DEPARTMENT OF HEALTH AND HUMAN SERVICES
Centers for Medicare & Medicaid Services
42 CFR Parts 413 and 424 [CMS-1446-P]
RIN 0938-AR65 Medicare Program; Prospective Payment System and Consolidated Billing for Skilled Nursing Facilities for FY 2014
AGENCY: Centers for Medicare & Medicaid Services (CMS), HHS.
ACTION: Proposed rule.
SUMMARY: This proposed rule would update the payment rates used under the prospective payment system (PPS) for skilled nursing facilities (SNF s) for fiscal year (FY) 2014, would revise and rebase the SNF market basket, and would make certain technical and conforming revisions in the re gulations text. This proposed rule also includes a proposed policy for reporting the SNF market basket forecast error correction in certain limited circumstances and a pr oposed new item for the Minimum Data Set (MDS), Version 3.0.
DATES: 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: 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 f our 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 th e "Submit a comment" instructions.2 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 co mments 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 de liver (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, S.W.,3 Washington, DC 20201 (Because access to the interior of the H ubert H. Humphrey Building is not readily available to persons without Federal G overnment 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 fo r persons wishing to re tain 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 indicat ed as appropriate for hand or courier delivery may be delayed and receiv ed after the comment period. For information on viewing public co mments, see the beginning of the "SUPPLEMENTARY INFORMATION" section.
FOR FURTHER INFORMATION CONTACT: Penny Gershman, (410) 786-6643, for informa tion related to c linical 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 inform ation related to the wage index. Bill Ullman, (410) 786-5667, for information re lated to level of care determinations, consolidated billing, a nd general information.4

SUPPLEMENTARY INFORMATION : Inspection of Public Comments: All comments received before the close of the co mment 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 website as s oon as possible after they have been received: http://www.regulations.gov . Follow the search instructions on that website to view public comments. Comments received timely will also be av ailable for public inspection as they are received, generally beginning approximately 3 weeks after publication of a document, at the headquarters of the Cent ers 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 appointm ent to view public comments, phone 1-800-743-
3951. Availability of Certain In formation Exclusively Through the Internet on the CMS
Website The Wage Index for Urban Areas Based on CBSA Labor Market Areas (Table A) and the Wage Index Based on CBSA Labor Mark et 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 rule s 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 tabl es are no longer published in the Federal Register in this manner, and instead are made available ex clusively 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 pa yment systems and streamline the published5 content to focus on policy discussion, we now propose to adopt a similar approach for the SNF PPS as well. As discussed in greater deta il in section VI. of this proposed rule, we would revise the applicable regulations te xt at §413.345 to accommodate this approach, consistent with the wording of the co rresponding statutory au thority at section 1888(e)(4)(H)(iii) of the Social Security Act (the Act). U nder this approach, effective October 1, 2013, the individual wage index valu es 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 avai lable exclusively thr ough the Internet on CMS’s SNF PPS website at http://www.cms.gov/Medicare/Medicare-Fee-for-ServicePayment/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 th e 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 av ailable exclusively through the Internet on the CMS website. In addition, we note that in previous year s, each rule or update notice issued under the annual SNF PPS rulemaking cycle has includ ed a detailed reiteration of the various individual legislative provisi ons that have affected the SN F PPS over the years, a number of which represented temporary measures that have long since expire d. That discussion, along with detailed background information on various other aspects of the SNF PPS, will now be made available exclusively on the CMS website as well, at http://www.cms.gov/Medicare/Medicare-F ee-for-Service-Payment/SNFPPS/index.html

.6 In connection with this change, this proposed rule is presented in a revised format that also serves to consolidate material on the in dividual rate component s that had previously appeared redundantly in several different portions of the pr eamble. 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 ru le’s reordered preamble discussion and the material that was presented in last ye ar’s SNF PPS update notice for FY 2013 (77 FR 46214, August 2, 2012). Crosswalk to FY 2013 Update Notice 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.C7 III.E Adjusted Rate Computation Example ..........................................III.F IV.A SNF Level of Care--Administr ative 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 SN F 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 Ra tes, Indexes (Urban) .......................Table 4 Table 5 C-M Adjusted Federal Ra tes, 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 Rela tive Importance.......................................Table 13 Table 18 C-M Distributions by Major RUG-IV Category....................Table 9 Table 19 C-M Distribution for Th erapy RUG-IV Groups....................Table 108 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 secti ons contained in this document, we are providing the following Table of Contents.
Table of Contents 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 Adjustment9 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 M easure Cost Category Growth 4. Proposed Market Basket Estimat e 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 Analyses10 Regulation Text Acronyms In addition, because of the many terms to which we refer by acronym in this proposed rule, we are listing these abbr eviations and their corresponding terms in alphabetical order below: AIDS Acquired Immune Deficiency Syndrome ARD Assessment reference date BBA Balanced Budget Act of 1997, Pub. L. 105-33 BBRA Medicare, Medicaid, and SCHIP Ba lanced Budget Refinement Act of 1999, Pub. L. 106-113 BIPA Medicare, Medicai d, and SCHIP Benefits Improvement and Protection Act of 2000, Pub. L. 106-554 CAH Critical access hospital CBSA Core-based statistical area CFR Code of Federal Regulations CMI Case-mix index CMS Centers for Medicare & Medicaid Services COT Change of therapy ECI Employment Cost Index EOT End of therapy EOT-R End of therapy - resumption FQHC Federally qualified health center FR Federal Register FY Fiscal year11 GAO Government Accountability Office HCPCS Healthcare Common Procedure Coding System HOMER Home office Medicare records IGI IHS (Information Handling Services) Global Insight, Inc. MDS Minimum data set MFP Multifactor productivity MMA Medicare Prescription Drug, Impr ovement, and Modernization Act of 2003, Pub. L. 108-173 MSA Metropolitan statistical area NAICS North American Industr ial Classification System OMB Office of Management and Budget OMRA Other Medicare Required Assessment PPS Prospective Payment System RAI Resident assessment instrument RAVEN Resident assessment validation entry RFA Regulatory Flexibil ity Act, Pub. L. 96-354 RHC Rural health clinic RIA Regulatory impact analysis RUG-III Resource Utilization Groups, Version 3 RUG-IV Resource Utilization Groups, Version 4 RUG-53 Refined 53-Group RUG-III Ca se-Mix Classification System SCHIP State Children's Health Insurance Program SNF Skilled nursing facility STM Staff time measurement12

STRIVE Staff time and resour ce intensity verification UMRA Unfunded Mandates Reform Act, Pub. L. 104-4 I. Executive Summary A. Purpose This proposed rule would update the SN F prospective payment rates for FY 2014 as required under section 1888(e)(4 )(E) of the Act. It woul d 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-mi x classification system, and the factors to be applied in making the area wage adjust ment 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 refl ect an update to the rates that we published in the SNF PPS update notice for FY 2013 (77 FR 46214) which reflect s the SNF market basket index, adjusted by the forecast erro r correction, if applicab le, 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 A. Statutory Basis and Scope13 As amended by section 4432 of the Bala nced Budget Act of 1997 (BBA, Pub. L. 105-33, enacted on August 5, 1997), section 188 8(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 e ffective for cost repor ting 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 servic es (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 comprehensiv e 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 th e Act, the SNF PPS included an initial, three-phase transition that ble nded a facility-specifi c rate (reflecting the individual facility’s hi storical cost experience) with the federal case-mix adjusted rate. The transition extended through the facility’s first three cost re porting 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 trans ition, as all facilities have been paid at the full federal rate effective with cost reporting periods begi nning in FY 2002. As we now base payments for SNFs entirely on the adjusted federal per diem rates, we no longe r include adjustment factors under the transition re lated to facility-specific rates for the upcoming FY.14 C. Required Annual Rate Updates Section 1888(e)(4)(E) of the Act requir es the SNF PPS payment rates to be updated annually. The most recent annual upda te occurred in an update notice that set forth updates to the SNF PPS payment rates for FY 2013 (77 FR 46214). Under this requirement, sect ion 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 da ys 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 th e 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 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 ra tes using allowable costs from hospital-based and freestanding SNF cost reports for reporting periods beginning in FY 1995. The data used in develo ping the federal rates also incorporated a “Part B add-on,” which is an estimate of th e amounts that, prior to the SNF PPS, would15 have been payable under Part B for covered SN F services furnished to individuals during the course of a covered Part A stay in a SNF. In developing the rates for the initial pe riod, we updated costs to the first effective year of the PPS (the 15-month period begi nning 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 compili ng 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 relate d to payments for excep tions to the routine cost limits. Using the formula that the BBA pr escribed, we set the federal rates at a level equal to the weighted mean of freestandi ng 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, a nd adjusted the portion of the federal rate attributable to wage-related costs by a wage index to refl ect 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 serv ices, and capital-related expenses. We use the SNF market basket index, adjusted in the manner descri bed below, to update the federal rates on an annual basis. In the SNF PPS final rule for FY 2008 (72 FR 43425 through 43430), we16
revised and rebased the market basket, whic h included updating the ba se year from FY 1997 to FY 2004. For FY 2014, we propose to revi se and rebase the market basket to reflect FY 2010 total cost data, as detaile d 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 re vised and rebased FY 2010-base d SNF market basket. For the FY 2014 proposed rule, the FY 2010-base d SNF market basket growth rate is estimated to be 2.3 percent, which is base d on the Information Handling Services (IHS) Global Insight, Inc. (IGI) first quarter 2013 fo recast 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 th e 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 fede ral 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 th e FY 2014 percentage increase in the FY 2010-based SNF market basket index fo r 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 (§41 3.337(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 rate s, because the initial 3-phase transition17 period from facility-specific to full federal ra tes 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 ac count 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 acc ount 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 succeed ing 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 th e 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 year s. As we stated in the final rule for FY 2004 that first issued the market bask et 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 mark et basket index was 2.7 percen tage points, while the actual increase was 2.2 percentage points, resulti ng in the actual increas e being 0.5 percentage point lower than the estimated increase. As th e forecast error calculation in this instance does not permit one to determine definitively if the forecast error adjustment threshold18 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 (otherwi se 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 re ferred to as a hundredth of a pe rcentage point) so that we may determine whether the forecast error co rrection threshold has been exceeded and whether the forecast error adjustment s hould be applied under §413.337(d)(2). This policy would apply only in those instances wher e the forecast error, when rounded to one significant digit, is 0.5 percentage point. For example, if the forecas t error is calculated to be 0.4 percentage point when rounded to one significant digit, then no further determinations are necessary, the forecast e rror 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 forecas t error will be reporte d 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 de termination of whether or not the threshold has been exceeded would be made by r ounding the forecast error calculation to the second significant digit. We believe this appr oach is necessary and appropriate to ensure that the necessity for a forecas t error adjustment is accurate ly determined in accordance with §413.337(d)(2), which enable s us to identify those instances where the difference between the actual and projected market bask et becomes sufficiently significant to indicate that the historical price changes are not being adequately reflected. This19 proposed policy would enable us to disti nguish between cases where the difference carried out to the second decimal place is less than the 0.5 thres hold 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 th reshold but rounds to 0.5 (0.51 to 0.54). We would apply the proposed policy when the difference between th e 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 si gnificant digit, or the hundredth of a percentage point. The forecasted FY 2012 SN F market basket percentage change was 2.7 percent. When rounded to the second signifi cant digit, it was 2.69 percent. This would be subtracted from the actual FY 2012 SNF ma rket basket percentage change, rounded to the second significant digit, of 2.18 percent to yield a negative forecas t error correction of 0.51 percentage point. As the forecast erro r correction, when rounde d to two significant digits, exceeds 0.5 percentage point, a for ecast 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 producti vity adjustment described below, once we have determined that a forecast error adjustme nt 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 basket20 percentage change exceeded the actual SN F 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 per centage change of 2.3 percent would be adjusted downward by the forecas t error correction of 0.5 percen tage 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

Index Forecasted FY 2012 Increase * Actual FY 2012 Increase** FY 2012 Difference SNF (rounded to one

significant digit) 2.7 2.2 -0.5 SNF (rounded to two

significant digits) 2.69 2.18 -0.51 *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). 4. Multifactor Productivity Adjustment Section 3401(b) of the Affordable Care Act requires that, in FY 2012 (and in subsequent FYs), the market basket per centage 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 secti on 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, costreporting period, or other annual period)” (the MFP adjustment). The Bureau of Labor Statistics (BLS) is the agen cy that publishes the offici al measure of private nonfarm21 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 pr oduced 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 deri ved 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 Productiv ity 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 fo r FY 2014 under section 1888 (e)(5)(B)(i) of the Act based on the proposed FY 2010-based SNF market basket. Sect ion 1888(e)(5)(B)(ii) of the Act, added by section 3401(b) of the Af fordable Care Act, requires that for FY 2012 and each subsequent FY, after determini ng the market basket percentage described in section 1888(e)(5)(B)(i) of th e Act, “the Secretary shall reduce such perc entage 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)(i i) of the Act furthe r states that the reduction of the market basket percentage by the MFP adjustment may result in the market basket percentage being less than ze ro for a FY, and may result in payment rates under section 1888(e) of the Ac t for a FY being less than such payment rates for the preceding FY. Thus, if the application of the MFP adjustment to the market basket22 percentage calculated under section 1888(e)(5)(B)(i) of the Act results in an MFPadjusted market basket percentage that is less than zero, then the annual update to the unadjusted federal per diem rates under sec tion 1888(e)(4)(E)(ii) of the Act would be negative, and such rates would decr ease 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 SN F PPS is based on IGI’s first quarter 2013 forecast of the proposed FY 2010-based SNF mark et 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 (a s added by section 3401(b) of th e 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 calculate d as described above and based on IGI’s first quarter 2013 forecast. The resulting MFP-adjust ed 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 unadjuste d federal rates be at a level equal to the market basket index percentage change. A ccordingly, 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 bask et 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 the23 market basket update factor by the forecast erro r 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, s ection 1888(e)(5)(B) of the Act requires us to reduce the market bask et 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 MFPadjusted 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-relate d 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 fo r FY 2014 from average prices for FY 2013. We would further adjust the rates by a wa ge index budget neutrality factor, described later in this section. Tabl es 2 and 3 reflect the update d components of the unadjusted federal rates for FY 2014, prio r to adjustment for case-mix.24
TABLE 2: FY 2014 Unadjusted Federal Rate Per Diem Urban

