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Proposed Rule

Medicare Program; Prospective Payment System and Consolidated Billing for Skilled Nursing Facilities for FY 2014

Action

Proposed Rule.

Summary

This proposed rule would update the payment rates used under the prospective payment system (PPS) for skilled nursing facilities (SNFs) for fiscal year (FY) 2014, would revise and rebase the SNF market basket, and would make certain technical and conforming revisions in the regulations text. This proposed rule also includes a proposed policy for reporting the SNF market basket forecast error correction in certain limited circumstances and a proposed new item for the Minimum Data Set (MDS), Version 3.0.

Unified Agenda

Prospective Payment System and Consolidated Billing for Skilled Nursing Facilities--Update for FY 2014 (CMS-1446-F)

3 actions from May 6th, 2013 to July 2013

  • May 6th, 2013
  • July 1st, 2013
    • NPRM Comment Period End
  • July 2013
    • Final Action
 

Table of Contents Back to Top

Tables Back to Top

DATES: Back to Top

To be assured consideration, comments must be received at one of the addresses provided below, no later than 5 p.m. on July 1, 2013.

ADDRESSES: Back to Top

In commenting, please refer to file code CMS-1446-P. Because of staff and resource limitations, we cannot accept comments by facsimile (FAX) transmission.

You may submit comments in one of four ways (please choose only one of the ways listed):

1. Electronically. You may submit electronic comments on this regulation to http://www.regulations.gov. Follow the “Submit a comment” instructions.

2. By regular mail. You may mail written comments to the following address only:Centers for Medicare & Medicaid Services,Department of Health and Human Services,Attention: CMS-1446-P,P.O. Box 8016,Baltimore, MD 21244-8016.

Please allow sufficient time for mailed comments to be received before the close of the comment period.

3. By express or overnight mail. You may send written comments to the following address only:Centers for Medicare & Medicaid Services,Department of Health and Human Services,Attention: CMS-1446-P,Mail Stop C4-26-05,7500 Security Boulevard,Baltimore, MD 21244-1850.

4. By hand or courier. If you prefer, you may deliver (by hand or courier) your written comments before the close of the comment period to either of the following addresses:

a. Centers for Medicare & Medicaid Services,Department of Health and Human Services,Room 445-G, Hubert H. Humphrey Building,200 Independence Avenue SW.,Washington, DC 20201.

(Because access to the interior of the Hubert H. Humphrey Building is not readily available to persons without Federal Government identification, commenters are encouraged to leave their comments in the CMS drop slots located in the main lobby of the building. A stamp-in clock is available for persons wishing to retain a proof of filing by stamping in and retaining an extra copy of the comments being filed.)

b. Centers for Medicare & Medicaid Services,Department of Health and Human Services,7500 Security Boulevard,Baltimore, MD 21244-1850.

If you intend to deliver your comments to the Baltimore address, please call telephone number (410) 786-7195 in advance to schedule your arrival with one of our staff members.

Comments mailed to the addresses indicated as appropriate for hand or courier delivery may be delayed and received after the comment period.

For information on viewing public comments, see the beginning of the SUPPLEMENTARY INFORMATION section.

FOR FURTHER INFORMATION CONTACT: Back to Top

Penny Gershman, (410) 786-6643, for information related to clinical issues.

John Kane, (410) 786-0557, for information related to the development of the payment rates and case-mix indexes.

Kia Sidbury, (410) 786-7816, for information related to the wage index.

Bill Ullman, (410) 786-5667, for information related to level of care determinations, consolidated billing, and general information.

SUPPLEMENTARY INFORMATION: Back to Top

Inspection of Public Comments: All comments received before the close of the comment period are available for viewing by the public, including any personally identifiable or confidential business information that is included in a comment. We post all comments received before the close of the comment period on the following Web site as soon as possible after they have been received: http://www.regulations.gov. Follow the search instructions on that Web site to view public comments.

Comments received timely will also be available for public inspection as they are received, generally beginning approximately 3 weeks after publication of a document, at the headquarters of the Centers for Medicare & Medicaid Services, 7500 Security Boulevard, Baltimore, Maryland 21244, Monday through Friday of each week from 8:30 a.m. to 4 p.m. To schedule an appointment to view public comments, phone 1-800-743-3951.

Availability of Certain Information Exclusively Through the Internet on the CMS Web Site Back to Top

The Wage Index for Urban Areas Based on CBSA Labor Market Areas (Table A) and the Wage Index Based on CBSA Labor Market Areas for Rural Areas (Table B) are published in the Federal Register as an Addendum to the annual SNF PPS rulemaking (that is, the SNF PPS proposed and final rules or, when applicable, the current update notice). However, as of FY 2012, a number of other Medicare payment systems adopted an approach in which such tables are no longer published in the Federal Register in this manner, and instead are made available exclusively through the Internet; see, for example, the FY 2012 Hospital Inpatient PPS (IPPS) final rule (76 FR 51476). To be consistent with these other Medicare payment systems and streamline the published content to focus on policy discussion, we now propose to adopt a similar approach for the SNF PPS as well. As discussed in greater detail in section VI. of this proposed rule, we would revise the applicable regulations text at § 413.345 to accommodate this approach, consistent with the wording of the corresponding statutory authority at section 1888(e)(4)(H)(iii) of the Social Security Act (the Act). Under this approach, effective October 1, 2013, the individual wage index values displayed in Tables A and B of this rule would no longer be published in the Federal Register as part of the annual SNF PPS rulemaking, and instead would be made available exclusively through the Internet on CMS's SNF PPS Web site at http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/WageIndex.html. Consistent with the provisions of section 1888(e)(4)(H)(iii) of the Act, we would continue to publish in the Federal Register the specific “factors to be applied in making the area wage adjustment” (for example, the SNF prospective payment system's use of the hospital wage index exclusive of its occupational mix adjustment) as part of our annual SNF PPS rulemaking process, but that document would no longer include a listing of the individual wage index values themselves, which would instead be made available exclusively through the Internet on the CMS Web Site.

In addition, we note that in previous years, each rule or update notice issued under the annual SNF PPS rulemaking cycle has included a detailed reiteration of the various individual legislative provisions that have affected the SNF PPS over the years, a number of which represented temporary measures that have long since expired. That discussion, along with detailed background information on various other aspects of the SNF PPS, will now be made available exclusively on the CMS Web site as well, at http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/index.html. In connection with this change, this proposed rule is presented in a revised format that also serves to consolidate material on the individual rate components that had previously appeared redundantly in several different portions of the preamble. The revised format also reorders the preamble discussion to achieve a more logical presentation, by systematically discussing each of the various rate components in the actual order in which it is applied to the SNF payment rates. For ease of reference, we are including the following crosswalk between this proposed rule's reordered preamble discussion and the material that was presented in last year's SNF PPS update notice for FY 2013 (77 FR 46214, August 2, 2012).

Crosswalk to FY 2013 Update Notice Back to Top

FY 2014 Proposed Rule FY 2013 Update Notice
I. Executive Summary I.
II.A Statutory Basis and Scope II.A
II.B Initial Transition II.A
II.C Required Annual Rate Updates II.B, III.D
III.A Federal Base Rates II.A, II.G.1, III.A.1
III.B.1 SNF Market Basket Index II.G.2, V
III.B.2 Use of the SNF Market Basket Percentage II.G.2, V.A
III.B.3 Forecast Error Adjustment II.G.2, V.B
III.B.4 Multifactor Productivity Adjustment (MFP) II.G.2, V.C
III.B.4.1 Incorporating the MFP into the Market Basket Update V.C.1
III.B.5 Market Basket Update Factor for FY 2014 V.D
III.C Case-Mix (C-M) Adjustment II.G.1, III.A.2, III.B
III.D Wage Index Adjustment III.C
III.E Adjusted Rate Computation Example III.F
IV.A SNF Level of Care—Administrative Presumption II.A, III.E
IV.B Consolidated Billing II.A, VI
IV.C Payment for SNF-Level Swing-Bed Services II.A, VII
V.A Revising and Rebasing the SNF Market Basket Index N/A
V.B Monitoring Impact of FY 2012 Policy Changes IV
V.C Ensuring Accuracy in Grouping to Rehabilitation Categories N/A
V.D SNF Therapy Research Project N/A
VI. Provisions of the Proposed Rule and Technical Correction N/A
VII. Collection of Information Requirements VIII.
VIII. Response to Comments N/A
IX. Economic Analyses X.
Table 1 Diff. Bet. Forecasted, Actual Market Basket Increases Table 1
Table 2 Unadjusted Federal Rate Per Diem (Urban) Table 2
Table 3 Unadjusted Federal Rate Per Diem (Rural) Table 3
Table 4 C-M Adjusted Federal Rates, Indexes (Urban) Table 4
Table 5 C-M Adjusted Federal Rates, Indexes (Rural) Table 5
Table 6 C-M Adj. Fed. Rates (Urban), Lab./Non-Lab. Components Table 6
Table 7 C-M Adj. Fed. Rates (Rural), Lab./Non-Lab. Components Table 7
Table 8 Rate Computation Example Table 8
Tables 9 through 16 Revising & Rebasing SNF Market Basket N/A
Table 17 Labor-Related Relative Importance Table 13
Table 18 C-M Distributions by Major RUG-IV Category Table 9
Table 19 C-M Distribution for Therapy RUG-IV Groups Table 10
Table 20 Mode of Therapy Provision Table 11
Table 21 Distribution of MDS Assessment Types Table 12
Table 22 Projected Impact Table 14
Table 23 Accounting Statement Table 15

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

Table of Contents Back to Top

I. Executive Summary

A. Purpose

B. Summary of Major Provisions

C. Summary of Cost and Benefits

II. Background

A. Statutory Basis and Scope

B. Initial Transition

C. Required Annual Rate Updates

III. SNF PPS Rate Setting Methodology and FY 2014 Update

A. Federal Base Rates

B. SNF Market Basket Update

1. SNF Market Basket Index

2. Use of the SNF Market Basket Percentage

3. Forecast Error Adjustment

4. Multifactor Productivity Adjustment

5. Market Basket Update Factor for FY 2014

C. Case-Mix Adjustment

D. Wage Index Adjustment

E. Adjusted Rate Computation Example

IV. Additional Aspects of the SNF PPS

A. SNF Level of Care—Administrative Presumption

B. Consolidated Billing

C. Payment for SNF-Level Swing-Bed Services

V. Other Issues

A. Revising and Rebasing the SNF Market Basket Index

1. Background

2. Revising and Rebasing the SNF Market Basket

3. Price Proxies Used to Measure Cost Category Growth

4. Proposed Market Basket Estimate for the FY 2014 SNF PPS Update

5. Labor-Related Share

B. Monitoring Impact of FY 2012 Policy Changes

1. RUG Distributions

2. Group Therapy Allocation

3. MDS 3.0 Changes

4. Conclusion

C. Ensuring Accuracy in Grouping to Rehabilitation RUG-IV Categories

D. SNF Therapy Research Project

VI. Provisions of the Proposed Rule and Technical Correction

VII. Collection of Information Requirements

VIII. Response to Comments

IX. Economic Analyses

Regulation Text

Acronyms Back to Top

In addition, because of the many terms to which we refer by acronym in this proposed rule, we are listing these abbreviations and their corresponding terms in alphabetical order below:

AIDSAcquired Immune Deficiency Syndrome

ARDAssessment reference date

BBABalanced Budget Act of 1997, Pub. L. 105-33

BBRAMedicare, Medicaid, and SCHIP Balanced Budget Refinement Act of 1999, Pub. L. 106-113

BIPAMedicare, Medicaid, and SCHIP Benefits Improvement and Protection Act of 2000, Pub. L. 106-554

CAHCritical access hospital

CBSACore-based statistical area

CFRCode of Federal Regulations

CMICase-mix index

CMSCenters for Medicare & Medicaid Services

COTChange of therapy

ECIEmployment Cost Index

EOTEnd of therapy

EOT-REnd of therapy—resumption

FQHCFederally qualified health center

FRFederal Register

FYFiscal year

GAOGovernment Accountability Office

HCPCSHealthcare Common Procedure Coding System

HOMERHome office Medicare records

IGIIHS (Information Handling Services) Global Insight, Inc.

MDSMinimum data set

MFPMultifactor productivity

MMAMedicare Prescription Drug, Improvement, and Modernization Act of 2003, Pub. L. 108-173

MSAMetropolitan statistical area

NAICSNorth American Industrial Classification System

OMBOffice of Management and Budget

OMRAOther Medicare Required Assessment

PPSProspective Payment System

RAIResident assessment instrument

RAVENResident assessment validation entry

RFARegulatory Flexibility Act, 96

RHC Rural health clinic

RIARegulatory impact analysis

RUG-IIIResource Utilization Groups, Version 3

RUG-VResource Utilization Groups, Version 4

RUG-53Refined 53-Group RUG-III Case-Mix Classification System

SCHIPState Children's Health Insurance Program

SNFSkilled nursing facility

STMStaff time measurement

STRIVEStaff time and resource intensity verification

UMRAUnfunded Mandates Reform Act, Pub. L. 104-4

I. Executive Summary Back to Top

A. Purpose

This proposed rule would update the SNF prospective payment rates for FY 2014 as required under section 1888(e)(4)(E) of the Act. It would also respond to section 1888(e)(4)(H) of the Act, which requires the Secretary to “provide for publication in the Federal Register” before the August 1 that precedes the start of each fiscal year, the unadjusted federal per diem rates, the case-mix classification system, and the factors to be applied in making the area wage adjustment used in computing the prospective payment rates for that fiscal year.

B. Summary of Major Provisions

In accordance with sections 1888(e)(4)(E)(ii)(IV) and 1888(e)(5) of the Act, the federal rates in this proposed rule would reflect an update to the rates that we published in the SNF PPS update notice for FY 2013 (77 FR 46214) which reflects the SNF market basket index, adjusted by the forecast error correction, if applicable, and the multifactor productivity adjustment for FY 2014.

C. Summary of Cost and Benefits

Provision description Total transfers
Proposed FY 2014 SNF PPS payment rate update The overall economic impact of this proposed rule would be an estimated increase of $500 million in aggregate payments to SNFs during FY 2014.

II. Background Back to Top

A. Statutory Basis and Scope

As amended by section 4432 of the Balanced Budget Act of 1997 (BBA, Pub. L. 105-33, enacted on August 5, 1997), section 1888(e) of the Act provides for the implementation of a PPS for SNFs. This methodology uses prospective, case-mix adjusted per diem payment rates applicable to all covered SNF services defined in section 1888(e)(2)(A) of the Act. The SNF PPS is effective for cost reporting periods beginning on or after July 1, 1998, and covers all costs of furnishing covered SNF services (routine, ancillary, and capital-related costs) other than costs associated with approved educational activities and bad debts. Under section 1888(e)(2)(A)(i) of the Act, covered SNF services include post-hospital extended care services for which benefits are provided under Part A, as well as those items and services (other than a small number of excluded services, such as physician services) for which payment may otherwise be made under Part B and which are furnished to Medicare beneficiaries who are residents in a SNF during a covered Part A stay. A comprehensive discussion of these provisions appears in the May 12, 1998 interim final rule (63 FR 26252).

B. Initial Transition

Under sections 1888(e)(1)(A) and 1888(e)(11) of the Act, the SNF PPS included an initial, three-phase transition that blended a facility-specific rate (reflecting the individual facility's historical cost experience) with the federal case-mix adjusted rate. The transition extended through the facility's first three cost reporting periods under the PPS, up to and including the one that began in FY 2001. Thus, the SNF PPS is no longer operating under the transition, as all facilities have been paid at the full federal rate effective with cost reporting periods beginning in FY 2002. As we now base payments for SNFs entirely on the adjusted federal per diem rates, we no longer include adjustment factors under the transition related to facility-specific rates for the upcoming FY.

C. Required Annual Rate Updates

Section 1888(e)(4)(E) of the Act requires the SNF PPS payment rates to be updated annually. The most recent annual update occurred in an update notice that set forth updates to the SNF PPS payment rates for FY 2013 (77 FR 46214).

Under this requirement, section 1888(e)(4)(H) of the Act specifies that we provide for publication annually in the Federal Register of the following:

  • The unadjusted federal per diem rates to be applied to days of covered SNF services furnished during the upcoming FY.
  • The case-mix classification system to be applied with respect to these services during the upcoming FY.
  • The factors to be applied in making the area wage adjustment with respect to these services.

Along with other revisions discussed later in this preamble, this proposed rule would provide the required annual updates to the per diem payment rates for SNFs for FY 2014.

III. SNF PPS Rate Setting Methodology and FY 2014 Update Back to Top

A. Federal Base Rates

Under section 1888(e)(4) of the Act, the SNF PPS uses per diem federal payment rates based on mean SNF costs in a base year (FY 1995) updated for inflation to the first effective period of the PPS. We developed the federal payment rates using allowable costs from hospital-based and freestanding SNF cost reports for reporting periods beginning in FY 1995. The data used in developing the federal rates also incorporated a “Part B add-on,” which is an estimate of the amounts that, prior to the SNF PPS, would have been payable under Part B for covered SNF services furnished to individuals during the course of a covered Part A stay in a SNF.

In developing the rates for the initial period, we updated costs to the first effective year of the PPS (the 15-month period beginning July 1, 1998) using a SNF market basket index, and then standardized for geographic variations in wages and for the costs of facility differences in case mix. In compiling the database used to compute the federal payment rates, we excluded those providers that received new provider exemptions from the routine cost limits, as well as costs related to payments for exceptions to the routine cost limits. Using the formula that the BBA prescribed, we set the federal rates at a level equal to the weighted mean of freestanding costs plus 50 percent of the difference between the freestanding mean and weighted mean of all SNF costs (hospital-based and freestanding) combined. We computed and applied separately the payment rates for facilities located in urban and rural areas, and adjusted the portion of the federal rate attributable to wage-related costs by a wage index to reflect geographic variations in wages.

B. SNF Market Basket Update

1. SNF Market Basket Index

Section 1888(e)(5)(A) of the Act requires us to establish a SNF market basket index that reflects changes over time in the prices of an appropriate mix of goods and services included in covered SNF services. Accordingly, we have developed a SNF market basket index that encompasses the most commonly used cost categories for SNF routine services, ancillary services, and capital-related expenses. We use the SNF market basket index, adjusted in the manner described below, to update the federal rates on an annual basis. In the SNF PPS final rule for FY 2008 (72 FR 43425 through 43430), we revised and rebased the market basket, which included updating the base year from FY 1997 to FY 2004. For FY 2014, we propose to revise and rebase the market basket to reflect FY 2010 total cost data, as detailed in section V.A. of this proposed rule.

We are also proposing to determine the FY 2014 market basket increase based on the percent increase in the revised and rebased FY 2010-based SNF market basket. For the FY 2014 proposed rule, the FY 2010-based SNF market basket growth rate is estimated to be 2.3 percent, which is based on the Information Handling Services (IHS) Global Insight, Inc. (IGI) first quarter 2013 forecast with historical data through fourth quarter 2012. In section III.B.5 of this proposed rule, we discuss the specific application of this adjustment to the forthcoming annual update of the SNF PPS payment rates.

2. Use of the SNF Market Basket Percentage

Section 1888(e)(5)(B) of the Act defines the SNF market basket percentage as the percentage change in the SNF market basket index from the midpoint of the previous FY to the midpoint of the current FY. For the federal rates set forth in this proposed rule, we use the percentage change in the SNF market basket index to compute the update factor for FY 2014. This is based on the IGI first quarter 2013 forecast (with historical data through the fourth quarter 2012) of the FY 2014 percentage increase in the FY 2010-based SNF market basket index for routine, ancillary, and capital-related expenses, which is used to compute the update factor in this proposed rule. As discussed in sections III.B.3. and III.B.4. of this proposed rule, this market basket percentage change would be reduced by the forecast error correction (§ 413.337(d)(2)), and by the MFP adjustment as required by section 1888(e)(5)(B)(ii) of the Act. Finally, as discussed in section II.B. of this proposed rule, we no longer compute update factors to adjust a facility-specific portion of the SNF PPS rates, because the initial 3-phase transition period from facility-specific to full federal rates that started with cost reporting periods beginning in July 1998 has expired.

3. Forecast Error Adjustment

As discussed in the June 10, 2003 supplemental proposed rule (68 FR 34768) and finalized in the August 4, 2003, final rule (68 FR 46057 through 46059), the regulations at § 413.337(d)(2) provide for an adjustment to account for market basket forecast error. The initial adjustment for market basket forecast error applied to the update of the FY 2003 rate for FY 2004, and took into account the cumulative forecast error for the period from FY 2000 through FY 2002, resulting in an increase of 3.26 percent to the FY 2004 update. Subsequent adjustments in succeeding FYs take into account the forecast error from the most recently available FY for which there is final data, and apply the difference between the forecasted and actual change in the market basket when the difference exceeds a specified threshold. We originally used a 0.25 percentage point threshold for this purpose; however, for the reasons specified in the FY 2008 SNF PPS final rule (72 FR 43425, August 3, 2007), we adopted a 0.5 percentage point threshold effective for FY 2008 and subsequent fiscal years. As we stated in the final rule for FY 2004 that first issued the market basket forecast error adjustment (68 FR 46058, August 4, 2003), the adjustment will “. . . reflect both upward and downward adjustments, as appropriate.”

For FY 2012 (the most recently available FY for which there is final data), the estimated increase in the market basket index was 2.7 percentage points, while the actual increase was 2.2 percentage points, resulting in the actual increase being 0.5 percentage point lower than the estimated increase. As the forecast error calculation in this instance does not permit one to determine definitively if the forecast error adjustment threshold has been exceeded, we are proposing a policy that would be applied in instances, and only those instances, where the forecast error calculation is equal to 0.5 percentage point, when rounded to one significant digit (otherwise referred to as a tenth of a percentage point), as further discussed below. When the forecast error, rounded to one significant digit, is equal to 0.5 percentage point, we propose to report the forecast error to two significant digits (otherwise referred to as a hundredth of a percentage point) so that we may determine whether the forecast error correction threshold has been exceeded and whether the forecast error adjustment should be applied under § 413.337(d)(2). This policy would apply only in those instances where the forecast error, when rounded to one significant digit, is 0.5 percentage point. For example, if the forecast error is calculated to be 0.4 percentage point when rounded to one significant digit, then no further determinations are necessary, the forecast error will be reported as 0.4 percentage point, and a forecast error adjustment will not be applied. Likewise, if the forecast error is determined to be 0.6 percentage point when rounded to one significant digit, then no further determination is necessary, the forecast error will be reported as 0.6 percentage point, and a forecast error adjustment will be applied.

We propose that when the forecast error is determined to be 0.5 percentage point, when rounded to one significant digit, the determination of whether or not the threshold has been exceeded would be made by rounding the forecast error calculation to the second significant digit. We believe this approach is necessary and appropriate to ensure that the necessity for a forecast error adjustment is accurately determined in accordance with § 413.337(d)(2), which enables us to identify those instances where the difference between the actual and projected market basket becomes sufficiently significant to indicate that the historical price changes are not being adequately reflected. This proposed policy would enable us to distinguish between cases where the difference carried out to the second decimal place is less than the 0.5 threshold but rounds to 0.5 (0.45 to 0.49) and cases where the difference carried out to the second decimal place is greater than the 0.5 threshold but rounds to 0.5 (0.51 to 0.54). We would apply the proposed policy when the difference between the actual and projected market basket is either positive or negative 0.5 percentage point.

As stated earlier, the forecast error calculation for FY 2012 is equal to 0.5 percentage point, rounded to one significant digit, or a tenth of a percentage point. Therefore, following the proposed policy outlined above, we would determine the forecast error for FY 2012 to the second significant digit, or the hundredth of a percentage point. The forecasted FY 2012 SNF market basket percentage change was 2.7 percent. When rounded to the second significant digit, it was 2.69 percent. This would be subtracted from the actual FY 2012 SNF market basket percentage change, rounded to the second significant digit, of 2.18 percent to yield a negative forecast error correction of 0.51 percentage point. As the forecast error correction, when rounded to two significant digits, exceeds 0.5 percentage point, a forecast error adjustment would be warranted under the policy outlined in the FY 2008 SNF PPS final rule (72 FR 43425) (see § 413.337(d)(2)).

Consistent with prior applications of the forecast error adjustment since establishing the 0.5 percentage point threshold, and consistent with our applications of both the market basket adjustment and productivity adjustment described below, once we have determined that a forecast error adjustment is warranted, we will continue to apply the adjustment itself at one significant digit (otherwise referred to as a tenth of a percentage point). Therefore, because the forecasted FY 2012 SNF market basket percentage change exceeded the actual SNF market basket percentage change for FY 2012 (the most recently available FY for which there is final data) by 0.51 percentage point, the FY 2014 SNF market basket percentage change of 2.3 percent would be adjusted downward by the forecast error correction of 0.5 percentage point, resulting in a net SNF market basket increase factor of 1.8 percent. Table 1 shows the forecasted and actual market basket amounts for FY 2012.

Table 1—Difference Between the Forecasted and Actual Market Basket Increases for FY 2012 Back to Top
Index Forecasted FY 2012 increase* Actual FY 2012 increase** FY 2012 difference
* Published in Federal Register; based on second quarter 2011 IGI forecast (2004-based index).
** Based on the first quarter 2013 IHS Global Insight forecast, with historical data through the fourth quarter 2012 (2004-based index).
SNF (rounded to one significant digit) 2.7 2.2 −0.5
SNF (rounded to two significant digits) 2.69 2.18 −0.51

4. Multifactor Productivity Adjustment

Section 3401(b) of the Affordable Care Act requires that, in FY 2012 (and in subsequent FYs), the market basket percentage under the SNF payment system as described in section 1888(e)(5)(B)(i) of the Act is to be reduced annually by the productivity adjustment described in section 1886(b)(3)(B)(xi)(II) of the Act. Section 1886(b)(3)(B)(xi)(II) of the Act, added by section 3401(a) of the Affordable Care Act, sets forth the definition of this productivity adjustment. The statute defines the productivity adjustment to be equal to “the 10-year moving average of changes in annual economy-wide private nonfarm business multi-factor productivity (as projected by the Secretary for the 10-year period ending with the applicable fiscal year, year, cost-reporting period, or other annual period)” (the MFP adjustment). The Bureau of Labor Statistics (BLS) is the agency that publishes the official measure of private nonfarm business multifactor productivity (MFP). Please see http://www.bls.gov/mfp to obtain the BLS historical published MFP data.

The projection of MFP is currently produced by IGI, an economic forecasting firm. 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. This process is described in greater detail in section III.F.3 of the FY 2012 SNF PPS final rule (76 FR 48527 through 48529).

a. Incorporating the Multifactor Productivity Adjustment Into the Market Basket Update

According to section 1888(e)(5)(A) of the Act, the Secretary “shall establish a skilled nursing facility market basket index that reflects changes over time in the prices of an appropriate mix of goods and services included in covered skilled nursing facility services.” As described in section III.B.1. of this proposed rule, we propose to estimate the SNF PPS market basket percentage for FY 2014 under section 1888(e)(5)(B)(i) of the Act based on the proposed FY 2010-based SNF market basket. Section 1888(e)(5)(B)(ii) of the Act, added by section 3401(b) of the Affordable Care Act, requires that for FY 2012 and each subsequent FY, after determining the market basket percentage described in section 1888(e)(5)(B)(i) of the Act, “the Secretary shall reduce such percentage by the productivity adjustment described in section 1886(b)(3)(B)(xi)(II)” (which we refer to as the MFP adjustment). Section 1888(e)(5)(B)(ii) of the Act further states that the reduction of the market basket percentage by the MFP adjustment may result in the market basket percentage being less than zero for a FY, and may result in payment rates under section 1888(e) of the Act for a FY being less than such payment rates for the preceding FY. Thus, if the application of the MFP adjustment to the market basket percentage calculated under section 1888(e)(5)(B)(i) of the Act results in an MFP-adjusted market basket percentage that is less than zero, then the annual update to the unadjusted federal per diem rates under section 1888(e)(4)(E)(ii) of the Act would be negative, and such rates would decrease relative to the prior FY.

