E8-17797. Medicare Program; Inpatient Rehabilitation Facility Prospective Payment System for Federal Fiscal Year 2009

AGENCY:

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

ACTION:

Final rule.

SUMMARY:

This final rule updates the prospective payment rates for inpatient rehabilitation facilities (IRFs) for Federal fiscal year (FY) 2009 (for discharges occurring on or after October 1, 2008 and on or before September 30, 2009) as required under section 1886(j)(3)(C) of the Social Security Act (the Act). Section 1886(j)(5) of the Act requires the Secretary to publish in the Federal Register on or before the August 1 that precedes the start of each fiscal year, the classification and weighting factors for the IRF prospective payment system's (PPS) case-mix groups and a description of the methodology and data used in computing the prospective payment rates for that fiscal year.

We are revising existing policies regarding the PPS within the authority granted under section 1886(j) of the Act.

DATES:

These regulations are effective October 1, 2008. The updated IRF prospective payment rates are applicable for discharges on or after October 1, 2008 and on or before September 30, 2009 (FY 2009).

FOR FURTHER INFORMATION CONTACT:

Susanne Seagrave, [phone], for information regarding the payment policies.

Jeanette Kranacs, [phone], for information regarding the wage index.

SUPPLEMENTARY INFORMATION:

Table of Contents

I. Background

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

B. Operational Overview of the Current IRF PPS

II. Provisions of the Proposed Rule

III. Analysis of and Responses to Public Comments

IV. Update to the Case-Mix Group (CMG) Relative Weights and Average Length of Stay Values for FY 2009

V. FY 2009 IRF PPS Federal Prospective Payment Rates

A. Increase Factor and Labor-Related Share for FY 2009

B. Area Wage Adjustment

C. Description of the IRF Standard Payment Conversion Factor and Payment Rates for FY 2009

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

VI. Update to Payments for High-Cost Outliers Under the IRF PPS

A. Update to the Outlier Threshold Amount for FY 2009

B. Update to the IRF Cost-to-Charge Ratio Ceilings

VII. Revisions to the Regulation Text in Response to the Medicare, Medicaid, and SCHIP Extension Act of 2007

VIII. Post Acute Care Payment Reform

IX. Miscellaneous Comments

X. Provisions of the Final Rule

XI. Collection of Information Requirements

XII. Regulatory Impact Statement

Regulation Text

Addendum

Acronyms

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

ASCA Administrative Simplification Compliance Act, Public Law 107-105

BBA Balanced Budget Act of 1997, Public Law 105-33

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

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

CBSA Core-Based Statistical Area

CCR Cost-to-Charge Ratio

CFR Code of Federal Regulations

CMG Case-Mix Group

DRA Deficit Reduction Act of 2005, Public Law 109-171

DSH Disproportionate Share Hospital

ECI Employment Cost Index

FI Fiscal Intermediary

FR Federal Register

FY Federal Fiscal Year

GDP Gross Domestic Product

HHH Hubert H. Humphrey Building

HIPAA Health Insurance Portability and Accountability Act, Public Law 104-191

IFMC Iowa Foundation for Medical Care

IPF Inpatient Psychiatric Facility

IPPS Inpatient Prospective Payment System

IRF Inpatient Rehabilitation Facility

IRF-PAI Inpatient Rehabilitation Facility-Patient Assessment Instrument

IRF PPS Inpatient Rehabilitation Facility Prospective Payment System

IRVEN Inpatient Rehabilitation Validation and Entry

LIP Low-Income Percentage

LTCH Long-Term Care Hospital

MAC Medicare Administrative Contractor

MEDPAR Medicare Provider Analysis and Review

MMA Medicare Prescription Drug, Improvement, and Modernization Act of 2003, Public Law 108-173

MMSEA Medicare, Medicaid, and SCHIP Extension Act of 2007, Public Law 110-173

MSA Metropolitan Statistical Area

NAICS North American Industrial Classification System

OMB Office of Management and Budget

PAI Patient Assessment Instrument

PPS Prospective Payment System

RAND RAND Corporation

RFA Regulatory Flexibility Act, Public Law 96-354

RIA Regulatory Impact Analysis

RIC Rehabilitation Impairment Category

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

SCHIP State Children's Health Insurance Program

SIC Standard Industrial Code

TEFRA Tax Equity and Fiscal Responsibility Act of 1982, Public Law 97-248

I. Background

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

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

Payments under the IRF PPS encompass inpatient operating and capital costs of furnishing covered rehabilitation services (that is, routine, ancillary, and capital costs) but not direct graduate medical education costs, costs of approved nursing and allied health education activities, bad debts, and other services or items outside the scope of the IRF PPS. Although a complete discussion of the IRF PPS provisions appears in the original FY 2002 IRF PPS final rule (66 FR 41316) and the FY 2006 IRF PPS final rule (70 FR 47880), we are providing below a general description of the IRF PPS for fiscal years (FYs) 2002 through 2008.

Under the IRF PPS from FY 2002 through FY 2005, as described in the FY 2002 IRF PPS final rule (66 FR 41316), the Federal prospective payment rates were computed across 100 distinct case-mix groups (CMGs). We constructed 95 CMGs using rehabilitation impairment categories (RICs), functional status (both motor and cognitive), and age (in some cases, cognitive status and age may not be a factor in defining a CMG). In addition, we constructed five special CMGs to account for very short stays and for patients who expire in the IRF.