Rate Component Nursing - Case-Mix Therapy - CaseMix Therapy - NonCase-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

Rate Component Nursing - Case-Mix Therapy - CaseMix Therapy - NonCase-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, us ing a classification system that accounts for the relative resource utilization of different pa tient types. The statute specifies that the adjustment is to reflect both a resident cla ssification system that the Secretary establishes to account for the relative resource use of diffe rent patient types, as well as resident assessment data and other data that the Secr etary considers appropria te. In the interim final rule with comment period that initi ally implemented the SNF PPS (63 FR 26252, May 12, 1998), we developed the RUG-III case-m ix classification system, which tied the amount of payment to resident resource use in combination with resi dent 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 ba sed 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 conduc ted a multi-year data collection and analysis under the Staff Time and Resource Intensity Verification (STRIVE) project to25 update the case-mix classification system for FY 2011. The resulting Resource Utilization Groups, Version 4 (R UG-IV) case-mix classification system reflected the data collected in 2006-2007 during the STRIVE proj ect, and was finalized in the FY 2010 SNF PPS final rule (74 FR 40288) to take eff ect in FY 2011 concurrently with an updated new resident assessment instrument, versi on 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 base d, 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-mi x 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 or ientation of the case-mix cla ssification system supports the SNF PPS’s use of an administrative presump tion 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 fo r 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 Instru ment (RAI) Manual. For an MDS to be considered valid for use in determinin g 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 website at http://www.cms.gov/Medicare/Quality -Initiatives-Patient-AssessmentInstruments/NursingHomeQualityInits/MDS30RAIManual.html

. In addition, we note that section 511 of the Medicare Prescription Drug,26 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 di em payment for any SNF residents with Acquired Immune Deficiency Syndrome (AIDS), effective with services furnished on or after October 1, 2004. This spec ial add-on for SNF residents with AIDS was to remain in effect until “. . . the Secretary certifies that th ere is an appropriate adjustment in the case mix . . . to compensate for the increased costs as sociated with [such] residents . . . .” The add-on for SNF residents with AIDS is al so 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 cer tification of the add-on for SNF residents with AIDS in that final rule’s implementa tion of the case-mix refinements for RUG-IV, thus allowing the add-on payment require d by section 511 of the MMA to remain in effect. For the limited number of SNF reside nts that qualify for this add-on, there is a significant increase in payments. For exampl e, using FY 2011 data, we identified fewer than 4,100 SNF residents with a diagnosis c ode of 042 (Human Immunodeficiency Virus (HIV) Infection). For FY 2014, an urban facili ty 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. Afte r an increase of 128 percent, this urban facility would receive a case-mix ad justed 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 esta blished 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 our27

current use of the In ternational Classificat ion of Diseases, 9th revision, Clinical Modification (ICD-9-CM), effective with the compliance date for using the International Classification of Diseases, 10th revision, Clinical Modificat ion (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 IC D-9-CM diagnosis co de 042 and ICD-10-CM diagnosis code B20 include AIDS, AIDS-re lated complex (ARC), and HIV infection, symptomatic, but ICD-9-CM diagnosis c ode 042 additionally includes AIDS-like syndrome whereas ICD-10-CM diagnosis c ode 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 refl ects 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 th e 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 va lues. These tables do not reflect the add-28

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 Fe deral Rates and Associated Indexes URBAN

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 $343.3729

RUG-IV Category Nursing Index Therapy Index Nursing Component Therapy Component Non-case Mix Therapy Comp Non-case Mix Component Total Rate 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 Fe deral Rates and Associated Indexes RURAL

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 $603.0330

RUG-IV Category Nursing Index Therapy Index Nursing Component Therapy Component Non-case Mix Therapy Comp Non-case Mix Component Total Rate 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 $341.6131

RUG-IV Category Nursing Index Therapy Index Nursing Component Therapy Component Non-case Mix Therapy Comp Non-case Mix Component Total Rate 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. Si nce the inception of the SNF PPS, we have used hospital inpatient wage data in devel oping a wage index to be appl ied to SNFs. We propose to continue this practice for FY 2014, as we contin ue to believe that in the absence of SNFspecific wage data, using the hospital inpatien t wage index is appropr iate and reasonable for the SNF PPS. As explained in the upda te notice for FY 2005 (69 FR 45786), the SNF PPS does not use the hospital area wage inde x’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 adjustme nt continues to be appropriate for SNF payments. For FY 2014, the updated wage data are for hospital co st reporting periods beginning on or after October 1, 2009 and before October 1, 2010 (FY 2010 cost report data). Finally, we propose to con tinue to use the same methodology discussed in the32 SNF PPS final rule for FY 2008 (72 FR 43423) to address those geographic areas in which there are no hospitals, and thus, no hosp ital wage index data on which to base the calculation of the FY 2014 SNF PPS wage inde x. For rural geographic areas that do not have hospitals, and therefore, lack hospital wage data on wh ich to base an area wage adjustment, we would use the average wage index from all contiguous Core-Based Statistical Areas (CBSAs) as a reasonab le 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 exis t there (for exampl e, 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 rura l Puerto Rico that is inappropriately higher than that in half of its urban areas); instead, we would con tinue to use the most recent wage index previously available for th at 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 reasona ble proxy for the wage index of that urban CBSA. For FY 2014, the only urban area wit hout 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 Ac t of 2000 (BIPA) (Pub. L. 106-554, enacted on December 21, 2000) authorized us to estab lish 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 require d to improve the quality of that data.33 Once calculated, we would apply the wage index adjustment to the labor-related portion of the federal rate. Each year, we cal culate a revised labor-r elated 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 la bor-related share to reflect the relative importance of the revised FY 2010-based SN F 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; ad ministrative and facilities support services ; all other: labor-related services (previous ly 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 im portance from the SNF market basket, and it approximates the labor-related portion of the total costs after taking into account historical and projected pri ce changes between the base year and FY 2014. The price proxies that move the different cost categories in the mark et basket do not necessarily change at the same rate, and the relati ve importance captures these changes. Accordingly, the relative importance figure mo re closely reflects the cost share weights for FY 2014 than the base year we ights 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 the34 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, a ll other: labor-relate d services (previously referred to in the FY 2004-based SNF market ba sket 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 laborrelated and non-labor-related components. In section V. of this proposed rule, Table 17 provides the FY 2014 labor-related share com ponents based on the revised and rebased FY 2010-based SNF market basket. TABLE 6: RUG-IV Case-Mix Adjust ed Federal Rates for Urban SNFs By Labor and Non-Labor Component 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 $117.8735

RUG-IV Category Total Rate Labor Portion Non-Labor Portion 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 Fe deral Rates for Rural SNFs by Labor and Non-Labor Component

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 $186.8236

RUG-IV Category Total Rate Labor Portion Non-Labor Portion 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 $68.7837

RUG-IV Category Total Rate Labor Portion Non-Labor Portion 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 f actor 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 deno minator of this ratio. We define the wage adjustment factor used in this calculati on as the labor share of the rate component multiplied by the wage index plus the non-labo r 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 website at http://cms.gov/Medicare/Med icare-Fee-for-ServicePayment/SNFPPS/WageIndex.html

. In the SNF PPS final rule for FY 2006 (70 FR 45026, August 4, 2005), we38 adopted the changes discusse d 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 st atistical areas. In addition, OMB published subsequent bulletins regarding CBSA change s, including changes in CBSA numbers and titles. We indicated in the FY 2008 SN F 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 desi gnations, 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 ofa blend of 50 percent of the FY 2006 MSAbased 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, Micr opolitian Statistical Areas, and Combined Statistical Areas, and gui dance on uses of the delineation of these areas. A copy of this bulletin may be obtained at http://www.whitehouse.gov/sites/defaul t/files/omb/bulle tins/2013/b-13-01.pdf . This39 bulletin states that it provides the delineat ions of all Metropolitan Statistical Areas, Metropolitan Divisions, Micropo litan Statistical Areas, Comb ined Statistical Areas, and New England City and Town Areas in the Un ited 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 Fe bruary 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 numbe r of significant changes. For example, there are new CBSAs, urban counties that b ecome rural, rural counties that become urban, and existing CBSAs that are being split apart. The changes made by the bulletin and th eir 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 suff icient time to assess the new changes and their ramifications, we intend to propose cha nges to the wage index based on the newest CBSA changes in the FY 2015 SNF PPS proposed ru le. 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 describe d below, Table 8 shows the adjustments made to the federal per diem rates to compute the provider's actual per diem PPS40 payment under the described scenario. We derive the Labor and Non-labor columns from Table 6. As illustrated in Table 8, SN F XYZ’s total PPS payment would equal $41,917.80. TABLE 8: Adjusted Rate Computation Example SNF XYZ: Located in Cedar Ra pids, IA (Urban CBSA 16300) Wage Index: 0.9001

RUG-IV Group Labor Wage Index Adjusted Labor NonLabor Adjusted Rate Percent Adjustment Medicare Days Payment 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 *Reflects a 128 percent adjustment from section 511 of the MMA. IV. Additional Asp ects of the SNF PPS A. SNF Level of Care--Administrative Presumption The establishment of the SNF PPS did not change Medicare's fundamental requirements for SNF coverage. However, b ecause 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 revi ew 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 classifi cation 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 th e federal payment rates in the Federal Register the designation of those specific RUGs under th e classification system that represent the required SNF level of care, as provided in §409.30. As set forth in the FY 2011 SNF PPS41 update notice (75 FR 42910), this designation reflects an administrative presumption under the 66-group RUG-IV system that benefi ciaries who are correctly assigned to one of the upper 52 RUG-IV groups on the initial 5-day, Medica re-required assessment are automatically classified as meeting the SNF level of care definiti on 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 meeti ng or not meeting the definition, but instead receives an individual level of care determination using the existing administrative criteria. This presumption recognizes the str ong likelihood that benefi ciaries assigned to one of the upper 52 RUG-IV groups during th e 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 guide lines 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 encomp assed by the following RUG-IV categories:

• Rehabilitation plus Extensive Services;

• Ultra High Rehabilitation;

• Very High Rehabilitation;

• High Rehabilitation;

• Medium Rehabilitation;

• Low Rehabilitation;

• Extensive Services;42

• Special Care High;

• Special Care Low; and,

• Clinically Complex. However, we note that this administrati ve presumption policy does not supersede the SNF’s responsibility to ensure that its decisions rela ting 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 th e basic statutory cr iterion of being reasonable and necessary to diagnose or treat a beneficiary' s condition (according to section 1862(a)(1) of th e Act). Accordingly, the presumption would not apply, for example, in those situations in whic h a resident's assignment to one of the upper . . . groups is itself based on the rece ipt 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 continui ng need for Part A SN F 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 (a s added by section 4432(b) of the BBA) require a SNF to submit consol idated Medicare bills to its fiscal intermediary or Medicare Administrative Contra ctor for almost all of the services that its43 residents receive during the course of a c overed 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-languag e pathology services that the resident receives during a noncovered stay. Section 188 8(e)(2)(A) of the Act excludes a small list of services from the consolidated billing pr ovision (primarily thos e services furnished by physicians and certain other t ypes 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 br oader categories (chemotherapy items, chemotherapy administra tion services, radioiso tope services, and customized prosthetic devices) that otherw ise remained subject to the provision. We discuss this BBRA amendment in greater de tail 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, whic h 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 id entified for exclusion from this provision a number of particular serv ice codes within four speci fied categories (that is,44 chemotherapy items, chemotherapy administrati on services, radioiso tope services, and customized prosthetic devices), but also gave the Secretary “. . . the authority to designate additional, individual services for exclus ion 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) (C onf. Rep.)) characterizes the individual services that this legislation targets for exclus ion 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 sy stem . . . .” 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 se rvices within those four categories (thus, leaving all of those serv ices 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 additiona l service codes that we mi ght designate for exclusion under our discretionary authority must meet the same statutory criteria used in identifying the original codes excluded from consolidat ed billing under secti on 103(a) of the BBRA: they must fall within one of the four servic e categories specified in the BBRA, and they also must meet the same sta ndards of high cost and low proba bility in the SNF setting, as discussed in the BBRA Conference report. A ccordingly, we characterized this statutory authority to identify additional service codes for exclusion “. . . as essentially affording the flexibility to revise the list of exclude d 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 prac tice)” (65 FR 46791). In this45 proposed rule, we specifically invite public comments identifying HCPCS codes in any of these four service cate gories (chemotherapy items, chemotherapy administration services, radioisotope services, and custom ized prosthetic devices) representing recent medical advances that might meet our crit eria for exclusion from SNF consolidated billing. We may consider excluding a part icular 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 amen dment (as well as the implementing regulations) identified a set of excluded services by mean s of specifying HCPCS codes that were in effect as of a pa rticular date (in that case, as of July 1, 1999). Identifying the excluded services in this manner made it possi ble 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 woul d identify these additional excl uded 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 exclusio ns in this manner, we could similarly accomplish routine future updates of these ad ditional codes through the issuance of program instructions. C. Payment for SNF-Level Swing-Bed Services46 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-le vel services furnished under a swing-bed agreement. However, in accordance with se ction 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 c onsistent with the statutory provision to integrate swing-bed rural hospitals into th e SNF PPS by the end of the transition period, June 30, 2002. Accordingly, all non-CAH swing-bed rura l 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 fina lized 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 website at http://www.cms.gov/Medicare/Medicare-F ee-for-Service-Payment/SNFPPS/index.html