For the FY 2014 update, the MFP adjustment is calculated as the 10-year moving average of changes in MFP for the period ending September 30, 2014. In accordance with section 1888(e)(5)(B)(i) of the Act and § 413.337(d)(2) of the regulations, the market basket percentage for FY 2014 for the SNF PPS is based on IGI's first quarter 2013 forecast of the proposed FY 2010-based SNF market basket update, as adjusted by the forecast error adjustment, and is estimated to be 1.8 percent. In accordance with section 1888(e)(5)(B)(ii) of the Act (as added by section 3401(b) of the Affordable Care Act) and § 413.337(d)(3), this market basket percentage is then reduced by the MFP adjustment (the 10-year moving average of changes in MFP for the period ending September 30, 2014) of 0.4 percent, which is calculated as described above and based on IGI's first quarter 2013 forecast. The resulting MFP-adjusted SNF market basket update is equal to 1.4 percent, or 1.8 percent less 0.4 percentage point.

5. Market Basket Update Factor for FY 2014

Sections 1888(e)(4)(E)(ii)(IV) and 1888(e)(5)(i) of the Act require that the update factor used to establish the FY 2014 unadjusted federal rates be at a level equal to the market basket index percentage change. Accordingly, we determined the total growth from the average market basket level for the period of October 1, 2012 through September 30, 2013 to the average market basket level for the period of October 1, 2013 through September 30, 2014. This process yields an update factor of 2.3 percent. As further explained in section III.B.3 of this proposed rule, as applicable, we adjust the market basket update factor by the forecast error from the most recently available FY for which there is final data and apply this adjustment whenever the difference between the forecasted and actual percentage change in the market basket exceeds a 0.5 percentage point threshold. Since the forecasted FY 2012 SNF market basket percentage change exceeded the actual FY 2012 SNF market basket percentage change (FY 2012 is the most recently available FY for which there is final data) by more than 0.5 percentage point, the FY 2014 market basket of 2.3 percent would be adjusted downward by the applicable difference, in this case of 0.5 percentage points, which reduces the FY 2014 market basket update factor to 1.8 percent. In addition, for FY 2014, section 1888(e)(5)(B) of the Act requires us to reduce the market basket percentage by the MFP adjustment (the 10-year moving average of changes in MFP for the period ending September 30, 2014) of 0.4 percent, as described in section III.B.4. of this proposed rule. The resulting MFP-adjusted SNF market basket update would be equal to 1.4 percent, or 1.8 percent less 0.4 percentage point. We are proposing that if more recent data become available (for example, a more recent estimate of the FY 2010-based SNF market basket, MFP adjustment, and/or FY 2004-based SNF market basket used for the forecast error calculation), we would use such data, if appropriate, to determine the FY 2014 SNF market basket update, FY 2014 labor-related share relative importance, and MFP adjustment in the FY 2014 SNF PPS final rule. We used the SNF market basket, adjusted as described above, to adjust each per diem component of the federal rates forward to reflect the change in the average prices for FY 2014 from average prices for FY 2013. We would further adjust the rates by a wage index budget neutrality factor, described later in this section. Tables 2 and 3 reflect the updated components of the unadjusted federal rates for FY 2014, prior to adjustment for case-mix.

Table 2—FY 2014 Unadjusted Federal Rate per Diem—Urban Back to Top
Rate component Nursing—case-mix Therapy—case-mix Therapy—non-case-mix Non-case-mix
Per Diem Amount $165.92 $124.98 $16.46 $84.67
Table 3—FY 2014 Unadjusted Federal Rate per Diem—Rural Back to Top
Rate component Nursing—case-mix Therapy—case-mix Therapy—non-case-mix Non-case-mix
Per Diem Amount $158.52 $144.11 $17.58 $86.25

C. Case-Mix Adjustment

Under section 1888(e)(4)(G)(i) of the Act, the federal rate also incorporates an adjustment to account for facility case-mix, using a classification system that accounts for the relative resource utilization of different patient types. The statute specifies that the adjustment is to reflect both a resident classification system that the Secretary establishes to account for the relative resource use of different patient types, as well as resident assessment data and other data that the Secretary considers appropriate. In the interim final rule with comment period that initially implemented the SNF PPS (63 FR 26252, May 12, 1998), we developed the RUG-III case-mix classification system, which tied the amount of payment to resident resource use in combination with resident characteristic information. Staff time measurement (STM) studies conducted in 1990, 1995, and 1997 provided information on resource use (time spent by staff members on residents) and resident characteristics that enabled us not only to establish RUG-III, but also to create case-mix indexes (CMIs). The original RUG-III grouper logic was based on clinical data collected in 1990, 1995, and 1997. As discussed in the SNF PPS proposed rule for FY 2010 (74 FR 22208), we subsequently conducted a multi-year data collection and analysis under the Staff Time and Resource Intensity Verification (STRIVE) project to update the case-mix classification system for FY 2011. The resulting Resource Utilization Groups, Version 4 (RUG-IV) case-mix classification system reflected the data collected in 2006-2007 during the STRIVE project, and was finalized in the FY 2010 SNF PPS final rule (74 FR 40288) to take effect in FY 2011 concurrently with an updated new resident assessment instrument, version 3.0 of the Minimum Data Set (MDS 3.0), which collects the clinical data used for case-mix classification under RUG-IV.

We note that case-mix classification is based, in part, on the beneficiary's need for skilled nursing care and therapy services. The case-mix classification system uses clinical data from the MDS to assign a case-mix group to each patient that is then used to calculate a per diem payment under the SNF PPS. As discussed in section IV.A of this proposed rule, the clinical orientation of the case-mix classification system supports the SNF PPS's use of an administrative presumption that considers a beneficiary's initial case-mix classification to assist in making certain SNF level of care determinations. Further, because the MDS is used as a basis for payment, as well as a clinical assessment, we have provided extensive training on proper coding and the time frames for MDS completion in our Resident Assessment Instrument (RAI) Manual. For an MDS to be considered valid for use in determining payment, the MDS assessment must be completed in compliance with the instructions in the RAI Manual in effect at the time the assessment is completed. For payment and quality monitoring purposes, the RAI Manual consists of both the Manual instructions and the interpretive guidance and policy clarifications posted on the appropriate MDS Web site at http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/NursingHomeQualityInits/MDS30RAIManual.html.

In addition, we note that section 511 of the Medicare Prescription Drug, Improvement, and Modernization Act of 2003 (MMA) (Pub. L. 108-173, enacted December 8, 2003) amended section 1888(e)(12) of the Act to provide for a temporary increase of 128 percent in the PPS per diem payment for any SNF residents with Acquired Immune Deficiency Syndrome (AIDS), effective with services furnished on or after October 1, 2004. This special add-on for SNF residents with AIDS was to remain in effect until “... the Secretary certifies that there is an appropriate adjustment in the case mix ... to compensate for the increased costs associated with [such] residents. ...” The add-on for SNF residents with AIDS is also discussed in Program Transmittal #160 (Change Request #3291), issued on April 30, 2004, which is available online at www.cms.gov/transmittals/downloads/r160cp.pdf. In the SNF PPS final rule for FY 2010 (74 FR 40288), we did not address the certification of the add-on for SNF residents with AIDS in that final rule's implementation of the case-mix refinements for RUG-IV, thus allowing the add-on payment required by section 511 of the MMA to remain in effect. For the limited number of SNF residents that qualify for this add-on, there is a significant increase in payments. For example, using FY 2011 data, we identified fewer than 4,100 SNF residents with a diagnosis code of 042 (Human Immunodeficiency Virus (HIV) Infection). For FY 2014, an urban facility with a resident with AIDS in RUG-IV group “HC2” would have a case-mix adjusted payment of $414.72 (see Table 4) before the application of the MMA adjustment. After an increase of 128 percent, this urban facility would receive a case-mix adjusted payment of approximately $945.56.

Currently, we use the ICD-9-CM code 042 to identify those residents for whom it is appropriate to apply the AIDS add-on established by section 511 of the MMA. In this context, we note that, in accordance with the requirements of the final rule published in the September 5, 2012 Federal Register (77 FR 54664), we will be discontinuing our current use of the International Classification of Diseases, 9th revision, Clinical Modification (ICD-9-CM), effective with the compliance date for using the International Classification of Diseases, 10th revision, Clinical Modification (ICD-10-CM) of October 1, 2014. Regarding the above-referenced ICD-9-CM diagnosis code of 042, we propose to transition to the equivalent ICD-10-CM diagnosis code of B20 upon the October 1, 2014 implementation date for conversion to ICD-10-CM, and we invite public comment on this proposal. We note that both ICD-9-CM diagnosis code 042 and ICD-10-CM diagnosis code B20 include AIDS, AIDS-related complex (ARC), and HIV infection, symptomatic, but ICD-9-CM diagnosis code 042 additionally includes AIDS-like syndrome whereas ICD-10-CM diagnosis code B20 does not. The term “AIDS-like syndrome” denotes a condition other than AIDS that has symptoms resembling those of AIDS, but a different etiology from the human immunodeficiency virus that causes AIDS. Accordingly, we believe that in omitting the category of AIDS-like syndrome, ICD-10-CM diagnosis code B20 actually reflects more accurately than its predecessor ICD-9-CM code the intended scope of the statutory provision, which is directed specifically at those residents who are “. . . afflicted with acquired immune deficiency syndrome (AIDS)” (see section 1888(e)(12)(A) of the Act, as amended by section 511 of the MMA).

Under section 1888(e)(4)(H), each update of the payment rates must include the case-mix classification methodology applicable for the coming FY. The payment rates set forth in this proposed rule reflect the use of the RUG-IV case-mix classification system from October 1, 2013, through September 30, 2014. We list the case-mix adjusted RUG-IV payment rates, provided separately for urban and rural SNFs, in Tables 4 and 5 with corresponding case-mix values. These tables do not reflect the add-on for SNF residents with AIDS enacted by section 511 of the MMA, which we apply only after making all other adjustments (such as wage and case-mix).

Table 4—RUG-IV Case-Mix Adjusted Federal Rates and Associated Indexes—Urban Back to Top
RUG-IV Category Nursing index Therapy index Nursing component Therapy component Non-case mix therapy comp Non-case mix component Total rate
RUX 2.67 1.87 443.01 $233.71 $84.67 $761.39
RUL 2.57 1.87 426.41 233.71 84.67 744.79
RVX 2.61 1.28 433.05 159.97 84.67 677.69
RVL 2.19 1.28 363.36 159.97 84.67 608.00
RHX 2.55 0.85 423.10 106.23 84.67 614.00
RHL 2.15 0.85 356.73 106.23 84.67 547.63
RMX 2.47 0.55 409.82 68.74 84.67 563.23
RML 2.19 0.55 363.36 68.74 84.67 516.77
RLX 2.26 0.28 374.98 34.99 84.67 494.64
RUC 1.56 1.87 258.84 233.71 84.67 577.22
RUB 1.56 1.87 258.84 233.71 84.67 577.22
RUA 0.99 1.87 164.26 233.71 84.67 482.64
RVC 1.51 1.28 250.54 159.97 84.67 495.18
RVB 1.11 1.28 184.17 159.97 84.67 428.81
RVA 1.10 1.28 182.51 159.97 84.67 427.15
RHC 1.45 0.85 240.58 106.23 84.67 431.48
RHB 1.19 0.85 197.44 106.23 84.67 388.34
RHA 0.91 0.85 150.99 106.23 84.67 341.89
RMC 1.36 0.55 225.65 68.74 84.67 379.06
RMB 1.22 0.55 202.42 68.74 84.67 355.83
RMA 0.84 0.55 139.37 68.74 84.67 292.78
RLB 1.50 0.28 248.88 34.99 84.67 368.54
RLA 0.71 0.28 117.80 34.99 84.67 237.46
ES3 3.58 593.99 $16.46 84.67 695.12
ES2 2.67 443.01 16.46 84.67 544.14
ES1 2.32 384.93 16.46 84.67 486.06
HE2 2.22 368.34 16.46 84.67 469.47
HE1 1.74 288.70 16.46 84.67 389.83
HD2 2.04 338.48 16.46 84.67 439.61
HD1 1.60 265.47 16.46 84.67 366.60
HC2 1.89 313.59 16.46 84.67 414.72
HC1 1.48 245.56 16.46 84.67 346.69
HB2 1.86 308.61 16.46 84.67 409.74
HB1 1.46 242.24 16.46 84.67 343.37
LE2 1.96 325.20 16.46 84.67 426.33
LE1 1.54 255.52 16.46 84.67 356.65
LD2 1.86 308.61 16.46 84.67 409.74
LD1 1.46 242.24 16.46 84.67 343.37
LC2 1.56 258.84 16.46 84.67 359.97
LC1 1.22 202.42 16.46 84.67 303.55
LB2 1.45 240.58 16.46 84.67 341.71
LB1 1.14 189.15 16.46 84.67 290.28
CE2 1.68 278.75 16.46 84.67 379.88
CE1 1.50 248.88 16.46 84.67 350.01
CD2 1.56 258.84 16.46 84.67 359.97
CD1 1.38 228.97 16.46 84.67 330.10
CC2 1.29 214.04 16.46 84.67 315.17
CC1 1.15 190.81 16.46 84.67 291.94
CB2 1.15 190.81 16.46 84.67 291.94
CB1 1.02 169.24 16.46 84.67 270.37
CA2 0.88 146.01 16.46 84.67 247.14
CA1 0.78 129.42 16.46 84.67 230.55
BB2 0.97 160.94 16.46 84.67 262.07
BB1 0.90 149.33 16.46 84.67 250.46
BA2 0.70 116.14 16.46 84.67 217.27
BA1 0.64 106.19 16.46 84.67 207.32
PE2 1.50 248.88 16.46 84.67 350.01
PE1 1.40 232.29 16.46 84.67 333.42
PD2 1.38 228.97 16.46 84.67 330.10
PD1 1.28 212.38 16.46 84.67 313.51
PC2 1.10 182.51 16.46 84.67 283.64
PC1 1.02 169.24 16.46 84.67 270.37
PB2 0.84 139.37 16.46 84.67 240.50
PB1 0.78 129.42 16.46 84.67 230.55
PA2 0.59 97.89 16.46 84.67 199.02
PA1 0.54 89.60 16.46 84.67 190.73
Table 5—RUG—IV Case-Mix Adjusted Federal Rates and Associated Indexes—Rural Back to Top
RUG-IV Category Nursing index Therapy index Nursing component Therapy component Non-case mix therapy comp Non-case mix component Total rate
RUX 2.67 1.87 $423.25 $269.49 $86.25 $778.99
RUL 2.57 1.87 407.40 269.49 86.25 763.14
RVX 2.61 1.28 413.74 184.46 86.25 684.45
RVL 2.19 1.28 347.16 184.46 86.25 617.87
RHX 2.55 0.85 404.23 122.49 86.25 612.97
RHL 2.15 0.85 340.82 122.49 86.25 549.56
RMX 2.47 0.55 391.54 79.26 86.25 557.05
RML 2.19 0.55 347.16 79.26 86.25 512.67
RLX 2.26 0.28 358.26 40.35 86.25 484.86
RUC 1.56 1.87 247.29 269.49 86.25 603.03
RUB 1.56 1.87 247.29 269.49 86.25 603.03
RUA 0.99 1.87 156.93 269.49 86.25 512.67
RVC 1.51 1.28 239.37 184.46 86.25 510.08
RVB 1.11 1.28 175.96 184.46 86.25 446.67
RVA 1.10 1.28 174.37 184.46 86.25 445.08
RHC 1.45 0.85 229.85 122.49 86.25 438.59
RHB 1.19 0.85 188.64 122.49 86.25 397.38
RHA 0.91 0.85 144.25 122.49 86.25 352.99
RMC 1.36 0.55 215.59 79.26 86.25 381.10
RMB 1.22 0.55 193.39 79.26 86.25 358.90
RMA 0.84 0.55 133.16 79.26 86.25 298.67
RLB 1.50 0.28 237.78 40.35 86.25 364.38
RLA 0.71 0.28 112.55 40.35 86.25 239.15
ES3 3.58 567.50 17.58 86.25 671.33
ES2 2.67 423.25 17.58 86.25 527.08
ES1 2.32 367.77 17.58 86.25 471.60
HE2 2.22 351.91 17.58 86.25 455.74
HE1 1.74 275.82 17.58 86.25 379.65
HD2 2.04 323.38 17.58 86.25 427.21
HD1 1.60 253.63 17.58 86.25 357.46
HC2 1.89 299.60 17.58 86.25 403.43
HC1 1.48 234.61 17.58 86.25 338.44
HB2 1.86 294.85 17.58 86.25 398.68
HB1 1.46 231.44 17.58 86.25 335.27
LE2 1.96 310.70 17.58 86.25 414.53
LE1 1.54 244.12 17.58 86.25 347.95
LD2 1.86 294.85 17.58 86.25 398.68
LD1 1.46 231.44 17.58 86.25 335.27
LC2 1.56 247.29 17.58 86.25 351.12
LC1 1.22 193.39 17.58 86.25 297.22
LB2 1.45 229.85 17.58 86.25 333.68
LB1 1.14 180.71 17.58 86.25 284.54
CE2 1.68 266.31 17.58 86.25 370.14
CE1 1.50 237.78 17.58 86.25 341.61
CD2 1.56 247.29 17.58 86.25 351.12
CD1 1.38 218.76 17.58 86.25 322.59
CC2 1.29 204.49 17.58 86.25 308.32
CC1 1.15 182.30 17.58 86.25 286.13
CB2 1.15 182.30 17.58 86.25 286.13
CB1 1.02 161.69 17.58 86.25 265.52
CA2 0.88 139.50 17.58 86.25 243.33
CA1 0.78 123.65 17.58 86.25 227.48
BB2 0.97 153.76 17.58 86.25 257.59
BB1 0.90 142.67 17.58 86.25 246.50
BA2 0.70 110.96 17.58 86.25 214.79
BA1 0.64 101.45 17.58 86.25 205.28
PE2 1.50 237.78 17.58 86.25 341.61
PE1 1.40 221.93 17.58 86.25 325.76
PD2 1.38 218.76 17.58 86.25 322.59
PD1 1.28 202.91 17.58 86.25 306.74
PC2 1.10 174.37 17.58 86.25 278.20
PC1 1.02 161.69 17.58 86.25 265.52
PB2 0.84 133.16 17.58 86.25 236.99
PB1 0.78 123.65 17.58 86.25 227.48
PA2 0.59 93.53 17.58 86.25 197.36
PA1 0.54 85.60 17.58 86.25 189.43

D. Wage Index Adjustment

Section 1888(e)(4)(G)(ii) of the Act requires that we adjust the federal rates to account for differences in area wage levels, using a wage index that the Secretary determines appropriate. Since the inception of the SNF PPS, we have used hospital inpatient wage data in developing a wage index to be applied to SNFs. We propose to continue this practice for FY 2014, as we continue to believe that in the absence of SNF-specific wage data, using the hospital inpatient wage index is appropriate and reasonable for the SNF PPS. As explained in the update notice for FY 2005 (69 FR 45786), the SNF PPS does not use the hospital area wage index's occupational mix adjustment, as this adjustment serves specifically to define the occupational categories more clearly in a hospital setting; moreover, the collection of the occupational wage data also excludes any wage data related to SNFs. Therefore, we believe that using the updated wage data exclusive of the occupational mix adjustment continues to be appropriate for SNF payments. For FY 2014, the updated wage data are for hospital cost reporting periods beginning on or after October 1, 2009 and before October 1, 2010 (FY 2010 cost report data).

Finally, we propose to continue to use the same methodology discussed in the SNF PPS final rule for FY 2008 (72 FR 43423) to address those geographic areas in which there are no hospitals, and thus, no hospital wage index data on which to base the calculation of the FY 2014 SNF PPS wage index. For rural geographic areas that do not have hospitals, and therefore, lack hospital wage data on which to base an area wage adjustment, we would use the average wage index from all contiguous Core-Based Statistical Areas (CBSAs) as a reasonable proxy. For FY 2014, there are no rural geographic areas that do not have hospitals, and thus, this methodology would not be applied. For rural Puerto Rico, we would not apply this methodology due to the distinct economic circumstances that exist there (for example, due to the close proximity to one another of almost all of Puerto Rico's various urban and non-urban areas, this methodology would produce a wage index for rural Puerto Rico that is inappropriately higher than that in half of its urban areas); instead, we would continue to use the most recent wage index previously available for that area. For urban areas without specific hospital wage index data, we would use the average wage indexes of all of the urban areas within the state to serve as a reasonable proxy for the wage index of that urban CBSA. For FY 2014, the only urban area without wage index data available is CBSA 25980, Hinesville-Fort Stewart, GA.

In addition, we note that section 315 of the Medicare, Medicaid, and SCHIP Benefits Improvement and Protection Act of 2000 (BIPA) (Pub. L. 106-554, enacted on December 21, 2000) authorized us to establish a geographic reclassification procedure that is specific to SNFs, but only after collecting the data necessary to establish a SNF wage index that is based on wage data from nursing homes. However, to date, this has proven to be unfeasible due to the volatility of existing SNF wage data and the significant amount of resources that would be required to improve the quality of that data.

Once calculated, we would apply the wage index adjustment to the labor-related portion of the federal rate. Each year, we calculate a revised labor-related share, based on the relative importance of labor-related cost categories (that is, those cost categories that are sensitive to local area wage costs) in the input price index. For the FY 2014 SNF PPS update, we are proposing to revise the labor-related share to reflect the relative importance of the revised FY 2010-based SNF market basket cost weights for the following cost categories (as discussed further in section V.A. of this proposed rule): wages and salaries; employee benefits; contract labor; the labor-related portion of nonmedical professional fees; administrative and facilities support services; all other: labor-related services (previously referred to in the FY 2004-based SNF market basket as labor-intensive); and a proportion of capital-related expenses.

We calculate the labor-related relative importance from the SNF market basket, and it approximates the labor-related portion of the total costs after taking into account historical and projected price changes between the base year and FY 2014. The price proxies that move the different cost categories in the market basket do not necessarily change at the same rate, and the relative importance captures these changes. Accordingly, the relative importance figure more closely reflects the cost share weights for FY 2014 than the base year weights from the SNF market basket.

We calculate the labor-related relative importance for FY 2014 in four steps. First, we compute the FY 2014 price index level for the total market basket and each cost category of the market basket. Second, we calculate a ratio for each cost category by dividing the FY 2014 price index level for that cost category by the total market basket price index level. Third, we determine the FY 2014 relative importance for each cost category by multiplying this ratio by the base year (FY 2010) weight. Finally, we add the FY 2014 relative importance for each of the labor-related cost categories (wages and salaries, employee benefits, the labor-related portion of non-medical professional fees, administrative and facilities support services, all other: labor-related services (previously referred to in the FY 2004-based SNF market basket as labor-intensive services), and a portion of capital-related expenses) to produce the FY 2014 labor-related relative importance. Tables 6 and 7 show the RUG-IV case-mix adjusted federal rates by labor-related and non-labor-related components. In section V. of this proposed rule, Table 17 provides the FY 2014 labor-related share components based on the revised and rebased FY 2010-based SNF market basket.

Table 6—RUG-IV Case-Mix Adjusted Federal Rates for Urban SNFs by Labor and Non-Labor Component Back to Top
RUG-IV Category Total rate Labor portion Non-labor portion
RUX 761.39 $531.18 $230.21
RUL 744.79 519.60 225.19
RVX 677.69 472.78 204.91
RVL 608.00 424.17 183.83
RHX 614.00 428.35 185.65
RHL 547.63 382.05 165.58
RMX 563.23 392.93 170.30
RML 516.77 360.52 156.25
RLX 494.64 345.08 149.56
RUC 577.22 402.69 174.53
RUB 577.22 402.69 174.53
RUA 482.64 336.71 145.93
RVC 495.18 345.46 149.72
RVB 428.81 299.16 129.65
RVA 427.15 298.00 129.15
RHC 431.48 301.02 130.46
RHB 388.34 270.92 117.42
RHA 341.89 238.52 103.37
RMC 379.06 264.45 114.61
RMB 355.83 248.24 107.59
RMA 292.78 204.26 88.52
RLB 368.54 257.11 111.43
RLA 237.46 165.66 71.80
ES3 695.12 484.94 210.18
ES2 544.14 379.61 164.53
ES1 486.06 339.09 146.97
HE2 469.47 327.52 141.95
HE1 389.83 271.96 117.87
HD2 439.61 306.69 132.92
HD1 366.60 255.75 110.85
HC2 414.72 289.33 125.39
HC1 346.69 241.86 104.83
HB2 409.74 285.85 123.89
HB1 343.37 239.55 103.82
LE2 426.33 297.42 128.91
LE1 356.65 248.81 107.84
LD2 409.74 285.85 123.89
LD1 343.37 239.55 103.82
LC2 359.97 251.13 108.84
LC1 303.55 211.77 91.78
LB2 341.71 238.39 103.32
LB1 290.28 202.51 87.77
CE2 379.88 265.02 114.86
CE1 350.01 244.18 105.83
CD2 359.97 251.13 108.84
CD1 330.10 230.29 99.81
CC2 315.17 219.88 95.29
CC1 291.94 203.67 88.27
CB2 291.94 203.67 88.27
CB1 270.37 188.62 81.75
CA2 247.14 172.41 74.73
CA1 230.55 160.84 69.71
BB2 262.07 182.83 79.24
BB1 250.46 174.73 75.73
BA2 217.27 151.58 65.69
BA1 207.32 144.63 62.69
PE2 350.01 244.18 105.83
PE1 333.42 232.61 100.81
PD2 330.10 230.29 99.81
PD1 313.51 218.72 94.79
PC2 283.64 197.88 85.76
PC1 270.37 188.62 81.75
PB2 240.50 167.78 72.72
PB1 230.55 160.84 69.71
PA2 199.02 138.84 60.18
PA1 190.73 133.06 57.67
Table 7—RUG-IV Case-Mix Adjusted Federal Rates for Rural SNFs by Labor and Non-Labor Component Back to Top
RUG-IV Category Total rate Labor portion Non-labor portion
RUX 778.99 $543.45 $235.54
RUL 763.14 532.40 230.74
RVX 684.45 477.50 206.95
RVL 617.87 431.05 186.82
RHX 612.97 427.63 185.34
RHL 549.56 383.40 166.16
RMX 557.05 388.62 168.43
RML 512.67 357.66 155.01
RLX 484.86 338.26 146.60
RUC 603.03 420.70 182.33
RUB 603.03 420.70 182.33
RUA 512.67 357.66 155.01
RVC 510.08 355.85 154.23
RVB 446.67 311.61 135.06
RVA 445.08 310.51 134.57
RHC 438.59 305.98 132.61
RHB 397.38 277.23 120.15
RHA 352.99 246.26 106.73
RMC 381.10 265.87 115.23
RMB 358.90 250.38 108.52
RMA 298.67 208.36 90.31
RLB 364.38 254.21 110.17
RLA 239.15 166.84 72.31
ES3 671.33 468.35 202.98
ES2 527.08 367.71 159.37
ES1 471.60 329.01 142.59
HE2 455.74 317.94 137.80
HE1 379.65 264.86 114.79
HD2 427.21 298.04 129.17
HD1 357.46 249.38 108.08
HC2 403.43 281.45 121.98
HC1 338.44 236.11 102.33
HB2 398.68 278.14 120.54
HB1 335.27 233.90 101.37
LE2 414.53 289.19 125.34
LE1 347.95 242.74 105.21
LD2 398.68 278.14 120.54
LD1 335.27 233.90 101.37
LC2 351.12 244.96 106.16
LC1 297.22 207.35 89.87
LB2 333.68 232.79 100.89
LB1 284.54 198.51 86.03
CE2 370.14 258.22 111.92
CE1 341.61 238.32 103.29
CD2 351.12 244.96 106.16
CD1 322.59 225.05 97.54
CC2 308.32 215.10 93.22
CC1 286.13 199.62 86.51
CB2 286.13 199.62 86.51
CB1 265.52 185.24 80.28
CA2 243.33 169.76 73.57
CA1 227.48 158.70 68.78
BB2 257.59 179.71 77.88
BB1 246.50 171.97 74.53
BA2 214.79 149.85 64.94
BA1 205.28 143.21 62.07
PE2 341.61 238.32 103.29
PE1 325.76 227.26 98.50
PD2 322.59 225.05 97.54
PD1 306.74 213.99 92.75
PC2 278.20 194.08 84.12
PC1 265.52 185.24 80.28
PB2 236.99 165.33 71.66
PB1 227.48 158.70 68.78
PA2 197.36 137.69 59.67
PA1 189.43 132.15 57.28

Section 1888(e)(4)(G)(ii) of the Act also requires that we apply this wage index in a manner that does not result in aggregate payments under the SNF PPS that are greater or less than would otherwise be made if the wage adjustment had not been made. For FY 2014 (federal rates effective October 1, 2013), we apply an adjustment to fulfill the budget neutrality requirement. We meet this requirement by multiplying each of the components of the unadjusted federal rates by a budget neutrality factor equal to the ratio of the weighted average wage adjustment factor for FY 2013 to the weighted average wage adjustment factor for FY 2014. For this calculation, we use the same 2012 claims utilization data for both the numerator and denominator of this ratio. We define the wage adjustment factor used in this calculation as the labor share of the rate component multiplied by the wage index plus the non-labor share of the rate component. The budget neutrality factor for FY 2014 is 1.0003. The wage index applicable to FY 2014 is set forth in Tables A and B, which appear in the Addendum of this proposed rule, and is also available on the CMS Web site at http://cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/WageIndex.html.