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

We established the Federal PPS rates using a standardized payment conversion factor (formerly referred to as the budget neutral conversion factor). For a detailed discussion of the budget neutral conversion factor, please refer to our FY 2004 IRF PPS final rule (68 FR 45684 through 45685). In the FY 2006 IRF PPS final rule (70 FR 47880), we discussed in detail the methodology for determining the standard payment conversion factor.

We applied the relative weighting factors to the standard payment conversion factor to compute the unadjusted Federal prospective payment rates under the IRF PPS from FYs 2002 through 2005. Within the structure of the payment system, we then made adjustments to account for interrupted stays, transfers, short stays, and deaths. Finally, we applied the applicable adjustments to account for geographic variations in wages (wage index), the percentage of low-income patients, location in a rural area (if applicable), and outlier payments (if applicable) to the IRF's unadjusted Federal prospective payment rates.

For cost reporting periods that began on or after January 1, 2002 and before October 1, 2002, we determined the final prospective payment amounts using the transition methodology prescribed in section 1886(j)(1) of the Act. Under this provision, IRFs transitioning into the PPS were paid a blend of the Federal IRF PPS rate and the payment that the IRF would have received had the IRF PPS not been implemented. This provision also allowed IRFs to elect to bypass this blended payment and immediately be paid 100 percent of the Federal IRF PPS rate. The transition methodology expired as of cost reporting periods beginning on or after October 1, 2002 (FY 2003), and payments for all IRFs now consist of 100 percent of the Federal IRF PPS rate.

We established a CMS Web site as a primary information resource for the IRF PPS. The Web site URL is http://www.cms.hhs.gov/​InpatientRehabFacPPS/​ and may be accessed to download or view publications, software, data specifications, educational materials, and other information pertinent to the IRF PPS.

Section 1886(j) of the Act confers broad statutory authority upon the Secretary to propose refinements to the IRF PPS. In the FY 2006 IRF PPS final rule (70 FR 47880) and in correcting amendments to the FY 2006 IRF PPS final rule (70 FR 57166) that we published on September 30, 2005, we finalized a number of refinements to the IRF PPS case-mix classification system (the CMGs and the corresponding relative weights) and the case-level and facility-level adjustments. These refinements included the adoption of OMB's Core-Based Statistical Area (CBSA) market definitions, modifications to the CMGs, tier comorbidities, and CMG relative weights, implementation of a new teaching status adjustment for IRFs, revision and rebasing of the IRF market basket, and updates to the rural, low-income percentage (LIP), and high-cost outlier adjustments. Any reference to the FY 2006 IRF PPS final rule in this final rule also includes the provisions effective in the correcting amendments. For a detailed discussion of the final key policy changes for FY 2006, please refer to the FY 2006 IRF PPS final rule (70 FR 47880 and 70 FR 57166).

In the FY 2007 IRF PPS final rule (71 FR 48354), we further refined the IRF PPS case-mix classification system (the CMG relative weights) and the case-level adjustments, to ensure that IRF PPS payments continue to reflect as accurately as possible the costs of care. For a detailed discussion of the FY 2007 policy revisions, please refer to the FY 2007 IRF PPS final rule (71 FR 48354).

In the FY 2008 IRF PPS final rule (72 FR 44284), we updated the Federal prospective payment rates and the outlier threshold, revised the IRF wage index policy, and clarified how we determine high-cost outlier payments for transfer cases. For more information on the policy changes implemented for FY 2008, please refer to the FY 2008 IRF PPS final rule (72 FR 44284), in which we published the final FY 2008 IRF Federal prospective payment rates.

After publication of the FY 2008 IRF PPS final rule (72 FR 44284), section 115 of the Medicare, Medicaid, and SCHIP Extension Act of 2007, Public Law 110-173 (MMSEA), amended section 1886(j)(3)(C) of the Act to apply a zero percent increase factor for FYs 2008 and 2009, effective for IRF discharges occurring on or after April 1, 2008. Section 1886(j)(3)(C) of the Act requires the Secretary to develop an increase factor to update the IRF Federal prospective payment rates for each FY. Based on the legislative change to the increase factor, we revised the FY 2008 Federal prospective payment rates for IRF discharges occurring on or after April 1, 2008. Thus, the final FY 2008 IRF Federal prospective payment rates that were published in the FY 2008 IRF PPS final rule (72 FR 44284) were effective for discharges occurring on or after October 1, 2007 and on or before March 31, 2008; and the revised FY 2008 IRF Federal prospective payment rates are effective for discharges occurring on or after April 1, 2008 and on or before September 30, 2008. The revised FY 2008 Federal prospective payment rates are available on the CMS Web site at http://www.cms.hhs.gov/​InpatientRehabFacPPS/​07_​DataFiles.asp#TopOfPage.

