Tobacco Cessation Measures—Will Hospitals Do the Right Thing? N Engl J Med 2012; 366:1172-1174. Available at: http://www.nejm.org/​doi/​full/​10.1056/​nejmp1115176.

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27.  U.S. Department of Health and Human Services. “The health consequences of smoking: A report of the Surgeon General.” Atlanta, GA, U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, 2004.

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28.  Centers for Disease Control and Prevention. Annual Smoking-Attributable Mortality, Years of Potential Life Lost, and Productivity Losses—United States, 2000-2004.” Morb Mortal Wkly Rep. 2008. 57(45): 1226-1228. Available at: http://www.cdc.gov/​mmwr/​preview/​mmwrhtml/​mm5745a3.htm.

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29.  Fiore, Michael C., Goplerud, Eric, Shroeder, Steven A. (2010). The Joint Commission's New Tobacco Cessation Measures—Will Hospitals Do the Right Thing? N Engl J Med 2012; 366:1172-1174. Available at http://www.nejm.org/​doi/​full/​10.1056/​nejmp1115176.

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30.  Centers for Disease Control and Prevention. “Best Practices for Comprehensive Tobacco Control Programs—2007.” Atlanta, GA, Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, 2007.

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31.  U.S. Department of Health and Human Services. The Health Consequences of Smoking—50 Years of Progress: A Report of the Surgeon General. Atlanta, GA: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, 2014. Available at http://www.cdc.gov/​tobacco/​data_​statistics/​sgr/​50th-anniversary/​index.htm. CDC. Vital Signs: Current cigarette smoking among adults aged ≥18 years with mental illness—United States, 2009-2011. MMWR 2013;62(05):81-87. Available at http://www.cdc.gov/​mmwr/​preview/​mmwrhtml/​mm6205a2.htm?​s_​cid=​mm6205a2_​w. Xu X, Bishop EE, Kennedy SM, Simpson SA, Pechacek TF. Annual healthcare spending attributable to cigarette smoking: an update. Am J Prev Med 2015;48(3):326-333.

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32.  Ross, S. (2005). Alcohol Use Disorders in the Elderly. Primary Psychiatry, 12(1):32-40.

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33.  AL Mirand and JW Welte. Alcohol consumption among the elderly in a general population, Erie County, New York. Am J Public Health. 1996 July; 86(7): 978-984.

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34.  Although the measure refers to “hospitals,” the measure is specified for all in-patient settings. https://www.qualitynet.org/​dcs/​ContentServer?​c=​Page&​pagename=​QnetPublic%2FPage%2FQnetTier4&​cid=​1228773989482.

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36.  Ibid.

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38.  Stephen Ross. Alcohol Use Disorders in the Elderly. Psychiatry Weekly (no date). Available at: http://www.psychweekly.com/​aspx/​article/​ArticleDetail.aspx?​articleid=​19.

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40.  Although the measure refers to “hospitals,” the measure is specified for all in-patient settings. https://www.qualitynet.org/​dcs/​ContentServer?​c=​Page&​pagename=​QnetPublic%2FPage%2FQnetTier4&​cid=​1228773989482.

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42.  Ibid.

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43.  Jack BW, Chetty VK, Anthony D, et al. A reengineered hospital discharge program to decrease rehospitalization. Ann Intern Med 2009; 150:178-187.

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44.  Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) Measure Specifications. Available at http://www.qualityforum.org/​Qps/​0647.

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45.  Ibid.

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46.  See http://www.ama-assn.org/​ama/​pub/​physician-resources/​physician-consortium-performance-improvement/​about-pcpi.page?​ The AMA-PCPI “is nationally recognized for measure development, specification and testing of measures, and enabling use of measures in electronic health records (EHRs) . . . [the organization] develops, tests, implements and disseminates evidence-based measures that reflect the best practices and best interest of medicine . . .”

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47.  Medicare Payment Advisory Commission. Promoting Greater Efficiency in Medicare. June 2007. Available at: http://www.medpac.gov/​documents/​reports/​Jun07_​EntireReport.pdf.