. V. Other Issues A. Revising and Rebasing the SNF Market Basket Index47 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 revise d 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 ru le (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 SN F 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 th e 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 servic es) 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 bask et represents routin e costs, costs of ancillary services, and capital-re lated 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 furt her 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 a48 specified mix of goods and services in a sele cted base period to the cost of purchasing that same group of goods and se rvices at current prices. We construct the market basket in three step s. The first step is to select a base period and estimate total base period expend iture shares for mutually exclusive and exhaustive spending categories. We use to tal costs for routine services, ancillary services, and capital. These shares are called “cost” or “expenditure” weights. The second step is to match each expenditure cate gory to a price/wage variable, called a price proxy. We draw these price proxy variables fr om publicly available statistical series published on a consistent schedu le, preferably at least quarter ly. The final step involves multiplying the price level for each spendi ng 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 i ndex 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 i ndex levels, from which we can calculate rates of growth. The market basket represents a fixe d-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 th e quantity or mix of goods and services purchased subsequent or prior to the ba se period are, by design, not considered. Consistent with our discussion in th e May 12, 1998 interim final rule with comment period (63 FR 26252), the FY 2002 fi nal 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 cost49 weights and price proxies reflect the mix of goods and services th at underlie Medicare allowable SNF costs (routine, ancilla ry, and capital-related) for FY 2010. 2. Revising and Rebasing the Skilled Nursing Facility Market Basket The terms “rebasing” and “revising,” wh ile often used interchangeably, actually denote different activities. Rebasing means sh ifting the base year for the structure of costs of the input price index (for example, for this propos ed rule, we propose to shift the base year cost structure from FY 2004 to FY 2010). Revising means changing data sources, cost categories, pri ce proxies, and/or methodology us ed in developing the input price index. We are proposing both to reba se and revise the SNF mark et basket to reflect FY 2010 Medicare allowable total cost data (r outine, ancillary, and capital-related). Medicare allowable costs are costs that ar e 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 Hea lth 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 Septem ber 30, 2009, and before October 1, 2010. We propose to maintain our policy of usi ng data from freestanding SNFs because freestanding SNF data reflect the actual cost structure faced by the SNF itself. In50 contrast, expense data for a hospital-based SN F reflect the allocation of overhead over the entire institution. Due to this method of a llocation, total expenses will be correct, but the individual component s’ expenses may be skewed. We developed cost category weights for the proposed FY 2010-based SNF market basket in two stages. First, we derived ba se weights for seven major categories (wages and salaries, employee benefits, contract la bor, pharmaceuticals, professional liability insurance, capital-related, a nd 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-Out put (I-O) tables for the nursing home industry aged forward using price changes. The met hodology we propose to use to age the data forward involves applying the annual price chan ges from the respective price proxies to the appropriate cost categories. We repeat th is practice for each year. We then apply the resulting 2010 distributions to the aggregate 2010 “all ot her” 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 availa ble being 2002. The 2007 BEA Benchmark I-O data are expected to be rel eased 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 data51

available. We note that the FY 2004-ba sed 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 IO data. For this SNF market basket revision a nd rebasing, we are proposing to include a total of 29 detailed cost categories for th e proposed FY 2010-based SNF market basket, which is six more cost categories than th e FY 2004-based SNF market basket. We are proposing to include five new cost cate gories in the proposed FY 2010-based SNF market basket: (1) Medical Instruments and Supplies; (2) Apparel; (3) Machinery and Equipment; (4) Administrative and Faciliti es Support Services ; and (5) Financial Services. Having separate categories for thes e costs enables them to be proxied more precisely. We are also propos ing to divide the Nonmedi cal Professional Fees cost category into Nonmedical Professional Fees: Labor-Related and Nonmedical Professional Fees: Nonlabor-Related. In a ddition, we are proposing to revise our labels for the Labor-Intensive Services and Nonlabor-I ntensive Services cost categories to All Other: Labor-Related Services and All Other: Nonlabor-Relat ed 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 th e FY 2002 SNF PPS final rule (66 FR 39582) and the FY 2004-based SNF market basket, de scribed in the FY 2008 SNF PPS final rule (72 FR 43425). It is a similar methodology as is used for the inpa tient hospital capital input price index described in the FY 1997 Hospital IPPS proposed rule (61 FR 27466),52 the FY 1997 Hospital IPPS final rule (61 FR 46196), the FY 2006 Hospital IPPS final rule (70 FR 47407), and the FY 2010 Hospita l IPPS final rule (74 FR 43857). The strength of this methodology is that it refl ects the vintage nature of capital, which represents the acquisition a nd 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 descri be the sources of the major category weights and their subcategories in the FY 2010-based SNF market basket.
TABLE 9: FY 2010-based SNF Mark et Basket Major Cost Weights

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 sa laries cost category using the FY 2010 SNF MCRs. We determined the sh are using Medicare allowable wages and salaries from Worksheet S-3, part II and to tal expenses from Worksheet B, part I. Medicare allowable wages and sa laries are equal to total wages and salaries minus: (1) excluded salaries from worksheet S-3, part II; and (2) nursing facility and nonreimbursable 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 th e SNF, and does not include the wages and53

salaries from contract labor, which are allocated to wages an d 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 shar e using Medicare allowable benefit costs from Worksheet S-3, part II and total expens es from Worksheet B. Medicare allowable benefits are equal to total benefits from Worksheet S-3, part II, minus excluded (nonMedicare allowable) benefits. Non-Medi care 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-ba sed SNF market basket.

● Contract Labor : We determined the weight fo r contract labor using 2010 SNF MCR data. We derived the share using Medi care 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 ma rket basket, we propose to allocate contract labor costs to the wages and salari es and employee benefits cost weights based on their relative proportion, under the assump tion that contract costs are similarly distributed and likely to change at the same rate as dire ct labor costs even though unit labor cost levels may be different. The cont ract labor allocation pr oportion for wages and54 salaries is equal to the wages and salaries cost weight as a percent of the sum of the wages and salaries cost wei ght and the employee benefits cost weight. Using the FY 2010 MCR data, this percentage is approximate ly 81 percent; therefore, we propose to allocate approximately 81 percent of the c ontract labor cost wei ght to the wages and salaries cost weight. The remaining proportion of the c ontract labor co st weight is allocated to the employee benefits cost wei ght. Table 10 shows the wages and salaries and employee benefit cost weights after co ntract labor allocation for both the FY 2004- based SNF market basket and the propos ed FY 2010-based SNF market basket. TABLE 10: Wages and Salaries and Em ployee Benefits Cost Weights after Contract Labor Allocation

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 wei ght was about 2 percentage po ints lower than the FY 2004- based SNF market basket wages and salari es 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 th e 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 we ight from the FY 2004-based SNF market basket contract labor cost wei ght, of which 81 percent of this increase is applied to the55 wages and salaries cost wei ght 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 c ontract 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 cost s using the non-salary costs from the Pharmacy cost center and the Drugs Charge d to Patients’ cost center, both found on Worksheet B of the SNF MCRs. Since these dr ug costs were attributable to the entire SNF and not limited to Medicare allowable se rvices, we adjusted the drug costs by the ratio of Medicare allowable pharmacy total co sts 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 cost s” (in which pharmacy costs are included) to the Medicare allowable and non-Medicare allowabl e 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 co st 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 Medica id drug expenditures is explained in detail below. This Medica id drug add-on increases the drug expenditure weight to over seven percent, and is c onsistent 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 M CR 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 Medi caid drug costs based on data representing56 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 Medica re Part D benefit, which would work directly with the pharmacy, a nd therefore, these costs woul d 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 Medi caid Statistical Information System, which yielded a dual eligible Medi caid 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 prov ides drug expenditure data for dual-eligible beneficiaries for 2010. The Medicaid Statis tical Information System is no longer a comprehensive database for dual-elig ible beneficiaries’ drug costs. The proposed adjusted FY 2010-based SNF market basket drug cost weight, representing all drug expend itures including those we estim ated 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 professiona l liability insurance cost weight for the proposed FY 2010-based SN F market basket, we used the same cost57 report methodology that was used to derive th e cost weight of the FY 2004-based SNF market basket (see 72 FR 25543-25544). Fo r the proposed FY 2010-based SNF market basket, the professional liability weight is 1.141 percent, which is sli ghtly 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 allowa ble 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 wei ght (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 ba sket depreciation cost weight of 2.301 percent. This depreciati on cost weight is furt her adjusted to account for a proportion of leasing expenses, which is described in more detail below. We determined the distribution between bu ilding and fixed equipment and movable equipment depreciation from the FY 2010 SN F 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-rela ted expenses from58

Worksheet A from the FY 2010 SNF MCRs. Sim ilar to the depreciation cost weight, we calculated the interest cost weight using tota l facility costs. As done with the last rebasing, we determined the split of interest expense between for-pro fit and not-for-profit facilities based on the distribu tion of long-term debt outstanding by type of SNF (forprofit or not-for-profit) from the FY 2010 SN F 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 capita l-related expenses attributable to leasing and other capitalrelated 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 cap ital-related expenses. In the FY 2004-based SNF market basket, l easing 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 sepa rate cost category, but are distributed among the cost categories of depreciation, interest, and ot her capital, reflecting the assumption that the underlying cost structure and price movement of leasing expenses is similar to capital costs in ge neral. As was done in prev ious 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, intere st, and other capital expenses to total capital costs, excluding lease expenses.59 Table 11 shows the capital-re lated 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-rel ated Expense Distribution of the FY 2010-based SNF market basket and th e FY 2004-based SNF market basket

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 pric e change of capital-related expenses accounts for the vintage nature of capital, wh ich is the acquisition and use of capital over time. To capture this vintage nature, the pr ice proxies must be vintage-weighted. The determination of these vintage weights occurs in two steps. First, we must determine the expected useful life of capita l 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 re basing. The specifics of the da ta 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 publ ishes various useful life-related statistics, including asset service lives a nd current-cost average age, historical cost average age, and60 industry-specific current cost net stocks of assets. While SNF-specific data are not available, we can use the BEA data to de velop estimates of useful life that are approximates of SNF capital purchases. There are two major issues we must addr ess 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), electrom edical equipment (9 years), me dical instruments and related equipment (12 years), communi cation 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 build ings (36 years), hospita ls and special care buildings (48 years), and lodgi ng (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 applic able 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 availabl e service life of an asse t, 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 approxima te movable and fixed asset ages for nursing and residential care se rvices (NAICS 623) using the published BEA data. For the61 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) a nd weight them using current cost net stock levels for each of th ese asset types in the nursing and residential care services industry. Current cost net stock levels are avai lable for download from the BEA website at http://www.bea.gov/national/F A2004/Details/Index.html. These detailed current cost net stock estim ates are not published in the Survey of Current Business, a U.S. Department of Commerce m onthly 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-speci fic historical cost av erage 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 a ll industries. This produces historical cost average age data for movabl e and fixed assets speci fic to NAICS 6230 of 3.2 and 12.2 years, respectively. Since averag es 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 asse ts, which we round to 6 and 25 years, respectively. We are proposing an interest vintage weight ti me span of 22 years, obtained by weighting the fixed and movable vintage we ights (25 years and 6 years, respectively) by the fixed and movable split (85 percen t 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 weight s. We were not able to find a historical time series of capita l expenditures by SNFs. Therefore, we approximated the capital expend iture patterns of SNFs over time, using alternative SNF62 data sources. For building and fixed equipmen t, 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 th e growth in capital-related costs in SNFs for building and fixed equipment. We believ e 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 likel y 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 esti mate 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 chan ges in intensity in SNF services, which are assumed to be associated with movable e quipment purchase pattern s. The assumption here is that as ancillary costs increase co mpared 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 ove r time required us to use alternative SNF data sources. We believe the resulting two time series, determined from beds and the63 ratio of ancillary to routine costs, reflect real capital pur chases of building and fixed equipment and movable equipment over time. To obtain nominal purchases, which are us ed to determine the vintage weights for interest, we converted the two real ca pital purchase series from 1963 through 2010 determined above to nominal capital purchase se ries using their respective price proxies (the BEA chained price index for nonresidenti al construction for hospitals & special care facilities and the PPI for Machinery and E quipment). We then combined the two nominal series into one nominal capital pur chase series for 1963 through 2010. Nominal capital purchases are needed for interest vi ntage weights to captur e the value of debt instruments. Once we created these capital purchase time series for 1963 through 2010, we averaged different periods to obtain an averag e 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 to tal amount of purchases during the expected useful life of the equipment or debt inst rument. 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 website at http://www.cms.gov/Research-StatisticsData-and-Systems/Statistics-Trends-andReports/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.64
TABLE 12: Vintage Weights for Proposed FY 2010-Based SNF PPS Capital-Related Price Proxies

Year 1 Building and Fixed Equipment Movable Equipment Interest 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* SOURCES: 2010 SNF MCRs; CMS, NOTE: Totals may not sum to 1.000 due to rounding. 1 Year 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.