B. Operational Overview of the Current IRF PPS

As described in the FY 2002 IRF PPS final rule, upon the admission and discharge of a Medicare Part A fee-for-service patient, the IRF is required to complete the appropriate sections of a patient assessment instrument, the Inpatient Rehabilitation Facility-Patient Assessment Instrument (IRF-PAI). All required data must be electronically encoded into the IRF-PAI software product. Generally, the software product includes patient classification programming called the GROUPER software. The GROUPER software uses specific IRF-PAI data elements to classify (or group) patients into distinct CMGs and account for the existence of any relevant comorbidities.

The GROUPER software produces a five-digit CMG number. The first digit is an alpha-character that indicates the comorbidity tier. The last four digits represent the distinct CMG number. Free downloads of the Inpatient Rehabilitation Validation and Entry (IRVEN) software product, including the GROUPER software, are available on the CMS Web site at http://www.cms.hhs.gov/​InpatientRehabFacPPS/​06_​Software.asp.

Once a patient is discharged, the IRF submits a Medicare claim as a Health Insurance Portability and Accountability Act (HIPAA), Public Law 104-191, compliant electronic claim or, if the Administrative Compliance Act (ASCA), Public Law 107-105, permits, a paper claim, a UB-04 or a CMS-1450, (as appropriate) using the five-digit CMG number and sends it to the appropriate Medicare fiscal intermediary (FI) or Medicare Administrative Contractor (MAC). Claims submitted to Medicare must comply with both ASCA and HIPAA. Section 3 of the ASCA amends section 1862(a) of the Act by adding paragraph (22) which requires the Medicare program, subject to section 1862(h) of the Act, to deny payment under Part A or Part B for any expenses for items or services “for which a claim is submitted other than in an electronic form specified by the Secretary.” Section 1862(h) of the Act, in turn, provides that the Secretary shall waive such denial in situations in which there is no method available for the submission of claims in an electronic form or the entity submitting the claim is a small provider.

In addition, the Secretary also has the authority to waive such denial “in such unusual cases as the Secretary finds appropriate.” We refer the reader to the final rule, “Medicare Program; Electronic Submission of Medicare Claims” (70 FR 71008, November 25, 2005). Section 3 of the ASCA operates in the context of the administrative simplification provisions of HIPAA, which include, among others, the requirements for transaction standards and code sets codified in 45 CFR, parts 160 and 162, subparts A and I through R (generally known as the Transactions Rule). The Transactions Rule requires covered entities, including covered healthcare providers, to conduct covered electronic transactions according to the applicable transaction standards. (See the program claim memoranda issued and published by CMS at: http://www.cms.hhs.gov/​ElectronicBillingEDITrans/​ and listed in the addenda to the Medicare Intermediary Manual, Part 3, section 3600. CMS instructions for the limited number of Medicare claims submitted on paper are available at: http://www.cms.hhs.gov/​manuals/​downloads/​clm104c25.pdf.)

The Medicare FI or MAC processes the claim through its software system. This software system includes pricing programming called the “PRICER” software. The PRICER software uses the CMG number, along with other specific claim data elements and provider-specific data, to adjust the IRF's prospective payment for interrupted stays, transfers, short stays, and deaths, and then applies the applicable adjustments to account for the IRF's wage index, percentage of low-income patients, rural location, and outlier payments. For discharges occurring on or after October 1, 2005, the IRF PPS payment also reflects the new teaching status adjustment that became effective as of FY 2006, as discussed in the FY 2006 IRF PPS final rule (70 FR 47880).

II. Provisions of the Proposed Rule

As discussed in the FY 2009 IRF PPS proposed rule (73 FR 22674), we proposed to make revisions to the regulation text in response to section 115 of the MMSEA. Specifically, we proposed to revise 42 CFR part 412. We discuss these proposed revisions and others in detail below.

A. Section 412.23 Excluded Hospitals: Classifications

We proposed to revise the regulation text in paragraph (b)(2)(i) and remove paragraph (b)(2)(ii) in response to section 115 of the MMSEA. To summarize, for cost reporting periods—

(1) Beginning on or after July 1, 2005, the hospital has served an inpatient population of whom at least 60 percent require intensive rehabilitation services for treatment of one or more of the conditions specified at paragraph (b)(2)(ii) of this section (as amended by removing former (b)(2)(ii) and redesignating former (b)(2)(iii) as the new (b)(2)(ii)).

(2) A comorbidity that meets the criteria as specified in § 412.23(b)(2)(i) may continue to be used to determine the compliance threshold.

B. Additional Proposed Changes

• Update the FY 2009 IRF PPS relative weights and average length of stay values using the most current and complete Medicare claims and cost report data, as discussed in section II of the FY 2009 IRF PPS proposed rule (73 FR 22674, 22676 through 22680).
• Update the FY 2009 IRF PPS payment rates by the proposed wage index and labor related share in a budget neutral manner, as discussed in sections III.A and B of the FY 2009 IRF PPS proposed rule (73 FR 22674, 22680 through 22686).
• Update the outlier threshold amount for FY 2009, as discussed in section IV.A of the FY 2009 IRF PPS proposed rule (73 FR 22674, 22686 through 22687).
• Update the cost-to-charge ratio ceiling and the national average urban and rural cost-to-charge ratios for purposes of determining outlier payments under the IRF PPS, as discussed in section IV.B of the FY 2009 IRF PPS proposed rule (73 FR 22674 at 22687).