In the SNF PPS final rule for FY 2006 (70 FR 45026, August 4, 2005), we adopted the changes discussed in the OMB Bulletin No. 03-04 (June 6, 2003), available online at http://www.whitehouse.gov/omb/bulletins/b03-04.html, which announced revised definitions for metropolitan statistical areas (MSAs), and the creation of micropolitan statistical areas and combined statistical areas. In addition, OMB published subsequent bulletins regarding CBSA changes, including changes in CBSA numbers and titles. We indicated in the FY 2008 SNF PPS final rule (72 FR 43423), that all subsequent SNF PPS rules and notices are considered to incorporate the CBSA changes published in the most recent OMB bulletin that applies to the hospital wage data used to determine the current SNF PPS wage index. The OMB bulletins are available online at http://www.whitehouse.gov/omb/bulletins/index.html.

In adopting the CBSA geographic designations, we provided for a 1-year transition in FY 2006 with a blended wage index for all providers. For FY 2006, the wage index for each provider consisted of a blend of 50 percent of the FY 2006 MSA-based wage index and 50 percent of the FY 2006 CBSA-based wage index (both using FY 2002 hospital data). We referred to the blended wage index as the FY 2006 SNF PPS transition wage index. As discussed in the SNF PPS final rule for FY 2006 (70 FR 45041), subsequent to the expiration of this 1-year transition on September 30, 2006, we used the full CBSA-based wage index values, as now presented in Tables A and B in the Addendum of this proposed rule.

On February 28, 2013, OMB issued OMB Bulletin No. 13-01, announcing revisions to the delineation of Metropolitan Statistical Areas, Micropolitian Statistical Areas, and Combined Statistical Areas, and guidance on uses of the delineation of these areas. A copy of this bulletin may be obtained at http://www.whitehouse.gov/sites/default/files/omb/bulletins/2013/b-13-01.pdf. This bulletin states that it 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 in the June 28, 2010 Federal Register (75 FR 37246-37252) and Census Bureau data.

While the revisions OMB published on February 28, 2013 are not as sweeping as the changes made when we adopted the CBSA geographic designations for FY 2006, the February 28, 2013 bulletin does contain a number of significant changes. For example, there are new CBSAs, urban counties that become rural, rural counties that become urban, and existing CBSAs that are being split apart.

The changes made by the bulletin and their ramifications must be extensively reviewed and assessed by CMS before using them for the SNF PPS wage index. Because the bulletin was not issued until February 28, 2013, we were unable to undertake such a lengthy process before publication of this FY 2014 proposed rule. By the time the bulletin was issued, the FY 2014 SNF PPS proposed rule was in the advanced stages of development. We had already developed the FY 2014 proposed wage index based on the previous OMB definitions. To allow for sufficient time to assess the new changes and their ramifications, we intend to propose changes to the wage index based on the newest CBSA changes in the FY 2015 SNF PPS proposed rule. Thus, we would continue to use the previous OMB definitions (that is, those used for the FY 2013 SNF PPS update notice) for the FY 2014 SNF PPS wage index.

E. Adjusted Rate Computation Example

Using the hypothetical SNF XYZ described below, Table 8 shows the adjustments made to the federal per diem rates to compute the provider's actual per diem PPS payment under the described scenario. We derive the Labor and Non-labor columns from Table 6. As illustrated in Table 8, SNF XYZ's total PPS payment would equal $41,917.80.

Table 8—Adjusted Rate Computation Example, SNF XYZ: Located in Cedar Rapids, IA (Urban CBSA 16300), Wage Index: 0.9001 Back to Top
RUG-IV group Labor Wage index Adjusted labor Non-labor Adjusted rate Percent adjustment Medicare days Payment
* Reflects a 128 percent adjustment from section 511 of the MMA.
RVX $472.78 0.9001 $425.55 $204.91 $630.46 $630.46 14 $8,826.44
ES2 379.61 0.9001 341.69 164.53 506.22 506.22 30 15,186.60
RHA 238.52 0.9001 214.69 103.37 318.06 318.06 16 5,088.96
CC2* 219.88 0.9001 197.91 95.29 293.20 668.50 10 6,685.00
BA2 151.58 0.9001 136.44 65.69 202.13 202.13 30 6,063.90
100 $41,850.90

IV. Additional Aspects of the SNF PPS Back to Top

A. SNF Level of Care—Administrative Presumption

The establishment of the SNF PPS did not change Medicare's fundamental requirements for SNF coverage. However, because the case-mix classification is based, in part, on the beneficiary's need for skilled nursing care and therapy, we have attempted, where possible, to coordinate claims review procedures with the existing resident assessment process and case-mix classification system discussed in section III.C of this proposed rule. This approach includes an administrative presumption that utilizes a beneficiary's initial classification in one of the upper 52 RUGs of the 66-group RUG-IV case-mix classification system to assist in making certain SNF level of care determinations.

In accordance with section 1888(e)(4)(H)(ii) of the Act and the regulations at § 413.345, we include in each update of the federal payment rates in the Federal Register the designation of those specific RUGs under the classification system that represent the required SNF level of care, as provided in § 409.30. As set forth in the FY 2011 SNF PPS update notice (75 FR 42910), this designation reflects an administrative presumption under the 66-group RUG-IV system that beneficiaries who are correctly assigned to one of the upper 52 RUG-IV groups on the initial 5-day, Medicare-required assessment are automatically classified as meeting the SNF level of care definition up to and including the assessment reference date on the 5-day Medicare-required assessment.

A beneficiary assigned to any of the lower 14 RUG-IV groups is not automatically classified as either meeting or not meeting the definition, but instead receives an individual level of care determination using the existing administrative criteria. This presumption recognizes the strong likelihood that beneficiaries assigned to one of the upper 52 RUG-IV groups during the immediate post-hospital period require a covered level of care, which would be less likely for those beneficiaries assigned to one of the lower 14 RUG-IV groups.

In the July 30, 1999 final rule (64 FR 41670), we indicated that we would announce any changes to the guidelines for Medicare level of care determinations related to modifications in the case-mix classification structure. In this proposed rule, we would continue to designate the upper 52 RUG-IV groups for purposes of this administrative presumption, consisting of all groups encompassed by the following RUG-IV categories:

  • Rehabilitation plus Extensive Services;
  • Ultra High Rehabilitation;
  • Very High Rehabilitation;
  • High Rehabilitation;
  • Medium Rehabilitation;
  • Low Rehabilitation;
  • Extensive Services;
  • Special Care High;
  • Special Care Low; and,
  • Clinically Complex.

However, we note that this administrative presumption policy does not supersede the SNF's responsibility to ensure that its decisions relating to level of care are appropriate and timely, including a review to confirm that the services prompting the beneficiary's assignment to one of the upper 52 RUG-IV groups (which, in turn, serves to trigger the administrative presumption) are themselves medically necessary. As we explained in the FY 2000 SNF PPS final rule (64 FR 41667), the administrative presumption:

“. . . is itself rebuttable in those individual cases in which the services actually received by the resident do not meet the basic statutory criterion of being reasonable and necessary to diagnose or treat a beneficiary's condition (according to section 1862(a)(1) of the Act). Accordingly, the presumption would not apply, for example, in those situations in which a resident's assignment to one of the upper . . . groups is itself based on the receipt of services that are subsequently determined to be not reasonable and necessary.”

Moreover, we want to stress the importance of careful monitoring for changes in each patient's condition to determine the continuing need for Part A SNF benefits after the assessment reference date of the 5-day assessment.

B. Consolidated Billing

Sections 1842(b)(6)(E) and 1862(a)(18) of the Act (as added by section 4432(b) of the BBA) require a SNF to submit consolidated Medicare bills to its fiscal intermediary or Medicare Administrative Contractor for almost all of the services that its residents receive during the course of a covered Part A stay. In addition, section 1862(a)(18) places the responsibility with the SNF for billing Medicare for physical therapy, occupational therapy, and speech-language pathology services that the resident receives during a noncovered stay. Section 1888(e)(2)(A) of the Act excludes a small list of services from the consolidated billing provision (primarily those services furnished by physicians and certain other types of practitioners), which remain separately billable under Part B when furnished to a SNF's Part A resident. These excluded service categories are discussed in greater detail in section V.B.2. of the May 12, 1998 interim final rule (63 FR 26295 through 26297).

We note that section 103 of the Medicare, Medicaid, and SCHIP Balanced Budget Refinement Act of 1999 (BBRA) (Pub. L. 106-113, enacted on November 29, 1999) amended this provision (section 1888(e)(2)(A) of the Act) by further excluding a number of individual “high-cost, low-probability” services, identified by Healthcare Common Procedure Coding System (HCPCS) codes, within several broader categories (chemotherapy items, chemotherapy administration services, radioisotope services, and customized prosthetic devices) that otherwise remained subject to the provision. We discuss this BBRA amendment in greater detail in the SNF PPS proposed and final rules for FY 2001 (65 FR 19231 through 19232, April 10, 2000, and 65 FR 46790 through 46795, July 31, 2000), as well as in Program Memorandum AB-00-18 (Change Request #1070), issued March 2000, which is available online at www.cms.gov/transmittals/downloads/ab001860.pdf.

As explained in the FY 2001 proposed rule (65 FR 19232), the amendments enacted in section 103 of the BBRA not only identified for exclusion from this provision a number of particular service codes within four specified categories (that is, chemotherapy items, chemotherapy administration services, radioisotope services, and customized prosthetic devices), but also gave the Secretary “. . . the authority to designate additional, individual services for exclusion within each of the specified service categories.” In the proposed rule for FY 2001, we also noted that the BBRA Conference report (H.R. Rep. No. 106-479 at 854 (1999) (Conf. Rep.)) characterizes the individual services that this legislation targets for exclusion as “. . . high-cost, low probability events that could have devastating financial impacts because their costs far exceed the payment [SNFs] receive under the prospective payment system. . . .” According to the conferees, section 103(a) of the BBRA “is an attempt to exclude from the PPS certain services and costly items that are provided infrequently in SNFs. . . .” By contrast, we noted that the Congress declined to designate for exclusion any of the remaining services within those four categories (thus, leaving all of those services subject to SNF consolidated billing), because they are relatively inexpensive and are furnished routinely in SNFs.

As we further explained in the final rule for FY 2001 (65 FR 46790), and as our longstanding policy, any additional service codes that we might designate for exclusion under our discretionary authority must meet the same statutory criteria used in identifying the original codes excluded from consolidated billing under section 103(a) of the BBRA: they must fall within one of the four service categories specified in the BBRA, and they also must meet the same standards of high cost and low probability in the SNF setting, as discussed in the BBRA Conference report. Accordingly, we characterized this statutory authority to identify additional service codes for exclusion “. . . as essentially affording the flexibility to revise the list of excluded codes in response to changes of major significance that may occur over time (for example, the development of new medical technologies or other advances in the state of medical practice)” (65 FR 46791). In this proposed rule, we specifically invite public comments identifying HCPCS codes in any of these four service categories (chemotherapy items, chemotherapy administration services, radioisotope services, and customized prosthetic devices) representing recent medical advances that might meet our criteria for exclusion from SNF consolidated billing. We may consider excluding a particular service if it meets our criteria for exclusion as specified above. Commenters should identify in their comments the specific HCPCS code that is associated with the service in question, as well as their rationale for requesting that the identified HCPCS code(s) be excluded.

We note that the original BBRA amendment (as well as the implementing regulations) identified a set of excluded services by means of specifying HCPCS codes that were in effect as of a particular date (in that case, as of July 1, 1999). Identifying the excluded services in this manner made it possible for us to utilize program issuances as the vehicle for accomplishing routine updates of the excluded codes, to reflect any minor revisions that might subsequently occur in the coding system itself (for example, the assignment of a different code number to the same service). Accordingly, in the event that we identify through the current rulemaking cycle any new services that would actually represent a substantive change in the scope of the exclusions from SNF consolidated billing, we would identify these additional excluded services by means of the HCPCS codes that are in effect as of a specific date (in this case, as of October 1, 2013). By making any new exclusions in this manner, we could similarly accomplish routine future updates of these additional codes through the issuance of program instructions.

C. Payment for SNF-Level Swing-Bed Services

Section 1883 of the Act permits certain small, rural hospitals to enter into a Medicare swing-bed agreement, under which the hospital can use its beds to provide either acute- or SNF-level care, as needed. For critical access hospitals (CAHs), Part A pays on a reasonable cost basis for SNF-level services furnished under a swing-bed agreement. However, in accordance with section 1888(e)(7) of the Act, these services furnished by non-CAH rural hospitals are paid under the SNF PPS, effective with cost reporting periods beginning on or after July 1, 2002. As explained in the FY 2002 final rule (66 FR 39562), this effective date is consistent with the statutory provision to integrate swing-bed rural hospitals into the SNF PPS by the end of the transition period, June 30, 2002.

Accordingly, all non-CAH swing-bed rural hospitals have now come under the SNF PPS. Therefore, all rates and wage indexes outlined in earlier sections of this proposed rule for the SNF PPS also apply to all non-CAH swing-bed rural hospitals. A complete discussion of assessment schedules, the MDS, and the transmission software (RAVEN-SB for Swing Beds) appears in the FY 2002 final rule (66 FR 39562) and in the FY 2010 final rule (74 FR 40288). As finalized in the FY 2010 SNF PPS final rule (74 FR 40356-57), effective October 1, 2010, non-CAH swing-bed rural hospitals are required to complete an MDS 3.0 swing-bed assessment which is limited to the required demographic, payment, and quality items. The latest changes in the MDS for swing-bed rural hospitals appear on the SNF PPS Web site at http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/index.html.

V. Other Issues Back to Top

A. Revising and Rebasing the SNF Market Basket Index

1. Background

Section 1888(e)(5)(A) of the Act requires the Secretary to establish a market basket index that reflects the changes over time in the prices of an appropriate mix of goods and services included in the SNF PPS. Effective for cost reporting periods beginning on or after July 1, 1998, we revised and rebased our 1977 routine costs input price index and adopted a total expenses SNF input price index using FY 1992 as the base year. In the FY 2002 SNF PPS final rule (66 FR 39582), we rebased and revised the market basket to a base year of FY 1997. We last rebased and revised the market basket to a base year of FY 2004 in the FY 2008 SNF PPS final rule (72 FR 43425). In this FY 2014 SNF PPS proposed rule, we are proposing to revise and rebase the SNF market basket to a base year of FY 2010.

The term “market basket” refers to the mix of goods and services needed to produce SNF care, and is also commonly used to denote the input price index that includes both weights (mix of goods and services) and price factors. The term “market basket” and “market basket index” used in this proposed rule refers to the SNF input price index.

The proposed FY 2010-based SNF market basket represents routine costs, costs of ancillary services, and capital-related costs. The percentage change in the market basket reflects the average change in the price of a fixed set of goods and services purchased by SNFs to furnish all services. For further background information, see the May 12, 1998 interim final rule with comment period (63 FR 26289), the FY 2002 final rule (66 FR 39582), and the FY 2008 final rule (72 FR 43425).

For purposes of the SNF PPS, the SNF market basket is a fixed-weight (Laspeyres-type) price index. A Laspeyres-type index compares the cost of purchasing a specified mix of goods and services in a selected base period to the cost of purchasing that same group of goods and services at current prices.

We construct the market basket in three steps. The first step is to select a base period and estimate total base period expenditure shares for mutually exclusive and exhaustive spending categories. We use total costs for routine services, ancillary services, and capital. These shares are called “cost” or “expenditure” weights. The second step is to match each expenditure category to a price/wage variable, called a price proxy. We draw these price proxy variables from publicly available statistical series published on a consistent schedule, preferably at least quarterly. The final step involves multiplying the price level for each spending category by the cost weight for that category. The sum of these products (that is, weights multiplied by proxy index levels) for all cost categories yields the composite index level of the market basket for a given quarter or year. Repeating the third step for other quarters and years produces a time series of market basket index levels, from which we can calculate rates of growth.

The market basket represents a fixed-weight index because it answers the question of how much more or less it would cost, at a later time, to purchase the same mix of goods and services that was purchased in the base period. The effects on total expenditures resulting from changes in the quantity or mix of goods and services purchased subsequent or prior to the base period are, by design, not considered.

Consistent with our discussion in the May 12, 1998 interim final rule with comment period (63 FR 26252), the FY 2002 final rule (66 FR 39582), and the FY 2008 proposed rule (72 FR 25541), and as further discussed below, to implement section 1888(e)(5)(A) of the Act we propose to revise and rebase the market basket so the cost weights and price proxies reflect the mix of goods and services that underlie Medicare allowable SNF costs (routine, ancillary, and capital-related) for FY 2010.

2. Revising and Rebasing the Skilled Nursing Facility Market Basket

The terms “rebasing” and “revising,” while often used interchangeably, actually denote different activities. Rebasing means shifting the base year for the structure of costs of the input price index (for example, for this proposed rule, we propose to shift the base year cost structure from FY 2004 to FY 2010). Revising means changing data sources, cost categories, price proxies, and/or methodology used in developing the input price index.

We are proposing both to rebase and revise the SNF market basket to reflect FY 2010 Medicare allowable total cost data (routine, ancillary, and capital-related). Medicare allowable costs are costs that are eligible for inclusion under the SNF PPS payments. For example, the SNF market basket excludes home health aide costs as these costs would be reimbursed under the Home Health PPS. We last rebased and revised the SNF market basket in the FY 2008 PPS final rule (72 FR 43425), reflecting data from FY 2004 Medicare allowable total costs.

We selected FY 2010 as the new base year because 2010 is the most recent year for which relatively complete Medicare cost report (MCR) data are available. In developing the proposed market basket, we reviewed SNF expenditure data from SNF MCRs (CMS Form 2540-96) for FY 2010 for each freestanding SNF that reported Medicare expenses and payments. The FY 2010 cost reports are those with cost reporting periods beginning after September 30, 2009, and before October 1, 2010. We propose to maintain our policy of using data from freestanding SNFs because freestanding SNF data reflect the actual cost structure faced by the SNF itself. In contrast, expense data for a hospital-based SNF reflect the allocation of overhead over the entire institution. Due to this method of allocation, total expenses will be correct, but the individual components' expenses may be skewed.

We developed cost category weights for the proposed FY 2010-based SNF market basket in two stages. First, we derived base weights for seven major categories (wages and salaries, employee benefits, contract labor, pharmaceuticals, professional liability insurance, capital-related, and a residual “all other”) from the SNF MCRs. Second, we are proposing to divide the residual “all other” cost category (21.534 percent) into subcategories, using U.S. Department of Commerce Bureau of Economic Analysis' (BEA) 2002 Benchmark Input-Output (I-O) tables for the nursing home industry aged forward using price changes. The methodology we propose to use to age the data forward involves applying the annual price changes from the respective price proxies to the appropriate cost categories. We repeat this practice for each year. We then apply the resulting 2010 distributions to the aggregate 2010 “all other” cost weight of 21.534 percent to yield the detailed 2010 all other cost weights. This is similar to the methodology we used to revise and rebase the SNF market basket to reflect FY 2004 data in the FY 2008 SNF final rule.

The BEA Benchmark I-O data are generally scheduled for publication every 5 years, with the most recent data available being 2002. The 2007 BEA Benchmark I-O data are expected to be released in the summer of 2013. We are proposing that if more recent BEA Benchmark I-O data for 2007 are released between the proposed and final rule with sufficient time to incorporate such data into the final rule that we would incorporate these data, as appropriate, into the FY 2010-based SNF PPS market basket for the final rule, so that the SNF market basket reflects the most recent BEA data available. We note that the FY 2004-based SNF market basket used the 1997 BEA Benchmark I-O data to disaggregate the “all other” (residual) cost category—the data available at the time of the rebasing. The 2002 BEA Benchmark I-O data (and the forthcoming 2007 BEA Benchmark I-O data) are updates of the 1997 BEA Benchmark I-O data.

For this SNF market basket revision and rebasing, we are proposing to include a total of 29 detailed cost categories for the proposed FY 2010-based SNF market basket, which is six more cost categories than the FY 2004-based SNF market basket. We are proposing to include five new cost categories in the proposed FY 2010-based SNF market basket: (1) Medical Instruments and Supplies; (2) Apparel; (3) Machinery and Equipment; (4) Administrative and Facilities Support Services; and (5) Financial Services. Having separate categories for these costs enables them to be proxied more precisely. We are also proposing to divide the Nonmedical Professional Fees cost category into Nonmedical Professional Fees: Labor-Related and Nonmedical Professional Fees: Nonlabor-Related. In addition, we are proposing to revise our labels for the Labor-Intensive Services and Nonlabor-Intensive Services cost categories to All Other: Labor-Related Services and All Other: Nonlabor-Related Services, respectively. A more thorough discussion of our proposals is provided below.

The capital-related portion of the FY 2010-based SNF market basket employs the same overall methodology used to develop the capital-related portion of the FY 1997-based SNF market basket, described in the FY 2002 SNF PPS final rule (66 FR 39582) and the FY 2004-based SNF market basket, described in the FY 2008 SNF PPS final rule (72 FR 43425). It is a similar methodology as is used for the inpatient hospital capital input price index described in the FY 1997 Hospital IPPS proposed rule (61 FR 27466), the FY 1997 Hospital IPPS final rule (61 FR 46196), the FY 2006 Hospital IPPS final rule (70 FR 47407), and the FY 2010 Hospital IPPS final rule (74 FR 43857). The strength of this methodology is that it reflects the vintage nature of capital, which represents the acquisition and use of capital over time. We explain this methodology in more detail below.

Table 9 presents the FY 2010-based and FY 2004-based SNF market basket major cost weights. Following the table, we describe the sources of the major category weights and their subcategories in the FY 2010-based SNF market basket.

Table 9—FY 2010-Based SNF Market Basket Major Cost Weights Back to Top
Cost Category Proposed FY 2010-based SNF market basket FY 2004-based SNF market basket
Wages and Salaries 46.057 48.105
Employee Benefits 10.491 10.699
Contract Labor 5.545 3.951
Pharmaceuticals 7.872 7.894
Professional Liability Insurance 1.141 1.717
Capital-related Expenses 7.360 7.207
All Other (residual) 21.534 20.427
  • Wages and Salaries: We derived the wages and salaries cost category using the FY 2010 SNF MCRs. We determined the share using Medicare allowable wages and salaries from Worksheet S-3, part II and total expenses from Worksheet B, part I. Medicare allowable wages and salaries are equal to total wages and salaries minus: (1) Excluded salaries from worksheet S-3, part II; and (2) nursing facility and non-reimbursable salaries from worksheet A, lines 18, 34 through 36, and 58 through 63. Medicare allowable total expenses are equal to total expenses from Worksheet B, lines 16, 21 through 30, 32, 33, 48, and 52 through 54. This share represents the wage and salary share of costs for employees for the SNF, and does not include the wages and salaries from contract labor, which are allocated to wages and salaries in a later step. The same cost report methodology was used to derive the wages and salaries cost weight of the FY 2004-based SNF market basket.
  • Employee Benefits: We determined the weight for employee benefits using FY 2010 SNF MCR data. We derived the share using Medicare allowable benefit costs from Worksheet S-3, part II and total expenses from Worksheet B. Medicare allowable benefits are equal to total benefits from Worksheet S-3, part II, minus excluded (non-Medicare allowable) benefits. Non-Medicare allowable benefits are derived by multiplying non-Medicare allowable salaries times the ratio of total benefit costs for the SNF to the total wage costs for the SNF. The same cost report methodology was used to derive the benefits cost weight of the FY 2004-based SNF market basket.
  • Contract Labor: We determined the weight for contract labor using 2010 SNF MCR data. We derived the share using Medicare allowable contract labor costs from Worksheet S-3, part II line 17 minus nursing facility (NF) contract labor costs, and Medicare allowable total costs from Worksheet B. (Worksheet S-3, part II line 17 only includes direct patient care contract labor attributable to SNF and NF services.) NF contract labor costs, which are not reimbursable under Medicare, are derived by multiplying total contract labor costs by the ratio of NF wages and salaries to the sum of NF and SNF wages and salaries.

As we did for the FY 2004-based SNF market basket, we propose to allocate contract labor costs to the wages and salaries and employee benefits cost weights based on their relative proportion, under the assumption that contract costs are similarly distributed and likely to change at the same rate as direct labor costs even though unit labor cost levels may be different. 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. Using the FY 2010 MCR data, this percentage is approximately 81 percent; therefore, we propose to allocate approximately 81 percent of the contract labor cost weight to the wages and salaries cost weight. The remaining proportion of the contract labor cost weight is allocated to the employee benefits cost weight. Table 10 shows the wages and salaries and employee benefit cost weights after contract labor allocation for both the FY 2004-based SNF market basket and the proposed FY 2010-based SNF market basket.