● All Other (residual) : We divided the residual “a ll other” cost category into65 subcategories, using the BEA’s Benchmark Input-Output Tables for the nursing home industry aged to 2010 using rela tive price changes. (The methodology we used to age the data involves applying the annual price change s from the price proxies to the appropriate cost categories. We repeat this practice fo r 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-base d SNF market basket, as discussed further below. We are also proposing to revise th e labels for the labor-i ntensive and nonlaborintensive cost categories; the new labels w ould be “all other: la bor-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 th e 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 accu rately reflect the concepts that they are intended to convey. We are not proposing a ch ange to our definiti on of the labor-related share, since we continue to classify a cost category as labor-related if the costs are laborintensive 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-relate d, and (2) nonmedical professional fees: nonlabor-re lated. We discuss the dis tinction between these two categories in more detail below in the discussion of the labor-related share. Table 13 compares the proposed FY 2010-ba sed SNF market bask et cost weights with the FY 2004-based SNF mark et basket cost weights.66
TABLE 13: Comparison of the Proposed FY 2010-based SNF Ma rket Basket Cost Weights and the FY 2004-based SNF Market Basket Cost Weights

Cost Category Proposed FY 2010-based SNF Market Basket Weights FY 2004- based SNF

Market Basket Weights 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 Fees(1) - 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 Supplies(2) 0.764 - Rubber and Plastics 0.981 1.513 Paper and Printing Products 0.838 1.394 Apparel (2) 0.195 - Machinery and Equipment (2) 0.190 - Miscellaneous Products 0.291 1.582 All Other Services 11.035 6.418 Labor-Related Services 6.227Nonmedical Professional Fees: Laborrelated (1) 3.427 - Administra tive and Facilities Support (3) 0.497 - All Other: Labor-Related Services(4) 2.303 3.521 NonLabor-Related Services 4.808 - Nonmedical Professional Fees: Nonlabor-related (1) 2.042 - Financial Services (5) 0.899 - Telephone Services 0.572 0.434 Postage 0.240 0.45467

Cost Category Proposed FY 2010-based SNF Market Basket Weights FY 2004- based SNF

Market Basket Weights All Other: N onlabor-related Services (4) 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 (1) For the FY 2010-based SNF Market basket, we are proposing to divide this category into nonmedical professional fees: labor-related and nonmedical professional fees: nonlaborrelated. (2) For the FY 2010-based SNF Market basket, we are proposing to create a separate cost category for these expenses to proxy the pr ice growth by a more specific index. These expenses were previously classified under miscellaneous products in the FY 2004-based SNF market basket. (3) For the FY 2010-based SNF Market basket, we are proposing to create a separate cost category for these expenses to proxy the pr ice growth by a more specific index. These expenses were previously classified under labor intensive serv ices cost weight in the FY 2004-based SNF market basket. (4) For the FY 2010-based SNF market basket, we are proposing to revise the labels for the laborintensive and nonlabor-intensive cost categories to be all other: labor-related and all other: nonlabor-related. (5) For the FY 2010-based SNF market basket, we are proposing to create a separate cost category for these expenses to proxy the pr ice 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.
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 appr opriate wage and price proxies currently available to represent the rate of change for each expenditure category. With four exceptions (three for the capital-related expens es cost categories and one for Professional Liability Insurance (PLI)), we base the wa ge and price proxies on Bureau of Labor Statistics (BLS) data, and group them in to one of the following BLS categories:68

• 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 pr ice indexes because they are not affected by shifts in occupation or industry mix, and becau se they measure pure price change and are available by both occupational group and by i ndustry. The industry ECIs are based on the 2004 North American Industry Cla ssification 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 th an 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. Re liability 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 i ndicates that the sample reflects the typical members of the population. (Sampling variab ility is variation th at 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 th erefore, it is importa nt for the underlying69 price proxies to be up-to-date, reflecting the mo st recent data available. We believe that using proxies that are publishe d 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, beca use we believe that this is an optimal way to stay abreast of the most curre nt 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 bask et updates are as transparent to the public as possible. In addition, this enab les the public to be able to ob tain 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 appl ied. The CPIs, PPIs, and ECIs that we have selected to propose in this regulation meet thes e criteria. Therefore, we believe that they continue to be the best meas ure 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 incorpor ate these data, as appr opriate, into the FY 2010-based SNF market basket for the final ru le. In addition, we propose that to the extent the incorporation of the 2007 Benc hmark 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 appropr iate 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 us ed for each cost category weight.70

• 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 wag es and salaries for nursing and residential care facilities (NAICS 623) and 50 percent of the EC I 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 th at provide a mix of health and social services, with many of the health servic es being largely some level of nursing services. Within NAICS 623 is NAICS 6231, which includes nursi ng care facilities primarily engaged in providing inpatient nursing and re habilitative services. Thes e facilities, which are most comparable to Medicare-certified SNFs, provi de skilled nursing a nd continuous personal care services for an extended period of time, a nd 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 deta iled nursing care f acilities (NAICS 6231), and therefore, IGI, the economic forecasting fi rm, 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 IG I to create a forecast for this detailed index. Additionally, in analyzi ng the historical trends, we be lieve this ECI is the most technically appropriate wage concept to use for the propos ed revised and rebased 2010- based SNF market basket as it is most compar able to Medicare-certified SNFs, which are engaged in providing inpatient nursi ng 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 for71
Nursing Care Facilities is calculated usi ng 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 wa ges 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 th e PPI for Commercial Natural Gas (BLS series code WPU0552) to measure th e 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 us e the CPI for Water and Sewerage Maintenance (All Urban Consumer s) (BLS series code CUUR0000SEHG01) to measure the price growth of this cost ca tegory. 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 re search alternative data sources, such as obtaining the data directly from the individua l states’ Departments of Insurance. We were unable to find a reliable data source that collects SNF-sp ecific PLI data. Therefore, we are proposing to use the CMS Hospital Professional Liability Index, which tracks price changes for commercial insurance premiu ms for a fixed level of coverage, holding nonprice factors constant (such as a change in the level of coverage). We used the same72

index in the FY 2004-based SNF ma rket basket. We believe th is is an appropriate proxy to measure the price growth associated with SNF professional liability insurance, as it captures the price inflation associated with ot her 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 pr oxy 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 th e 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 seri es code PCU32551-32551), Soap and Cleaning Compound Manufacturing (NAICS 325610) (BLS series code PCU32561– 32561), and All Other Chemical Product a nd Preparation Manufacturing (NAICS 3259A0) (BLS series code PCU3259—3259). Using the 2002 Benchmark I-O data, we f ound that these four NAICS industries accounted for approximately 95 percent of SN F chemical expenses. The remaining 573 percent of SNF chemical expenses are fo r 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 chem ical 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 be tween the proposed and final rule with sufficient time to incorporate such data into the final rule, we w ould incorporate these data, as appropriate, into th e 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 refl ect these more recent da ta on SNF chemical purchases, to better align th e costs with its price proxy. Table 14 below provides the weights for the blended chemical index. TABLE 14: Proposed Chemical Blended Index Weights NAICS Industry Description Weights 325190 Other basic organic chemical manufacturing 7% 325510 Paint and coating manufacturing 12% 325610 Soap and cleaning compound manufacturing 49%
3259A0 All other chemical pr oduct 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 belie ve our proposed chemical blended index for the FY 2010-based SNF market basket is te chnically 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 the74 price growth of this cost category. Th e 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 expens es by a more specific price index that better reflects the price grow th 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 measur e 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 cate gory. The FY 2004-based SNF market basket did not have a separate cost category for these expenses. Rather, these expenses were classified in the miscellane ous 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 se parate cost category for these expenses. Rather, these expenses were classified in the miscellane ous products cost category and proxied by the PPI for Finished Goods le ss Food and Energy (BLS series code75 WPUSOP3500). As stated above, we are propos ing 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 cha nge in the Miscellaneous Products cost category, we are proposing to us e 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-Rel ated and Nonmedical Professional Fees: Nonlabor-Related: We are proposing to use the ECI for Total Compensation for Professional and Related Occupations (P rivate Industry) (BLS series code CIU2010000120000I) to measure the price growth of these categories. As described in more detail below, for this revising and re basing of the SNF market basket we are proposing to divide the nonmedical professi onal fees cost categor y into two separate cost categories: (1) nonmedi cal professional fees : labor-related; and (2) nonmedical professional fees: nonlabor-rela ted. 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 geogr aphic 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 this76 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 Se rvice Occupations (Pri vate Industry). As stated above, we are proposing to create a separate cost cat egory 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 (P rivate Industry) (BLS series code CIU2010000300000I) to measure the price growth of this cost ca tegory (previously referred to as the labor-intensive cost cate gory 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: labo r-related services.

• Financial Services : We are proposing to use th e ECI for Total Compensation for Financial Activities (Private Indust ry) (BLS series code CIU201520A000000I) to measure the price growth of this cost cat egory. The FY 2004-based SNF market basket did not have a separate cost category for th ese 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 propos ing to create a separate cost category for these expenses to reflect th e specific price changes asso ciated 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.77

• 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 nonl abor-intensive cost category in the FY 2004-based SNF market bask et 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 doublecounting of food and energy prices, which are already captured elsewhere in the market basket. Consequently, we believe that th e incorporation of this proxy represents a technical improvement to the market basket.

• Capital-Related Expenses : For the capital price pr oxies (with the exception of the price proxy for the other capital-related cost category we ight), we calculate vintage weighted price proxies. Th e methodology used to derive the vintage weights was described above. Below, we describe th e 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 sp ecial 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 inde x used the Boeckh Institutional Construction Index, which is not publicly av ailable. We compared the BEA index with the Boeckh Institutional Construction Inde x and found that the av erage growth rates in the two series78 were similar over the historical time peri od. We are proposing to use the BEA price index in the FY 2010-based SNF ma rket basket as this index is a publicly available index that reflects the price inflati on associated with nonresidenti al construction, such as the construction of hospitals and sp ecial 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 fo r Machinery and Equipment (BLS series code WPU11). The same price proxy was us ed 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 Av erage 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 pr oxy. While SNFs may face different interest rate levels than those include d 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 cha nge in this cost category, we are proposing to use the Average Yiel d for Moody's AAA Corporate Bonds. Again, the proposed revised and rebased SNF market ba sket 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.79

• 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 s lightly different as we have provided the full BLS naming convention. Table 15 shows the propos ed price proxies for the FY 2010-based SNF Market Basket. TABLE 15: Proposed Price Proxies fo r the FY 2010-based SNF Market Basket 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 11.03580
Cost Category Weight Proposed Price Proxy 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 f acilities - 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 prop osed 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 wi th history through the fourth quarter81 of 2012, the most recent estimate of the propos ed FY 2010-based SNF market basket for FY 2014 is 2.3 percent. IG I 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-ba sed 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 betw een the two market baskets is -0.3 percentage point. This is primarily the re sult 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

Fiscal Year (FY) Proposed Rebased FY 2010-based SNF Market Basket FY 2004-based SNF Basket 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 Source: IHS Global Insight, Inc. 1s t quarter 2013 forecast with historical data through 4th quarter 2012

5. Labor-related Share82 We define the labor-related share (LRS) as those expenses that are labor-intensive and vary with, or are influenced by, the loca l labor market. Each year, we calculate a revised labor-related share based on the re lative 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-re lated share to reflect the relative importance of the following proposed FY 2010-based SNF market ba sket cost weights that we believe are labor-intensive and vary with, or are influen ced by, the local labor market: (1) wages and salaries; (2) employee benefits ; (3) contract labor; (4) th e labor-relate d portion of nonmedical professional fees; (5) administrativ e and facilities suppor t 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-r elated expenses. We are proposing to continue to in clude a proportion of capital-r elated 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 comp rised of building maintenance and security services (including, but not lim ited to, commercial and industrial machinery and equipment repair, nonresidential main tenance and repair, and investigation and security services). Because these services tend to be la bor-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 of83 the administrative and facilities support serv ices 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 SN F market basket labor-intensive cost category. As previously stated, we are propos ing to establish a se parate administrative and facilities support services cost categor y so that we can use the ECI for Total Compensation for Office and Admi nistrative 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 a nd auditing services, engineering services, legal services, and management and consulti ng services) were purchased in the local labor market and, thus, all of their associated fees varied with the lo cal 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 attri butable to local firms and th e 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 wei ghted 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.84

● 89 percent of architectur al, engineering services.

● 78 percent of legal services.

● 87 percent of manageme nt consulting services. Together, these four categor ies represent 2.672 percentage points of th e total costs for the proposed FY 2010-based SNF market ba sket. We applied the percentages from this special survey to their respective SNF ma rket 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, withthe remaining 0.387 categorized as nonlaborrelated. In addition to the professional services lis ted 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 ca tegory 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 th eir home office, we analyzed data from a variety of sources to determine what pro portion of these costs should be appropriately include d in the labor-related share. Our proposed methodology is based on data from the MCRs, as well as a CMS database of Home Office Medi care Records (HOMER) (a data base that provides city and state information (addresses) fo r 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 of fice. We propose to determine the proportion85

of NAICS 55 costs that should be allocated to the labor-relat ed 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 informati on from the MCR, while a home office MSA was determined using the Medicare HOMER Database, which pr ovided a home office Zip Code, as well. As stated above, we are proposing to de termine the proportion of NAICS 55 costs that should be allocated to the labor-relat ed share based on the percent of SNF home office compensation attributable to those SN Fs that had home offices located in their respective labor markets. Using this proposed methodology, we determined that 32 percent of SNF home office compensation cost s were for SNFs that had home offices located in their respective lo cal labor markets; therefore, we propos e 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 sh are, 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 es timate 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 th e 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 percen tage points as nonlabor-related.86

The Benchmark I-O data contains other sm aller cost categories that we allocate fully to either “nonmedical professional fees : labor-related” or “nonmedical professional fees: nonlabor-related.” Toge ther, the sum of these smalle r 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 percenta ge 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 categorie s 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 SN F market basket, compared to the laborrelated share that was used for the FY 2013 SNF PPS update. TABLE 17: Labor-related Relative Importance, FY 2013 and FY 2014 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 Wages and salaries 1 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 services 2 3.364 2.292 Capital-related (.391) 2.333 2.770 Total 68.383 69.764 1 As discussed above in section V.A.2 in this preambl e, the wages and salaries and employee benefits cost weight reflect contract labor costs. 2 Previously referred to as labor-in tensive services cost category in th e FY 2004-based SNF market basket. B. Monitoring Impact of FY 2012 Policy Changes87
In the FY 2012 SNF PPS final rule, we st ated 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 website which highlight some of the trends we have observed over a given time period. These memos may be accessed through the SNF PPS website at http://www.cms.gov/Medicar e/Medicare-Fee-forService-Payment/SNFPPS/Downloads/SNF_Monitoring.zip

. Below, we provide a summary of the resu lts derived from this monitoring effort. 1. RUG Distributions As stated in the FY 2012 SNF PPS final rule (76 FR 48493), th e 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 utiliz ation 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 reca librated parity adjustment. We have posted data illustrating the RUG-IV distribution of days for th e entirety of FY 2011, as compared to the days distribution used to cal culate the parity adjustment in the FY 201288 final rule, and the distribution of days for FY 2012, all of which may be found athttp://www.cms.gov/Medicare/Medicare-Fee-for-ServicePayment/SNFPPS/Downloads/SNF_Monitoring.zip. Additionally, case-mix utilization ob served during FY 2012 has not shown unanticipated changes in patient classifi cation. 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 serv ice days by the major RUG classification categories for FY 2011 and FY 2012.
TABLE 18: SNF Case-Mix Distribu tions by Major RUG-IV Category
FY 2011 FY 2012 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 ad justment 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 classificat ion (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 aforemen tioned case-mix distribution shifts reflect89 residents that had previously been classified into therapy groups but now index maximize into nursing groups instead. Looking specifically at the case-mix di stribution for Rehab ilitation RUGs only, the data show an increase in the percentage of service days at th e 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
FY 2011 FY 2012 Ultra-High Rehabilitation ( ≥ 720 minutes of therapy per week) 44.8% 48.6% Very-High Rehabilitation (500 – 719 mi nutes of therapy per week) 26.9% 25.6% High Rehabilitation (325 – 499 minut es of therapy per week) 10.8% 10.1% Medium Rehabilitation (150 – 324 minut es 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 pe rcentage of service days wh ich classify into the VeryHigh, 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 ma ximization into the Special Care RUG-IV category. 2. Group Therapy Allocation To account more accurately for resource ut ilization 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 woul d result in some change to the type of therapy mode (that is, individua l, concurrent, or group) used for SNF residents. As noted in the section above, we have not observed a ny significant difference in patient case mix. However, as illustrated in Table 20, providers have significantly changed the mode of therapy since our STRI VE study (2006-2007). TABLE 20: Mode of Therapy Provision90