III. Analysis of and Responses to Public Comments

We received approximately 17 timely items of correspondence containing multiple comments on the FY 2009 IRF PPS proposed rule (73 FR 22674) from the public. We received comments from various trade associations, inpatient rehabilitation facilities, health care industry organizations, and health care consulting firms. The following discussion, arranged by subject area, includes a summary of the public comments that we received, and our responses to the comments appear under the appropriate subject heading.

IV. Update to the CMG Relative Weights and Average Length of Stay Values for FY 2009

As specified in 42 CFR 412.620(b)(1), we calculate a relative weight for each CMG that is proportional to the resources needed by an average inpatient rehabilitation case in that CMG. For example, cases in a CMG with a relative weight of 2, on average, will cost twice as much as cases in a CMG with a relative weight of 1. Relative weights account for the variance in cost per discharge due to the variance in resource utilization among the payment groups, and their use helps to ensure that IRF PPS payments support beneficiary access to care as well as provider efficiency.

In the FY 2009 IRF PPS proposed rule (73 FR 22674, 22676 through 22680), we proposed updates to the CMG relative weights and average length of stay values using the most recent available data (FY 2006 IRF claims, FY 2006 IRF-PAI, and FY 2006 IRF cost report data) to ensure that IRF PPS payments continue to reflect as accurately as possible the costs of care in IRFs. We proposed to do this using the same methodology, with one change, that was described in the original, FY 2002 IRF PPS final rule (66 FR 41316) and the FY 2006 IRF PPS final rule (70 FR 47880, 47887 through 47888). The proposed change to the methodology involves using new, more detailed cost-to-charge ratio (CCR) data from the cost reports of IRF subprovider units of primary acute care hospitals, instead of CCR data from the associated primary acute care hospitals, to calculate IRFs' average costs per case. In general, we proposed to make this change in the methodology because the more detailed CCR data from the IRF subprovider cost reports are now available in sufficient detail, and the relationship between costs and charge in the primary acute care hospital could differ from the relationship between costs and charges in the IRF subprovider units, making the data from the IRF subprovider units potentially more accurate for estimating the average costs per case in these units. For freestanding IRFs, we proposed to continue using CCR data from the freestanding IRF's cost report. We also noted that in future years we would continue to estimate the CMG relative weights using both the primary acute care hospital CCRs and the IRF subprovider unit CCRs to ensure that we continue to use the most appropriate data in updating the CMG relative weights.

In addition, we proposed to make changes to the CMG relative weights for FY 2009 in such a way that total estimated aggregate payments to IRFs for FY 2009 would be the same with or without the proposed changes (that is, in a budget neutral manner) by applying a budget neutrality factor to the standard payment amount, as described in section II of the FY 2009 IRF PPS proposed rule (73 FR 22674 at 22677). To compute the budget neutrality factor used to update the CMG relative weights, we proposed to use the following steps:

Step 1. Calculate the estimated total amount of IRF PPS payments for FY 2009 (with no proposed changes to the CMG relative weights).

Step 2. Apply the proposed changes to the CMG relative weights (as discussed above) to calculate the estimated total amount of IRF PPS payments for FY 2009.

Step 3. Divide the amount calculated in step 1 by the amount calculated in step 2 to determine the budget neutrality factor that would maintain the same total estimated aggregate payments in FY 2009 with and without the proposed changes to the CMG relative weights.

Step 4. Apply the proposed budget neutrality factor to the FY 2008 IRF PPS standard payment amount after the application of the budget-neutral wage adjustment factor.

Note that the budget neutrality factor that we use to update the CMG relative weights for FY 2009 changed from 0.9969 in the proposed rule to 0.9939 in this final rule due to the use of updated FY 2007 IRF claims data in this final rule.

We received five comments on the proposed updates to the CMG relative weights and average length of stay values, which are summarized below.

Comment: Several commenters supported the proposed update to the CMG relative weights for FY 2009, with one commenter referring to the proposed update as a “step in the right direction.” However, several commenters specifically suggested that we analyze the FY 2007 IRF claims and cost report data in computing the CMG relative weights for FY 2009, as these data would reflect more of the impact of recent changes in the 75 percent rule and the IRF medical necessity reviews than the FY 2006 IRF claims and cost report data. Further, one commenter recommended that we seek additional cost information to use to compute the CMG relative weights, including nursing staff time data, ancillary cost data, and other alternatives to the IRF claims and cost report data that we currently use to compute the CMG relative weights. Finally, a couple of commenters recommended that we recalibrate the CMG relative weights more frequently, with one commenter specifically asking that we recalibrate the CMG relative weights again next year (for FY 2010) using the most recent available data.

Response: We agree with the commenters that we should analyze the most recent available IRF data to compute the CMG relative weights for FY 2009 in order to ensure that IRF PPS payments continue to reflect as accurately as possible the costs of care in IRFs. For the proposed rule, we used data from FY 2006 IRF claims, FY 2006 IRF-PAI, and FY 2006 IRF cost reports because that was the best available data at the time. For this final rule, we have updated the IRF claims data used in our analysis of the CMG relative weights and average length of stay values from FY 2006 to FY 2007.