Table 10—Wages and Salaries and Employee Benefits Cost Weights After Contract Labor Allocation Back to Top
Major cost categories Proposed FY 2010-based SNF market basket FY 2004-Based SNF market basket
Wages and salaries 50.573 51.337
Employee benefits 11.520 11.418

Prior to contract labor allocation, the proposed FY 2010-based SNF market basket wages and salaries cost weight was about 2 percentage points lower than the FY 2004-based SNF market basket wages and salaries cost weight while the proposed FY 2010-based employee benefit cost weight was 0.2 percentage point lower than the FY 2004-based employee benefit cost weight. After the allocation of contract labor, the proposed FY 2010-based wages and salaries cost weight is about 0.7 percentage point lower than the FY 2004-based wages and salaries cost weight while the proposed FY 2010-based employee benefits cost weight is about 0.1 percentage point higher than the FY 2004-based employee benefit cost weight. This is due to the increase in the FY 2010-based SNF market basket contract labor cost weight from the FY 2004-based SNF market basket contract labor cost weight, of which 81 percent of this increase is applied to the wages and salaries cost weight and 19 percent is applied to the employee benefit cost weight, offsetting the actual decrease in the wages and salaries and employee benefit cost weights prior to the contract labor allocation.

  • Pharmaceuticals: We derive the cost weight for pharmaceuticals in two steps using the FY 2010 SNF MCR and Medicare claims data.

First, we calculated pharmaceutical costs using the non-salary costs from the Pharmacy cost center and the Drugs Charged to Patients' cost center, both found on Worksheet B of the SNF MCRs. Since these drug costs were attributable to the entire SNF and not limited to Medicare allowable services, we adjusted the drug costs by the ratio of Medicare allowable pharmacy total costs to total pharmacy costs from Worksheet B, part I, column 11. Worksheet B, part I allocates the general service cost centers, which are often referred to as “overhead costs” (in which pharmacy costs are included) to the Medicare allowable and non-Medicare allowable cost centers. This resulted in a proposed FY 2010-based SNF market basket drug cost weight of 3.1 percent compared to the FY 2004-based SNF market basket drug cost weight, which was 3.2 percent using the same methodology. This drug cost share does not include the drug expenses associated with Medicaid patients. The methodology for including the Medicaid drug expenditures is explained in detail below. This Medicaid drug add-on increases the drug expenditure weight to over seven percent, and is consistent with the Medicaid drug add-on method that was used in the FY 2004-based SNF market basket.

Second, for the FY 2010-based SNF market basket, we are proposing to continue to adjust the drug expenses reported on the MCR to include an estimate of total Medicaid drug costs, which are not represented in the Medicare-allowable drug cost weight. Similar to the last rebasing, we are estimating Medicaid drug costs based on data representing dual-eligible Medicaid beneficiaries. Medicaid drug costs are estimated by multiplying Medicaid dual eligible drug costs per day times the number of Medicaid days as reported in the Medicare allowable skilled nursing cost center in the SNF MCR. Medicaid dual eligible drug costs per day (where the day represents an unduplicated drug supply day) were estimated using a sample of 2010 Part D claims for those dual-eligible beneficiaries who had a Medicare SNF stay during the year. Medicaid dual-eligible beneficiaries would receive their drugs through the Medicare Part D benefit, which would work directly with the pharmacy, and therefore, these costs would not be represented in the Medicare SNF MCRs. A random 20 percent sample of Medicare Part D claims data yielded a Medicaid drug cost per day of $17.39. We note that the FY 2004-based SNF market basket relied on data from the Medicaid Statistical Information System, which yielded a dual eligible Medicaid drug cost per day of $13.65 for 2004. For the revised and rebased FY 2010-based SNF market basket, we propose to use Part D claims to estimate total Medicaid drug costs as this provides drug expenditure data for dual-eligible beneficiaries for 2010. The Medicaid Statistical Information System is no longer a comprehensive database for dual-eligible beneficiaries' drug costs.

The proposed adjusted FY 2010-based SNF market basket drug cost weight, representing all drug expenditures including those we estimated for Medicaid, is 7.872 percent. The FY 2004-based SNF market basket pharmaceutical cost weight was 7.894 percent.

  • Professional Liability Insurance: We calculated the professional liability insurance cost weight using costs from Worksheet S-2 of the MCRs as the sum of premiums, paid losses, and self-insurance. To derive the professional liability insurance cost weight for the proposed FY 2010-based SNF market basket, we used the same cost report methodology that was used to derive the cost weight of the FY 2004-based SNF market basket (see 72 FR 25543-25544). For the proposed FY 2010-based SNF market basket, the professional liability weight is 1.141 percent, which is slightly lower than the 1.717 weight for the FY 2004-based SNF market basket.
  • Capital-Related: We derived the weight for overall capital-related expenses using the FY 2010 SNF MCRs. We calculated the Medicare allowable capital-related cost weight from Worksheet B, part II. In determining the subcategory weights for capital, we used information from the FY 2010 SNF MCR and the 2010 Bureau of Census' Service Annual Survey (SAS) data. For the FY 2004-based SNF market basket, we relied on the Bureau of Census Business Expenditure Survey (BES). The SAS data is a replacement/extension of the BES data, reflecting more recent data.

We calculated the depreciation cost weight (that is, depreciation costs excluding leasing costs) using depreciation costs from Worksheet S-2. Since the depreciation costs reflect the entire SNF facility (Medicare and non-Medicare allowable units) we used total facility costs as the denominator. This methodology assumes that the depreciation of an asset is the same regardless of whether the asset was used for Medicare or non-Medicare patients. This methodology yielded a FY 2010-based SNF market basket depreciation cost weight of 2.301 percent. This depreciation cost weight is further adjusted to account for a proportion of leasing expenses, which is described in more detail below. We determined the distribution between building and fixed equipment and movable equipment depreciation from the FY 2010 SNF MCR, as well. The FY 2010 SNF MCR data showed a fixed/moveable depreciation split of 85/15, which is the same split used in the FY 2004-based SNF market basket.

We also derived the interest expense share of capital-related expenses from Worksheet A from the FY 2010 SNF MCRs. Similar to the depreciation cost weight, we calculated the interest cost weight using total facility costs. As done with the last rebasing, we determined the split of interest expense between for-profit and not-for-profit facilities based on the distribution of long-term debt outstanding by type of SNF (for-profit or not-for-profit) from the FY 2010 SNF MCRs. We estimated the split between for-profit and not-for-profit interest expense to be 41/59 percent.

Because the data were not available in the MCRs, we used the most recent 2010 SAS data to derive the capital-related expenses attributable to leasing and other capital-related expenses. Based on the 2010 SAS data, we determined the leasing costs to be 30 percent of total capital-related expenses, while we determined the other capital-related costs (insurance, taxes, licenses, other) to be 18 percent of total capital-related expenses. In the FY 2004-based SNF market basket, leasing costs represent 21 percent of total capital-related expenses while other capital-related costs represent 13 percent of total capital-related expenses.

Lease expenses are not broken out as a separate cost category, but are distributed among the cost categories of depreciation, interest, and other capital, reflecting the assumption that the underlying cost structure and price movement of leasing expenses is similar to capital costs in general. As was done in previous rebasings, we assumed 10 percent of lease expenses are overhead and assigned them to the other capital expenses cost category. We distributed the remaining lease expenses to the three cost categories based on the proportion of depreciation, interest, and other capital expenses to total capital costs, excluding lease expenses.

Table 11 shows the capital-related expense distribution (including expenses from leases) in the proposed FY 2010-based SNF market basket and the FY 2004-based SNF market basket.

Table 11—Comparison of the Capital-Related Expense Distribution of the FY 2010-Based SNF Market Basket and the FY 2004-Based SNF Market Basket Back to Top
Cost category Proposed FY 2010-based SNF market basket FY 2004-based SNF market basket
Capital-related expenses 7.360 7.207
Total Depreciation 3.180 2.858
Total Interest 2.096 3.037
Other Capital-related Expenses 2.084 1.312

Our methodology for determining the price change of capital-related expenses accounts for the vintage nature of capital, which is the acquisition and use of capital over time. To capture this vintage nature, the price proxies must be vintage-weighted. The determination of these vintage weights occurs in two steps. First, we must determine the expected useful life of capital and debt instruments held by SNFs. Second, we must identify the proportion of expenditures within a cost category that is attributable to each individual year over the useful life of the relevant capital assets, or the vintage weights. We rely on Bureau of Economic Analysis (BEA) fixed asset data to derive the useful lives of both fixed and movable capital, which is the same data source used to derive the useful lives during the last rebasing. The specifics of the data sources used are explained below.

Estimates of useful lives for movable and fixed assets for the proposed FY 2010-based SNF market basket are 6 and 25 years, respectively. These estimates are based on several data sources from the BEA, which publishes various useful life-related statistics, including asset service lives and current-cost average age, historical cost average age, and industry-specific current cost net stocks of assets. While SNF-specific data are not available, we can use the BEA data to develop estimates of useful life that are approximates of SNF capital purchases.

There are two major issues we must address in using the BEA service life data to develop SNF-specific estimates. First, these data are published at a detailed asset level and not at an aggregate level, such as movable and fixed assets. There are 43 detailed movable assets in the BEA estimates. Some examples include computer software (34 months service life), electromedical equipment (9 years), medical instruments and related equipment (12 years), communication equipment (15 years), and office equipment (8 years). There are 23 detailed fixed assets in the BEA estimates. Some examples of detailed fixed assets are medical office buildings (36 years), hospitals and special care buildings (48 years), and lodging (32 years). Again, there are no service life estimates at an aggregate level, such as movable and fixed assets. The second reason BEA service life data are not directly applicable to SNFs is that service lives are not industry-specific; they apply to many different industries and, in most cases, to all industries in the economy. We seek estimates applicable to nursing homes for our SNF-specific estimates. BEA also publishes average asset age estimates. Average age estimates are updated more regularly than service lives data but reflect an average age rather than a service life. To get an estimate of the available service life of an asset, the average age is multiplied by 2 to reflect that some assets are retired prior to the useful life being exhausted. Average age data are available by detailed and aggregate asset levels for the overall economy and were last published in 2012.

We developed a methodology to approximate movable and fixed asset ages for nursing and residential care services (NAICS 623) using the published BEA data. For the proposed FY 2010 SNF market basket, we use the average age for each asset type from the BEA fixed assets Table 2.9 for all assets (not SNF-specific) and weight them using current cost net stock levels for each of these asset types in the nursing and residential care services industry. Current cost net stock levels are available for download from the BEA Web site at http://www.bea.gov/national/FA2004/Details/Index.html.

These detailed current cost net stock estimates are not published in the Survey of Current Business, a U.S. Department of Commerce monthly publication that provides data on U.S. businesses. Historical cost average age estimates for all industries are published in the BEA fixed assets Table 2.10; there are no industry-specific estimates for historical cost average age. Industry-specific historical cost average ages for NAICS 6230 is estimated by multiplying the industry specific current cost average age by the ratio of historical cost to current cost average age for all industries. This produces historical cost average age data for movable and fixed assets specific to NAICS 6230 of 3.2 and 12.2 years, respectively. Since averages are measures of central tendency, we multiply each of these estimates by two to produce estimates of likely useful lives of 6.4 and 24.5 years for movable and fixed assets, which we round to 6 and 25 years, respectively. We are proposing an interest vintage weight time span of 22 years, obtained by weighting the fixed and movable vintage weights (25 years and 6 years, respectively) by the fixed and movable split (85 percent and 15 percent, respectively).

Given the expected useful life of capital and debt instruments, we must determine the proportion of capital expenditures attributable to each year of the expected useful life by cost category. These proportions represent the vintage weights. We were not able to find a historical time series of capital expenditures by SNFs. Therefore, we approximated the capital expenditure patterns of SNFs over time, using alternative SNF data sources. For building and fixed equipment, we used the stock of beds in nursing homes from the National Nursing Home Survey (NNHS) conducted by the National Center for Health Statistics (NCHS) for 1962 through 1999. For 2000 through 2010, we extrapolated the 1999 bed data forward using a 10-year moving average of growth in the number of beds from the SNF MCR data. We then used the change in the stock of beds each year to approximate building and fixed equipment purchases for that year. This procedure assumes that bed growth reflects the growth in capital-related costs in SNFs for building and fixed equipment. We believe that this assumption is reasonable because the number of beds reflects the size of a SNF, and as a SNF adds beds, it also likely adds fixed capital.

For movable equipment, we used available SNF data to capture the changes in intensity of SNF services that would likely be accompanied by the purchase of movable equipment. We used the same methodology to estimate the change in intensity as published in the FY 2008 SNF final rule for the period from 1962 through 2004. For more details of the methodology, see the FY 2008 SNF PPS final rule (72 FR 43428). We propose to use the same methodology to estimate the ratio of ancillary to routine costs for 2005 through 2010 from the SNF MCR. The time series of the ratio of ancillary costs to routine costs for SNFs measures changes in intensity in SNF services, which are assumed to be associated with movable equipment purchase patterns. The assumption here is that as ancillary costs increase compared to routine costs, the SNF caseload becomes more complex and would require more movable equipment. Again, the lack of movable equipment purchase data for SNFs over time required us to use alternative SNF data sources. We believe the resulting two time series, determined from beds and the ratio of ancillary to routine costs, reflect real capital purchases of building and fixed equipment and movable equipment over time.

To obtain nominal purchases, which are used to determine the vintage weights for interest, we converted the two real capital purchase series from 1963 through 2010 determined above to nominal capital purchase series using their respective price proxies (the BEA chained price index for nonresidential construction for hospitals & special care facilities and the PPI for Machinery and Equipment). We then combined the two nominal series into one nominal capital purchase series for 1963 through 2010. Nominal capital purchases are needed for interest vintage weights to capture the value of debt instruments.

Once we created these capital purchase time series for 1963 through 2010, we averaged different periods to obtain an average capital purchase pattern over time: (1) For building and fixed equipment, we averaged 24, 25-year periods; (2) for movable equipment, we averaged 43, 6-year periods; and (3) for interest, we averaged 27, 22-year periods. We calculate the vintage weight for a given year by dividing the capital purchase amount in any given year by the total amount of purchases during the expected useful life of the equipment or debt instrument. Following publication of the FY 2010 IPPS/Rate Year 2010 LTCH PPS proposed rule, and to provide greater transparency, we posted on the CMS market basket Web site at http://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/MedicareProgramRatesStats/MarketBasketResearch.html, an illustrative spreadsheet that contains an example of how the vintage-weighted price indexes are calculated.

Table 12 shows the resulting vintage weights for each of these cost categories.

Table 12—Vintage Weights for Proposed FY 2010-Based SNF PPS Capital-Related Price Proxies Back to Top
Year1 Building and fixed equipment Movable equipment Interest
SOURCES: 2010 SNF MCRs; CMS,
NOTE: Totals may not sum to 1.000 due to rounding.
1Year 1 represents the vintage weight applied to the farthest year while the vintage weight for year 25, for example, would apply to the most recent year.
1 .061 .165 .030
2 .059 .160 .030
3 .053 .167 .032
4 .050 .167 .033
5 .046 .169 .035
6 .043 .171 .037
7 .041 .039
8 .039 .040
9 .036 .041
10 .034 .043
11 .034 .045
12 .034 .047
13 .033 .048
14 .032 .048
15 .031 .050
16 .031 .052
17 .032 .055
18 .034 .058
19 .035 .060
20 .036 .060
21 .038 .058
22 .039 .058
23 .042
24 .043
25 .044
Total 1.000* 1.000* 1.000*
  • All Other (residual): We divided the residual “all other” cost category into subcategories, using the BEA's Benchmark Input-Output Tables for the nursing home industry aged to 2010 using relative price changes. (The methodology we used to age the data involves applying the annual price changes from the price proxies to the appropriate cost categories. We repeat this practice for each year. We then apply the resulting 2010 distributions to the aggregate 2010 “all other” cost weight of 21.534 percent to yield the detailed 2010 all other cost weights.)

For the FY 2010-based SNF market basket, we are proposing to include five new cost categories compared to the FY 2004-based SNF market basket, as discussed further below. We are also proposing to revise the labels for the labor-intensive and nonlabor-intensive cost categories; the new labels would be “all other: labor-related”, and “all other: nonlabor-related”. As discussed in more detail below, we classify a cost category as labor-related and include it in the labor-related share if the cost category is determined to be labor-intensive and its cost varies with the local labor market. In previous regulations, we grouped cost categories that met both of these criteria into labor-intensive services. We believe the new labels more accurately reflect the concepts that they are intended to convey. We are not proposing a change to our definition of the labor-related share, since we continue to classify a cost category as labor-related if the costs are labor-intensive and vary with the local labor market.

For nonmedical professional fees, we are proposing to create two separate cost categories: (1) Nonmedical professional fees: labor-related, and (2) nonmedical professional fees: Nonlabor-related. We discuss the distinction between these two categories in more detail below in the discussion of the labor-related share.

Table 13 compares the proposed FY 2010-based SNF market basket cost weights with the FY 2004-based SNF market basket cost weights.

Table 13—Comparison of the Proposed FY 2010-Based SNF Market Basket Cost Weights and the FY 2004-Based SNF Market Basket Cost Weights Back to Top
Cost category Proposed FY 2010-based SNF market basket weights FY 2004-based SNF market basket weights
1For the FY 2010-based SNF Market basket, we are proposing to divide this category into nonmedical professional fees: labor-related and nonmedical professional fees: nonlabor-related.
2For the FY 2010-based SNF Market basket, we are proposing to create a separate cost category for these expenses to proxy the price growth by a more specific index. These expenses were previously classified under miscellaneous products in the FY 2004-based SNF market basket.
3For the FY 2010-based SNF Market basket, we are proposing to create a separate cost category for these expenses to proxy the price growth by a more specific index. These expenses were previously classified under labor intensive services cost weight in the FY 2004-based SNF market basket.
4For the FY 2010-based SNF market basket, we are proposing to revise the labels for the labor-intensive and nonlabor-intensive cost categories to be all other: labor-related and all other: nonlabor-related.
5For the FY 2010-based SNF market basket, we are proposing to create a separate cost category for these expenses to proxy the price growth by a more specific index. These expenses were previously classified under nonlabor intensive services cost weight in the FY 2004-based SNF market basket.
Total 100.000 100.000
Compensation 62.093 62.755
Wages and Salaries 50.573 51.337
Employee Benefits 11.520 11.418
Nonmedical Professional Fees1 1.322
Nonmedical Professional Fees 1.322
Utilities 2.223 1.551
Electricity 1.411 0.919
Fuels, Non-highway 0.667 0.453
Water and Sewerage 0.145 0.179
Professional Liability Insurance 1.141 1.717
Professional Liability Insurance 1.141 1.717
All Other 27.183 25.448
All Other Products 16.148 19.03
Pharmaceuticals 7.872 7.894
Food, Wholesale Purchase 3.661 2.906
Food, Retail Purchase 1.190 3.151
Chemicals 0.166 0.589
Medical Instruments and Supplies2 0.764
Rubber and Plastics 0.981 1.513
Paper and Printing Products 0.838 1.394
Apparel2 0.195
Machinery and Equipment2 0.190
Miscellaneous Products 0.291 1.582
All Other Services 11.035 6.418
Labor-Related Services 6.227
Nonmedical Professional Fees: Labor-related1 3.427
Administrative and Facilities Support3 0.497
All Other: Labor-Related Services4 2.303 3.521
NonLabor-Related Services 4.808
Nonmedical Professional Fees: Nonlabor-related1 2.042
Financial Services5 0.899
Telephone Services 0.572 0.434
Postage 0.240 0.454
All Other: Nonlabor-related Services4 1.055 2.008
Capital-related Expenses 7.360 7.207
Total Depreciation 3.180 2.858
Building and Fixed Equipment 2.701 2.437
Movable Equipment 0.479 0.421
Total Interest 2.096 3.037
For-Profit SNFs 0.869 1.197
Non-profit SNFs 1.227 1.84
Other Capital-related Expenses 2.084 1.312
Other 2.084 1.312

3. Price Proxies Used To Measure Cost Category Growth

After developing the 29 cost weights for the proposed FY 2010-based SNF market basket, we selected the most appropriate wage and price proxies currently available to represent the rate of change for each expenditure category. With four exceptions (three for the capital-related expenses cost categories and one for Professional Liability Insurance (PLI)), we base the wage and price proxies on Bureau of Labor Statistics (BLS) data, and group 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 2004 North American Industry Classification System (NAICS).
  • 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 PPI were available.

We evaluated the price proxies using the criteria of reliability, timeliness, availability, and relevance. Reliability indicates that the index is based on valid statistical methods and has low sampling variability. 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 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 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. Finally, relevance means that the proxy is applicable and representative of the cost category weight to which it is applied. The CPIs, PPIs, and ECIs that we have selected to propose in this regulation 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.

As discussed above, we propose that if the 2007 Benchmark I-O data become available between the proposed and final rule with sufficient time to incorporate such data into the final rule, we would incorporate these data, as appropriate, into the FY 2010-based SNF market basket for the final rule. In addition, we propose that to the extent the incorporation of the 2007 Benchmark I-O data results in a different composition of costs included in a particular cost category, we would revise that specific price proxy, as appropriate, to ensure that the costs included in each detailed cost category are aligned with the most appropriate price proxy. Table 15 lists all price proxies for the proposed revised and rebased SNF market basket. Below is a detailed explanation of the price proxies used for each cost category weight.

  • Wages and Salaries: We are proposing to use the ECI for Wages and Salaries for Nursing Care Facilities (Private Industry) (NAICS 6231; BLS series code CIU2026231000000I) to measure price growth of this category. The FY 2004-based SNF market basket used a blended index based on 50 percent of the ECI for wages and salaries for nursing and residential care facilities (NAICS 623) and 50 percent of the ECI for wages and salaries for hospital workers (NAICS 622). For the FY 2010-based SNF market basket, we are proposing to use the Nursing Care Facilities ECI, as we believe this ECI better reflects wage trends consistent with services provided by Medicare-certified SNFs.

NAICS 623 includes facilities that provide a mix of health and social services, with many of the health services being largely some level of nursing services. Within NAICS 623 is NAICS 6231, which includes nursing care facilities primarily engaged in providing inpatient nursing and rehabilitative services. These facilities, which are most comparable to Medicare-certified SNFs, provide skilled nursing and continuous personal care services for an extended period of time, and therefore, have a permanent core staff of registered or licensed practical nurses. At the time of the last rebasing, BLS had just begun publishing ECI data for the more detailed nursing care facilities (NAICS 6231), and therefore, IGI, the economic forecasting firm, was unable to forecast this price proxy.

BLS has now published over six years of historical data for the ECI for Nursing Care Facilities (NAICS 6231), which allows IGI to create a forecast for this detailed index. Additionally, in analyzing the historical trends, we believe this ECI is the most technically appropriate wage concept to use for the proposed revised and rebased 2010-based SNF market basket as it is most comparable to Medicare-certified SNFs, which are engaged in providing inpatient nursing and rehabilitative services.

  • Employee Benefits: We are proposing to use the ECI for Benefits for Nursing Care Facilities (NAICS 6231) to measure price growth of this category. The ECI for Benefits for Nursing Care Facilities is calculated using BLS's total compensation (BLS series ID CIU2016231000000I) for nursing care facilities series and the relative importance of wages and salaries within total compensation. We believe this ECI and constructed series is technically appropriate for the reason stated above in the wages and salaries price proxy section. We used a blended benefits index in the FY 2004-based SNF market basket.
  • Electricity: We are proposing to use the PPI for Commercial Electric Power (BLS series code WPU0542) to measure the price growth of this cost category. We used the same index in the FY 2004-based SNF market basket.
  • Fuels, nonhighway: We are proposing to use the PPI for Commercial Natural Gas (BLS series code WPU0552) to measure the price growth of this cost category. We used the same index in the FY 2004-based SNF market basket.
  • Water and Sewerage: We are proposing to use the CPI for Water and Sewerage Maintenance (All Urban Consumers) (BLS series code CUUR0000SEHG01) to measure the price growth of this cost category. We used the same index in the FY 2004-based SNF market basket.
  • Professional Liability Insurance: We are proposing to use the CMS Hospital Professional Liability Insurance Index to measure price growth of this category. In the FY 2008 proposed rule (72 FR 25552), we stated our difficulties associated with pricing malpractice costs experienced in all healthcare sectors, including hospitals and physicians. We also stated our intent to research alternative data sources, such as obtaining the data directly from the individual states' Departments of Insurance. We were unable to find a reliable data source that collects SNF-specific PLI data. Therefore, we are proposing to use the CMS Hospital Professional Liability Index, which tracks price changes for commercial insurance premiums for a fixed level of coverage, holding nonprice factors constant (such as a change in the level of coverage). We used the same index in the FY 2004-based SNF market basket. We believe this is an appropriate proxy to measure the price growth associated with SNF professional liability insurance, as it captures the price inflation associated with other medical institutions that serve Medicare patients.
  • Pharmaceuticals: We are proposing 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 that was used in the FY 2004-based SNF market basket, though BLS has since changed the naming convention of this series.
  • Food: Wholesale Purchases: We are proposing to use the PPI for Processed Foods and Feeds (BLS series code WPU02) to measure the price growth of this cost category. We used the same index in the FY 2004-based SNF market basket.
  • Food: Retail Purchase: We are proposing to use the CPI for Food Away From Home (All Urban Consumers) (BLS series code CUUR0000SEFV) to measure the price growth of this cost category. We used the same index in the FY 2004-based SNF market basket.
  • Chemicals: For measuring price change in the Chemicals cost category, we are proposing to use a blended PPI composed of the PPIs for Other Basic Organic Chemical Manufacturing (NAICS 325190) (BLS series code PCU32519-32519), Paint and Coating Manufacturing (NAICS 325510) (BLS series code PCU32551-32551), Soap and Cleaning Compound Manufacturing (NAICS 325610) (BLS series code PCU32561-32561), and All Other Chemical Product and Preparation Manufacturing (NAICS 3259A0) (BLS series code PCU3259-3259).

Using the 2002 Benchmark I-O data, we found that these four NAICS industries accounted for approximately 95 percent of SNF chemical expenses. The remaining 5 percent of SNF chemical expenses are for five other incidental NAICS chemicals industries, such as Alkalies and Chlorine Manufacturing. We are proposing to create a blended index based on those four NAICS chemical expenses listed above that account for 95 percent of SNF chemical expenses. We are proposing to create a blend based on each NAICS' expenses as a share of their sum. As stated above, we propose that if the 2007 Benchmark I-O data become available between the proposed and final rule with sufficient time to incorporate such data into the final rule, we would incorporate these data, as appropriate, into the FY 2010-based SNF market basket for the final rule. In addition, we propose that to the extent the incorporation of the 2007 Benchmark I-O data results in a different composition of chemical costs, we may revise, as appropriate, the blended chemical index set forth above to reflect these more recent data on SNF chemical purchases, to better align the costs with its price proxy. Table 14 below provides the weights for the blended chemical index.

Table 14—Proposed Chemical Blended Index Weights Back to Top
NAICS Industry description Weights (percent)
325190 Other basic organic chemical manufacturing 7
325510 Paint and coating manufacturing 12
325610 Soap and cleaning compound manufacturing 49
3259A0 All other chemical product and preparation manufacturing 32
100

The FY 2004-based SNF market basket also used a blended chemical proxy that was based on 1997 Benchmark I-O data. We believe our proposed chemical blended index for the FY 2010-based SNF market basket is technically appropriate, as it reflects more recent data on SNFs' purchasing patterns.