STRIVE FY 2011 FY 2012 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 concur rent 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 gr oup therapy, and data from FY 2012 indicate that facilities are prov iding 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 ther apy services provided to SNF residents. Effective for services provided on or af ter 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 classificat ion 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 cas es where the resident’s therapy has changed to such a degree that it is no longer consis tent with the resident’s current RUG-IV91 classification, then the SNF must complete a COT OMRA to reclassify the resident into the appropriate RUG-IV category. The ne w RUG-IV group resulting from the COT OMRA is billed starting the first day of th e 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
FY 2011 FY 2012 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/ Resump tion) (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 OM RA, 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 website

at http://www.cms.gov/Medicare/M edicare-Fee-for-ServicePayment/SNFPPS/Downloads/SNF_Monitoring.zip . Based on the data reviewed thus far, we have found no evidence of the possi ble 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 th e combined impact of the recalibration of the92 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 ha s not been affected significantly, which suggests that the aforementioned changes, wh ile ensuring more accurate payment, have been absorbed into facility pr actices 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 informati on to the aforementioned website only as appropriate. C. Ensuring Accuracy in Grouping to Rehabilitation RUG-IV Categories As noted in section III.C of this propos ed rule, under secti on 1888(e)(4)(G)(i) of the Act, the federal rate incorporates an adju stment to account for facility case mix, using a classification system that accounts for th e relative resource utili zation 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 nur sing home patients and to provide an improved method of tracking the quality of thei r care. In 1998, the first version of RUGIII was a 44-group model for classifying SNF patients into homogeneous groups according to their clinical ch aracteristics and the amount and type of resources they use as measured by the Resident Assessment In strument, the Minimum Data Set (MDS). A detailed description of the RUG-III groups appe ars 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 equita ble prospective payment levels for patients with different service use. In FY 2006, the RUG-III classification sy stem was refined to include 53 groups93

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 compri sing a new Extensive Services plus Rehabilitation payment cat egory, to account for the higher cost of beneficiaries requiring both re habilitation and certain high-in tensity medical services. A detailed explanation of the RUG-III refineme nt 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 pa tient 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 propos ed 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 pe r 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 rece ive at least 150 minutes of therapy of any combination of the three rehabilitation disciplines: physical therapy, occupational therapy, and speech therapy. Subsequently, across all itera tions 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 re mained the same. As set forth in the FY 2010 final rule (74 FR 40389), to be classifi ed into the Medium Rehab category under94
RUG III or RUG IV, the resident must re ceive “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 Servic es 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 refl ects the SNF level of care requirement under §409.31(b)(1) that skilled services must be need ed and received on a daily basis, and the provision at §409.34(a)(2) which spec ifies that the “daily basi s” 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 R UG groups were based on staff time over the requisite number of distinct therapy da ys. For example, the policy would be implemented correctly if a patie nt received a total of 150 minut es of therapy in the form of physical therapy on Monday and Wednesd ay, 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 Hi gh 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 Ex tensive Services qualifiers remained the same under the SNF PPS from 1998 until th e 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 part icular resident receives duri ng 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 di scussed above) to classify95 inappropriately into those RUG categories. For example, a resident receives 150 minutes of therapy in the form of physical ther apy 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 cl assification 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 lookback period, without distinguishing between di stinct 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 de scribed above to be classified into the Medium Rehab category even though the reside nt did not actually receive 5 distinct calendar days of therapy as required by the cr iteria. This resident would not meet the classification criteria for the Medium Rehab cat egory 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 Servic es categories, which require rehabilitation services for at least 45 minutes a week with three days of any combination of the three rehabilitation disciplines (a nd restorative nursing 6 days per week). Similar to the Medium Rehab classification criteria, the inte nt here, as well, is to require distinct calendar days of therapy during the 7-day l ook-back period (in this case, 3 distinct calendar days of therapy). For example, this policy would be impleme nted correctly if a resident received a total of 90 minutes of therapy in the form of physical therapy on96 Monday and Wednesday, occupational thera py 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 resident s who do not meet the Low Rehab qualifiers under the intended policy to classify inappropr iately 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 receiv ed 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 clas sified in a Low Rehab RUG. As explained above, we are clarifying th at our classificati on criteria for the Rehabilitation RUG categories require that th e resident receive the requisite number of distinct calendar days of therapy to be clas sified 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 dis tinct calendar days of thera py provided by all rehabilitation disciplines, allowing some residents to be cl assified into Rehabilitation RUG categories when they do not actually meet our classificati on 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 cla ssification criteria as intended, we propose to add item O0420 to the MDS Item Set, Dist inct 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 assessmen t, which would be used to classify the resident into the correct Rehabilitation RUG category. We invite comments on our97 proposal to add this item to the MDS Item Set so that we may properly implement our Rehabilitation RUG classification criteria ba sed on the number of distinct calendar days of therapy a patient recei ved, as described above. D. SNF Therapy Research Project Currently, the therapy paymen t rate component of the SN F PPS is based solely on the amount of therapy provided to a patient during the 7-day look-b ack period, regardless of the specific patient characteristics. The am ount of therapy a patient receives is used to classify the resident into a RUG category, wh ich 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 proj ect 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 fo r therapy services under the SNF PPS. Comments may be included as part of comments on this pr oposed rule. We are also soliciting comments outside the comment peri od 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 website athttp://www.cms.gov/Medicare/Medicare-Fee-for-ServicePayment/SNFPPS/therapyresearch.html. VI. Provisions of the Proposed Rule and Technical Correction As discussed in section III. of this pr oposed rule, this proposed rule would update the payment rates under the SNF PPS for FY 2014 as required by section98 1888(e)(4)(E)(ii). Also, as discussed in sec tion III.B.3. of this proposed rule, we propose that when the forecast error, rounded to one si gnificant digit, is 0.5 percentage point, we would calculate the forecast erro r to 2 significant digits in or der 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 conve rsion 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 appr opriate 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 pr evious 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 refl ect a base year of FY 2010, and to use this revised and rebased market basket to dete rmine the SNF market basket percentage increase for 2014. In addition, we propose to re vise the labor-related share to reflect the relative importance of the la bor-related cost weights in the proposed FY 2010-based SNF market basket. Also, as discu ssed in section V.C. of this pr oposed rule, to help ensure accuracy in grouping to the rehabilitation R UG categories, we propose to add item O0420 to the MDS Item Set, which would require f acilities to record th e number of distinct calendar days of therapy provided by all th e rehabilitation discip lines over the 7-day look-back period for the current assessment. In addition, as discussed ear lier in this proposed rule , we are proposing to adopt99 an approach already being followed by othe r 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 website at http://www.cms.gov/Medicare/Medicare-Fee-forService-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 sec tion 1888(e)(4)(H)(iii), to state that CMS publishes in the Federal Register “the factors to be applie d 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 adjust ment), effective October 1, 2013, it would no longer include a listing of the individual wa ge index values themselves, which would instead be made available exclusively th rough the Internet on the CMS website. Further, we propose to make a minor techni cal correction in the regulations text at §424.11(e)(4), regarding the type s of practitioners (in addi tion to physicians) that can sign the required SNF level of car e certification and recertifica tions. In the calendar year (CY) 2011 Medicare Physician Fee Schedule (M PFS) final rule with comment period (75 FR 73387, 73602, 73626-27), we revised the regu lations 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. Ho wever, we inadvertently neglected to make a conforming revision in the regulations text at §424.11(e)(4), an omission that we now100 propose to rectify. VII. Collection of Information Requirements 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 collecti on 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 auto mated collection techniques. We are soliciting public comment on each of the section 3506(c)(2)(A)-required issues for the following informati on 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, Pub. L. 100-203 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 ce rtain data items that are co llected 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.101 As discussed in section V.C. of the pr eamble, this rule proposes to add PPSrelated Item O0420 to the MDS 3.0 form to cap ture the number of distinct calendar days a SNF resident has received therapy in a se ven-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 w ould be added to ensure that our existing Rehabilitation RUG classification policies are properl y 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 measurab le adjustments to our burden estimates. Consequently, we are not revising the burde n estimates that have been approved under OCN 0938-1140 (CMS-R-250) for the Nursing Ho me 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 recordkeep ing requirements. These requirements are not effective until they have been approved by the OMB. To obtain copies of the supporting st atement and any related forms for the proposed paperwork collection referen ced above, access CMS’ website at http://www.cms.hhs.gov/PaperworkReductionActof1995 , or email your request, including your address, phone number, OM B 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:102 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, Attent ion: CMS Desk Officer, (CMS–1446–P) Fax: (202) 395–6974; or E-mail: OIRA_submission@omb.eop.gov

. VIII. Response to Comments Because of the large number of public comments we normally receive on Federal Register documents, we are not able to acknowle dge or respond to them individually. We will consider all comments we receive by th e 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 A. Regulatory Impact Analysis 1. Introduction We have examined the impacts of this proposed rule as required by Executive Order 12866 on Regulatory Pla nning and Review (September 30, 1993), Executive Order 13563 on Improving Regulation and Regulator y Review (January 18, 2011), the Regulatory Flexibility Act (RFA) (Septemb er 19, 1980, Pub. L. 96-354), 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 agenci es to assess all costs and benefits of available regulatory alterna tives and, if regulation is n ecessary, to select regulatory approaches that maximize net benefits (inc luding potential economi c, environmental,103 public health and safety effects, distributive impacts, and equity). Executive Order 13563 emphasizes the importance of quantifying both co sts and benefits, of reducing costs, of harmonizing rules, and of promoting flexibil ity. This rule has been designated an economically significant rule, under secti on 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 SN F 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 th e start of each fiscal year, of the unadjusted federal per diem rates, the case-mi x 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 di sseminating 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 upda tes 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 th e payment rates, as adjusted by the MFP adjustment and forecast error correction. Th e impact analysis of this proposed rule represents the projected effect s 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 adju stments for future changes in such variables104 as days or case-mix. Certain events may occur to limit the scope or accuracy of our impact analysis, as this analysis is future-orien ted and, thus, very susceptible to forecasting errors due to certain events that may occur within the assessed impact tim e period. Some examples of possible events may include newly-legislated general Medicare program funding changes by the Congress, or changes specifically rela ted 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 thes e changes may not be specific to the SNF PPS, the nature of the Medicare program is su ch that the changes may interact and, thus, the complexity of the interaction of thes e 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 Ca re 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 Secret ary 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 include d in the “total” column of Table 22. In updating the SNF rates for FY 2014, we made a number of sta ndard annual revisions and clarifications105 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 th e resulting payments according to the classifications in Table 22, e .g. facility type, geographic re gion, facility ownership, and compare the difference between current and proposed payments to determine the overall impact. The breakdown of the various categorie s of data in the table follows.
The first column shows the breakdown of all SNFs by urban or rural status, hospital-based or freestanding stat us, census region, and ownership. The first row of figures describes the es timated 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. Th e urban and rural designations are based on the location of the facility under the CBSA desi gnation. The next nineteen rows show the effects on facilities by urban versus rural st atus by census region. The last three rows show the effects on facilitie s by ownership (that is, govern ment, profit, and non-profit106 status). The second column in the table shows the number of facilities in the impact database. The third column of the ta ble shows the effect of the annual update to the wage index. This represents the eff ect of using the most recent wage data available. The total impact of this change is zero percent; how ever, 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 (consis ting of the market basket increase of 2.3 percentage points, reduced by the 0.5 per centage point forecast error correction and further reduced by the 0.4 percen tage 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 percen t, 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 faciliti es would experience payment increases, the projected impact on providers for FY 2014 varies due to the impact of the wage index update. For exampl e, 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 Impa ct to the SNF PPS for FY 2014
Number of

Facilities FY 2014 Update Wage Data Total FY 2014 Change Group Total 15,376 0.0% 1.4%107

Number of

Facilities FY 2014 Update Wage Data Total FY 2014 Change 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% 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.

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 SN Fs, resulting from the SNF market basket update to the payment rates, as adjusted by the forecast error co rrection and the MFP108 adjustment. Section 1888(e) of the Act establishes the SNF PPS for the payment of Medicare SNF services for cost reporting periods begi nning on or after July 1, 1998. This section of the statute prescribes a detailed formul a for calculating paymen t 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 Septembe r 30, 1995). In acco rdance with the statute, we also incorporated a number of el ements into the SNF PPS (for example, casemix classification methodology, a market basket index, a wage inde x, 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. Accordin gly, 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 st atement 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 th is 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).109
TABLE 23: Accounting Statement: Classi fication of Estimated Expenditures, from the 2013 SNF PPS Fiscal Year to the 2014 SNF PPS Fiscal Year Category Transfers Annualized Monetized Transfers $500 million* From Whom To Whom? Federal Gove rnment to SNF Medicare Providers * The net increase of $500 million in transfer paymen ts is a result of the MFP-adjusted market basket increase of $500 million.