We note that we used FY 2006 IRF-PAI data for analyzing the CMG relative weights in the proposed rule because we implemented some minor adjustments to the classification system for FY 2007 in the FY 2007 IRF PPS final rule (71 FR 48354, 48360 through 48370). Accordingly, some of the CMGs that appeared on the FY 2006 IRF claims data would not be the same CMGs that would be assigned under the current, post-FY 2007 IRF classification system. We therefore used the FY 2006 IRF-PAI data for the proposed rule to ensure that the appropriate current CMG was assigned for all of the FY 2006 claims. However, use of the IRF-PAI data was no longer necessary when we used the FY 2007 IRF claims data for this final rule because the CMG information on the FY 2007 IRF claims data incorporated all of the changes to the IRF classification system that were implemented in the FY 2007 IRF PPS final rule (71 FR 48354, 48360 through 48370). We did not implement any changes to the IRF classification system in the FY 2008 IRF PPS final rule (72 FR 44284). The results of our analysis of the FY 2007 IRF claims data are reflected in the CMG relative weights and average length of stay values presented in Table 1 in this final rule.

We further note that we have not updated the IRF cost report data used in this final rule. Although we agree with the commenter that it is important to analyze the most recent available cost report data to reflect as fully as possible the changes in IRF patient populations that may have occurred as a result of changes in the 75 percent rule and the IRF medical necessity reviews, only a small portion of the FY 2007 IRF cost reports are available for analysis at this time. Accordingly, we have continued to use the FY 2006 cost report data for analyzing IRFs' costs per case in this final rule because these are the most complete IRF cost report data available at this time. However, we will continue to evaluate the need for further updates and refinements to the CMG relative weights and average length of stay values in future years and would update the cost report data, as appropriate, when the data become available.

We appreciate the commenter's suggestions regarding alternative data to use in analyzing the costs of caring for IRF patients, and we will carefully consider the commenter's suggestions for future refinements to the methodology for computing the CMG relative weights.

Finally, we agree with the commenters that we may need to update the CMG relative weight and average length of stay analysis frequently to ensure that IRF payments continue to reflect the costs of caring for IRF patients, especially in light of recent changes resulting from changes to the 75 percent rule and the IRF medical necessity reviews. We intend to continue analyzing the most recent available data, and will propose future refinements to the IRF classification and weighting system based on that analysis, as appropriate.

Comment: One commenter stated a concern that the methodology used to revise the IRF classification system in the FY 2006 IRF PPS final rule (70 FR 47880) may have reduced the overall IRF case mix weights. This commenter asked CMS to re-examine this issue.

Response: As discussed in the FY 2006 IRF PPS final rule (70 FR 47880, 47886 through 47904), the FY 2007 IRF PPS final rule (71 FR 48354, 48373 through 48374), and the FY 2008 IRF PPS final rule (72 FR 44284 at 44293), we have analyzed the data and it continues to show that the FY 2006 refinements to the IRF classification system did not cause a reduction in the overall IRF case mix weights or in aggregate IRF payments. We have met with industry representatives several times in order to understand their concerns. We have also discussed the results of our analysis with them, which continues to show that we implemented the FY 2006 refinements to the IRF classification system in a budget neutral manner, so that estimated aggregate payments to providers would not increase or decrease as a result of these refinements.

Comment: One commenter questioned why only 141 (40 percent) of the proposed FY 2009 CMG relative weight values increased compared with the FY 2008 CMG relative weight values, while 212 (60 percent) of the proposed FY 2009 CMG relative weight values decreased compared with the FY 2008 CMG relative weight values. This commenter generally expressed surprise at the proposed FY 2009 CMG relative weights values, but indicated that certain changes appeared to be correct, particularly the increases in the CMG relative weights for some of the orthopedic conditions. However, the commenter questioned why the CMG relative weight values for other types of cases decreased.

Response: As we discussed in the proposed rule (73 FR 22674 at 22680), updates to the CMG relative weights will result in some increases and some decreases to the CMG relative weight values. This is due to the distributional nature of CMG relative weight changes. However, our updated analysis of the CMG relative weight values presented in Table 1 of this final rule (which is based on more recent data than that used in the proposed rule, as explained previously in this section) now shows that more than half of the CMG relative weights will increase and, further, that more than half of beneficiaries are in payment groups for which the CMG relative weight will increase between FY 2008 and FY 2009. Specifically, our analysis shows that 57 percent of patients are classified into one of the 177 payment groups (that is, the combination of CMG and tier) that will experience an increase in the CMG relative weight value between FYs 2008 and 2009, and 43 percent of patients are classified into one of the 176 classification groups that will experience a decrease in the CMG relative weight value between FYs 2008 and 2009.

Final Decision: We received only positive comments in support of the proposal to change the methodology for determining IRFs' average costs per case by using more detailed cost-to-charge ratio (CCR) data from the cost reports of IRF subprovider units of primary acute care hospitals to calculate the IRF subprovider units' average costs per case. Thus, after carefully considering all of the comments that we received on the proposed updates to the CMG relative weights and average length of stay values, we are finalizing this change to the methodology for the reasons explained previously and as described in more detail in the proposed rule (73 FR 22674, 22676 through 22677). For freestanding IRFs, we will continue to use the CCR data from the freestanding IRFs' cost reports. Consistent with the methodology that we used to compute the CMG relative weights for FYs 2002 through 2008, with the one change described above, we are implementing the updates to the CMG relative weights and average length of stay values presented in Table 1 below. As recommended by the commenters, we have updated the CMG relative weights and average length of stay values in Table 1 using FY 2007 IRF claims data for this final rule. Further, as noted previously, we have continued to use FY 2006 IRF cost report data for this final rule because it is the best available cost report data at this time.