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48.  US DHHS. “National Healthcare Disparities Report 2013.” Available at: http://www.ahrq.gov/​research/​findings/​nhqrdr/​nhdr13/​chap7.html.

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49.  Guide to Patient and Family Engagement: Environmental Scan Report. May 2012. Agency for Healthcare Research and Quality. Rockville, MD. Available at: http://www.ahrq.gov/​research/​findings/​final-reports/​ptfamilyscan/​ptfamily1.html.

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52.  In the FY 2013 IPPS/LTCH PPS final rule, we adopted HBIPS-6, beginning with the FY 2014 payment determination (77 FR 53650-53651). We refer readers to that rule for a detailed discussion of this measure.

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54.  Kripalani S, LeFevre F, Phillips CO, et al. Deficits in communication and information transfer between hospital based and primary care physicians: implications for patient safety and continuity of care. JAMA 2007;297(8):831-841.

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55.  Timely Transmission of Transition Record (Discharged from Inpatient Facility to Home/Self Care or Any Other Site of Care), available at http://www.ama-assn.sorg/​apps/​listserv/​x-check/​qmeasure.cgi?​submit=​PCPI.

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56.  Kripalani S, LeFevre F, Phillips CO, et al. Deficits in communication and information transfer between hospital based and primary care physicians: Implications for patient safety and continuity of care. JAMA 2007;297(8):831-841.

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57.  Medicare Payment Advisory Commission. Promoting Greater Efficiency in Medicare. June 2007. Available at: http://www.medpac.gov/​documents/​reports/​Jun07_​EntireReport.pdf.

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58.  Timely Transmission of Transition Record (Discharged from Inpatient Facility to Home/Self Care or Any Other Site of Care), available at http://www.ama-assn.sorg/​apps/​listserv/​x-check/​qmeasure.cgi?​submit=​PCPI.

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59.  US DHHS. “National Healthcare Disparities Report 2013.” Available at: http://www.ahrq.gov/​research/​findings/​nhqrdr/​nhdr13/​chap7.html.

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62.  In the FY 2013 IPPS/LTCH PPS final rule, we adopted HBIPS-7 Post Discharge Continuing Care Plan Transmitted to the Next Level of Care Provider Upon Discharge, beginning with the FY 2014 payment determination (77 FR 53651-53652). We refer readers to that rule for a detailed discussion of this measure.

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64.  van Walraven C, Seth R, Austin PC, Laupacis A. (2002). Effect of discharge summary availability during postdischarge visits on hospital readmission. Journal of General Internal Medicine 17:186-192.

65.  Jack BW, Chetty VK, Anthony D, et al. (2009). A reengineered hospital discharge program to decrease rehospitalization. Ann Intern Med.150 (3),178-187.

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66.  van Walraven C, Seth R, Austin PC, Laupacis A. (2002). Effect of discharge summary availability during postdischarge visits on hospital readmission. Journal of General Internal Medicine 17:186-192.

67.  Jack BW, Chetty VK, Anthony D, et al. (2009). A reengineered hospital discharge program to decrease rehospitalization. Ann Intern Med. 150 (3),178-187.

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68.  Kripalani S, LeFevre F, Phillips CO, et al. Deficits in communication and information transfer between hospital based and primary care physicians: implications for patient safety and continuity of care. JAMA 2007;297(8):831-841.

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69.  Timely Transmission of Transition Record (Discharged from Inpatient Facility to Home/Self Care or Any Other Site of Care), available at http://www.ama-assn.sorg/​apps/​listserv/​x-check/​qmeasure.cgi?​submit=​PCPI.

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70.  The American Diabetes Association, APA, the American Association of Clinical Endocrinologists, and the North American Association for the Study of Obesity (2004). Consensus development conference on antipsychotic drugs and obesity and diabetes. Diabetes Care, 27, 596-601. Marder, Stephen R., M.D., et al. Physical Health Monitoring of Patients with Schizophrenia. Am J Psychiatry. 2004 Aug;161(8):1334-49.