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, respectiv ely, in estimated payments compared with FY 2013. Providers in the rural Pacifi c region would experience the largest estimated increase in payments of approximately 2.5 percent. Provi ders in the rural West South Central region would experience the sma llest 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 signi ficant impact on a substantial nu mber of small entities. For purposes of the RFA, small entities include small businesses, non-profit organizations, and small governmental jurisdictions. Most SN Fs 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 Sm all Business Administration's latest size standards (NAICS 623110), with total revenu es of $25.5 million or less in any 1 year.110 (For details, see the Small Busi ness Administrati on’s website at http://www.sba.gov/category/navigation- structure/contracting/contractingofficials/eligibility-size-standards ). Individuals and States are not included in the definition of a small entity. In addition, appr oximately 25 percent of SNFs classified as small entities are non-profit or ganizations. Finally, the estimated number of small business entities does no t 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 th e 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 ra tes, 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 experi ence 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 H ealth 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 unde r the RFA. According to MedPAC, Medicare covers appr oximately 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 worth111 noting that the distribution of da ys and payments is highly vari able. That is, the majority of SNFs have significantly lower Medicare ut ilization (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 imp act 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 ru le 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 opera tions 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 th e Act, we define a small rural hospital as a hospital that is located outsi de of a Metropolita n Statistical Area a nd 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 hospi tal-based SNF. We anticipate that the impact on small rural hospitals would be sim ilar 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 fac ilities 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 th reshold discussed above, the Secretary has112 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 i ssuing any rule whose mandates require spending in any 1 year of $100 million in 1995 dollars, updated annually for inflation. In 2013, that thre shold is approximately $141 million. This proposed rule would not impose spending costs on State, local, or tribal governments in the aggregate, or by the pr ivate sector, of $141 million. D. Federalism Analysis Executive Order 13132 establishes certain requ irements that an agency must meet when it promulgates a proposed rule (and subseq uent final rule) that impose substantial direct requirement costs on State and local gov ernments, preempts State law, or otherwise has federalism implications. This proposed ru le would have no substantial direct effect on State and local governments, preempt Stat e law, or otherwise have federalism implications.113
List of Subjects
42 CFR Part 413 Health facilities, Kidney diseases , Medicare, Reporting and recordkeeping requirements.
42 CFR Part 424 Emergency medical services, Health f acilities, Health professions, Medicare, Reporting and recordkeeping requirements.114 For the reasons set forth in the preamble, the Centers for Medicar e & Medicaid Services proposes to amend 42 CFR chapter IV as set forth below:
PART 413--PRINCIPLES OF REAS ONABLE COST REIMBURSEMENT;
PAYMENT FOR END-STAGE RENAL DISEASE SERVICES; OPTIONAL
PROSPECTIVELY DETERMINED PAYMENT RATES FOR SKILLED
NURSING FACILITIES 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 revise d 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 th e standardized Federal rates, the resident classification system that pr ovides the basis for case-mix adjustment (including the designation of those speci fic 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 3. The authority citation for part 424 continues to read as follows:115
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 pa ragraph (e)(4) to read as follows: §424.11 General procedures.
* * * * * (e) * * *
(4) A nurse practitioner or clinical nurse specialist as define d in paragraph (e)(5) or (e)(6) of this section, or a physician assistant as define d in section 1861 (aa)(5) of the Act, in the circumstances specified in §424.20(e).
* * * * *CMS-1446-P

Authority: (Catalog of Federal Domestic Assi stance Program No. 93.773, Medicare-- Hospital Insurance; and Program No. 93.774, Medicare--Supplementary Medical Insurance Program)

Dated: April 4, 2013

.

______________________________ Marilyn Tavenner, Acting Administrator, Centers for Medicare & Medicaid Services.

Approved: April 25, 2013

__________________________________ Kathleen Sebelius, Secretary.
BILLING CODE 4120-01-P117
Note: The following addendum will not appear in the Code of Federal Regulations. Addendum – FY 2014 CBSA Wage Index Tables In this addendum, we provide the wage inde x 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 propos ed rule, we are currently proposing to take an approach already being followed by other Medicare payment systems, whereby for SNF PPS rules and not ices published on or after October 1, 2013, these wage index tables woul d henceforth be made available exclusively through the Internet on the CMS website rather than being published in the Federal Register as part of the annual SNF PPS rulemaking.
TABLE A: FY 2014 WAGE INDEX FO R URBAN AREAS BA SED ON CBSA LABOR MARKET AREAS CBSA Code Urban Area (Constituent Counties) Wage Index 10180 Abilene, TX Callahan County, TX Jones County, TX Taylor County, TX 0.8260

10380 Aguadilla-Isabela-San Sebastián, PR 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 0.3662

10420 Akron, OH Portage County, OH Summit County, OH 0.8485118 10500 Albany, GA Baker County, GA Dougherty County, GA Lee County, GA Terrell County, GA Worth County, GA 0.8750

10580 Albany-Schenectady-Troy, NY Albany County, NY Rensselaer County, NY Saratoga County, NY Schenectady County, NY Schoharie County, NY 0.8636

10740 Albuquerque, NM Bernalillo County, NM Sandoval County, NM Torrance County, NM Valencia County, NM 0.9704

10780 Alexandria, LA Grant Parish, LA Rapides Parish, LA 0.7821

10900 Allentown-Bethlehem-Easton, PA-NJ Warren County, NJ Carbon County, PA Lehigh County, PA Northampton County, PA 0.9208

11020 Altoona, PA Blair County, PA 0.9140
11100 Amarillo, TX Armstrong County, TX Carson County, TX Potter County, TX Randall County, TX 0.8993

11180 Ames, IA Story County, IA 0.9465 11260 Anchorage, AK Anchorage Municipality, AK Matanuska-Susitna Borough, AK 1.2259

11300 Anderson, IN Madison County, IN 0.9694
11340 Anderson, SC Anderson County, SC 0.8803119 11460 Arbor, MI Washtenaw County, MI 1.0125
11500 Anniston-Oxford, AL Calhoun County, AL 0.7369 11540 Appleton, WI Calumet County, WI Outagamie County, WI 0.9485

11700 Asheville, NC Buncombe County, NC Haywood County, NC Henderson County, NC Madison County, NC 0.8508

12020 Athens-Clarke County, GA Clarke County, GA Madison County, GA Oconee County, GA Oglethorpe County, GA 0.9284120 12060 Atlanta-Sandy Springs-Marietta, GA 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 0.9465

12100 Atlantic City-Hammonton, NJ Atlantic County, NJ 1.2310 12220 Auburn-Opelika, AL Lee County, AL 0.7802 12260 Augusta-Richmond County, GA-SC Burke County, GA Columbia County, GA McDuffie County, GA Richmond County, GA Aiken County, SC Edgefield County, SC 0.9189121 12420 Austin-Round Rock, TX Bastrop County, TX Caldwell County, TX Hays County, TX Travis County, TX Williamson County, TX 0.9616

12540 Bakersfield, CA Kern County, CA 1.1730
12580 Baltimore-Towson, MD Anne Arundel County, MD Baltimore County, MD Carroll County, MD Harford County, MD Howard County, MD Queen Anne's County, MD Baltimore City, MD 0.9916

12620 Bangor, ME Penobscot County, ME 0.9751
12700 Barnstable Town, MA Barnstable County, MA 1.3062 12940 Baton Rouge, LA 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 0.8050

12980 Battle Creek, MI Calhoun County, MI 0.9763 13020 Bay City, MI Bay County, MI 0.9526
13140 Beaumont-Port Arthur, TX Hardin County, TX Jefferson County, TX Orange County, TX 0.8634

13380 Bellingham, WA Whatcom County, WA 1.1940122 13460 Bend, OR Deschutes County, OR 1.1857 13644 Bethesda-Frederick-Gaithersburg, MD Frederick County, MD Montgomery County, MD 1.0348

13740 Billings, MT Carbon County, MT Yellowstone County, MT 0.8727

13780 Binghamton, NY Broome County, NY Tioga County, NY 0.7863

13820 Birmingham-Hoover, AL Bibb County, AL Blount County, AL Chilton County, AL Jefferson County, AL St. Clair County, AL Shelby County, AL Walker County, AL 0.8395

13900 Bismarck, ND Burleigh County, ND Morton County, ND 0.7312

13980 Blacksburg-Christiansburg-Radford, VA Giles County, VA Montgomery County, VA Pulaski County, VA Radford City, VA 0.8354

14020 Bloomington, IN Greene County, IN Monroe County, IN Owen County, IN 0.9343

14060 Bloomington-Normal, IL McLean County, IL 0.9349 14260 Boise City-Nampa, ID Ada County, ID Boise County, ID Canyon County, ID Gem County, ID Owyhee County, ID 0.9298

14484 Boston-Quincy, MA Norfolk County, MA Plymouth County, MA Suffolk County, MA 1.2505123 14500 Boulder, CO Boulder County, CO 0.9891 14540 Bowling Green, KY Edmonson County, KY Warren County, KY 0.8314

14740 Bremerton-Silverdale, WA Kitsap County, WA 1.0311 14860 Bridgeport-Stamford-Norwalk, CT Fairfield County, CT 1.3287 15180 Brownsville-Harlingen, TX Cameron County, TX 0.8213
15260 Brunswick, GA Brantley County, GA Glynn County, GA McIntosh County, GA 0.7716

15380 Buffalo-Niagara Falls, NY Erie County, NY Niagara County, NY 1.0048

15500 Burlington, NC Alamance County, NC 0.8552 15540 Burlington-South Burlington, VT Chittenden County, VT Franklin County, VT Grand Isle County, VT 1.0173

15764 Cambridge-Newton-Framingham, MA Middlesex County, MA 1.1201
15804 Camden, NJ Burlington County, NJ Camden County, NJ Gloucester County, NJ 1.0297

15940 Canton-Massillon, OH Carroll County, OH Stark County, OH 0.8729

15980 Cape Coral-Fort Myers, FL Lee County, FL 0.8720 16020 Cape Girardeau-Jackson, MO-IL Alexander County, IL Bollinger County, MO Cape Girardeau County, MO 0.9213124 16180 Carson City, NV Carson City, NV 1.0767 16220 Casper, WY Natrona County, WY 1.0154 16300 Cedar Rapids, IA Benton County, IA Jones County, IA Linn County, IA 0.9001

16580 Champaign-Urbana, IL Champaign County, IL Ford County, IL Piatt County, IL 0.9450

16620 Charleston, WV Boone County, WV Clay County, WV Kanawha County, WV Lincoln County, WV Putnam County, WV 0.8147

16700 Charleston-North Charleston-Summerville, SC Berkeley County, SC Charleston County, SC Dorchester County, SC 0.9013

16740 Charlotte-Gastonia-Concord, NC-SC Anson County, NC Cabarrus County, NC Gaston County, NC Mecklenburg County, NC Union County, NC York County, SC 0.9479

16820 Charlottesville, VA Albemarle County, VA Fluvanna County, VA Greene County, VA Nelson County, VA Charlottesville City, VA 0.8443

16860 Chattanooga, TN-GA Catoosa County, GA Dade County, GA Walker County, GA Hamilton County, TN Marion County, TN Sequatchie County, TN 0.8499125 16940 Cheyenne, WY Laramie County, WY 0.9534 16974 Chicago-Naperville-Joliet, IL Cook County, IL DeKalb County, IL DuPage County, IL Grundy County, IL Kane County, IL Kendall County, IL McHenry County, IL Will County, IL 1.0446

17020 Chico, CA Butte County, CA 1.1637

17140 Cincinnati-Mi ddletown, OH-KY-IN 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 0.9382

17300 Clarksville, TN-KY Christian County, KY Trigg County, KY Montgomery County, TN Stewart County, TN 0.7376

17420 Cleveland, TN Bradley County, TN Polk County, TN 0.7528

17460 Cleveland-Elyria-Mentor, OH Cuyahoga County, OH Geauga County, OH Lake County, OH Lorain County, OH Medina County, OH 0.9306126 17660 Coeur d'Alene, ID Kootenai County, ID 0.9102 17780 College Station-Bryan, TX Brazos County, TX Burleson County, TX Robertson County, TX 0.9537

17820 Colorado Springs, CO El Paso County, CO Teller County, CO 0.9321

17860 Columbia, MO Boone County, MO Howard County, MO 0.8231

17900 Columbia, SC Calhoun County, SC Fairfield County, SC Kershaw County, SC Lexington County, SC Richland County, SC Saluda County, SC 0.8680

17980 Columbus, GA-AL Russell County, AL Chattahoochee County, GA Harris County, GA Marion County, GA Muscogee County, GA 0.7896

18020 Columbus, IN Bartholomew County, IN 0.9860
18140 Columbus, OH Delaware County, OH Fairfield County, OH Franklin County, OH Licking County, OH Madison County, OH Morrow County, OH Pickaway County, OH Union County, OH 0.9700

18580 Corpus Christi, TX Aransas County, TX Nueces County, TX San Patricio County, TX 0.8469

18700 Corvallis, OR Benton County, OR 1.0641127 18880 Crestview-Fort Walton Beach-Destin, FL Okaloosa County, FL 0.8948
19060 Cumberland, MD-WV Allegany County, MD Mineral County, WV 0.8088

19124 Dallas-Plano-Irving, TX Collin County, TX Dallas County, TX Delta County, TX Denton County, TX Ellis County, TX Hunt County, TX Kaufman County, TX Rockwall County, TX 0.9872

19140 Dalton, GA Murray County, GA Whitfield County, GA 0.8662

19180 Danville, IL Vermilion County, IL 0.9500
19260 Danville, VA Pittsylvania County, VA Danville City, VA 0.7921

19340 Davenport-Moline-Rock Island, IA-IL Henry County, IL Mercer County, IL Rock Island County, IL Scott County, IA 0.9345

19380 Dayton, OH Greene County, OH Miami County, OH Montgomery County, OH Preble County, OH 0.8941

19460 Decatur, AL Lawrence County, AL Morgan County, AL 0.7195

19500 Decatur, IL Macon County, IL 0.7946 19660 Deltona-Daytona Beach-Ormond Beach, FL Volusia County, FL 0.8596128 19740 Denver-Aurora-Broomfield, CO 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 1.0461

19780 Des Moines-West Des Moines, IA Dallas County, IA Guthrie County, IA Madison County, IA Polk County, IA Warren County, IA 0.9433

19804 Detroit-Livonia-Dearborn, MI Wayne County, MI 0.9256
20020 Dothan, AL Geneva County, AL Henry County, AL Houston County, AL 0.7136

20100 Dover, DE Kent County, DE 0.9981 20220 Dubuque, IA Dubuque County, IA 0.8828
20260 Duluth, MN-WI Carlton County, MN St. Louis County, MN Douglas County, WI 0.9351