Table 1—Relative Weights and Average Lengths of Stay for Case-Mix Groups

CMG	CMG description (M=motor, C=cognitive, A=age)	Relative weight				Average length of stay
		Tier 1	Tier 2	Tier 3	None	Tier 1	Tier 2	Tier 3	None
0101	Stroke: M>51.05	0.7712	0.7108	0.6381	0.6059	9	10	9	8
0102	Stroke: M>44.45 and M<51.05 and C>18.5	0.9694	0.8936	0.8021	0.7617	11	11	11	10
0103	Stroke: M>44.45 and M<51.05 and C<18.5	1.1478	1.0580	0.9496	0.9018	14	14	12	12
0104	Stroke: M>38.85 and M<44.45	1.2192	1.1238	1.0087	0.9579	13	14	13	13
0105	Stroke: M>34.25 and M<38.85	1.4320	1.3199	1.1848	1.1251	16	18	15	15
0106	Stroke: M>30.05 and M<34.25	1.6632	1.5330	1.3761	1.3067	19	19	17	17
0107	Stroke: M>26.15 and M<30.05	1.8970	1.7485	1.5695	1.4904	20	21	19	19
0108	Stroke: M<26.15 and A>84.5	2.2795	2.1011	1.8860	1.7910	27	26	23	22
0109	Stroke: M>22.35 and M<26.15 and A<84.5	2.1786	2.0081	1.8025	1.7117	22	23	21	22
0110	Stroke: M<22.35 and A<84.5	2.7217	2.5087	2.2518	2.1384	30	30	27	26
0201	Traumatic brain injury: M>53.35 and C>23.5	0.7556	0.6464	0.5818	0.5295	10	10	8	8
0202	Traumatic brain injury: M>44.25 and M<53.35 and C>23.5	1.0305	0.8817	0.7935	0.7222	13	11	10	10
0203	Traumatic brain injury: M>44.25 and C<23.5	1.1487	0.9828	0.8846	0.8051	12	13	12	11
0204	Traumatic brain injury: M>40.65 and M<44.25	1.2934	1.1066	0.9959	0.9064	15	14	13	12
0205	Traumatic brain injury: M>28.75 and M<40.65	1.5739	1.3466	1.2119	1.1030	17	17	16	14
0206	Traumatic brain injury: M>22.05 and M<28.75	1.9530	1.6709	1.5039	1.3687	21	21	18	18
0207	Traumatic brain injury: M<22.05	2.6307	2.2508	2.0257	1.8437	36	28	24	22
0301	Non-traumatic brain injury: M>41.05	1.1084	0.9308	0.8358	0.7650	12	12	11	10
0302	Non-traumatic brain injury: M>35.05 and M<41.05	1.4120	1.1857	1.0647	0.9746	14	15	13	13
0303	Non-traumatic brain injury: M>26.15 and M<35.05	1.6938	1.4224	1.2772	1.1691	17	17	16	15
0304	Non-traumatic brain injury: M<26.15	2.3130	1.9424	1.7441	1.5966	27	23	21	20
0401	Traumatic spinal cord injury: M>48.45	0.9255	0.7883	0.7732	0.6566	12	12	11	9
0402	Traumatic spinal cord injury: M>30.35 and M<48.45	1.3933	1.1868	1.1640	0.9886	17	15	16	13
0403	Traumatic spinal cord injury: M>16.05 and M<30.35	2.2823	1.9440	1.9067	1.6194	28	23	23	21
0404	Traumatic spinal cord injury: M<16.05 and A>63.5	3.9766	3.3872	3.3222	2.8215	53	40	37	34
0405	Traumatic spinal cord injury: M<16.05 and A<63.5	.0347	2.5850	2.5354	2.1532	42	30	29	27
0501	Non-traumatic spinal cord injury: M>51.35	0.8107	0.6397	0.5945	0.5245	9	9	8	8
0502	Non-traumatic spinal cord injury: M>40.15 and M<51.35	1.0994	0.8675	0.8062	0.7113	13	11	11	10
0503	Non-traumatic spinal cord injury: M>31.25 and M<40.15	1.4315	1.1296	1.0497	0.9261	16	14	13	13
0504	Non-traumatic spinal cord injury: M>29.25 and M<31.25	1.7229	1.3596	1.2634	1.1147	21	17	16	15
0505	Non-traumatic spinal cord injury: M>23.75 and M<29.25	2.0360	1.6066	1.4930	1.3173	23	21	19	17
0506	Non-traumatic spinal cord injury: M<23.75	2.8325	2.2351	2.0770	1.8325	32	27	25	23
0601	Neurological: M>47.75	0.9245	0.7546	0.7174	0.6542	11	9	10	9
0602	Neurological: M>37.35 and M<47.75	1.2366	1.0094	0.9596	0.8750	12	13	12	12
0603	Neurological: M>25.85 and M<37.35	1.5763	1.2866	1.2232	1.1154	16	16	15	14
0604	Neurological: M<25.85	2.0887	1.7049	1.6208	1.4780	24	21	20	18
0701	Fracture of lower extremity: M>42.15	0.9187	0.7742	0.7300	0.6563	11	10	10	9
0702	Fracture of lower extremity: M>34.15 and M<42.15	1.2116	1.0209	0.9627	0.8655	14	14	12	12
0703	Fracture of lower extremity: M>28.15 and M<34.15	1.4846	1.2510	1.1797	1.0606	16	16	15	14
0704	Fracture of lower extremity: M<28.15	1.8994	1.6005	1.5093	1.3569	20	20	19	17
0801	Replacement of lower extremity joint: M>49.55	0.7000	0.5704	0.5172	0.4714	8	7	8	7
0802	Replacement of lower extremity joint: M>37.05 and M<49.55	0.9380	0.7643	0.6931	0.6317	10	10	9	9
0803	Replacement of lower extremity joint: M>28.65 and M<37.05 and A>83.5	1.3383	1.0905	0.9889	0.9013	14	13	13	12
0804	Replacement of lower extremity joint: M>28.65 and M<37.05 and A<83.5	1.1745	0.9571	0.8679	0.7910	13	12	11	10