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71.  The American Diabetes Association, APA, the American Association of Clinical Endocrinologists, and the North American Association for the Study of Obesity (2004). Consensus development conference on antipsychotic drugs and obesity and diabetes. Diabetes Care, 27, 596-601.

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72.  Ibid.

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73.  Ibid.

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74.  The American Diabetes Association (2006). Antipsychotic Medications and the Risk of Diabetes and Cardiovascular Disease. Available at: http://professional.diabetes.org/​admin/​UserFiles/​file/​CE/​AntiPsych%20Meds/​Professional%20Tool%20%231(1).pdf (emphasis added).

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75.  Roohafsza, H, Khani, A, Afshar, H, Garakyaraghi, A, Ghodsi, B. Lipid profile in antipsychotic drug users: A comparative study. ARYA Atheroscler. May 2013; 9(3): 198-202 (emphasis added).

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76.  De Hert, M., Dekker, J.M. & Wood, D. (2009). Cardiovascular disease and diabetes in people with severe mental illness. Position statement from the European Psychiatric Association (EPA), supported by the European Association for the Study of Diabetes (EASD) and the European Society of Cardiology (ESC). Eur Psychiatry, 24, 412-424; Zolnierek, C.D. (2009). Non-psychiatric hospitalization of people with mental illnesses: A systematic review. Journal of Advanced Nursing, 65 (8), 1570-1583.

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77.  National Association of State Mental Health Program Directors Medical Directors Council (2006). Morbidity and mortality in people with serious mental illness. Available at: http://www.nasmhpd.org/​docs/​publications/​MDCdocs/​Mortality%20and%20Morbidity%20Final%20Report%208.18.08.pdf.

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78.  The Mount Sinai Conference was conferred to “focus on specific questions regarding the pharmacotherapy of schizophrenia . . . Participants in the conference were selected based on their knowledge of and contributions to the literature in this area . . . Also in attendance [were] various groups concerned with improving psychopharmacology in routine practice settings.” Marder, Stephen R., M.D., et al. Physical Health Monitoring of Patients with Schizophrenia. Am J Psychiatry. 2004 Aug;161(8):1334-49.

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79.  Marder, Stephen R., M.D., et al. Physical Health Monitoring of Patients with Schizophrenia. Am J Psychiatry. 2004 Aug;161(8):1334-49.

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80.  See e.g., Brooks, Megan. “Metabolic Screening in Antipsychotic Users: Whose Job Is It?” Medscape Medical News. 8 May 2012. Available at http://www.medscape.com/​viewarticle/​763468. Mittal D, Li C, Viverito K, Williams JS, Landes RD, Thapa PB, Owen R. Monitoring for metabolic side effects among outpatients with dementia receiving antipsychotics. Psychiatr Serv. 2014 Sep 1;65(9):1147-53.

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81.  Nasrallah, H. A, MD (2012). There is no excuse for failing to provide metabolic monitoring for patients receiving antipsychotics. Current Psychiatry, 4 (citing Mitchell AJ, Delaffon V, Vancampfort D, et al. Guideline concordant monitoring of metabolic risk in people treated with antipsychotic medication: Systematic review and meta-analysis of screening practices. Psychol Med. 2012;42(1):125-147.)

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82.  Development of Quality Measures for Inpatient Psychiatric Facilities. February 2015. U.S. Department of Health and Human Services, Assistant Secretary for Planning and Evaluation, Office of Disability, Aging, and Long-term Care Policy. Page xi, at http://aspe.hhs.gov/​daltcp/​reports/​2015/​ipf.cfm.

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84.  Health Services Advisory Group. Inpatient Psychiatric Facility Outcome and Process Measure Development and Maintenance: Screening of Metabolic Disorders Measure Workgroup. Tampa, FL; 2015. Available at: http://www.cms.gov/​Medicare/​Quality-Initiatives-Patient-Assessment-Instruments/​MMS/​Downloads/​Inpatient-Psychiatric-Facility-IPF-Outcome-and-Process-Measure-Development-and-Maintenance.zip.