20500 Durham-Chapel Hill, NC Chatham County, NC Durham County, NC Orange County, NC Person County, NC 0.9707

20740 Eau Claire, WI Chippewa County, WI Eau Claire County, WI 1.0174129 20764 Edison-New Brunswick, NJ Middlesex County, NJ Monmouth County, NJ Ocean County, NJ Somerset County, NJ 1.0956

20940 El Centro, CA Imperial County, CA 0.8885
21060 Elizabethtown, KY Hardin County, KY Larue County, KY 0.7928

21140 Elkhart-Goshen, IN Elkhart County, IN 0.9369
21300 Elmira, NY Chemung County, NY 0.8396
21340 El Paso, TX El Paso County, TX 0.8441
21500 Erie, PA Erie County, PA 0.7973 21660 Eugene-Springfield, OR Lane County, OR 1.1773
21780 Evansville, IN-KY Gibson County, IN Posey County, IN Vanderburgh County, IN Warrick County, IN Henderson County, KY Webster County, KY 0.8367

21820 Fairbanks, AK Fairbanks North Star Borough, AK 1.1043 21940 Fajardo, PR Ceiba Municipio, PR Fajardo Municipio, PR Luquillo Municipio, PR 0.3744

22020 Fargo, ND-MN Cass County, ND Clay County, MN 0.7835

22140 Farmington, NM San Juan County, NM 0.9776130 22180 Fayetteville, NC Cumberland County, NC Hoke County, NC 0.8460

22220 Fayetteville-Springdale-Rogers, AR-MO Benton County, AR Madison County, AR Washington County, AR McDonald County, MO 0.8993

22380 Flagstaff, AZ Coconino County, AZ 1.2840
22420 Flint, MI Genesee County, MI 1.1303
22500 Florence, SC Darlington County, SC Florence County, SC 0.7968

22520 Florence-Muscle Shoals, AL Colbert County, AL Lauderdale County, AL 0.7553

22540 Fond du Lac, WI Fond du Lac County, WI 0.9517
22660 Fort Collins-Loveland, CO Larimer County, CO 0.9743 22744 Fort Lauderdale-Pompano Beach-Deerfield Beach, FL Broward County, FL 1.0422
22900 Fort Smith, AR-OK Crawford County, AR Franklin County, AR Sebastian County, AR Le Flore County, OK Sequoyah County, OK 0.7588

23060 Fort Wayne, IN Allen County, IN Wells County, IN Whitley County, IN 0.9048

23104 Fort Worth-Arlington, TX Johnson County, TX Parker County, TX Tarrant County, TX Wise County, TX 0.9552131 23420 Fresno, CA Fresno County, CA 1.1817
23460 Gadsden, AL Etowah County, AL 0.8017
23540 Gainesville, FL Alachua County, FL Gilchrist County, FL 0.9751

23580 Gainesville, GA Hall County, GA 0.9292 23844 Gary, IN Jasper County, IN Lake County, IN Newton County, IN Porter County, IN 0.9440

24020 Glens Falls, NY Warren County, NY Washington County, NY 0.8402

24140 Goldsboro, NC Wayne County, NC 0.8316
24220 Grand Forks, ND-MN Polk County, MN Grand Forks County, ND 0.7321

24300 Grand Junction, CO Mesa County, CO 0.9347 24340 Grand Rapids-Wyoming, MI Barry County, MI Ionia County, MI Kent County, MI Newaygo County, MI 0.9129

24500 Great Falls, MT Cascade County, MT 0.9274 24540 Greeley, CO Weld County, CO 0.9694 24580 Green Bay, WI Brown County, WI Kewaunee County, WI Oconto County, WI 0.9627132 24660 Greensboro-High Point, NC Guilford County, NC Randolph County, NC Rockingham County, NC 0.8288

24780 Greenville, NC Greene County, NC Pitt County, NC 0.9382

24860 Greenville-Mauldin-Easley, SC Greenville County, SC Laurens County, SC Pickens County, SC 0.9611

25020 Guayama, PR Arroyo Municipio, PR Guayama Municipio, PR Patillas Municipio, PR 0.3723

25060 Gulfport-Biloxi, MS Hancock County, MS Harrison County, MS Stone County, MS 0.8610

25180 Hagerstown-Martinsburg, MD-WV Washington County, MD Berkeley County, WV Morgan County, WV 0.9273

25260 Hanford-Corcoran, CA Kings County, CA 1.1171 25420 Harrisburg-Carlisle, PA Cumberland County, PA Dauphin County, PA Perry County, PA 0.9515

25500 Harrisonburg, VA Rockingham County, VA Harrisonburg City, VA 0.9128

25540 Hartford-West Hartford-East Hartford, CT Hartford County, CT Middlesex County, CT Tolland County, CT 1.1056

25620 Hattiesburg, MS Forrest County, MS Lamar County, MS Perry County, MS 0.7972133 25860 Hickory-Lenoir-Morganton, NC Alexander County, NC Burke County, NC Caldwell County, NC Catawba County, NC 0.8383

25980 Hinesville-Fort Stewart, GA 1 Liberty County, GA Long County, GA 0.8602

26100 Holland-Grand Haven, MI Ottawa County, MI 0.8050
26180 Honolulu, HI Honolulu County, HI 1.2109 26300 Hot Springs, AR Garland County, AR 0.8510 26380 Houma-Bayou Cane-Thibodaux, LA Lafourche Parish, LA Terrebonne Parish, LA 0.7556

26420 Houston-Sugar Land-Baytown, TX 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 0.9945

26580 Huntington-Ashland, WV-KY-OH Boyd County, KY Greenup County, KY Lawrence County, OH Cabell County, WV Wayne County, WV 0.8858

26620 Huntsville, AL Limestone County, AL Madison County, AL 0.8199

26820 Idaho Falls, ID Bonneville County, ID Jefferson County, ID 0.9351134 26900 Indianapolis-Carmel, IN 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 1.0151

26980 Iowa City, IA Johnson County, IA Washington County, IA 0.9896

27060 Ithaca, NY Tompkins County, NY 0.9366
27100 Jackson, MI Jackson County, MI 0.8981
27140 Jackson, MS Copiah County, MS Hinds County, MS Madison County, MS Rankin County, MS Simpson County, MS 0.8196

27180 Jackson, TN Chester County, TN Madison County, TN 0.7720

27260 Jacksonville, FL Baker County, FL Clay County, FL Duval County, FL Nassau County, FL St. Johns County, FL 0.8987

27340 Jacksonville, NC Onslow County, NC 0.7894
27500 Janesville, WI Rock County, WI 0.9110 27620 Jefferson City, MO Callaway County, MO Cole County, MO Moniteau County, MO Osage County, MO 0.8501135 27740 Johnson City, TN Carter County, TN Unicoi County, TN Washington County, TN 0.7257

27780 Johnstown, PA Cambria County, PA 0.8486
27860 Jonesboro, AR Craighead County, AR Poinsett County, AR 0.8017

27900 Joplin, MO Jasper County, MO Newton County, MO 0.8016

28020 Kalamazoo-Portage, MI Kalamazoo County, MI Van Buren County, MI 1.0001

28100 Kankakee-Bradley, IL Kankakee County, IL 0.9698 28140 Kansas City, MO-KS 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 0.9487

28420 Kennewick-Pasco-Richland, WA Benton County, WA Franklin County, WA 0.9499

28660 Killeen-Temple-Fort Hood, TX Bell County, TX Coryell County, TX Lampasas County, TX 0.8963136 28700 Kingsport-Bristol-Bristol, TN-VA Hawkins County, TN Sullivan County, TN Bristol City, VA Scott County, VA Washington County, VA 0.7223

28740 Kingston, NY Ulster County, NY 0.9104
28940 Knoxville, TN Anderson County, TN Blount County, TN Knox County, TN Loudon County, TN Union County, TN 0.7484

29020 Kokomo, IN Howard County, IN Tipton County, IN 0.9099

29100 La Crosse, WI-MN Houston County, MN La Crosse County, WI 1.0248

29140 Lafayette, IN Benton County, IN Carroll County, IN Tippecanoe County, IN 0.9996

29180 Lafayette, LA Lafayette Parish, LA St. Martin Parish, LA 0.8266

29340 Lake Charles, LA Calcasieu Parish, LA Cameron Parish, LA 0.7798

29404 Lake County-Kenosha County, IL-WI Lake County, IL Kenosha County, WI 1.0249

29420 Lake Havasu City-Kingman, AZ Mohave County, AZ 0.9953
29460 Lakeland-Winter Haven, FL Polk County, FL 0.8316
29540 Lancaster, PA Lancaster County, PA 0.9704137 29620 Lansing-East Lansing, MI Clinton County, MI Eaton County, MI Ingham County, MI 1.0663

29700 Laredo, TX Webb County, TX 0.7618
29740 Las Cruces, NM Dona Ana County, NM 0.9210 29820 Las Vegas-Paradise, NV Clark County, NV 1.1682
29940 Lawrence, KS Douglas County, KS 0.8700
30020 Lawton, OK Comanche County, OK 0.7926
30140 Lebanon, PA Lebanon County, PA 0.8192
30300 Lewiston, ID-WA Nez Perce County, ID Asotin County, WA 0.9254

30340 Lewiston-Auburn, ME Androscoggin County, ME 0.9086 30460 Lexington-Fayette, KY Bourbon County, KY Clark County, KY Fayette County, KY Jessamine County, KY Scott County, KY Woodford County, KY 0.8850

30620 Lima, OH Allen County, OH 0.9170
30700 Lincoln, NE Lancaster County, NE Seward County, NE 0.9505

30780 Little Rock-North Little Rock-Conway, AR Faulkner County, AR Grant County, AR Lonoke County, AR Perry County, AR Pulaski County, AR Saline County, AR 0.8661138 30860 Logan, UT-ID Franklin County, ID Cache County, UT 0.8791

30980 Longview, TX Gregg County, TX Rusk County, TX Upshur County, TX 0.8971

31020 Longview, WA Cowlitz County, WA 1.0504 31084 Los Angeles-Long Beach-Glendale, CA Los Angeles County, CA 1.2315 31140 Louisville-Jefferson County, KY-IN 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 0.8892

31180 Lubbock, TX Crosby County, TX Lubbock County, TX 0.8994

31340 Lynchburg, VA Amherst County, VA Appomattox County, VA Bedford County, VA Campbell County, VA Bedford City, VA Lynchburg City, VA 0.8808

31420 Macon, GA Bibb County, GA Crawford County, GA Jones County, GA Monroe County, GA Twiggs County, GA 0.8860

31460 Madera-Chowchilla, CA Madera County, CA 0.8352139 31540 Madison, WI Columbia County, WI Dane County, WI Iowa County, WI 1.1463

31700 Manchester-Nashua, NH Hillsborough County, NH 1.0099
31740 Manhattan, KS Geary County, KS Pottawatomie County, KS Riley County, KS 0.7876

31860 Mankato-North Mankato, MN Blue Earth County, MN Nicollet County, MN 0.9316

31900 Mansfield, OH Richland County, OH 0.8448 32420 Mayagüez, PR Hormigueros Municipio, PR Mayagüez Municipio, PR 0.3769

32580 McAllen-Edinburg-Mission, TX Hidalgo County, TX 0.8429
32780 Medford, OR Jackson County, OR 1.0735 32820 Memphis, TN-MS-AR Crittenden County, AR DeSoto County, MS Marshall County, MS Tate County, MS Tunica County, MS Fayette County, TN Shelby County, TN Tipton County, TN 0.9075

32900 Merced, CA Merced County, CA 1.2788
33124 Miami-Miami Beach-Kendall, FL Miami-Dade County, FL 0.9912 33140 Michigan City-La Porte, IN LaPorte County, IN 0.9255
33260 Midland, TX Midland County, TX 1.0092140 33340 Milwaukee-Waukesha-West Allis, WI Milwaukee County, WI Ozaukee County, WI Washington County, WI Waukesha County, WI 0.9868

33460 Minneapolis-St. Paul-Bloomington, MN-WI 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 1.1260

33540 Missoula, MT Missoula County, MT 0.9100
33660 Mobile, AL Mobile County, AL 0.7475
33700 Modesto, CA Stanislaus County, CA 1.3641
33740 Monroe, LA Ouachita Parish, LA Union Parish, LA 0.7550

33780 Monroe, MI Monroe County, MI 0.8755 33860 Montgomery, AL Autauga County, AL Elmore County, AL Lowndes County, AL Montgomery County, AL 0.7507

34060 Morgantown, WV Monongalia County, WV Preston County, WV 0.8267

34100 Morristown, TN Grainger County, TN Hamblen County, TN Jefferson County, TN 0.6884141 34580 Mount Vernon-Anacortes, WA Skagit County, WA 1.0697
34620 Muncie, IN Delaware County, IN 0.8780 34740 Muskegon-Norton Shores, MI Muskegon County, MI 0.9625 34820 Myrtle Beach-North Myrtle Beach-Conway, SC Horry County, SC 0.8663 34900 Napa, CA Napa County, CA 1.5354 34940 Naples-Marco Island, FL Collier County, FL 0.9147
34980 Nashville-Davidson—Murfreesboro-Franklin, TN 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 0.9174

35004 Nassau-Suffolk, NY Nassau County, NY Suffolk County, NY 1.2764

35084 Newark-Union, NJ-PA Essex County, NJ Hunterdon County, NJ Morris County, NJ Sussex County, NJ Union County, NJ Pike County, PA 1.1273

35300 New Haven-Milford, CT New Haven County, CT 1.1933142 35380 New Orleans-Metairie-Kenner, LA 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 0.8789

35644 New York-White Plains-Wayne, NY-NJ 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 1.3117

35660 Niles-Benton Harbor, MI Berrien County, MI 0.8479
35840 North Port-Bradenton-Sarasota-Venice, FL Manatee County, FL Sarasota County, FL 0.9468

35980 Norwich-New London, CT New London County, CT 1.1871 36084 Oakland-Fremont-Hayward, CA Alameda County, CA Contra Costa County, CA 1.7061

36100 Ocala, FL Marion County, FL 0.8461 36140 Ocean City, NJ Cape May County, NJ 1.0628
36220 Odessa, TX Ector County, TX 0.9702 36260 Ogden-Clearfield, UT Davis County, UT Morgan County, UT Weber County, UT 0.9209143 36420 Oklahoma City, OK Canadian County, OK Cleveland County, OK Grady County, OK Lincoln County, OK Logan County, OK McClain County, OK Oklahoma County, OK 0.8896