0805	Replacement of lower extremity joint: M>22.05 and M<28.65	1.4661	1.1947	1.0833	0.9874	16	16	13	13
0806	Replacement of lower extremity joint: M<22.05	1.8139	1.4780	1.3403	1.2215	18	18	17	15
0901	Other orthopedic: M>44.75	0.8584	0.7574	0.6829	0.6041	10	10	9	9
0902	Other orthopedic: M>34.35 and M<44.75	1.1473	1.0122	0.9127	0.8074	13	13	12	11
0903	Other orthopedic: M>24.15 and M<34.35	1.4840	1.3093	1.1806	1.0443	16	16	15	14
0904	Other orthopedic: M<24.15	1.9620	1.7310	1.5608	1.3807	22	22	19	18
1001	Amputation, lower extremity: M>47.65	0.9356	0.9061	0.7797	0.7137	11	12	11	10
1002	Amputation, lower extremity: M>36.25 and M<47.65	1.2522	1.2127	1.0435	0.9552	14	15	13	12
1003	Amputation, lower extremity: M<36.25	1.8193	1.7619	1.5161	1.3877	19	21	19	17
1101	Amputation, non-lower extremity: M>36.35	1.1846	0.9851	0.9851	0.8558	12	12	13	11
1102	Amputation, non-lower extremity: M<36.35	1.7288	1.4377	1.4377	1.2490	17	18	17	15
1201	Osteoarthritis: M>37.65	1.0319	0.9668	0.8483	0.7541	11	12	11	10
1202	Osteoarthritis: M>30.75 and M<37.65	1.3034	1.2212	1.0715	0.9525	14	15	13	13
1203	Osteoarthritis: M<30.75	1.6379	1.5346	1.3465	1.1969	16	18	17	15
1301	Rheumatoid, other arthritis: M>36.35	1.0983	0.9874	0.8499	0.7648	12	12	11	10
1302	Rheumatoid, other arthritis: M>26.15 and M<36.35	1.4790	1.3296	1.1445	1.0299	15	16	14	13
1303	Rheumatoid, other arthritis: M<26.15	1.9140	1.7208	1.4812	1.3329	24	22	18	17
1401	Cardiac: M>48.85	0.8003	0.7221	0.6388	0.5667	10	11	9	8
1402	Cardiac: M>38.55 and M<48.85	1.1095	1.0010	0.8856	0.7856	13	13	12	11
1403	Cardiac: M>31.15 and M<38.55	1.3578	1.2251	1.0838	0.9615	15	15	13	13
1404	Cardiac: M<31.15	1.7628	1.5905	1.4071	1.2483	20	20	17	16
1501	Pulmonary: M>49.25	0.9603	0.8386	0.7413	0.7038	11	12	10	9
1502	Pulmonary: M>39.05 and M<49.25	1.2297	1.0739	0.9494	0.9013	13	13	12	11
1503	Pulmonary: M>29.15 and M<39.05	1.5640	1.3658	1.2074	1.1463	16	17	14	14
1504	Pulmonary: M<29.15	1.9525	1.7051	1.5073	1.4310	22	19	17	17
1601	Pain syndrome: M>37.15	1.1094	0.8968	0.7667	0.7068	13	13	10	10
1602	Pain syndrome: M>26.75 and M<37.15	1.4978	1.2108	1.0351	0.9543	16	16	13	13
1603	Pain syndrome: M<26.75	1.9287	1.5590	1.3328	1.2287	22	19	17	16
1701	Major multiple trauma without brain or spinal cord injury: M>39.25	1.0454	0.9189	0.8461	0.7419	11	12	11	10
1702	Major multiple trauma without brain or spinal cord injury: M>31.05 and M<39.25	1.3777	1.2110	1.1151	0.9778	14	15	14	13
1703	Major multiple trauma without brain or spinal cord injury: M>25.55 and M<31.05	1.6566	1.4561	1.3408	1.1757	18	17	16	15
1704	Major multiple trauma without brain or spinal cord injury: M<25.55	2.0776	1.8261	1.6815	1.4744	23	24	21	19
1801	Major multiple trauma with brain or spinal cord injury: M>40.85	1.2189	0.9629	0.9044	0.7757	15	13	13	10
1802	Major multiple trauma with brain or spinal cord injury: M>23.05 and M<40.85	1.8398	1.4533	1.3651	1.1708	19	17	16	15
1803	Major multiple trauma with brain or spinal cord injury: M<23.05	3.1442	2.4838	2.3329	2.0009	37	31	26	24
1901	Guillian Barre: M>35.95	1.1582	0.9288	0.9288	0.8782	15	11	11	12
1902	Guillian Barre: M>18.05 and M<35.95	2.3408	1.8772	1.8772	1.7749	26	22	25	22
1903	Guillian Barre: M<18.05	3.5944	2.8825	2.8825	2.7254	33	35	41	31
2001	Miscellaneous: M>49.15	0.8820	0.7282	0.6614	0.5928	11	9	9	8
2002	Miscellaneous: M>38.75 and M<49.15	1.1873	0.9803	0.8904	0.7980	12	13	11	11
2003	Miscellaneous: M>27.85 and M<38.75	1.5231	1.2575	1.1422	1.0237	16	16	14	13
2004	Miscellaneous: M<27.85	2.0363	1.6812	1.5271	1.3686	22	20	19	17
2101	Burns: M>0	2.3666	2.3666	2.1481	1.7454	25	25	25	17
5001	Short-stay cases, length of stay is 3 days or fewer				0.1476				3
5101	Expired, orthopedic, length of stay is 13 days or fewer				0.6783				8
5102	Expired, orthopedic, length of stay is 14 days or more				1.5432				19
5103	Expired, not orthopedic, length of stay is 15 days or fewer				0.7086				9
5104	Expired, not orthopedic, length of stay is 16 days or more				1.9586				23