  • Medical Instruments and Supplies: We are proposing to use the PPI for Medical, Surgical, and Personal Aid Devices (BLS series code WPU156) to measure the price growth of this cost category. The FY 2004-based SNF market basket did not include a separate cost category for these expenses. Rather, these expenses were classified in the miscellaneous products cost category and proxied by the PPI for Finished Goods less Food and Energy (BLS series code WPUSOP3500). As stated above, we are proposing to break-out this cost category to proxy these expenses by a more specific price index that better reflects the price growth of medical instruments and supplies.
  • Rubber and Plastics: We are proposing to use the PPI for Rubber and Plastic Products (BLS series code WPU07) to measure price growth of this cost category. We used the same index in the FY 2004-based SNF market basket.
  • Paper and Printing Products: We are proposing to use the PPI for Converted Paper and Paperboard Products (BLS series code WPU0915) to measure the price growth of this cost category. We used the same index in the FY 2004-based SNF market basket.
  • Apparel: We are proposing to use the PPI for Apparel (BLS series code WPU0381) to measure the price growth of this cost category. The FY 2004-based SNF market basket did not have a separate cost category for these expenses. Rather, these expenses were classified in the miscellaneous products cost category and proxied by the PPI for Finished Goods less Food and Energy. As stated above, we are proposing to break-out this cost category to proxy these expenses by a more specific price index that better reflects the price growth of apparel products.
  • Machinery and Equipment: We are proposing to use the PPI for Machinery and Equipment (BLS series code WPU11) to measure the price growth of this cost category. The 2004-based index did not have a separate cost category for these expenses. Rather, these expenses were classified in the miscellaneous products cost category and proxied by the PPI for Finished Goods less Food and Energy (BLS series code WPUSOP3500). As stated above, we are proposing to break-out this cost category to proxy these expenses by a more specific price index that reflects the price growth of machinery and equipment.
  • Miscellaneous Products: For measuring price change in the Miscellaneous Products cost category, we are proposing to use the PPI for Finished Goods less Food and Energy (BLS series code WPUSOP3500). Both food and energy are already adequately represented in separate cost categories and should not also be reflected in this cost category. We used the same index in the FY 2004-based SNF market basket.
  • Nonmedical Professional Fees: Labor-Related and Nonmedical Professional Fees: Nonlabor-Related: We are proposing to use the ECI for Total Compensation for Professional and Related Occupations (Private Industry) (BLS series code CIU2010000120000I) to measure the price growth of these categories. As described in more detail below, for this revising and rebasing of the SNF market basket we are proposing to divide the nonmedical professional fees cost category into two separate cost categories: (1) Nonmedical professional fees: labor-related; and (2) nonmedical professional fees: Nonlabor-related. By separating these two categories we are able to identify more precisely which categories are to be included in the labor-related share, which is used in applying the SNF PPS geographic adjustment factor. We are proposing to proxy both of these cost categories by the ECI for Total Compensation for Professional and Related Occupations (Private Industry). This is the same proxy that was used in the FY 2004-based SNF market basket.
  • Administrative and Facilities Support Services: We are proposing to use the ECI for Total Compensation for Office and Administrative Support Services (Private Industry) (BLS series code CIU2010000220000I) to measure the price growth of this category. The FY 2004-based SNF market basket did not have a separate cost category for these expenses. Rather, these expenses were classified under labor intensive services and proxied by the ECI for Compensation for Service Occupations (Private Industry). As stated above, we are proposing to create a separate cost category for these expenses to reflect the specific price changes associated with these services.
  • All Other: Labor-Related Services: We are proposing to use the ECI for Total Compensation for Service Occupations (Private Industry) (BLS series code CIU2010000300000I) to measure the price growth of this cost category (previously referred to as the labor-intensive cost category in the FY 2004-based SNF market basket index). We used the same index in the FY 2004-based SNF market basket. As explained above, for this revising and rebasing of the SNF market basket, we are proposing to revise our label for the labor-intensive services to the all other: labor-related services.
  • Financial Services: We are proposing to use the ECI for Total Compensation for Financial Activities (Private Industry) (BLS series code CIU201520A000000I) to measure the price growth of this cost category. The FY 2004-based SNF market basket did not have a separate cost category for these expenses. Rather, these expenses were classified under nonlabor intensive services cost category and proxied by the CPI for All Items (Urban). As stated above, we are proposing to create a separate cost category for these expenses to reflect the specific price changes associated with these services.
  • Telephone Services: We are proposing to use the CPI for Telephone Services (Urban) (BLS series code CUUR0000SEED) to measure the price growth of this cost category. We used the same index in the FY 2004-based SNF market basket.
  • Postage: We are proposing to use the CPI for Postage and Delivery Services (Urban) (BLS series code CUUR0000SEEC) to measure the price growth of this cost category. We used the same index in the FY 2004-based SNF market basket.
  • All Other: NonLabor-Related Services: We are proposing to use the CPI for All Items Less Food and Energy (BLS series code CUUR0000SA0L1E) to measure the price growth of this cost category (previously referred to as the nonlabor-intensive cost category in the FY 2004-based SNF market basket index). Previously these costs were proxied by the CPI for All Items (Urban). We believe that using the CPI for All Items Less Food and Energy (BLS series code CUUR0000SA0L1E) will remove any double-counting of food and energy prices, which are already captured elsewhere in the market basket. Consequently, we believe that the incorporation of this proxy represents a technical improvement to the market basket.
  • Capital-Related Expenses: For the capital price proxies (with the exception of the price proxy for the other capital-related cost category weight), we calculate vintage weighted price proxies. The methodology used to derive the vintage weights was described above. Below, we describe the price proxies for the SNF capital-related expenses:
  • Depreciation—Building and Fixed Equipment: For measuring price change in this cost category, we are proposing to use BEA's chained price index for nonresidential construction for hospital and special care facilities. This is a publicly available price index used by BEA to deflate current-dollar private fixed investment for hospitals and special care facilities. The 2004-based index used the Boeckh Institutional Construction Index, which is not publicly available. We compared the BEA index with the Boeckh Institutional Construction Index and found that the average growth rates in the two series were similar over the historical time period. We are proposing to use the BEA price index in the FY 2010-based SNF market basket as this index is a publicly available index that reflects the price inflation associated with nonresidential construction, such as the construction of hospitals and special care facilities. As stated above, 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.
  • Depreciation—Movable Equipment: For measuring price change in this cost category, we are proposing to use the PPI for Machinery and Equipment (BLS series code WPU11). The same price proxy was used in the FY 2004-based SNF market basket index.
  • Interest—Government and Nonprofit SNFs: For measuring price change in this cost category, we are proposing to use the Average Yield for Municipal Bonds from the Bond Buyer Index of 20 bonds. CMS input price indexes, including this proposed rebased and revised SNF market basket, appropriately reflect the rate of change in the price proxy and not the level of the price proxy. While SNFs may face different interest rate levels than those included in the Bond Buyer Index, the rate of change between the two is not significantly different. The same price proxy was used in the FY 2004-based SNF market basket index.
  • Interest—For-profit SNFs: For measuring price change in this cost category, we are proposing to use the Average Yield for Moody's AAA Corporate Bonds. Again, the proposed revised and rebased SNF market basket index focuses on the rate of change in this interest rate, not on the level of the interest rate. The same price proxy was used in the FY 2004-based SNF market basket index.
  • Other Capital-related Expenses: For measuring price change in this cost category, we are proposing the CPI-U for Rent of Primary Residence (BLS series ID CUUR0000SEHA). The same price proxy was used in the FY2004-based SNF market basket index, though the naming convention is slightly different as we have provided the full BLS naming convention.

Table 15 shows the proposed price proxies for the FY 2010-based SNF Market Basket.

Table 15—Proposed Price Proxies for the FY 2010-Based SNF Market Basket Back to Top
Cost category Weight Proposed price proxy
Compensation 62.093
Wages and Salaries 50.573 ECI for Wages and Salaries for Nursing Care Facilities.
Employee Benefits 11.520 ECI for Benefits for Nursing Care Facilities.
Utilities 2.223
Electricity 1.411 PPI for Commercial Electric Power.
Fuels, Nonhighway 0.667 PPI for Commercial Natural Gas.
Water and Sewerage 0.145 CPI-U for Water and Sewerage Maintenance.
Professional Liability Insurance 1.141 CMS Hospital Professional Liability Insurance Index.
All Other 27.183
Other Products 16.148
Pharmaceuticals 7.872 PPI for Pharmaceuticals for Human Use, Prescription.
Food, Wholesale Purchase 3.661 PPI for Processed Foods and Feeds.
Food, Retail Purchases 1.190 CPI-U for Food Away From Home.
Chemicals 0.166 Blend of Chemical PPIs.
Medical Instruments and Supplies 0.764 PPI for Medical, Surgical, and Personal Aid Devices.
Rubber and Plastics 0.981 PPI for Rubber and Plastic Products.
Paper and Printing Products 0.838 PPI for Converted Paper and Paperboard Products.
Apparel 0.195 PPI for Apparel.
Machinery and Equipment 0.190 PPI for Machinery and Equipment.
Miscellaneous Products 0.291 PPI for Finished Goods Less Food and Energy.
All Other Services 11.035
Labor-Related Services 6.227
Nonmedical Professional Fees: Labor-related 3.427 ECI for Total Compensation for Professional and Related Occupations.
Administrative and Facilities Support 0.497 ECI for Total Compensation for Office and Administrative Support.
All Other: Labor-Related Services 2.303 ECI for Total Compensation for Service Occupations.
Non Labor-Related Services 4.808
Nonmedical Professional Fees: Non Labor-Related 2.042 ECI for Total Compensation for Professional and Related Occupations.
Financial Services 0.899 ECI for Total Compensation for Financial Activities.
Telephone Services 0.572 CPI-U for Telephone Services.
Postage 0.240 CPI-U for Postage and Delivery Services.
All Other: Nonlabor-Related Services 1.055 CPI-U for All Items Less Food and Energy.
Capital-Related Expenses 7.360
Total Depreciation 3.180
Building and Fixed Equipment 2.701 BEA chained price index for nonresidential construction for hospitals and special care facilities—vintage weighted (25 years).
Movable Equipment 0.479 PPI for Machinery and Equipment—vintage weighted (6 years).
Total Interest 2.096
For-Profit SNFs 0.869 Average yield on municipal bonds (Bond Buyer Index 20 bonds)—vintage weighted (22 years).
Government and Nonprofit SNFs 1.227 Average yield on Moody's AAA corporate bonds—vintage weighted (22 years).
Other Capital-Related Expenses 2.084 CPI-U for Rent of Primary Residence.
Total 100.000

4. Proposed Market Basket Estimate for the FY 2014 SNF PPS Update

As discussed previously in this proposed rule, beginning with the FY 2014 SNF PPS update, we are proposing to adopt the FY 2010-based SNF market basket as the appropriate market basket of goods and services for the SNF PPS.

Based on IGI's first quarter 2013 forecast with history through the fourth quarter of 2012, the most recent estimate of the proposed FY 2010-based SNF market basket for FY 2014 is 2.3 percent. IGI is a nationally recognized economic and financial forecasting firm that contracts with CMS to forecast the components of CMS' market baskets. Based on IGI's first quarter 2013 forecast with history through the fourth quarter of 2012, the estimate of the current FY 2004-based SNF market basket for FY 2014 is 2.5 percent.

Table 16 compares the proposed FY 2010-based SNF market basket and the FY 2004-based SNF market basket percent changes. For the historical period between FY 2008 and FY 2012, the average difference between the two market baskets is −0.3 percentage point. This is primarily the result of lower compensation price increases in the FY 2010-based market basket compared to the FY 2004-based SNF market basket. For the forecasted period between FY 2013 and FY 2015, the difference in the market basket forecasts is similar.

Table 16—Proposed FY 2010-Based SNF Market Basket and FY 2004-Based SNF Market Basket, Percent Changes: 2008-2015 Back to Top
Fiscal year (FY) Proposed rebased FY 2010-based SNF market basket FY 2004-based SNF basket
Source: IHS Global Insight, Inc. 1st quarter 2013 forecast with historical data through 4th quarter 2012.
Historical data:    
FY 2008 3.5 3.6
FY 2009 2.4 2.8
FY 2010 1.8 2.0
FY 2011 2.0 2.2
FY 2012 1.8 2.2
Average FY 2008-2012 2.3 2.6
Forecast:    
FY 2013 1.9 2.3
FY 2014 2.3 2.5
FY 2015 2.4 2.6
Average FY 2013-2015 2.2 2.5

5. Labor-Related Share

We define the labor-related share (LRS) as those expenses that are labor-intensive and vary with, or are influenced by, the local labor market. Each year, we calculate a revised labor-related share based on the relative importance of labor-related cost categories in the input price index. In this FY 2014 SNF PPS proposed rule, we are proposing to revise the labor-related share to reflect the relative importance of the following proposed FY 2010-based SNF market basket cost weights that we believe are labor-intensive and vary with, or are influenced by, the local labor market: (1) Wages and salaries; (2) employee benefits; (3) contract labor; (4) the labor-related portion of nonmedical professional fees; (5) administrative and facilities support services; (6) all other: labor-related services (previously referred to in the FY 2004-based SNF market basket as labor-intensive); and (7) a proportion of capital-related expenses. We are proposing to continue to include a proportion of capital-related expenses because a portion of these expenses are deemed to be labor-intensive and vary with, or are influenced by, the local labor market. For example, a proportion of construction costs for a medical building would be attributable to local construction workers' compensation expenses.

Consistent with previous SNF market basket revisions and rebasings, the “all other: labor-related services” cost category is mostly comprised of building maintenance and security services (including, but not limited to, commercial and industrial machinery and equipment repair, nonresidential maintenance and repair, and investigation and security services). Because these services tend to be labor-intensive and are mostly performed at the SNF facility (and therefore, unlikely to be purchased in the national market), we believe that they meet our definition of labor-related services.

For the proposed FY 2010-based SNF market basket, the proposed inclusion of the administrative and facilities support services cost category into the labor-related share remains consistent with the current labor-related share, since this cost category was previously included in the FY 2004-based SNF market basket labor-intensive cost category. As previously stated, we are proposing to establish a separate administrative and facilities support services cost category so that we can use the ECI for Total Compensation for Office and Administrative Support Services to reflect the specific price changes associated with these services.

For the FY 2004-based SNF market basket, we assumed that all nonmedical professional services (including accounting and auditing services, engineering services, legal services, and management and consulting services) were purchased in the local labor market and, thus, all of their associated fees varied with the local labor market. As a result, we previously included 100 percent of these costs in the labor-related share. In an effort to determine more accurately the share of nonmedical professional fees that should be included in the labor-related share, we surveyed SNFs regarding the proportion of those fees that are attributable to local firms and the proportion that are purchased from national firms. We notified the public of our intent to conduct this survey on December 9, 2005 (70 FR 73250) and received no comments (71 FR 8588).

With approval from OMB, we reached out to the industry and received responses to our survey from 141 SNFs. Using data on full-time equivalents to allocate responding SNFs across strata (region of the country and urban/rural status), post-stratification weights were calculated. Based on these weighted results, we determined that SNFs purchase, on average, the following portions of contracted professional services inside their local labor market:

  • 86 percent of accounting and auditing services.
  • 89 percent of architectural, engineering services.
  • 78 percent of legal services.
  • 87 percent of management consulting services.

Together, these four categories represent 2.672 percentage points of the total costs for the proposed FY 2010-based SNF market basket. We applied the percentages from this special survey to their respective SNF market basket weights to separate them into labor-related and nonlabor-related costs. As a result, we are designating 2.285 of the 2.672 total to the labor-related share, with the remaining 0.387 categorized as nonlabor-related.

In addition to the professional services listed above, we also classified expenses under NAICS 55, Management of Companies and Enterprises, into the nonmedical professional fees cost category. The NAICS 55 data are mostly comprised of corporate, subsidiary, and regional managing offices, or otherwise referred to as home offices. Formerly, all of the expenses within this category were considered to vary with, or be influenced by, the local labor market, and thus, were included in the labor-related share. Because many SNFs are not located in the same geographic area as their home office, we analyzed data from a variety of sources to determine what proportion of these costs should be appropriately included in the labor-related share.

Our proposed methodology is based on data from the MCRs, as well as a CMS database of Home Office Medicare Records (HOMER) (a database that provides city and state information (addresses) for home offices). The MCR requires SNFs to report their home office compensation costs. Using the HOMER database to determine the home office location for each home office provider number, we compared the location of the SNF with the location of the SNF's home office. We propose to determine the proportion of NAICS 55 costs that should be allocated to the labor-related share based on the percent of SNF home office compensation attributable to SNFs that had home offices located in their respective local labor markets—defined as being in the same MSA. We determined a SNF's MSA using its Zip Code information from the MCR, while a home office MSA was determined using the Medicare HOMER Database, which provided a home office Zip Code, as well.

As stated above, we are proposing to determine the proportion of NAICS 55 costs that should be allocated to the labor-related share based on the percent of SNF home office compensation attributable to those SNFs that had home offices located in their respective labor markets. Using this proposed methodology, we determined that 32 percent of SNF home office compensation costs were for SNFs that had home offices located in their respective local labor markets; therefore, we propose to allocate 32 percent of NAICS 55 expenses to the labor-related share. We believe that this methodology provides a reasonable estimate of the NAICS 55 expenses that are appropriately allocated to the labor-related share, because we primarily rely on data on home office compensation costs as provided by SNFs on Medicare cost reports. By combining these data with the specific MSAs for the SNF and their associated home office, we believe we have a reasonable estimate of the proportion of SNF's home office costs that would be incurred in the local labor market.

In the proposed FY 2010-based SNF market basket, NAICS 55 expenses that were subject to allocation based on the home office allocation methodology represent 1.833 percent of the total costs. Based on the home office results, we are apportioning 0.587 percentage point of the 1.833 percentage points figure into the labor-related share and designating the remaining 1.247 percentage points as nonlabor-related.

The Benchmark I-O data contains other smaller cost categories that we allocate fully to either “nonmedical professional fees: Labor-related” or “nonmedical professional fees: nonlabor-related.” Together, the sum of these smaller cost categories, the four nonmedical professional fees cost categories where survey results were available, and the NAICS 55 expenses represent all nonmedical professional fees, or 5.469 percent of total costs in the SNF market basket. Of the 5.469 percentage points, 3.427 percentage points represent professional fees: Labor-related while 2.042 percentage points represent nonmedical professional fees: Nonlabor-related.

Each year, we calculate a revised labor-related share based on the relative importance of labor-related cost categories in the SNF market basket. Table 17 summarizes the proposed updated labor-related share for FY 2014, which is based on the proposed rebased and revised FY 2010-based SNF market basket, compared to the labor-related share that was used for the FY 2013 SNF PPS update.

Table 17—Labor-Related Relative Importance, FY 2013 and FY 2014 Back to Top
Relative importance, labor-related, FY 2013 (FY 2004-based index) 12:2 forecast Relative importance, labor-related, FY 2014 (FY 2010-based index) 13:1 forecast
1As discussed above in section V.A.2 in this preamble, the wages and salaries and employee benefits cost weight reflect contract labor costs.
2Previously referred to as labor-intensive services cost category in the FY 2004 -based SNF market basket.
Wages and salaries1 49.847 49.204
Employee benefits 11.532 11.546
Nonmedical Professional fees: labor-related 1.307 3.451
Administrative and facilities support services N/A 0.501
All Other: Labor-related services2 3.364 2.292
Capital-related (.391) 2.333 2.770
Total 68.383 69.764

B. Monitoring Impact of FY 2012 Policy Changes

In the FY 2012 SNF PPS final rule, we stated we would monitor the impact of certain FY 2012 policy changes on various aspects of the SNF PPS (76 FR 48498). Specifically, we have been monitoring the impact of the following FY 2012 policy changes:

  • Recalibration of the FY 2011 SNF parity adjustment to align overall payments under RUG-IV with those under RUG-III.
  • Allocation of group therapy time to pay more appropriately for group therapy services based on resource utilization and cost.
  • Implementation of changes to the MDS 3.0 patient assessment instrument, most notably the introduction of the Change-of-Therapy (COT) Other Medicare Required Assessment (OMRA).

We have posted quarterly memos to the SNF PPS Web site which highlight some of the trends we have observed over a given time period. These memos may be accessed through the SNF PPS Web site at http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/Downloads/SNF_Monitoring.zip. Below, we provide a summary of the results derived from this monitoring effort.

1. RUG Distributions

As stated in the FY 2012 SNF PPS final rule (76 FR 48493), the recalibration of the FY 2011 parity adjustment used 8 months of FY 2011 data as the basis for the recalibration. We observed that case-mix utilization patterns continued to be consistent over the final 4 months of FY 2011 and would not have resulted in a significant difference in the calculated amount of the recalibrated parity adjustment. We have posted data illustrating the RUG-IV distribution of days for the entirety of FY 2011, as compared to the days distribution used to calculate the parity adjustment in the FY 2012 final rule, and the distribution of days for FY 2012, all of which may be found at http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/Downloads/SNF_Monitoring.zip.

Additionally, case-mix utilization observed during FY 2012 has not shown unanticipated changes in patient classification. Overall patient case mix is not significantly different from that observed in FY 2011. Table 18 illustrates a breakdown of the SNF case-mix distribution of service days by the major RUG classification categories for FY 2011 and FY 2012.

Table 18—SNF Case-Mix Distributions by Major RUG-IV Category Back to Top
FY 2011 (percent) FY 2012 (percent)
Rehabilitation Plus Extensive Services 2.5 1.8
Rehabilitation 87.9 88.8
Extensive Services 0.6 0.7
Special Care 4.6 4.9
Clinically Complex 2.5 2.2
Behavioral Symptoms and Cognitive Performance 0.4 0.3
Reduced Physical Function 1.5 1.4

As illustrated in Table 18, there has been a decrease in the Rehabilitation Plus Extensive Services category and increases in some of the medically-based RUG categories, specifically Special Care and Extensive Services.

It should be noted that the recalibration of the parity adjustment applied only to those RUG-IV groups with a therapy component (Rehabilitation Plus Extensive Services and Rehabilitation). This caused a shift in the hierarchy of nursing case-mix weights among the various RUG-IV groups. Since SNFs are permitted to “index maximize” when determining a resident's RUG classification (that is, of those RUGs for which the resident qualifies, SNFs are permitted to choose the one with the highest per diem payment), it is possible that the aforementioned case-mix distribution shifts reflect residents that had previously been classified into therapy groups but now index maximize into nursing groups instead.

Looking specifically at the case-mix distribution for Rehabilitation RUGs only, the data show an increase in the percentage of service days at the highest therapy level (Ultra High Rehabilitation) in FY 2012. This is illustrated in Table 19.

Table 19—SNF Case-Mix Distribution for Therapy RUG-IV Groups, by Minor RUG-IV Therapy Categories Back to Top
FY 2011 (percent) FY 2012 (percent)
Ultra-High Rehabilitation (≥ 720 minutes of therapy per week) 44.8 48.6
Very-High Rehabilitation (500-719 minutes of therapy per week) 26.9 25.6
High Rehabilitation (325-499 minutes of therapy per week) 10.8 10.1
Medium Rehabilitation (150-324 minutes of therapy per week) 7.6 6.2
Low Rehabilitation (45-149 minutes of therapy per week) 0.1 0.1

Although the decreases in the percentage of service days which classify into the Very-High, High, and Medium Rehabilitation RUG-IV therapy categories may be explained by the increased utilization of the Ultra-High Rehabilitation RUG-IV therapy category, some of the decrease may be due to index maximization into the Special Care RUG-IV category.

2. Group Therapy Allocation

To account more accurately for resource utilization and cost and to equalize the payment incentives across therapy modes, we allocated group therapy time beginning in FY 2012. We anticipated that this policy would result in some change to the type of therapy mode (that is, individual, concurrent, or group) used for SNF residents. As noted in the section above, we have not observed any significant difference in patient case mix. However, as illustrated in Table 20, providers have significantly changed the mode of therapy since our STRIVE study (2006-2007).

Table 20—Mode of Therapy Provision Back to Top
STRIVE (percent) FY 2011 (percent) FY 2012 (percent)
Individual 74 91.8 99.5
Concurrent 25 0.8 0.4
Group <1 7.4 0.1

In the FY 2010 final rule (74 FR 40288, 40315-40319), we established a policy that, beginning in FY 2011, we would allocate concurrent therapy without the allocation of group therapy and, as a result, providers shifted from concurrent therapy to group therapy. In the FY 2012 SNF PPS final rule (76 FR 48486, 48511-48517), we established a policy that would allocate group therapy, and data from FY 2012 indicate that facilities are providing individual therapy almost exclusively.

3. MDS 3.0 Changes

In the FY 2012 SNF PPS final rule, we introduced a new assessment called the COT OMRA to capture more accurately the therapy services provided to SNF residents. Effective for services provided on or after October 1, 2011, SNFs are required to complete a COT OMRA for patients classified into a RUG-IV therapy category (and for patients receiving therapy services who are classified into a nursing RUG because of index maximization), whenever the intensity of therapy changes to such a degree that it would no longer reflect the RUG-IV classification and payment assigned for the patient based on the most recent assessment used for Medicare payment (76 FR 48525). An evaluation of the necessity for a COT OMRA must be completed at the end of each COT observation period, which is a successive 7-day window beginning on the day following the ARD set for the most recent scheduled or unscheduled PPS assessment (or beginning the day therapy resumes in cases where an EOT-R OMRA is completed), and ending every seven calendar days thereafter. In cases where the resident's therapy has changed to such a degree that it is no longer consistent with the resident's current RUG-IV classification, then the SNF must complete a COT OMRA to reclassify the resident into the appropriate RUG-IV category. The new RUG-IV group resulting from the COT OMRA is billed starting the first day of the 7-day COT observation period for which the COT OMRA was completed and remains at this level until a new assessment is done that changes the patient's RUG-IV classification. Table 21 shows the distribution of all MDS assessment types as a percentage of all MDS assessments.

Table 21—Distribution of MDS Assessment Types Back to Top
FY 2011 (percent) FY 2012 (percent)
Scheduled PPS assessment 95 84
Start-of-Therapy (SOT) OMRA 2 2
End-of-Therapy (EOT) OMRA (w/o Resumption) 3 3
Combined SOT/EOT OMRA 0 0
End-of-Therapy OMRA (w/Resumption) (EOT-R OMRA) N/A 0
Combined SOT/EOT-R OMRA N/A 0
Change-of-Therapy (COT) OMRA N/A 11

Prior to the implementation of the COT OMRA, scheduled PPS assessments comprised the vast majority of completed assessments. With the implementation of the COT OMRA for FY 2012, scheduled PPS assessments still comprise the vast majority of completed MDS assessments, though the COT OMRA is the most frequently completed OMRA.

4. Conclusion

Information related to our monitoring activities is posted on the SNF PPS Web site at http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/Downloads/SNF_Monitoring.zip. Based on the data reviewed thus far, we have found no evidence of the possible negative impacts on SNF providers cited in comments in the FY 2012 final rule (see 76 FR 48497-98, 48537), particularly references to a potential “double hit” from the combined impact of the recalibration of the FY 2011 SNF parity adjustment and the FY 2012 policy changes (for example, allocation of group therapy time and introduction of the COT OMRA). As noted in the data provided in this section, overall case mix has not been affected significantly, which suggests that the aforementioned changes, while ensuring more accurate payment, have been absorbed into facility practices in such a manner that facilities continue to maintain historical trends in terms of patient case mix. Therefore, while we will continue our SNF monitoring efforts, we will post information to the aforementioned Web site only as appropriate.