36500 Olympia, WA Thurston County, WA 1.1650
36540 Omaha-Council Bluffs, NE-IA Harrison County, IA Mills County, IA Pottawattamie County, IA Cass County, NE Douglas County, NE Sarpy County, NE Saunders County, NE Washington County, NE 0.9797

36740 Orlando-Kissimmee, FL Lake County, FL Orange County, FL Osceola County, FL Seminole County, FL 0.9101

36780 Oshkosh-Neenah, WI Winnebago County, WI 0.9438
36980 Owensboro, KY Daviess County, KY Hancock County, KY McLean County, KY 0.7823

37100 Oxnard-Thousand Oaks-Ventura, CA Ventura County, CA 1.3132 37340 Palm Bay-Melbourne-Titusville, FL Brevard County, FL 0.8707
37380 Palm Coast, FL Flagler County, FL 0.8209 37460 Panama City-Lynn Haven-Panama City Beach, FL Bay County, FL 0.7909144 37620 Parkersburg-Marietta-Vienna, WV-OH Washington County, OH Pleasants County, WV Wirt County, WV Wood County, WV 0.7576

37700 Pascagoula, MS George County, MS Jackson County, MS 0.7574

37764 Peabody, MA Essex County, MA 1.0571 37860 Pensacola-Ferry Pass-Brent, FL Escambia County, FL Santa Rosa County, FL 0.7800

37900 Peoria, IL Marshall County, IL Peoria County, IL Stark County, IL Tazewell County, IL Woodford County, IL 0.8290

37964 Philadelphia, PA Bucks County, PA Chester County, PA Delaware County, PA Montgomery County, PA Philadelphia County, PA 1.0926

38060 Phoenix-Mesa-Scottsdale, AZ Maricopa County, AZ Pinal County, AZ 1.0505

38220 Pine Bluff, AR Cleveland County, AR Jefferson County, AR Lincoln County, AR 0.8103

38300 Pittsburgh, PA Allegheny County, PA Armstrong County, PA Beaver County, PA Butler County, PA Fayette County, PA Washington County, PA Westmoreland County, PA 0.8713

38340 Pittsfield, MA Berkshire County, MA 1.0966145 38540 Pocatello, ID Bannock County, ID Power County, ID 0.9795

38660 Ponce, PR Juana Díaz Municipio, PR Ponce Municipio, PR Villalba Municipio, PR 0.4614

38860 Portland-South Portland-Biddeford, ME Cumberland County, ME Sagadahoc County, ME York County, ME 1.0023

38900 Portland-Vancouver-Beaverton, OR-WA Clackamas County, OR Columbia County, OR Multnomah County, OR Washington County, OR Yamhill County, OR Clark County, WA Skamania County, WA 1.1848

38940 Port St. Lucie, FL Martin County, FL St. Lucie County, FL 0.9391

39100 Poughkeepsie-Newburgh-Middletown, NY Dutchess County, NY Orange County, NY 1.1593

39140 Prescott, AZ Yavapai County, AZ 1.0199
39300 Providence-New Bedford-Fall River, RI-MA Bristol County, MA Bristol County, RI Kent County, RI Newport County, RI Providence County, RI Washington County, RI 1.0579

39340 Provo-Orem, UT Juab County, UT Utah County, UT 0.9501

39380 Pueblo, CO Pueblo County, CO 0.8250
39460 Punta Gorda, FL Charlotte County, FL 0.8771146 39540 Racine, WI Racine County, WI 0.9352 39580 Raleigh-Cary, NC Franklin County, NC Johnston County, NC Wake County, NC 0.9286

39660 Rapid City, SD Meade County, SD Pennington County, SD 0.9608

39740 Reading, PA Berks County, PA 0.9105 39820 Redding, CA Shasta County, CA 1.5053 39900 Reno-Sparks, NV Storey County, NV Washoe County, NV 1.0369

40060 Richmond, VA 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 0.9723

40140 Riverside-San Bernardino-Ontario, CA Riverside County, CA San Bernardino County, CA 1.1492147 40220 Roanoke, VA Botetourt County, VA Craig County, VA Franklin County, VA Roanoke County, VA Roanoke City, VA Salem City, VA 0.9233

40340 Rochester, MN Dodge County, MN Olmsted County, MN Wabasha County, MN 1.1712

40380 Rochester, NY Livingston County, NY Monroe County, NY Ontario County, NY Orleans County, NY Wayne County, NY 0.8770

40420 Rockford, IL Boone County, IL Winnebago County, IL 0.9792

40484 Rockingham County-St rafford County, NH Rockingham County, NH Strafford County, NH 1.0215

40580 Rocky Mount, NC Edgecombe County, NC Nash County, NC 0.8786

40660 Rome, GA Floyd County, GA 0.8962
40900 Sacramento-Arden-Arcade-Roseville, CA El Dorado County, CA Placer County, CA Sacramento County, CA Yolo County, CA 1.5211

40980 Saginaw-Saginaw Township North, MI Saginaw County, MI 0.8886
41060 St. Cloud, MN Benton County, MN Stearns County, MN 1.0703

41100 St. George, UT Washington County, UT 0.9385148 41140 St. Joseph, MO-KS Doniphan County, KS Andrew County, MO Buchanan County, MO DeKalb County, MO 0.9876

41180 St. Louis, MO-IL 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 0.9373

41420 Salem, OR Marion County, OR Polk County, OR 1.1195

41500 Salinas, CA Monterey County, CA 1.5626 41540 Salisbury, MD Somerset County, MD Wicomico County, MD 0.8986

41620 Salt Lake City, UT Salt Lake County, UT Summit County, UT Tooele County, UT 0.9396

41660 San Angelo, TX Irion County, TX Tom Green County, TX 0.8053149 41700 San Antonio, TX Atascosa County, TX Bandera County, TX Bexar County, TX Comal County, TX Guadalupe County, TX Kendall County, TX Medina County, TX Wilson County, TX 0.8939

41740 San Diego-Carlsbad-San Marcos, CA San Diego County, CA 1.2104 41780 Sandusky, OH Erie County, OH 0.7821 41884 San Francisco-San Mateo-Redwood City, CA Marin County, CA San Francisco County, CA San Mateo County, CA 1.6200

41900 San Germán-Cabo Rojo, PR Cabo Rojo Municipio, PR Lajas Municipio, PR Sabana Grande Municipio, PR San Germán Municipio, PR 0.4569

41940 San Jose-Sunnyvale-Santa Clara, CA San Benito County, CA Santa Clara County, CA 1.6761150 41980 San Juan-Caguas-Guaynabo, PR 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 0.4374

42020 San Luis Obispo-Paso Robles, CA San Luis Obispo County, CA 1.3089151 42044 Santa Ana-Anaheim-Irvine, CA Orange County, CA 1.2036
42060 Santa Barbara-Santa Maria-Goleta, CA Santa Barbara County, CA 1.3165
42100 Santa Cruz-Watsonville, CA Santa Cruz County, CA 1.7835
42140 Santa Fe, NM Santa Fe County, NM 1.0179
42220 Santa Rosa-Petaluma, CA Sonoma County, CA 1.6743
42340 Savannah, GA Bryan County, GA Chatham County, GA Effingham County, GA 0.8572

42540 Scranton--Wilkes-Barre, PA Lackawanna County, PA Luzerne County, PA Wyoming County, PA 0.8283

42644 Seattle-Bellevue-Everett, WA King County, WA Snohomish County, WA 1.1784

42680 Sebastian-Vero Beach, FL Indian River County, FL 0.8797 43100 Sheboygan, WI Sheboygan County, WI 0.9242
43300 Sherman-Denison, TX Grayson County, TX 0.8760 43340 Shreveport-Bossier City, LA Bossier Parish, LA Caddo Parish, LA De Soto Parish, LA 0.8297

43580 Sioux City, IA-NE-SD Woodbury County, IA Dakota County, NE Dixon County, NE Union County, SD 0.9202152 43620 Sioux Falls, SD Lincoln County, SD McCook County, SD Minnehaha County, SD Turner County, SD 0.8310

43780 South Bend-Mishawaka, IN-MI St. Joseph County, IN Cass County, MI 0.9465

43900 Spartanburg, SC Spartanburg County, SC 0.8797 44060 Spokane, WA Spokane County, WA 1.1221 44100 Springfield, IL Menard County, IL Sangamon County, IL 0.9204

44140 Springfield, MA Franklin County, MA Hampden County, MA Hampshire County, MA 1.0422

44180 Springfield, MO Christian County, MO Dallas County, MO Greene County, MO Polk County, MO Webster County, MO 0.8476

44220 Springfield, OH Clark County, OH 0.8483 44300 State College, PA Centre County, PA 0.9615
44600 Steubenville-Weirton, OH-WV Jefferson County, OH Brooke County, WV Hancock County, WV 0.7415

44700 Stockton, CA San Joaquin County, CA 1.3792
44940 Sumter, SC Sumter County, SC 0.7626 45060 Syracuse, NY Madison County, NY Onondaga County, NY Oswego County, NY 0.9937153 45104 Tacoma, WA Pierce County, WA 1.1623
45220 Tallahassee, FL Gadsden County, FL Jefferson County, FL Leon County, FL Wakulla County, FL 0.8602

45300 Tampa-St. Petersburg-Clearwater, FL Hernando County, FL Hillsborough County, FL Pasco County, FL Pinellas County, FL 0.9114

45460 Terre Haute, IN Clay County, IN Sullivan County, IN Vermillion County, IN Vigo County, IN 0.9747

45500 Texarkana, TX-Texarkana, AR Miller County, AR Bowie County, TX 0.7459

45780 Toledo, OH Fulton County, OH Lucas County, OH Ottawa County, OH Wood County, OH 0.8854

45820 Topeka, KS Jackson County, KS Jefferson County, KS Osage County, KS Shawnee County, KS Wabaunsee County, KS 0.9012

45940 Trenton-Ewing, NJ Mercer County, NJ 1.0622
46060 Tucson, AZ Pima County, AZ 0.8991154 46140 Tulsa, OK Creek County, OK Okmulgee County, OK Osage County, OK Pawnee County, OK Rogers County, OK Tulsa County, OK Wagoner County, OK 0.8179

46220 Tuscaloosa, AL Greene County, AL Hale County, AL Tuscaloosa County, AL 0.8498

46340 Tyler, TX Smith County, TX 0.8562
46540 Utica-Rome, NY Herkimer County, NY Oneida County, NY 0.8806

46660 Valdosta, GA Brooks County, GA Echols County, GA Lanier County, GA Lowndes County, GA 0.7558

46700 Vallejo-Fairfield, CA Solano County, CA 1.6355
47020 Victoria, TX Calhoun County, TX Goliad County, TX Victoria County, TX 0.8986

47220 Vineland-Millville-Bridgeton, NJ Cumberland County, NJ 1.0674155 47260 Virginia Beach-Norfolk-Newport News, VA-NC 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 0.8928

47300 Visalia-Porterville, CA Tulare County, CA 0.9989
47380 Waco, TX McLennan County, TX 0.8248
47580 Warner Robins, GA Houston County, GA 0.7718 47644 Warren-Troy-Farmington Hills, MI Lapeer County, MI Livingston County, MI Macomb County, MI Oakland County, MI St. Clair County, MI 0.9464156 47894 Washington-Arlington-Al exandria, DC-VA-MD-WV 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 1.0570

47940 Waterloo-Cedar Falls, IA Black Hawk County, IA Bremer County, IA Grundy County, IA 0.8366

48140 Wausau, WI Marathon County, WI 0.8652
48300 Wenatchee-East Wenatchee, WA Chelan County, WA Douglas County, WA 1.0151

48424 West Palm Beach-Boca Raton-Boynton Beach, FL Palm Beach County, FL 0.9637 48540 Wheeling, WV-OH Belmont County, OH Marshall County, WV Ohio County, WV 0.6702

48620 Wichita, KS Butler County, KS Harvey County, KS Sedgwick County, KS Sumner County, KS 0.8710157 48660 Wichita Falls, TX Archer County, TX Clay County, TX Wichita County, TX 0.9578

48700 Williamsport, PA Lycoming County, PA 0.8303 48864 Wilmington, DE-MD-NJ New Castle County, DE Cecil County, MD Salem County, NJ 1.0632

48900 Wilmington, NC Brunswick County, NC New Hanover County, NC Pender County, NC 0.8900

49020 Winchester, VA-WV Frederick County, VA Winchester City, VA Hampshire County, WV 0.9072

49180 Winston-Salem, NC Davie County, NC Forsyth County, NC Stokes County, NC Yadkin County, NC 0.8373

49340 Worcester, MA Worcester County, MA 1.1632
49420 Yakima, WA Yakima County, WA 1.0399
49500 Yauco, PR Guánica Municipio, PR Guayanilla Municipio, PR Peñuelas Municipio, PR Yauco Municipio, PR 0.3798

49620 York-Hanover, PA York County, PA 0.9580 49660 Youngstown-Warren-Boardman, OH-PA Mahoning County, OH Trumbull County, OH Mercer County, PA 0.8406

49700 Yuba City, CA 1 Sutter County, CA Yuba County, CA 1.1809158

1 At this time, there are no hospitals located in th is urban area on which to base a wage index. TABLE B: FY 2014 WAGE INDEX BASED ON CBSA LABOR MARKET AREAS FOR RURAL AREAS

State Code Nonurban Area Wage Index 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 49740 Yuma, AZ Yuma County, AZ 0.9715159

State Code Nonurban Area Wage Index 28 Nebraska 0.8893 29 Nevada 0.9822 30 New Hampshire 1.0381 31 New Jersey 1

- 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 Rico 1 0.4047 41 Rhode Island 1

- 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

1 All counties within the State are cla ssified as urban, with the exception of Puerto Rico. Puerto Rico has areas designated as rural; however, no short-term, acu te care hospitals are located in the area(s) for FY 2014. The Puerto Rico wage index is the same as FY 2013.
[FR Doc. 2013-10558 Filed 05/01/2013 at 4:15 pm; Publication Date: 05/06/2013]