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85.  American Diabetes Association, American Psychological Association, American Association of Clinical Endocrinologists, North American Association for the Study of Obesity. Consensus development conference on antipsychotic drugs and obesity and diabetes. Diabetes Care. 2004;27(596-601).

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86.  American Diabetes Association, American Psychological Association, American Association of Clinical Endocrinologists, North American Association for the Study of Obesity. Consensus development conference on antipsychotic drugs and obesity and diabetes. Diabetes Care. 2004;27(596-601).

87.  National Institute for Health and Care Excellence (NICE). Bipolar disorder: The assessment and management of bipolar disorder in adults, children and young people in primary and secondary care. London, UK 2014.

88.  National Institute for Health and Care Excellence (NICE). Psychosis and schizophrenia in adults: Treatment and management. London, UK 2014.

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89.  Cuffel B, Held M, Goldman W. Predictive Models and the Effectiveness of Strategies for Improving Outpatient Follow-up Under Managed Care. Psychiatric Services. 2002 November; 53 (11): 1438-1443.

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90.  Cohn T. Metabolic Monitoring for Patients on Antipsychotic Medications. Psychiatric Times. December 2013.

91.  Rodday AM, Parsons SK, Mankiw C, et al. Child and Adolescent Psychiatrists' Reported Monitoring Behaviors for Second-Generation Antipsychotics. J. Child Adolesc. Psychopharmacol. 2015.

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92.  Health Services Advisory Group. Inpatient Psychiatric Facility Outcome and Process Measure Development and Maintenance: Screening of Metabolic Disorders Measure Workgroup. Tampa, FL; 2015. Available at: http://www.cms.gov/​Medicare/​Quality-Initiatives-Patient-Assessment-Instruments/​MMS/​Downloads/​Inpatient-Psychiatric-Facility-IPF-Outcome-and-Process-Measure-Development-and-Maintenance.zip.

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93.  Blair R, Liu J, Rosenau M, et al. Development of Quality Measures for Inpatient Psychiatric Facilities: Final Report. 2015; Washington, DC: Office of the Assistant Secretary for Planning and Evaluation, U.S. Department of Health & Human Services 2015. Available at: http://aspe.hhs.gov/​daltcp/​reports/​2015/​ipf.cfm. Accessed April 21, 2015.

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94.  Health Services Advisory Group. Inpatient Psychiatric Facility Outcome and Process Measure Development and Maintenance: Screening of Metabolic Disorders Measure Workgroup. Tampa, FL; 2015. Available at: http://www.cms.gov/​Medicare/​Quality-Initiatives-Patient-Assessment-Instruments/​MMS/​Downloads/​Inpatient-Psychiatric-Facility-IPF-Outcome-and-Process-Measure-Development-and-Maintenance.zip.

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95.  National Institute for Health and Care Excellence (NICE). Bipolar disorder: The assessment and management of bipolar disorder in adults, children and young people in primary and secondary care. London, UK 2014.

96.  National Institute for Health and Care Excellence (NICE). Psychosis and schizophrenia in adults: Treatment and management. London, UK 2014.

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97.  Cuffel B, Held M, Goldman W. Predictive Models and the Effectiveness of Strategies for Improving Outpatient Follow-up Under Managed Care. Psychiatric Services. 2002 November; 53 (11): 1438-1443.

Back to Citation

98.  Health Services Advisory Group. Inpatient Psychiatric Facility Outcome and Process Measure Development and Maintenance: Screening of Metabolic Disorders Measure Workgroup. Tampa, FL; 2015. Available at: http://www.cms.gov/​Medicare/​Quality-Initiatives-Patient-Assessment-Instruments/​MMS/​Downloads/​Inpatient-Psychiatric-Facility-IPF-Outcome-and-Process-Measure-Development-and-Maintenance.zip.