C. Ensuring Accuracy in Grouping to Rehabilitation RUG-IV Categories

As noted in section III.C of this proposed rule, under section 1888(e)(4)(G)(i) of the Act, the federal rate incorporates an adjustment to account for facility case mix, using a classification system that accounts for the relative resource utilization of different patient types. As part of the Nursing Home Case-Mix and Quality demonstration project, Version III of the Resource Utilization Groups (RUG-III) case-mix classification system was developed to capture resource use of nursing home patients and to provide an improved method of tracking the quality of their care. In 1998, the first version of RUG-III was a 44-group model for classifying SNF patients into homogeneous groups according to their clinical characteristics and the amount and type of resources they use as measured by the Resident Assessment Instrument, the Minimum Data Set (MDS). A detailed description of the RUG-III groups appears in the interim final rule with comment period from May 12, 1998 (63 FR 26262-26263). The RUG-III groups were the basis for the case mix indexes used to establish equitable prospective payment levels for patients with different service use.

In FY 2006, the RUG-III classification system was refined to include 53 groups for case-mix classification that continued to be based on patient data collected on the MDS 2.0. This reflected the addition of 9 new RUG groups comprising a new Extensive Services plus Rehabilitation payment category, to account for the higher cost of beneficiaries requiring both rehabilitation and certain high-intensity medical services. A detailed explanation of the RUG-III refinement appears in the FY 2006 proposed rule (70 FR 29076-29079, May 19, 2005).

In FY 2011, the RUG-IV classification system was implemented and included 66 groups for case-mix classification based on patient data collected on the newest version of the Resident Assessment Instrument, MDS 3.0. A detailed explanation of the RUG-IV model appears in the FY 2010 proposed rule (74 FR 22220-22238, May 12, 2009).

In the May 12, 1998 interim final rule with comment period (63 FR 26252, 26256), we explained how the RUG-III system was used to place SNF patients into one of 44 patient groups or subcategories used for payment. The RUG category of Medium Rehabilitation (Medium Rehab) was explained in conjunction with the RUG categories of High and Very High Rehabilitation. Among other requirements specific to each category, “all three require at least 5 days per week of skilled rehabilitative therapy, but they are split according to weekly treatment time” (63 FR 26258). To qualify for Medium Rehab, a patient also needs to receive at least 150 minutes of therapy of any combination of the three rehabilitation disciplines: physical therapy, occupational therapy, and speech therapy.

Subsequently, across all iterations of the SNF PPS (including the RUG refinement in FY 2006 and the transition from RUG-III to RUG-IV in FY 2011), the criteria for classification into the Medium Rehab category remained the same. As set forth in the FY 2010 final rule (74 FR 40389), to be classified into the Medium Rehab category under RUG III or RUG IV, the resident must receive “5 days any combination of 3 rehabilitation disciplines.” In order for the SNF resident to qualify for the Medium Rehab or Medium Rehab plus Extensive Services category, he or she must receive five distinct calendar days of therapy within a 7-day time period (and at least 150 minutes of therapy across that time as well). This reflects the SNF level of care requirement under § 409.31(b)(1) that skilled services must be needed and received on a daily basis, and the provision at § 409.34(a)(2) which specifies that the “daily basis” criterion can be met by skilled rehabilitation services that are needed and provided at least 5 days per week. Further, the payment rates for these RUG groups were based on staff time over the requisite number of distinct therapy days. For example, the policy would be implemented correctly if a patient received a total of 150 minutes of therapy in the form of physical therapy on Monday and Wednesday, occupational therapy on Sunday and Tuesday, and speech therapy on Friday. In this example, therapy services are being provided over a separate and distinct 5-day period (Sunday, Monday, Tuesday, Wednesday, and Friday). Similarly, 5 distinct calendar days of therapy are required to classify into the High, Very High, and Ultra High Rehabilitation categories. The amount of therapy provided over the 7-day look-back period is currently recorded on the MDS 3.0 in section O, item O0400A, O0400B, and O0400C.

Medium Rehab and Medium Rehab Plus Extensive Services qualifiers remained the same under the SNF PPS from 1998 until the present; however, the MDS did not contain the appropriate items to permit providers to report the number of distinct calendar days of therapy that a particular resident receives during a given week, inadvertently allowing residents who do not meet the Medium Rehab and Medium Rehab Plus Extensive Services qualifiers (under the intended policy as discussed above) to classify inappropriately into those RUG categories. For example, a resident receives 150 minutes of therapy in the form of physical therapy and occupational therapy on Monday (one session of physical therapy and one session of occupational therapy) and Wednesday (one session of physical therapy and one session of occupational therapy) and speech therapy on Friday. The intent of the Medium Rehab classification criteria is for such a resident not to classify into the Medium Rehab RUG category, since he or she only received therapy on 3 days (Monday, Wednesday, and Friday) during the 7-day look-back period for this PPS assessment. However, the MDS item set only requires the SNF to record the number of days therapy was received by each therapy discipline during that 7-day look-back period, without distinguishing between distinct calendar days. Thus, in the example above, the SNF would record on the MDS: 2 days of physical therapy, 2 days of occupational therapy, and 1 day of speech therapy. Currently, the RUG grouper adds these days together, allowing the resident described above to be classified into the Medium Rehab category even though the resident did not actually receive 5 distinct calendar days of therapy as required by the criteria. This resident would not meet the classification criteria for the Medium Rehab category as they were intended to be applied.

In rare instances, the same issue can occur with the Low Rehabilitation (Low Rehab) and Low Rehab Plus Extensive Services categories, which require rehabilitation services for at least 45 minutes a week with three days of any combination of the three rehabilitation disciplines (and restorative nursing 6 days per week). Similar to the Medium Rehab classification criteria, the intent here, as well, is to require distinct calendar days of therapy during the 7-day look-back period (in this case, 3 distinct calendar days of therapy). For example, this policy would be implemented correctly if a resident received a total of 90 minutes of therapy in the form of physical therapy on Monday and Wednesday, occupational therapy on Wednesday and Friday, and speech therapy on Friday. In this example, therapy services are being provided over 3 distinct calendar days (Monday, Wednesday, and Friday). However, as with the Medium Rehab category, it is possible for certain residents who do not meet the Low Rehab qualifiers under the intended policy to classify inappropriately into the Low Rehab category. For example, if a resident were to receive 90 minutes of therapy in the form of physical therapy and occupational therapy on Monday, and physical therapy and speech therapy on Tuesday, this patient would only have received therapy for 2 distinct days in that 7-day look-back period; however, based on the information currently recorded on the MDS, the patient would still be classified in a Low Rehab RUG.

As explained above, we are clarifying that our classification criteria for the Rehabilitation RUG categories require that the resident receive the requisite number of distinct calendar days of therapy to be classified into the Rehabilitation RUG category. However, the MDS item set currently does not contain an item that permits SNFs to report the total number of distinct calendar days of therapy provided by all rehabilitation disciplines, allowing some residents to be classified into Rehabilitation RUG categories when they do not actually meet our classification criteria. To permit facilities to report the number of distinct calendar days that a resident receives therapy, and to permit implementation of our Rehabilitation RUG classification criteria as intended, we propose to add item O0420 to the MDS Item Set, Distinct Calendar Days of Therapy. Effective October 1, 2013, facilities would be required to record under this item the number of distinct calendar days of therapy provided by all the rehabilitation disciplines over the 7-day look-back period for the current assessment, which would be used to classify the resident into the correct Rehabilitation RUG category. We invite comments on our proposal to add this item to the MDS Item Set so that we may properly implement our Rehabilitation RUG classification criteria based on the number of distinct calendar days of therapy a patient received, as described above.

D. SNF Therapy Research Project

Currently, the therapy payment rate component of the SNF PPS is based solely on the amount of therapy provided to a patient during the 7-day look-back period, regardless of the specific patient characteristics. The amount of therapy a patient receives is used to classify the resident into a RUG category, which then determines the per diem payment for that resident. CMS has contracted with Acumen, LLC and the Brookings Institution to identify potential alternatives to the existing methodology used to pay for therapy services received under the SNF PPS.

As an initial step, the project will review past research studies and policy issues related to SNF PPS therapy payment and options for improving or replacing the current system of paying for SNF therapy services received. We welcome comments and ideas on the existing methodology used to pay for therapy services under the SNF PPS. Comments may be included as part of comments on this proposed rule. We are also soliciting comments outside the comment period and these comments should be sent via email to SNFTherapyPayments@cms.hhs.gov. We will also regularly update the public on the progress of this project on the project Web site at http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/therapyresearch.html.

VI. Provisions of the Proposed Rule and Technical Correction Back to Top

As discussed in section III. of this proposed rule, this proposed rule would update the payment rates under the SNF PPS for FY 2014 as required by section 1888(e)(4)(E)(ii). Also, as discussed in section III.B.3. of this proposed rule, we propose that when the forecast error, rounded to one significant digit, is 0.5 percentage point, we would calculate the forecast error to 2 significant digits in order to determine whether the forecast error threshold has been exceeded. Further, as discussed in section III.C. of this proposed rule, we propose that upon the conversion to ICD-10-CM effective October 1, 2014, we would use the ICD-10-CM code B20 (in place of the ICD-9-CM code 042) to identify those residents for whom it is appropriate to apply the AIDS add-on established under section 511 of the MMA. In addition, as discussed in section III.D. of this proposed rule, to allow for sufficient time to assess the February 28, 2013 OMB changes to the statistical area delineations and their ramifications, we intend to propose changes to the wage index based on the newest CBSA changes in the FY 2015 SNF PPS proposed rule. Thus, we would continue to use the previous OMB definitions (that is, those used for the FY 2013 SNF PPS update notice) for the FY 2014 SNF PPS wage index.

As discussed previously in section V.A of this proposed rule, we propose to revise and rebase the SNF market basket index to reflect a base year of FY 2010, and to use this revised and rebased market basket to determine the SNF market basket percentage increase for 2014. In addition, we propose to revise the labor-related share to reflect the relative importance of the labor-related cost weights in the proposed FY 2010-based SNF market basket. Also, as discussed in section V.C. of this proposed rule, to help ensure accuracy in grouping to the rehabilitation RUG categories, we propose to add item O0420 to the MDS Item Set, which would require facilities to record the number of distinct calendar days of therapy provided by all the rehabilitation disciplines over the 7-day look-back period for the current assessment.

In addition, as discussed earlier in this proposed rule, we are proposing to adopt an approach already being followed by other Medicare payment systems, under which the lengthy wage index tables that are currently published in the Federal Register as part of the annual SNF PPS rulemaking, would instead be made available exclusively through the Internet on the CMS Web site at http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/WageIndex.html. To adopt this approach, we propose to revise § 413.345. Currently, § 413.345 states that CMS publishes the wage index in the Federal Register. We propose to revise this language, consistent with the language of the corresponding statutory authority at section 1888(e)(4)(H)(iii), to state that CMS publishes in the Federal Register“the factors to be applied in making the area wage adjustment.” Accordingly, while the annual Federal Register publication would continue to include a discussion of the various applicable “factors” applied in making the area wage adjustment (for example, the SNF PPS's use of the hospital wage index exclusive of its occupational mix adjustment), effective October 1, 2013, it would no longer include a listing of the individual wage index values themselves, which would instead be made available exclusively through the Internet on the CMS Web site.

Further, we propose to make a minor technical correction in the regulations text at § 424.11(e)(4), regarding the types of practitioners (in addition to physicians) that can sign the required SNF level of care certification and recertifications. In the calendar year (CY) 2011 Medicare Physician Fee Schedule (MPFS) final rule with comment period (75 FR 73387, 73602, 73626-27), we revised the regulations at § 424.20(e)(2) to implement section 3108 of the Affordable Care Act, which amended section 1814(a)(2) of the Act, by adding physician assistants to the provision authorizing nurse practitioners and clinical nurse specialists to perform this function. However, we inadvertently neglected to make a conforming revision in the regulations text at § 424.11(e)(4), an omission that we now propose to rectify.

VII. Collection of Information Requirements Back to Top

Under the Paperwork Reduction Act of 1995 (PRA), we are required to provide a 60-day notice in the Federal Register and solicit public comments before a collection of information requirement is submitted to the Office of Management and Budget (OMB) for review and approval. In order to evaluate fairly whether an information collection should be approved by OMB, section 3506(c)(2)(A) of the PRA requires that we solicit comments 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 estimate of the information collection burden.
  • The quality, utility, and clarity of the information to be collected.
  • Recommendations to minimize the information collection burden on the affected public, including automated collection techniques.

We are soliciting public comment on each of the section 3506(c)(2)(A)-required issues for the following information collection requirements (ICRs):

ICRs Regarding Nursing Home and Swing Bed PPS Item Sets

Under sections 4204(b) and 4214(d) of the Omnibus Budget Reconciliation Act of 1987 (OBRA 1987, 100 enacted on December 22, 1987), the submission and retention of resident assessment data for purposes of carrying out OBRA 1987 are not subject to the PRA. While certain data items that are collected under the SNF resident assessment instrument (or MDS 3.0) fall under the OBRA 1987 exemption, MDS 3.0's PPS-related item sets are outside the scope of OBRA 1987 and require PRA consideration.

As discussed in section V.C. of the preamble, this rule proposes to add PPS-related Item O0420 to the MDS 3.0 form to capture the number of distinct calendar days a SNF resident has received therapy in a seven-day look-back period. The Item would be added to allow the RUG-IV grouper software to calculate more accurately the number of therapy days a SNF resident has received in order to place him or her into the correct RUG-IV payment group. The Item would not be added as the result of any change in statute or policy; rather, it would be added to ensure that our existing Rehabilitation RUG classification policies are properly implemented as intended.

While we are proposing to add Item O0420 to the MDS 3.0 form, we do not believe this action will cause any measurable adjustments to our burden estimates. Consequently, we are not revising the burden estimates that have been approved under OCN 0938-1140 (CMS-R-250) for the Nursing Home and Swing Bed PPS Item Sets.

Submission of PRA-Related Comments

We have submitted a copy of this proposed rule to OMB for its review of the rule's information collection and recordkeeping requirements. These 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 paperwork collection referenced above, access CMS' Web site at http://www.cms.hhs.gov/PaperworkReductionActof1995, or email your request, including your address, phone number, OMB number, and CMS document identifier, to Paperwork@cms.hhs.gov, or call the Reports Clearance Office on (410) 786-1326.

We invite public comments on this proposed information collection and recordkeeping requirement. If you comment on this proposed information collection and recordkeeping requirement, please do either of the following:

1. Submit your comments electronically as specified in the ADDRESSES section of this proposed rule; or

2. Submit your comments to the Office of Information and Regulatory Affairs, Office of Management and Budget, Attention: CMS Desk Officer, (CMS-1446-P) Fax: (202) 395-6974; or Email: OIRA_submission@omb.eop.gov.

VIII. Response to Comments Back to Top

Because of the large number of public comments we normally receive on Federal Register documents, we are not able to acknowledge or respond to them individually. We will consider all comments we receive by the date and time specified in the DATES section of this preamble, and when we proceed with a subsequent document, we will respond to the comments in the preamble to that document.

IX. Economic Analyses Back to Top

A. Regulatory Impact Analysis

1. Introduction

We have examined the impacts of this proposed 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, 96), section 1102(b) of the Act, section 202 of the Unfunded Mandates Reform Act of 1995 (UMRA, 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). Executive Order 13563 emphasizes the importance of quantifying both costs and benefits, of reducing costs, of harmonizing rules, and of promoting flexibility. This rule has been designated an economically significant rule, under section 3(f)(1) of Executive Order 12866. Accordingly, we have prepared a regulatory impact analysis (RIA) as further discussed below. Also, the rule has been reviewed by OMB.

2. Statement of Need

This proposed rule would update the SNF prospective payment rates for FY 2014 as required under section 1888(e)(4)(E) of the Act. It also responds to section 1888(e)(4)(H) of the Act, which requires the Secretary to “provide for publication in the Federal Register” before the August 1 that precedes the start of each fiscal year, of the unadjusted federal per diem rates, the case-mix classification system, and the factors to be applied in making the area wage adjustment. As these statutory provisions prescribe a detailed methodology for calculating and disseminating payment rates under the SNF PPS, we do not have the discretion to adopt an alternative approach.

3. Overall Impacts

This proposed rule sets forth proposed updates of the SNF PPS rates contained in the update notice for FY 2013 (77 FR 46214). Based on the above, we estimate that the aggregate impact would be an increase of $500 million in payments to SNFs, resulting from the SNF market basket update to the payment rates, as adjusted by the MFP adjustment and forecast error correction. The impact analysis of this proposed rule represents the projected effects of the changes in the SNF PPS from FY 2013 to FY 2014. Although the best data available are utilized, there is no attempt to predict behavioral responses to these changes, or to make adjustments for future changes in such variables as days or case-mix.

Certain events may occur to limit the scope or accuracy of our impact analysis, as this analysis is future-oriented and, thus, very susceptible to forecasting errors due to certain events that may occur within the assessed impact time period. Some examples of possible events may include newly-legislated general Medicare program funding changes by the Congress, or changes specifically related to SNFs. In addition, changes to the Medicare program may continue to be made as a result of previously-enacted legislation, or new statutory provisions. Although these changes may not be specific to the SNF PPS, the nature of the Medicare program is such that the changes may interact and, thus, the complexity of the interaction of these changes could make it difficult to predict accurately the full scope of the impact upon SNFs.

In accordance with sections 1888(e)(4)(E) and 1888(e)(5) of the Act, we update the FY 2013 payment rates by a factor equal to the market basket index percentage change adjusted by the FY 2012 forecast error adjustment (if applicable) and the MFP adjustment to determine the payment rates for FY 2014. As discussed previously, for FY 2012 and each subsequent FY, as required by section 1888(e)(5)(B) of the Act as amended by section 3401(b) of the Affordable Care Act, the market basket percentage is reduced by the MFP adjustment. The special AIDS add-on established by section 511 of the MMA remains in effect until “. . . such date as the Secretary certifies that there is an appropriate adjustment in the case mix. . . .” We have not provided a separate impact analysis for the MMA provision. Our latest estimates indicate that there are fewer than 4,100 beneficiaries who qualify for the add-on payment for residents with AIDS. The impact to Medicare is included in the “total” column of Table 22. In updating the SNF rates for FY 2014, we made a number of standard annual revisions and clarifications mentioned elsewhere in this proposed rule (for example, the update to the wage and market basket indexes used for adjusting the federal rates).

The annual update set forth in this proposed rule applies to SNF payments in FY 2014. Accordingly, the analysis that follows only describes the impact of this single year. In accordance with the requirements of the Act, we will publish a notice or rule for each subsequent FY that will provide for an update to the SNF payment rates and include an associated impact analysis.

4. Detailed Economic Analysis

The FY 2014 impacts appear in Table 22. Using the most recently available data, in this case FY 2012, we apply the current FY 2013 wage index and labor-related share value to the number of payment days to simulate FY 2013 payments. Then, using the same FY 2012 data, we apply the FY 2014 wage index and labor-related share value to simulate FY 2014 payments. We tabulate the resulting payments according to the classifications in Table 22, e.g. facility type, geographic region, facility ownership, and compare the difference between current and proposed payments to determine the overall impact. The breakdown of the various categories of data in the table follows.

The first column shows the breakdown of all SNFs by urban or rural status, hospital-based or freestanding status, census region, and ownership.

The first row of figures describes the estimated effects of the various changes on all facilities. The next six rows show the effects on facilities split by hospital-based, freestanding, urban, and rural categories. The urban and rural designations are based on the location of the facility under the CBSA designation. The next nineteen rows show the effects on facilities by urban versus rural status by census region. The last three rows show the effects on facilities by ownership (that is, government, profit, and non-profit status).

The second column in the table shows the number of facilities in the impact database.

The third column of the table shows the effect of the annual update to the wage index. This represents the effect of using the most recent wage data available. The total impact of this change is zero percent; however, there are distributional effects of the change.

The fourth column shows the effect of all of the changes on the FY 2014 payments. The update of 1.4 percent (consisting of the market basket increase of 2.3 percentage points, reduced by the 0.5 percentage point forecast error correction and further reduced by the 0.4 percentage point MFP adjustment) is constant for all providers and, though not shown individually, is included in the total column. It is projected that aggregate payments will increase by 1.4 percent, assuming facilities do not change their care delivery and billing practices in response.

As illustrated in Table 22, the combined effects of all of the changes vary by specific types of providers and by location. Though all facilities would experience payment increases, the projected impact on providers for FY 2014 varies due to the impact of the wage index update. For example, due to changes from updating the wage index, providers in the rural Pacific region would experience a 2.5 percent increase in FY 2014 total payments and providers in the urban East South Central region would experience a 0.7 percent increase in FY 2014 total payments.

Table 22—RUG-IV Projected Impact to the SNF PPS for FY 2014 Back to Top
Number of facilities FY 2014 Update wage data (percent) Total FY 2014 change (percent)
Note: The Total column includes the 2.3 percent market basket increase, reduced by the 0.5 percentage point forecast error correction and further reduced by the 0.4 percentage point MFP adjustment. Additionally, we found no SNFs in rural outlying areas.
Group:      
Total 15,376 0.0 1.4
Urban 10,578 0.1 1.5
Rural 4,798 −0.3 1.1
Hospital based urban 757 0.2 1.6
Freestanding urban 9,821 0.1 1.5
Hospital based rural 402 −0.3 1.1
Freestanding rural 4,396 −0.3 1.1
Urban by region:      
New England 804 0.6 2.0
Middle Atlantic 1,452 0.9 2.3
South Atlantic 1,740 −0.5 0.8
East North Central 2,048 −0.3 1.1
East South Central 525 −0.7 0.7
West North Central 868 −0.6 0.8
West South Central 1,240 −0.2 1.2
Mountain 490 0.2 1.6
Pacific 1,405 0.8 2.2
Outlying 6 0.1 1.5
Rural by region:      
New England 153 0.4 1.8
Middle Atlantic 262 −0.2 1.2
South Atlantic 608 −0.5 0.9
East North Central 928 −0.8 0.6
East South Central 551 −0.7 0.7
West North Central 1,114 0.6 2.0
West South Central 813 −0.8 0.6
Mountain 246 0.3 1.7
Pacific 123 1.0 2.5
Ownership:      
Government 830 0.2 1.6
Profit 10,722 0.0 1.4
Non-profit 3,824 0.0 1.4

5. Alternatives Considered

As described above, we estimate that the aggregate impact for FY 2014 would be an increase of $500 million in payments to SNFs, resulting from the SNF market basket update to the payment rates, as adjusted by the forecast error correction and the MFP adjustment.

Section 1888(e) of the Act establishes the SNF PPS for the payment of Medicare SNF services for cost reporting periods beginning on or after July 1, 1998. This section of the statute prescribes a detailed formula for calculating payment rates under the SNF PPS, and does not provide for the use of any alternative methodology. It specifies that the base year cost data to be used for computing the SNF PPS payment rates must be from FY 1995 (October 1, 1994, through September 30, 1995). In accordance with the statute, we also incorporated a number of elements into the SNF PPS (for example, case-mix classification methodology, a market basket index, a wage index, and the urban and rural distinction used in the development or adjustment of the federal rates). Further, section 1888(e)(4)(H) of the Act specifically requires us to disseminate the payment rates for each new FY through the Federal Register, and to do so before the August 1 that precedes the start of the new FY. Accordingly, we are not pursuing alternatives with respect to the payment methodology as discussed above.

6. Accounting Statement

As required by OMB Circular A-4 (available online at www.whitehouse.gov/sites/default/files/omb/assets/regulatory_matters_pdf/a-4.pdf), in Table 23, we have prepared an accounting statement showing the classification of the expenditures associated with the provisions of this proposed rule. Table 23 provides our best estimate of the possible changes in Medicare payments under the SNF PPS as a result of the policies in this proposed rule, based on the data for 15,376 SNFs in our database. All expenditures are classified as transfers to Medicare providers (that is, SNFs).

Table 23—Accounting Statement: Classification of Estimated Expenditures, From the 2013 SNF PPS Fiscal Year to the 2014 SNF PPS Fiscal Year Back to Top
Category Transfers
* The net increase of $500 million in transfer payments is a result of the MFP-adjusted market basket increase of $500 million.
Annualized Monetized Transfers $500 million.*
From Whom To Whom? Federal Government to SNF Medicare Providers.

7. Conclusion

This proposed rule sets forth updates of the SNF PPS rates contained in the update notice for FY 2013 (77 FR 46214). Based on the above, we estimate the overall estimated payments for SNFs in FY 2014 are projected to increase by $500 million, or 1.4 percent, compared with those in FY 2013. We estimate that in FY 2014 under RUG-IV, SNFs in urban and rural areas would experience, on average, a 1.5 and 1.1 percent increase, respectively, in estimated payments compared with FY 2013. Providers in the rural Pacific region would experience the largest estimated increase in payments of approximately 2.5 percent. Providers in the rural West South Central region would experience the smallest increase in payments of 0.6 percent.

B. Regulatory Flexibility Act Analysis

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, non-profit organizations, and small governmental jurisdictions. Most SNFs and most other providers and suppliers are small entities, either by their non-profit status or by having revenues of $25.5 million or less in any 1 year. For purposes of the RFA, approximately 91 percent of SNFs are considered small businesses according to the Small Business Administration's latest size standards (NAICS 623110), with total revenues of $25.5 million or less in any 1 year. (For details, see the Small Business Administration's Web site at http://www.sba.gov/category/navigation-structure/contracting/contracting-officials/eligibility-size-standards). Individuals and States are not included in the definition of a small entity. In addition, approximately 25 percent of SNFs classified as small entities are non-profit organizations. Finally, the estimated number of small business entities does not distinguish provider establishments that are within a single firm and, therefore, the number of SNFs classified as small entities may be higher than the estimate above.

This proposed rule sets forth updates of the SNF PPS rates contained in the update notice for FY 2013 (77 FR 46214). Based on the above, we estimate that the aggregate impact would be an increase of $500 million in payments to SNFs, resulting from the SNF market basket update to the payment rates, as adjusted by the forecast error correction and the MFP adjustment. While it is projected in Table 22 that all providers would experience a net increase in payments, we note that some individual providers within the same region or group may experience different impacts on payments than others due to the distributional impact of the FY 2014 wage indexes and the degree of Medicare utilization.

Guidance issued by the Department of Health and Human Services on the proper assessment of the impact on small entities in rulemakings, utilizes a cost or revenue impact of 3 to 5 percent as a significance threshold under the RFA. According to MedPAC, Medicare covers approximately 12 percent of total patient days in freestanding facilities and 23 percent of facility revenue (Report to the Congress: Medicare Payment Policy, March 2013, available at http://www.medpac.gov/documents/Mar13_EntireReport.pdf). However, it is worth noting that the distribution of days and payments is highly variable. That is, the majority of SNFs have significantly lower Medicare utilization (Report to the Congress: Medicare Payment Policy, March 2013, available at http://www.medpac.gov/documents/Mar13_EntireReport.pdf). As a result, for most facilities, when all payers are included in the revenue stream, the overall impact on total revenues should be substantially less than those impacts presented in Table 22. As indicated in Table 22, the effect on facilities is projected to be an aggregate positive impact of 1.4 percent. As the overall impact on the industry as a whole, and thus on small entities specifically, is less than the 3 to 5 percent threshold discussed above, the Secretary has determined that this proposed rule would not have a significant impact on a substantial number of small entities.

In addition, section 1102(b) of the 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 603 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. This proposed rule would affect small rural hospitals that (a) furnish SNF services under a swing-bed agreement or (b) have a hospital-based SNF. We anticipate that the impact on small rural hospitals would be similar to the impact on SNF providers overall. Moreover, as noted in the FY 2012 final rule (76 FR 48539), the category of small rural hospitals would be included within the analysis of the impact of this proposed rule on small entities in general. As indicated in Table 22, the effect on facilities is projected to be an aggregate positive impact of 1.4 percent. As the overall impact on the industry as a whole is less than the 3 to 5 percent threshold discussed above, the Secretary has determined that this proposed rule would not have a significant impact on a substantial number of small rural hospitals.