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99.  American Diabetes Association, American Psychological Association, American Association of Clinical Endocrinologists, North American Association for the Study of Obesity. Consensus development conference on antipsychotic drugs and obesity and diabetes. Diabetes Care. 2004;27(596-601).

100.  National Institute for Health and Care Excellence (NICE). Bipolar disorder: The assessment and management of bipolar disorder in adults, children and young people in primary and secondary care. London, UK2014.

101.  National Institute for Health and Care Excellence (NICE). Psychosis and schizophrenia in adults: Treatment and management. London, UK2014.

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102.  Blair R, Liu J, Rosenau M, et al. Development of Quality Measures for Inpatient Psychiatric Facilities: Final Report. 2015; Washington, DC: Office of the Assistant Secretary for Planning and Evaluation, U.S. Department of Health & Human Services 2015. Available at: http://aspe.hhs.gov/​daltcp/​reports/​2015/​ipf.cfm. Accessed April 21, 2015.

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103.  American Diabetes Association, American Psychological Association, American Association of Clinical Endocrinologists, North American Association for the Study of Obesity. Consensus development conference on antipsychotic drugs and obesity and diabetes. Diabetes Care. 2004;27(596-601).

104.  National Institute for Health and Care Excellence (NICE). Bipolar disorder: The assessment and management of bipolar disorder in adults, children and young people in primary and secondary care. London, UK2014.

105.  National Institute for Health and Care Excellence (NICE). Psychosis and schizophrenia in adults: Treatment and management. London, UK 2014.

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106.  Health Services Advisory Group. Inpatient Psychiatric Facility Outcome and Process Measure Development and Maintenance: Screening of Metabolic Disorders Measure Workgroup. Tampa, FL: Health Services Advisory Group; 2015. Available at: http://www.cms.gov/​Medicare/​Quality-Initiatives-Patient-Assessment-Instruments/​MMS/​Downloads/​Inpatient-Psychiatric-Facility-IPF-Outcome-and-Process-Measure-Development-and-Maintenance.zip.

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107.  Musil R, Obermeier M, Russ P, Hamerle M. Weight gain and antipsychotics: A drug safety review. Expert Opin Drug Saf. 2015;14(1):73-96.

108.  Chiliza B, Asmal L, Oosthuizen P, et al. Changes in body mass and metabolic profiles in patients with first-episode schizophrenia treated for 12 months with a first-generation antipsychotic. Eur. Psychiatry. 2015;30(2):277-283.

109.  Alvarez-Jimenez M, Gonzalez-Blanch C, Crespo-Facorro B, et al. Antipsychotic-induced weight gain in chronic and first-episode psychotic disorders: A systematic critical reappraisal. CNS Drugs. 2008;22(7):547-562.

110.  Strassnig M, Miewald J, Keshavan M, Ganguli R. Weight gain in newly diagnosed first-episode psychosis patients and healthy comparisons: One-year analysis. Schizophr. Res. 2007;93(1-3):90-98.

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111.  National Institute for Health and Care Excellence (NICE). Psychosis and schizophrenia in adults: Treatment and management. 2014; http://www.nice.org.uk/​guidance/​cg178. Accessed CG 178.

112.  National Institute for Health and Care Excellence (NICE). Bipolar disorder: the assessment and management of bipolar disorder in adults, children and young people in primary and secondary care. 2014; http://www.nice.org.uk/​guidance/​cg185. Accessed CG 185.

113.  Marder SR, Essock SM, Miller AL, et al. Physical health monitoring of patients with schizophrenia. Am. J. Psychiatry. 2004;161(8):1334-1349.

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117.  In the FY 2015 IPF PPS final rule we estimated 1,626 IPFs and are adjusting that estimate by −9 to account for more recent data.

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118.  In the FY 2015 IPF PPS final rule we estimated 556 cases per year and are adjusting that estimate by −125 to account for more recent data.

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[FR Doc. 2015-18903 Filed 7-31-15; 4:15 pm]

BILLING CODE 4120-01-P