C. Unfunded Mandates Reform Act Analysis

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 2013, that threshold is approximately $141 million. This proposed rule would not impose spending costs on State, local, or tribal governments in the aggregate, or by the private sector, of $141 million.

D. Federalism Analysis

Executive Order 13132 establishes certain requirements that an agency must meet when it promulgates a proposed rule (and subsequent final rule) that impose substantial direct requirement costs on State and local governments, preempts State law, or otherwise has federalism implications. This proposed rule would have no substantial direct effect on State and local governments, preempt State law, or otherwise have federalism implications.

List of Subjects Back to Top

For the reasons set forth in the preamble, the Centers for Medicare & Medicaid Services proposes to amend 42 CFR chapter IV as set forth below:

begin regulatory text

PART 413—PRINCIPLES OF REASONABLE COST REIMBURSEMENT; PAYMENT FOR END-STAGE RENAL DISEASE SERVICES; OPTIONAL PROSPECTIVELY DETERMINED PAYMENT RATES FOR SKILLED NURSING FACILITIES Back to Top

1.The authority citation for part 413 continues to read as follows:

Authority:

Secs. 1102, 1812(d), 1814(b), 1815, 1833(a), (i), and (n), 1861(v), 1871, 1881, 1883, and 1886 of the Social Security Act (42 U.S.C. 1302, 1395d(d), 1395f(b), 1395g, 1395l(a), (i), and (n), 1395x(v), 1395hh, 1395rr, 1395tt, and 1395ww); sec. 124 of Pub. L. 106-133 (113 Stat. 1501A-332) and sec. 3201 of Pub. L. 112-96 (126 Stat. 156).

2.Section 413.345 is revised to read as follows:

§ 413.345 Publication of Federal prospective payment rates.

CMS publishes information pertaining to each update of the Federal payment rates in the Federal Register. This information includes the standardized Federal rates, the resident classification system that provides the basis for case-mix adjustment (including the designation of those specific Resource Utilization Groups under the resident classification system that represent the required SNF level of care, as provided in § 409.30 of this chapter), and the factors to be applied in making the area wage adjustment. This information is published before May 1 for the fiscal year 1998 and before August 1 for the fiscal years 1999 and after.

PART 424—CONDITIONS FOR MEDICARE PAYMENT Back to Top

3.The authority citation for part 424 continues to read as follows:

Authority:

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

4.Section 424.11 is amended by revising paragraph (e)(4) to read as follows:

§ 424.11 General procedures.

* * * * *

(e) * * *

(4) A nurse practitioner or clinical nurse specialist as defined in paragraph (e)(5) or (e)(6) of this section, or a physician assistant as defined in section 1861(aa)(5) of the Act, in the circumstances specified in § 424.20(e).

* * * * *

Authority:

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

end regulatory text

Dated: April 4, 2013.

Marilyn Tavenner,

Acting Administrator, Centers for Medicare & Medicaid Services.

Approved: April 25, 2013.

Kathleen Sebelius,

Secretary.

Note:

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

Addendum—FY 2014 CBSA Wage Index Tables Back to Top

In this addendum, we provide the wage index tables referred to in the preamble to this proposed rule. Tables A and B display the CBSA-based wage index values for urban and rural providers. As noted previously in this proposed rule, we are currently proposing to take an approach already being followed by other Medicare payment systems, whereby for SNF PPS rules and notices published on or after October 1, 2013, these wage index tables would henceforth be made available exclusively through the Internet on the CMS Web site rather than being published in the Federal Register as part of the annual SNF PPS rulemaking.

Table A—FY 2014 Wage Index for Urban Areas Based on CBSA Labor Market Areas Back to Top
CBSA Code Urban area (constituent counties) Wage index
1At this time, there are no hospitals located in this urban area on which to base a wage index.
10180 Abilene, TX 0.8260
Callahan County, TX  
Jones County, TX  
Taylor County, TX  
10380 Aguadilla-Isabela-San Sebastián, PR 0.3662
Aguada Municipio, PR  
Aguadilla Municipio, PR  
Añasco Municipio, PR  
Isabela Municipio, PR  
Lares Municipio, PR  
Moca Municipio, PR  
Rincón Municipio, PR  
San Sebastián Municipio, PR  
10420 Akron, OH 0.8485
Portage County, OH  
Summit County, OH  
10500 Albany, GA 0.8750
Baker County, GA  
Dougherty County, GA  
Lee County, GA  
Terrell County, GA  
Worth County, GA  
10580 Albany-Schenectady-Troy, NY 0.8636
Albany County, NY  
Rensselaer County, NY  
Saratoga County, NY  
Schenectady County, NY  
Schoharie County, NY  
10740 Albuquerque, NM 0.9704
Bernalillo County, NM  
Sandoval County, NM  
Torrance County, NM  
Valencia County, NM  
10780 Alexandria, LA 0.7821
Grant Parish, LA  
Rapides Parish, LA  
10900 Allentown-Bethlehem-Easton, PA-NJ 0.9208
Warren County, NJ  
Carbon County, PA  
Lehigh County, PA  
Northampton County, PA  
11020 Altoona, PA 0.9140
Blair County, PA  
11100 Amarillo, TX 0.8993
Armstrong County, TX  
Carson County, TX  
Potter County, TX  
Randall County, TX  
11180 Ames, IA 0.9465
Story County, IA  
11260 Anchorage, AK 1.2259
Anchorage Municipality, AK  
Matanuska-Susitna Borough, AK  
11300 Anderson, IN 0.9694
Madison County, IN  
11340 Anderson, SC 0.8803
Anderson County, SC  
11460 Arbor, MI 1.0125
Washtenaw County, MI  
11500 Anniston-Oxford, AL 0.7369
Calhoun County, AL  
11540 Appleton, WI 0.9485
Calumet County, WI  
Outagamie County, WI  
11700 Asheville, NC 0.8508
Buncombe County, NC  
Haywood County, NC  
Henderson County, NC  
Madison County, NC  
12020 Athens-Clarke County, GA 0.9284
Clarke County, GA  
Madison County, GA  
Oconee County, GA  
Oglethorpe County, GA  
12060 Atlanta-Sandy Springs-Marietta, GA 0.9465
Barrow County, GA  
Bartow County, GA  
Butts County, GA  
Carroll County, GA  
Cherokee County, GA  
Clayton County, GA  
Cobb County, GA  
Coweta County, GA  
Dawson County, GA  
DeKalb County, GA  
Douglas County, GA  
Fayette County, GA  
Forsyth County, GA  
Fulton County, GA  
Gwinnett County, GA  
Haralson County, GA  
Heard County, GA  
Henry County, GA  
Jasper County, GA  
Lamar County, GA  
Meriwether County, GA  
Newton County, GA  
Paulding County, GA  
Pickens County, GA  
Pike County, GA  
Rockdale County, GA  
Spalding County, GA  
Walton County, GA  
12100 Atlantic City-Hammonton, NJ 1.2310
Atlantic County, NJ  
12220 Auburn-Opelika, AL 0.7802
Lee County, AL  
12260 Augusta-Richmond County, GA-SC 0.9189
Burke County, GA  
Columbia County, GA  
McDuffie County, GA  
Richmond County, GA  
Aiken County, SC  
Edgefield County, SC  
12420 Austin-Round Rock, TX 0.9616
Bastrop County, TX  
Caldwell County, TX  
Hays County, TX  
Travis County, TX  
Williamson County, TX  
12540 Bakersfield, CA 1.1730
Kern County, CA  
12580 Baltimore-Towson, MD 0.9916
Anne Arundel County, MD  
Baltimore County, MD  
Carroll County, MD  
Harford County, MD  
Howard County, MD  
Queen Anne's County, MD  
Baltimore City, MD  
12620 Bangor, ME 0.9751
Penobscot County, ME  
12700 Barnstable Town, MA 1.3062
Barnstable County, MA  
12940 Baton Rouge, LA 0.8050
Ascension Parish, LA  
East Baton Rouge Parish, LA  
East Feliciana Parish, LA  
Iberville Parish, LA  
Livingston Parish, LA  
Pointe Coupee Parish, LA  
St. Helena Parish, LA  
West Baton Rouge Parish, LA  
West Feliciana Parish, LA  
12980 Battle Creek, MI 0.9763
Calhoun County, MI  
13020 Bay City, MI 0.9526
Bay County, MI  
13140 Beaumont-Port Arthur, TX 0.8634
Hardin County, TX  
Jefferson County, TX  
Orange County, TX  
13380 Bellingham, WA 1.1940
Whatcom County, WA  
13460 Bend, OR 1.1857
Deschutes County, OR  
13644 Bethesda-Frederick-Gaithersburg, MD 1.0348
Frederick County, MD  
Montgomery County, MD  
13740 Billings, MT 0.8727
Carbon County, MT  
Yellowstone County, MT  
13780 Binghamton, NY 0.7863
Broome County, NY  
Tioga County, NY  
13820 Birmingham-Hoover, AL 0.8395
Bibb County, AL  
Blount County, AL  
Chilton County, AL  
Jefferson County, AL  
St. Clair County, AL  
Shelby County, AL  
Walker County, AL  
13900 Bismarck, ND 0.7312
Burleigh County, ND  
Morton County, ND  
13980 Blacksburg-Christiansburg-Radford, VA 0.8354
Giles County, VA  
Montgomery County, VA  
Pulaski County, VA  
Radford City, VA  
14020 Bloomington, IN 0.9343
Greene County, IN  
Monroe County, IN  
Owen County, IN  
14060 Bloomington-Normal, IL 0.9349
McLean County, IL  
14260 Boise City-Nampa, ID 0.9298
Ada County, ID  
Boise County, ID  
Canyon County, ID  
Gem County, ID  
Owyhee County, ID  
14484 Boston-Quincy, MA 1.2505
Norfolk County, MA  
Plymouth County, MA  
Suffolk County, MA  
14500 Boulder, CO 0.9891
Boulder County, CO  
14540 Bowling Green, KY 0.8314
Edmonson County, KY  
Warren County, KY  
14740 Bremerton-Silverdale, WA 1.0311
Kitsap County, WA  
14860 Bridgeport-Stamford-Norwalk, CT 1.3287
Fairfield County, CT  
15180 Brownsville-Harlingen, TX 0.8213
Cameron County, TX  
15260 Brunswick, GA 0.7716
Brantley County, GA  
Glynn County, GA  
McIntosh County, GA  
15380 Buffalo-Niagara Falls, NY 1.0048
Erie County, NY  
Niagara County, NY  
15500 Burlington, NC 0.8552
Alamance County, NC  
15540 Burlington-South Burlington, VT 1.0173
Chittenden County, VT  
Franklin County, VT  
Grand Isle County, VT  
15764 Cambridge-Newton-Framingham, MA 1.1201
Middlesex County, MA  
15804 Camden, NJ 1.0297
Burlington County, NJ  
Camden County, NJ  
Gloucester County, NJ  
15940 Canton-Massillon, OH 0.8729
Carroll County, OH  
Stark County, OH  
15980 Cape Coral-Fort Myers, FL 0.8720
Lee County, FL  
16020 Cape Girardeau-Jackson, MO-IL 0.9213
Alexander County, IL  
Bollinger County, MO  
Cape Girardeau County, MO  
16180 Carson City, NV 1.0767
Carson City, NV  
16220 Casper, WY 1.0154
Natrona County, WY  
16300 Cedar Rapids, IA 0.9001
Benton County, IA  
Jones County, IA  
Linn County, IA  
16580 Champaign-Urbana, IL 0.9450
Champaign County, IL  
Ford County, IL  
Piatt County, IL  
16620 Charleston, WV 0.8147
Boone County, WV  
Clay County, WV  
Kanawha County, WV  
Lincoln County, WV  
Putnam County, WV  
16700 Charleston-North Charleston-Summerville, SC 0.9013
Berkeley County, SC  
Charleston County, SC  
Dorchester County, SC  
16740 Charlotte-Gastonia-Concord, NC-SC 0.9479
Anson County, NC  
Cabarrus County, NC  
Gaston County, NC  
Mecklenburg County, NC  
Union County, NC  
York County, SC  
16820 Charlottesville, VA 0.8443
Albemarle County, VA  
Fluvanna County, VA  
Greene County, VA  
Nelson County, VA  
Charlottesville City, VA  
16860 Chattanooga, TN-GA 0.8499
Catoosa County, GA  
Dade County, GA  
Walker County, GA  
Hamilton County, TN  
Marion County, TN  
Sequatchie County, TN  
16940 Cheyenne, WY 0.9534
Laramie County, WY  
16974 Chicago-Naperville-Joliet, IL 1.0446
Cook County, IL  
DeKalb County, IL  
DuPage County, IL  
Grundy County, IL  
Kane County, IL  
Kendall County, IL  
McHenry County, IL  
Will County, IL  
17020 Chico, CA 1.1637
Butte County, CA  
17140 Cincinnati-Middletown, OH-KY-IN 0.9382
Dearborn County, IN  
Franklin County, IN  
Ohio County, IN  
Boone County, KY  
Bracken County, KY  
Campbell County, KY  
Gallatin County, KY  
Grant County, KY  
Kenton County, KY  
Pendleton County, KY  
Brown County, OH  
Butler County, OH  
Clermont County, OH  
Hamilton County, OH  
Warren County, OH  
17300 Clarksville, TN-KY 0.7376
Christian County, KY  
Trigg County, KY  
Montgomery County, TN  
Stewart County, TN  
17420 Cleveland, TN 0.7528
Bradley County, TN  
Polk County, TN  
17460 Cleveland-Elyria-Mentor, OH 0.9306
Cuyahoga County, OH  
Geauga County, OH  
Lake County, OH  
Lorain County, OH  
Medina County, OH  
17660 Coeur d'Alene, ID 0.9102
Kootenai County, ID  
17780 College Station-Bryan, TX 0.9537
Brazos County, TX  
Burleson County, TX  
Robertson County, TX  
17820 Colorado Springs, CO 0.9321
El Paso County, CO  
Teller County, CO  
17860 Columbia, MO 0.8231
Boone County, MO  
Howard County, MO  
17900 Columbia, SC 0.8680
Calhoun County, SC  
Fairfield County, SC  
Kershaw County, SC  
Lexington County, SC  
Richland County, SC  
Saluda County, SC  
17980 Columbus, GA-AL 0.7896
Russell County, AL  
Chattahoochee County, GA  
Harris County, GA  
Marion County, GA  
Muscogee County, GA  
18020 Columbus, IN 0.9860
Bartholomew County, IN  
18140 Columbus, OH 0.9700
Delaware County, OH  
Fairfield County, OH  
Franklin County, OH  
Licking County, OH  
Madison County, OH  
Morrow County, OH  
Pickaway County, OH  
Union County, OH  
18580 Corpus Christi, TX 0.8469
Aransas County, TX  
Nueces County, TX  
San Patricio County, TX  
18700 Corvallis, OR 1.0641
Benton County, OR  
18880 Crestview-Fort Walton Beach-Destin, FL 0.8948
Okaloosa County, FL  
19060 Cumberland, MD-WV 0.8088
Allegany County, MD  
Mineral County, WV  
19124 Dallas-Plano-Irving, TX 0.9872
Collin County, TX  
Dallas County, TX  
Delta County, TX  
Denton County, TX  
Ellis County, TX  
Hunt County, TX  
Kaufman County, TX  
Rockwall County, TX  
19140 Dalton, GA 0.8662
Murray County, GA  
Whitfield County, GA  
19180 Danville, IL 0.9500
Vermilion County, IL  
19260 Danville, VA 0.7921
Pittsylvania County, VA  
Danville City, VA  
19340 Davenport-Moline-Rock Island, IA-IL 0.9345
Henry County, IL  
Mercer County, IL  
Rock Island County, IL  
Scott County, IA  
19380 Dayton, OH 0.8941
Greene County, OH  
Miami County, OH  
Montgomery County, OH  
Preble County, OH  
19460 Decatur, AL 0.7195
Lawrence County, AL  
Morgan County, AL  
19500 Decatur, IL 0.7946
Macon County, IL  
19660 Deltona-Daytona Beach-Ormond Beach, FL 0.8596
Volusia County, FL  
19740 Denver-Aurora-Broomfield, CO 1.0461
Adams County, CO  
Arapahoe County, CO  
Broomfield County, CO  
Clear Creek County, CO  
Denver County, CO  
Douglas County, CO  
Elbert County, CO  
Gilpin County, CO  
Jefferson County, CO  
Park County, CO  
19780 Des Moines-West Des Moines, IA 0.9433
Dallas County, IA  
Guthrie County, IA  
Madison County, IA  
Polk County, IA  
Warren County, IA  
19804 Detroit-Livonia-Dearborn, MI 0.9256
Wayne County, MI  
20020 Dothan, AL 0.7136
Geneva County, AL  
Henry County, AL  
Houston County, AL  
20100 Dover, DE 0.9981
Kent County, DE  
20220 Dubuque, IA 0.8828
Dubuque County, IA  
20260 Duluth, MN-WI 0.9351
Carlton County, MN  
St. Louis County, MN  
Douglas County, WI  
20500 Durham-Chapel Hill, NC 0.9707
Chatham County, NC  
Durham County, NC  
Orange County, NC  
Person County, NC  
20740 Eau Claire, WI 1.0174
Chippewa County, WI  
Eau Claire County, WI  
20764 Edison-New Brunswick, NJ 1.0956
Middlesex County, NJ  
Monmouth County, NJ  
Ocean County, NJ  
Somerset County, NJ  
20940 El Centro, CA 0.8885
Imperial County, CA  
21060 Elizabethtown, KY 0.7928
Hardin County, KY  
Larue County, KY  
21140 Elkhart-Goshen, IN 0.9369
Elkhart County, IN  
21300 Elmira, NY 0.8396
Chemung County, NY  
21340 El Paso, TX 0.8441
El Paso County, TX  
21500 Erie, PA 0.7973
Erie County, PA  
21660 Eugene-Springfield, OR 1.1773
Lane County, OR  
21780 Evansville, IN-KY 0.8367
Gibson County, IN  
Posey County, IN  
Vanderburgh County, IN  
Warrick County, IN  
Henderson County, KY  
Webster County, KY  
21820 Fairbanks, AK 1.1043
Fairbanks North Star Borough, AK  
21940 Fajardo, PR 0.3744
Ceiba Municipio, PR  
Fajardo Municipio, PR  
Luquillo Municipio, PR  
22020 Fargo, ND-MN 0.7835
Cass County, ND  
Clay County, MN  
22140 Farmington, NM 0.9776
San Juan County, NM  
22180 Fayetteville, NC 0.8460
Cumberland County, NC  
Hoke County, NC  
22220 Fayetteville-Springdale-Rogers, AR-MO 0.8993
Benton County, AR  
Madison County, AR  
Washington County, AR  
McDonald County, MO  
22380 Flagstaff, AZ 1.2840
Coconino County, AZ  
22420 Flint, MI 1.1303
Genesee County, MI  
22500 Florence, SC 0.7968
Darlington County, SC  
Florence County, SC  
22520 Florence-Muscle Shoals, AL 0.7553
Colbert County, AL  
Lauderdale County, AL  
22540 Fond du Lac, WI 0.9517
Fond du Lac County, WI  
22660 Fort Collins-Loveland, CO 0.9743
Larimer County, CO  
22744 Fort Lauderdale-Pompano Beach-Deerfield Beach, FL 1.0422
Broward County, FL  
22900 Fort Smith, AR-OK 0.7588
Crawford County, AR  
Franklin County, AR  
Sebastian County, AR  
Le Flore County, OK  
Sequoyah County, OK  
23060 Fort Wayne, IN 0.9048
Allen County, IN  
Wells County, IN  
Whitley County, IN  
23104 Fort Worth-Arlington, TX 0.9552
Johnson County, TX  
Parker County, TX  
Tarrant County, TX  
Wise County, TX  
23420 Fresno, CA 1.1817
Fresno County, CA  
23460 Gadsden, AL 0.8017
Etowah County, AL  
23540 Gainesville, FL 0.9751
Alachua County, FL  
Gilchrist County, FL  
23580 Gainesville, GA 0.9292
Hall County, GA  
23844 Gary, IN 0.9440
Jasper County, IN  
Lake County, IN  
Newton County, IN  
Porter County, IN  
24020 Glens Falls, NY 0.8402
Warren County, NY  
Washington County, NY  
24140 Goldsboro, NC 0.8316
Wayne County, NC  
24220 Grand Forks, ND-MN 0.7321
Polk County, MN  
Grand Forks County, ND  
24300 Grand Junction, CO 0.9347
Mesa County, CO  
24340 Grand Rapids-Wyoming, MI 0.9129
Barry County, MI  
Ionia County, MI  
Kent County, MI  
Newaygo County, MI  
24500 Great Falls, MT 0.9274
Cascade County, MT  
24540 Greeley, CO 0.9694
Weld County, CO  
24580 Green Bay, WI 0.9627
Brown County, WI  
Kewaunee County, WI  
Oconto County, WI  
24660 Greensboro-High Point, NC 0.8288
Guilford County, NC  
Randolph County, NC  
Rockingham County, NC  
24780 Greenville, NC 0.9382
Greene County, NC  
Pitt County, NC  
24860 Greenville-Mauldin-Easley, SC 0.9611
Greenville County, SC  
Laurens County, SC  
Pickens County, SC  
25020 Guayama, PR 0.3723
Arroyo Municipio, PR  
Guayama Municipio, PR  
Patillas Municipio, PR  
25060 Gulfport-Biloxi, MS 0.8610
Hancock County, MS  
Harrison County, MS  
Stone County, MS  
25180 Hagerstown-Martinsburg, MD-WV 0.9273
Washington County, MD  
Berkeley County, WV  
Morgan County, WV  
25260 Hanford-Corcoran, CA 1.1171
Kings County, CA  
25420 Harrisburg-Carlisle, PA 0.9515
Cumberland County, PA  
Dauphin County, PA  
Perry County, PA  
25500 Harrisonburg, VA 0.9128
Rockingham County, VA  
Harrisonburg City, VA  
25540 Hartford-West Hartford-East Hartford, CT 1.1056
Hartford County, CT  
Middlesex County, CT  
Tolland County, CT  
25620 Hattiesburg, MS 0.7972
Forrest County, MS  
Lamar County, MS  
Perry County, MS  
25860 Hickory-Lenoir-Morganton, NC 0.8383
Alexander County, NC  
Burke County, NC  
Caldwell County, NC  
Catawba County, NC  
25980 Hinesville-Fort Stewart, GA1 0.8602
Liberty County, GA  
Long County, GA  
26100 Holland-Grand Haven, MI 0.8050
Ottawa County, MI  
26180 Honolulu, HI 1.2109
Honolulu County, HI  
26300 Hot Springs, AR 0.8510
Garland County, AR  
26380 Houma-Bayou Cane-Thibodaux, LA 0.7556
Lafourche Parish, LA  
Terrebonne Parish, LA  
26420 Houston-Sugar Land-Baytown, TX 0.9945
Austin County, TX  
Brazoria County, TX  
Chambers County, TX  
Fort Bend County, TX  
Galveston County, TX  
Harris County, TX  
Liberty County, TX  
Montgomery County, TX  
San Jacinto County, TX  
Waller County, TX  
26580 Huntington-Ashland, WV-KY-OH 0.8858
Boyd County, KY  
Greenup County, KY  
Lawrence County, OH  
Cabell County, WV  
Wayne County, WV  
26620 Huntsville, AL 0.8199
Limestone County, AL  
Madison County, AL  
26820 Idaho Falls, ID 0.9351
Bonneville County, ID  
Jefferson County, ID  
26900 Indianapolis-Carmel, IN 1.0151
Boone County, IN  
Brown County, IN  
Hamilton County, IN  
Hancock County, IN  
Hendricks County, IN  
Johnson County, IN  
Marion County, IN  
Morgan County, IN  
Putnam County, IN  
Shelby County, IN  
26980 Iowa City, IA 0.9896
Johnson County, IA  
Washington County, IA  
27060 Ithaca, NY 0.9366
Tompkins County, NY  
27100 Jackson, MI 0.8981
Jackson County, MI  
27140 Jackson, MS 0.8196
Copiah County, MS  
Hinds County, MS  
Madison County, MS  
Rankin County, MS  
Simpson County, MS  
27180 Jackson, TN 0.7720
Chester County, TN  
Madison County, TN  
27260 Jacksonville, FL 0.8987
Baker County, FL  
Clay County, FL  
Duval County, FL  
Nassau County, FL  
St. Johns County, FL  
27340 Jacksonville, NC 0.7894
Onslow County, NC  
27500 Janesville, WI 0.9110
Rock County, WI  
27620 Jefferson City, MO 0.8501
Callaway County, MO  
Cole County, MO  
Moniteau County, MO  
Osage County, MO  
27740 Johnson City, TN 0.7257
Carter County, TN  
Unicoi County, TN  
Washington County, TN  
27780 Johnstown, PA 0.8486
Cambria County, PA  
27860 Jonesboro, AR 0.8017
Craighead County, AR  
Poinsett County, AR  
27900 Joplin, MO 0.8016
Jasper County, MO  
Newton County, MO  
28020 Kalamazoo-Portage, MI 1.0001
Kalamazoo County, MI  
Van Buren County, MI  
28100 Kankakee-Bradley, IL 0.9698
Kankakee County, IL  
28140 Kansas City, MO-KS 0.9487
Franklin County, KS  
Johnson County, KS  
Leavenworth County, KS  
Linn County, KS  
Miami County, KS  
Wyandotte County, KS  
Bates County, MO  
Caldwell County, MO  
Cass County, MO  
Clay County, MO  
Clinton County, MO  
Jackson County, MO  
Lafayette County, MO  
Platte County, MO  
Ray County, MO  
28420 Kennewick-Pasco-Richland, WA 0.9499
Benton County, WA  
Franklin County, WA  
28660 Killeen-Temple-Fort Hood, TX 0.8963
Bell County, TX  
Coryell County, TX  
Lampasas County, TX  
28700 Kingsport-Bristol-Bristol, TN-VA 0.7223
Hawkins County, TN  
Sullivan County, TN  
Bristol City, VA  
Scott County, VA  
Washington County, VA  
28740 Kingston, NY 0.9104
Ulster County, NY  
28940 Knoxville, TN 0.7484
Anderson County, TN  
Blount County, TN  
Knox County, TN  
Loudon County, TN  
Union County, TN  
29020 Kokomo, IN 0.9099
Howard County, IN  
Tipton County, IN  
29100 La Crosse, WI-MN 1.0248
Houston County, MN  
La Crosse County, WI  
29140 Lafayette, IN 0.9996
Benton County, IN  
Carroll County, IN  
Tippecanoe County, IN  
29180 Lafayette, LA 0.8266
Lafayette Parish, LA  
St. Martin Parish, LA  
29340 Lake Charles, LA 0.7798
Calcasieu Parish, LA  
Cameron Parish, LA  
29404 Lake County-Kenosha County, IL-WI 1.0249
Lake County, IL  
Kenosha County, WI  
29420 Lake Havasu City-Kingman, AZ 0.9953
Mohave County, AZ  
29460 Lakeland-Winter Haven, FL 0.8316
Polk County, FL  
29540 Lancaster, PA 0.9704
Lancaster County, PA  
29620 Lansing-East Lansing, MI 1.0663
Clinton County, MI  
Eaton County, MI  
Ingham County, MI  
29700 Laredo, TX 0.7618
Webb County, TX  
29740 Las Cruces, NM 0.9210
Dona Ana County, NM  
29820 Las Vegas-Paradise, NV 1.1682
Clark County, NV  
29940 Lawrence, KS 0.8700
Douglas County, KS  
30020 Lawton, OK 0.7926
Comanche County, OK  
30140 Lebanon, PA 0.8192
Lebanon County, PA  
30300 Lewiston, ID-WA 0.9254
Nez Perce County, ID  
Asotin County, WA  
30340 Lewiston-Auburn, ME 0.9086
Androscoggin County, ME  
30460 Lexington-Fayette, KY 0.8850
Bourbon County, KY  
Clark County, KY  
Fayette County, KY  
Jessamine County, KY  
Scott County, KY  
Woodford County, KY  
30620 Lima, OH 0.9170
Allen County, OH  
30700 Lincoln, NE 0.9505
Lancaster County, NE  
Seward County, NE  
30780 Little Rock-North Little Rock-Conway, AR 0.8661
Faulkner County, AR  
Grant County, AR  
Lonoke County, AR  
Perry County, AR  
Pulaski County, AR  
Saline County, AR  
30860 Logan, UT-ID 0.8791
Franklin County, ID  
Cache County, UT  
30980 Longview, TX 0.8971
Gregg County, TX  
Rusk County, TX  
Upshur County, TX  
31020 Longview, WA 1.0504
Cowlitz County, WA  
31084 Los Angeles-Long Beach-Glendale, CA 1.2315
Los Angeles County, CA  
31140 Louisville-Jefferson County, KY-IN 0.8892
Clark County, IN  
Floyd County, IN  
Harrison County, IN  
Washington County, IN  
Bullitt County, KY  
Henry County, KY  
Meade County, KY  
Nelson County, KY  
Oldham County, KY  
Shelby County, KY  
Spencer County, KY  
Trimble County, KY  
31180 Lubbock, TX 0.8994
Crosby County, TX  
Lubbock County, TX  
31340 Lynchburg, VA 0.8808
Amherst County, VA  
Appomattox County, VA  
Bedford County, VA  
Campbell County, VA  
Bedford City, VA  
Lynchburg City, VA  
31420 Macon, GA 0.8860
Bibb County, GA  
Crawford County, GA  
Jones County, GA  
Monroe County, GA  
Twiggs County, GA  
31460 Madera-Chowchilla, CA 0.8352
Madera County, CA  
31540 Madison, WI 1.1463
Columbia County, WI  
Dane County, WI  
Iowa County, WI  
31700 Manchester-Nashua, NH 1.0099
Hillsborough County, NH  
31740 Manhattan, KS 0.7876
Geary County, KS  
Pottawatomie County, KS  
Riley County, KS  
31860 Mankato-North Mankato, MN 0.9316
Blue Earth County, MN  
Nicollet County, MN  
31900 Mansfield, OH 0.8448
Richland County, OH  
32420 Mayagüez, PR 0.3769
Hormigueros Municipio, PR  
Mayagüez Municipio, PR  
32580 McAllen-Edinburg-Mission, TX 0.8429
Hidalgo County, TX  
32780 Medford, OR 1.0735
Jackson County, OR  
32820 Memphis, TN-MS-AR 0.9075
Crittenden County, AR  
DeSoto County, MS  
Marshall County, MS  
Tate County, MS  
Tunica County, MS  
Fayette County, TN  
Shelby County, TN  
Tipton County, TN  
32900 Merced, CA 1.2788
Merced County, CA  
33124 Miami-Miami Beach-Kendall, FL 0.9912
Miami-Dade County, FL  
33140 Michigan City-La Porte, IN 0.9255
LaPorte County, IN  
33260 Midland, TX 1.0092
Midland County, TX  
33340 Milwaukee-Waukesha-West Allis, WI 0.9868
Milwaukee County, WI  
Ozaukee County, WI  
Washington County, WI  
Waukesha County, WI  
33460 Minneapolis-St. Paul-Bloomington, MN-WI 1.1260
Anoka County, MN  
Carver County, MN  
Chisago County, MN  
Dakota County, MN  
Hennepin County, MN  
Isanti County, MN  
Ramsey County, MN  
Scott County, MN  
Sherburne County, MN  
Washington County, MN  
Wright County, MN  
Pierce County, WI  
St. Croix County, WI  
33540 Missoula, MT 0.9100
Missoula County, MT  
33660 Mobile, AL 0.7475
Mobile County, AL  
33700 Modesto, CA 1.3641
Stanislaus County, CA  
33740 Monroe, LA 0.7550
Ouachita Parish, LA  
Union Parish, LA  
33780 Monroe, MI 0.8755
Monroe County, MI  
33860 Montgomery, AL 0.7507
Autauga County, AL  
Elmore County, AL  
Lowndes County, AL  
Montgomery County, AL  
34060 Morgantown, WV 0.8267
Monongalia County, WV  
Preston County, WV  
34100 Morristown, TN 0.6884
Grainger County, TN  
Hamblen County, TN  
Jefferson County, TN  
34580 Mount Vernon-Anacortes, WA 1.0697
Skagit County, WA  
34620 Muncie, IN 0.8780
Delaware County, IN  
34740 Muskegon-Norton Shores, MI 0.9625
Muskegon County, MI  
34820 Myrtle Beach-North Myrtle Beach-Conway, SC 0.8663
Horry County, SC  
34900 Napa, CA 1.5354
Napa County, CA  
34940 Naples-Marco Island, FL 0.9147
Collier County, FL  
34980 Nashville-Davidson—Murfreesboro-Franklin, TN 0.9174
Cannon County, TN  
Cheatham County, TN  
Davidson County, TN  
Dickson County, TN  
Hickman County, TN  
Macon County, TN  
Robertson County, TN  
Rutherford County, TN  
Smith County, TN  
Sumner County, TN  
Trousdale County, TN  
Williamson County, TN  
Wilson County, TN  
35004 Nassau-Suffolk, NY 1.2764
Nassau County, NY  
Suffolk County, NY  
35084 Newark-Union, NJ-PA 1.1273
Essex County, NJ  
Hunterdon County, NJ  
Morris County, NJ  
Sussex County, NJ  
Union County, NJ  
Pike County, PA  
35300 New Haven-Milford, CT 1.1933
New Haven County, CT  
35380 New Orleans-Metairie-Kenner, LA 0.8789
Jefferson Parish, LA  
Orleans Parish, LA  
Plaquemines Parish, LA  
St. Bernard Parish, LA  
St. Charles Parish, LA  
St. John the Baptist Parish, LA  
St. Tammany Parish, LA  
35644 New York-White Plains-Wayne, NY-NJ 1.3117
Bergen County, NJ  
Hudson County, NJ  
Passaic County, NJ  
Bronx County, NY  
Kings County, NY  
New York County, NY  
Putnam County, NY  
Queens County, NY  
Richmond County, NY  
Rockland County, NY  
Westchester County, NY  
35660 Niles-Benton Harbor, MI 0.8479
Berrien County, MI  
35840 North Port-Bradenton-Sarasota-Venice, FL 0.9468
Manatee County, FL  
Sarasota County, FL  
35980 Norwich-New London, CT 1.1871
New London County, CT  
36084 Oakland-Fremont-Hayward, CA 1.7061
Alameda County, CA  
Contra Costa County, CA  
36100 Ocala, FL 0.8461
Marion County, FL  
36140 Ocean City, NJ 1.0628
Cape May County, NJ  
36220 Odessa, TX 0.9702
Ector County, TX  
36260 Ogden-Clearfield, UT 0.9209
Davis County, UT  
Morgan County, UT  
Weber County, UT  
36420 Oklahoma City, OK 0.8896
Canadian County, OK  
Cleveland County, OK  
Grady County, OK  
Lincoln County, OK  
Logan County, OK  
McClain County, OK  
Oklahoma County, OK  
36500 Olympia, WA 1.1650
Thurston County, WA  
36540 Omaha-Council Bluffs, NE-IA 0.9797
Harrison County, IA  
Mills County, IA  
Pottawattamie County, IA  
Cass County, NE  
Douglas County, NE  
Sarpy County, NE  
Saunders County, NE  
Washington County, NE  
36740 Orlando-Kissimmee, FL 0.9101
Lake County, FL  
Orange County, FL  
Osceola County, FL  
Seminole County, FL  
36780 Oshkosh-Neenah, WI 0.9438
Winnebago County, WI  
36980 Owensboro, KY 0.7823
Daviess County, KY  
Hancock County, KY  
McLean County, KY  
37100 Oxnard-Thousand Oaks-Ventura, CA 1.3132
Ventura County, CA  
37340 Palm Bay-Melbourne-Titusville, FL 0.8707
Brevard County, FL  
37380 Palm Coast, FL 0.8209
Flagler County, FL  
37460 Panama City-Lynn Haven-Panama City Beach, FL 0.7909
Bay County, FL  
37620 Parkersburg-Marietta-Vienna, WV-OH 0.7576
Washington County, OH  
Pleasants County, WV  
Wirt County, WV  
Wood County, WV  
37700 Pascagoula, MS 0.7574
George County, MS  
Jackson County, MS  
37764 Peabody, MA 1.0571
Essex County, MA  
37860 Pensacola-Ferry Pass-Brent, FL 0.7800
Escambia County, FL  
Santa Rosa County, FL  
37900 Peoria, IL 0.8290
Marshall County, IL  
Peoria County, IL  
Stark County, IL  
Tazewell County, IL  
Woodford County, IL  
37964 Philadelphia, PA 1.0926
Bucks County, PA  
Chester County, PA  
Delaware County, PA  
Montgomery County, PA  
Philadelphia County, PA  
38060 Phoenix-Mesa-Scottsdale, AZ 1.0505
Maricopa County, AZ  
Pinal County, AZ  
38220 Pine Bluff, AR 0.8103
Cleveland County, AR  
Jefferson County, AR  
Lincoln County, AR  
38300 Pittsburgh, PA 0.8713
Allegheny County, PA  
Armstrong County, PA  
Beaver County, PA  
Butler County, PA  
Fayette County, PA  
Washington County, PA  
Westmoreland County, PA  
38340 Pittsfield, MA 1.0966
Berkshire County, MA  
38540 Pocatello, ID 0.9795
Bannock County, ID  
Power County, ID  
38660 Ponce, PR 0.4614
Juana Díaz Municipio, PR  
Ponce Municipio, PR  
Villalba Municipio, PR  
38860 Portland-South Portland-Biddeford, ME 1.0023
Cumberland County, ME  
Sagadahoc County, ME  
York County, ME  
38900 Portland-Vancouver-Beaverton, OR-WA 1.1848
Clackamas County, OR  
Columbia County, OR  
Multnomah County, OR  
Washington County, OR  
Yamhill County, OR  
Clark County, WA  
Skamania County, WA  
38940 Port St. Lucie, FL 0.9391
Martin County, FL  
St. Lucie County, FL  
39100 Poughkeepsie-Newburgh-Middletown, NY 1.1593
Dutchess County, NY  
Orange County, NY  
39140 Prescott, AZ 1.0199
Yavapai County, AZ  
39300 Providence-New Bedford-Fall River, RI-MA 1.0579
Bristol County, MA  
Bristol County, RI  
Kent County, RI  
Newport County, RI  
Providence County, RI  
Washington County, RI  
39340 Provo-Orem, UT 0.9501
Juab County, UT  
Utah County, UT  
39380 Pueblo, CO 0.8250
Pueblo County, CO  
39460 Punta Gorda, FL 0.8771
Charlotte County, FL  
39540 Racine, WI 0.9352
Racine County, WI  
39580 Raleigh-Cary, NC 0.9286
Franklin County, NC  
Johnston County, NC  
Wake County, NC  
39660 Rapid City, SD 0.9608
Meade County, SD  
Pennington County, SD  
39740 Reading, PA 0.9105
Berks County, PA  
39820 Redding, CA 1.5053
Shasta County, CA  
39900 Reno-Sparks, NV 1.0369
Storey County, NV  
Washoe County, NV  
40060 Richmond, VA 0.9723
Amelia County, VA  
Caroline County, VA  
Charles City County, VA  
Chesterfield County, VA  
Cumberland County, VA  
Dinwiddie County, VA  
Goochland County, VA  
Hanover County, VA  
Henrico County, VA  
King and Queen County, VA  
King William County, VA  
Louisa County, VA  
New Kent County, VA  
Powhatan County, VA  
Prince George County, VA  
Sussex County, VA  
Colonial Heights City, VA  
Hopewell City, VA  
Petersburg City, VA  
Richmond City, VA  
40140 Riverside-San Bernardino-Ontario, CA 1.1492
Riverside County, CA  
San Bernardino County, CA  
40220 Roanoke, VA 0.9233
Botetourt County, VA  
Craig County, VA  
Franklin County, VA  
Roanoke County, VA  
Roanoke City, VA  
Salem City, VA  
40340 Rochester, MN 1.1712
Dodge County, MN  
Olmsted County, MN  
Wabasha County, MN  
40380 Rochester, NY 0.8770
Livingston County, NY  
Monroe County, NY  
Ontario County, NY  
Orleans County, NY  
Wayne County, NY  
40420 Rockford, IL 0.9792
Boone County, IL  
Winnebago County, IL  
40484 Rockingham County-Strafford County, NH 1.0215
Rockingham County, NH  
Strafford County, NH  
40580 Rocky Mount, NC 0.8786
Edgecombe County, NC  
Nash County, NC  
40660 Rome, GA 0.8962
Floyd County, GA  
40900 Sacramento-Arden-Arcade-Roseville, CA 1.5211
El Dorado County, CA  
Placer County, CA  
Sacramento County, CA  
Yolo County, CA  
40980 Saginaw-Saginaw Township North, MI 0.8886
Saginaw County, MI  
41060 St. Cloud, MN 1.0703
Benton County, MN  
Stearns County, MN  
41100 St. George, UT 0.9385
Washington County, UT  
41140 St. Joseph, MO-KS 0.9876
Doniphan County, KS  
Andrew County, MO  
Buchanan County, MO  
DeKalb County, MO  
41180 St. Louis, MO-IL 0.9373
Bond County, IL  
Calhoun County, IL  
Clinton County, IL  
Jersey County, IL  
Macoupin County, IL  
Madison County, IL  
Monroe County, IL  
St. Clair County, IL  
Crawford County, MO  
Franklin County, MO  
Jefferson County, MO  
Lincoln County, MO  
St. Charles County, MO  
St. Louis County, MO  
Warren County, MO  
Washington County, MO  
St. Louis City, MO  
41420 Salem, OR 1.1195
Marion County, OR  
Polk County, OR  
41500 Salinas, CA 1.5626
Monterey County, CA  
41540 Salisbury, MD 0.8986
Somerset County, MD  
Wicomico County, MD  
41620 Salt Lake City, UT 0.9396
Salt Lake County, UT  
Summit County, UT  
Tooele County, UT  
41660 San Angelo, TX 0.8053
Irion County, TX  
Tom Green County, TX  
41700 San Antonio, TX 0.8939
Atascosa County, TX  
Bandera County, TX  
Bexar County, TX  
Comal County, TX  
Guadalupe County, TX  
Kendall County, TX  
Medina County, TX  
Wilson County, TX  
41740 San Diego-Carlsbad-San Marcos, CA 1.2104
San Diego County, CA  
41780 Sandusky, OH 0.7821
Erie County, OH  
41884 San Francisco-San Mateo-Redwood City, CA 1.6200
Marin County, CA  
San Francisco County, CA  
San Mateo County, CA  
41900 San Germán-Cabo Rojo, PR 0.4569
Cabo Rojo Municipio, PR  
Lajas Municipio, PR  
Sabana Grande Municipio, PR  
San Germán Municipio, PR  
41940 San Jose-Sunnyvale-Santa Clara, CA 1.6761
San Benito County, CA  
Santa Clara County, CA  
41980 San Juan-Caguas-Guaynabo, PR 0.4374
Aguas Buenas Municipio, PR  
Aibonito Municipio, PR  
Arecibo Municipio, PR  
Barceloneta Municipio, PR  
Barranquitas Municipio, PR  
Bayamón Municipio, PR  
Caguas Municipio, PR  
Camuy Municipio, PR  
Canóvanas Municipio, PR  
Carolina Municipio, PR  
Cataño Municipio, PR  
Cayey Municipio, PR  
Ciales Municipio, PR  
Cidra Municipio, PR  
Comerío Municipio, PR  
Corozal Municipio, PR  
Dorado Municipio, PR  
Florida Municipio, PR  
Guaynabo Municipio, PR  
Gurabo Municipio, PR  
Hatillo Municipio, PR  
Humacao Municipio, PR  
Juncos Municipio, PR  
Las Piedras Municipio, PR  
Loíza Municipio, PR  
Manatí Municipio, PR  
Maunabo Municipio, PR  
Morovis Municipio, PR  
Naguabo Municipio, PR  
Naranjito Municipio, PR  
Orocovis Municipio, PR  
Quebradillas Municipio, PR  
Río Grande Municipio, PR  
San Juan Municipio, PR  
San Lorenzo Municipio, PR  
Toa Alta Municipio, PR  
Toa Baja Municipio, PR  
Trujillo Alto Municipio, PR  
Vega Alta Municipio, PR  
Vega Baja Municipio, PR  
Yabucoa Municipio, PR  
42020 San Luis Obispo-Paso Robles, CA 1.3089
San Luis Obispo County, CA  
42044 Santa Ana-Anaheim-Irvine, CA 1.2036
Orange County, CA  
42060 Santa Barbara-Santa Maria-Goleta, CA 1.3165
Santa Barbara County, CA  
42100 Santa Cruz-Watsonville, CA 1.7835
Santa Cruz County, CA  
42140 Santa Fe, NM 1.0179
Santa Fe County, NM  
42220 Santa Rosa-Petaluma, CA 1.6743
Sonoma County, CA  
42340 Savannah, GA 0.8572
Bryan County, GA  
Chatham County, GA  
Effingham County, GA  
42540 Scranton—Wilkes-Barre, PA 0.8283
Lackawanna County, PA  
Luzerne County, PA  
Wyoming County, PA  
42644 Seattle-Bellevue-Everett, WA 1.1784
King County, WA  
Snohomish County, WA  
42680 Sebastian-Vero Beach, FL 0.8797
Indian River County, FL  
43100 Sheboygan, WI 0.9242
Sheboygan County, WI  
43300 Sherman-Denison, TX 0.8760
Grayson County, TX  
43340 Shreveport-Bossier City, LA 0.8297
Bossier Parish, LA  
Caddo Parish, LA  
De Soto Parish, LA  
43580 Sioux City, IA-NE-SD 0.9202
Woodbury County, IA  
Dakota County, NE  
Dixon County, NE  
Union County, SD  
43620 Sioux Falls, SD 0.8310
Lincoln County, SD  
McCook County, SD  
Minnehaha County, SD  
Turner County, SD  
43780 South Bend-Mishawaka, IN-MI 0.9465
St. Joseph County, IN  
Cass County, MI  
43900 Spartanburg, SC 0.8797
Spartanburg County, SC  
44060 Spokane, WA 1.1221
Spokane County, WA  
44100 Springfield, IL 0.9204
Menard County, IL  
Sangamon County, IL  
44140 Springfield, MA 1.0422
Franklin County, MA  
Hampden County, MA  
Hampshire County, MA  
44180 Springfield, MO 0.8476
Christian County, MO  
Dallas County, MO  
Greene County, MO  
Polk County, MO  
Webster County, MO  
44220 Springfield, OH 0.8483
Clark County, OH  
44300 State College, PA 0.9615
Centre County, PA  
44600 Steubenville-Weirton, OH-WV 0.7415
Jefferson County, OH  
Brooke County, WV  
Hancock County, WV  
44700 Stockton, CA 1.3792
San Joaquin County, CA  
44940 Sumter, SC 0.7626
Sumter County, SC  
45060 Syracuse, NY 0.9937
Madison County, NY  
Onondaga County, NY  
Oswego County, NY  
45104 Tacoma, WA 1.1623
Pierce County, WA  
45220 Tallahassee, FL 0.8602
Gadsden County, FL  
Jefferson County, FL  
Leon County, FL  
Wakulla County, FL  
45300 Tampa-St. Petersburg-Clearwater, FL 0.9114
Hernando County, FL  
Hillsborough County, FL  
Pasco County, FL  
Pinellas County, FL  
45460 Terre Haute, IN 0.9747
Clay County, IN  
Sullivan County, IN  
Vermillion County, IN  
Vigo County, IN  
45500 Texarkana, TX-Texarkana, AR 0.7459
Miller County, AR  
Bowie County, TX  
45780 Toledo, OH 0.8854
Fulton County, OH  
Lucas County, OH  
Ottawa County, OH  
Wood County, OH  
45820 Topeka, KS 0.9012
Jackson County, KS  
Jefferson County, KS  
Osage County, KS  
Shawnee County, KS  
Wabaunsee County, KS  
45940 Trenton-Ewing, NJ 1.0622
Mercer County, NJ  
46060 Tucson, AZ 0.8991
Pima County, AZ  
46140 Tulsa, OK 0.8179
Creek County, OK  
Okmulgee County, OK  
Osage County, OK  
Pawnee County, OK  
Rogers County, OK  
Tulsa County, OK  
Wagoner County, OK  
46220 Tuscaloosa, AL 0.8498
Greene County, AL  
Hale County, AL  
Tuscaloosa County, AL  
46340 Tyler, TX 0.8562
Smith County, TX  
46540 Utica-Rome, NY 0.8806
Herkimer County, NY  
Oneida County, NY  
46660 Valdosta, GA 0.7558
Brooks County, GA  
Echols County, GA  
Lanier County, GA  
Lowndes County, GA  
46700 Vallejo-Fairfield, CA 1.6355
Solano County, CA  
47020 Victoria, TX 0.8986
Calhoun County, TX  
Goliad County, TX  
Victoria County, TX  
47220 Vineland-Millville-Bridgeton, NJ 1.0674
Cumberland County, NJ  
47260 Virginia Beach-Norfolk-Newport News, VA-NC 0.8928
Currituck County, NC  
Gloucester County, VA  
Isle of Wight County, VA  
James City County, VA  
Mathews County, VA  
Surry County, VA  
York County, VA  
Chesapeake City, VA  
Hampton City, VA  
Newport News City, VA  
Norfolk City, VA  
Poquoson City, VA  
Portsmouth City, VA  
Suffolk City, VA  
Virginia Beach City, VA  
Williamsburg City, VA  
47300 Visalia-Porterville, CA 0.9989
Tulare County, CA  
47380 Waco, TX 0.8248
McLennan County, TX  
47580 Warner Robins, GA 0.7718
Houston County, GA  
47644 Warren-Troy-Farmington Hills, MI 0.9464
Lapeer County, MI  
Livingston County, MI  
Macomb County, MI  
Oakland County, MI  
St. Clair County, MI  
47894 Washington-Arlington-Alexandria, DC-VA-MD-WV 1.0570
District of Columbia, DC  
Calvert County, MD  
Charles County, MD  
Prince George's County, MD  
Arlington County, VA  
Clarke County, VA  
Fairfax County, VA  
Fauquier County, VA  
Loudoun County, VA  
Prince William County, VA  
Spotsylvania County, VA  
Stafford County, VA  
Warren County, VA  
Alexandria City, VA  
Fairfax City, VA  
Falls Church City, VA  
Fredericksburg City, VA  
Manassas City, VA  
Manassas Park City, VA  
Jefferson County, WV  
47940 Waterloo-Cedar Falls, IA 0.8366
Black Hawk County, IA  
Bremer County, IA  
Grundy County, IA  
48140 Wausau, WI 0.8652
Marathon County, WI  
48300 Wenatchee-East Wenatchee, WA 1.0151
Chelan County, WA  
Douglas County, WA  
48424 West Palm Beach-Boca Raton-Boynton Beach, FL 0.9637
Palm Beach County, FL  
48540 Wheeling, WV-OH 0.6702
Belmont County, OH  
Marshall County, WV  
Ohio County, WV  
48620 Wichita, KS 0.8710
Butler County, KS  
Harvey County, KS  
Sedgwick County, KS  
Sumner County, KS  
48660 Wichita Falls, TX 0.9578
Archer County, TX  
Clay County, TX  
Wichita County, TX  
48700 Williamsport, PA 0.8303
Lycoming County, PA  
48864 Wilmington, DE-MD-NJ 1.0632
New Castle County, DE  
Cecil County, MD  
Salem County, NJ  
48900 Wilmington, NC 0.8900
Brunswick County, NC  
New Hanover County, NC  
Pender County, NC  
49020 Winchester, VA-WV 0.9072
Frederick County, VA  
Winchester City, VA  
Hampshire County, WV  
49180 Winston-Salem, NC 0.8373
Davie County, NC  
Forsyth County, NC  
Stokes County, NC  
Yadkin County, NC  
49340 Worcester, MA 1.1632
Worcester County, MA  
49420 Yakima, WA 1.0399
Yakima County, WA  
49500 Yauco, PR 0.3798
Guánica Municipio, PR  
Guayanilla Municipio, PR  
Peñuelas Municipio, PR  
Yauco Municipio, PR  
49620 York-Hanover, PA 0.9580
York County, PA  
49660 Youngstown-Warren-Boardman, OH-PA 0.8406
Mahoning County, OH  
Trumbull County, OH  
Mercer County, PA  
49700 Yuba City, CA1 1.1809
Sutter County, CA  
Yuba County, CA  
49740 Yuma, AZ 0.9715
Yuma County, AZ  
Table B—FY 2014 Wage Index Based on CBSA Labor Market Areas for Rural Areas Back to Top
State code Nonurban area Wage index
1All counties within the State are classified as urban, with the exception of Puerto Rico. Puerto Rico has areas designated as rural; however, no short-term, acute care hospitals are located in the area(s) for FY 2014. The Puerto Rico wage index is the same as FY 2013.
1 Alabama 0.7175
2 Alaska 1.3720
3 Arizona 0.9205
4 Arkansas 0.7374
5 California 1.2697
6 Colorado 0.9844
7 Connecticut 1.1356
8 Delaware 1.0116
10 Florida 0.8009
11 Georgia 0.7482
12 Hawaii 0.9919
13 Idaho 0.7637
14 Illinois 0.8392
15 Indiana 0.8547
16 Iowa 0.8470
17 Kansas 0.7963
18 Kentucky 0.7726
19 Louisiana 0.7610
20 Maine 0.8273
21 Maryland 0.8733
22 Massachusetts 1.3671
23 Michigan 0.8308
24 Minnesota 0.9140
25 Mississippi 0.7610
26 Missouri 0.7780
27 Montana 0.9136
28 Nebraska 0.8893
29 Nevada 0.9822
30 New Hampshire 1.0381
31 New Jersey1
32 New Mexico 0.8843
33 New York 0.8235
34 North Carolina 0.8118
35 North Dakota 0.6814
36 Ohio 0.8281
37 Oklahoma 0.7712
38 Oregon 0.9437
39 Pennsylvania 0.8350
40 Puerto Rico1 0.4047
41 Rhode Island1
42 South Carolina 0.8337
43 South Dakota 0.8199
44 Tennessee 0.7458
45 Texas 0.7889
46 Utah 0.8769
47 Vermont 0.9782
48 Virgin Islands 0.7089
49 Virginia 0.7802
50 Washington 1.0574
51 West Virginia 0.7398
52 Wisconsin 0.8934
53 Wyoming 0.9280
65 Guam 0.9611

[FR Doc. 2013-10558 Filed 5-1-13; 4:15 pm]

BILLING CODE 4120-01-P

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