V. FY 2009 IRF PPS Federal Prospective Payment Rates

A. Increase Factor and Labor-Related Share for FY 2009

Section 1886(j)(3)(C) of the Act requires the Secretary to establish an increase factor that reflects changes over time in the prices of an appropriate mix of goods and services included in the covered IRF services, which is referred to as a market basket index. According to section 1886(j)(3)(A)(i) of the Act, the increase factor shall be used to update the IRF Federal prospective payment rates for each FY. However, section 115 of the MMSEA, amended section 1886(j)(3)(C) of the Act to apply a zero percent increase factor for FYs 2008 and 2009, effective for IRF discharges occurring on or after April 1, 2008. Thus, we are applying an increase factor of zero percent to update the IRF Federal prospective payment rates for FY 2009 in this final rule.

We continue to use the methodology described in the FY 2006 IRF PPS final rule to update the IRF labor-related share for FY 2009 (70 FR 47880, 47908 through 47917). The IRF labor-related share for FY 2009 is the sum of the FY 2009 relative importance of each labor-related cost category, and reflects the different rates of price change for these cost categories between the base year (FY 2002) and FY 2009. Consistent with our proposal to update the labor-related share with the most recent available data, the labor-related share for this final rule reflects Global Insight's second quarter 2008 forecast. (Global Insight is a nationally recognized economic and financial forecasting firm that contracts with CMS to forecast the components of providers' market baskets.) As shown in Table 2, the total FY 2009 Rehabilitation, Psychiatric, and Long-Term Care Hospital Market Basket (RPL) labor-related share in this final rule is 75.464 percent.

Table 2—FY 2009 IRF RPL Labor-Related Share Relative Importance

Cost category	FY 2009 IRF labor-related share relative importance
Wages and salaries	52.552
Employee benefits	13.982
Professional fees	2.890
All other labor intensive services	2.120
Subtotal	71.544
Labor-related share of capital costs (.46)	3.920
Total	75.464
SOURCE: GLOBAL INSIGHT, INC, 2nd QTR, 2008; @USMACRO/CONTROL0508 @CISSIM/TL0508.SIM Historical Data through 1st QTR, 2008.

We received five comments on the increase factor and labor-related share for FY 2009, which are summarized below.

Comment: Two commenters expressed concern that the zero percent increase factor that we are applying to the IRF Federal prospective payment rates for FY 2009, would impose a financial burden on IRFs. These commenters noted that the zero percent increase factor for FY 2009 was required by section 115 of the MMSEA, which also made revisions to the 60 percent rule. The commenters requested that any future legislative changes to the 60 percent rule also be considered in combination with updates to the IRF Federal prospective payment rates.

Response: As we discussed in the FY 2009 IRF PPS proposed rule (73 FR 22674, 22680 through 22681), section 115 of the MMSEA amended section 1886(j)(3)(C) of the Act to apply a zero percent increase factor for FYs 2008 and 2009, effective for IRF discharges occurring on or after April 1, 2008. While we understand that the effect of the zero percent increase factor is to maintain FY 2009 IRF PPS payment rates at FY 2008 levels, the statute does not give CMS the discretion to implement an increase factor other than zero percent for FY 2009. We will respond to any future legislative changes to the 60 percent rule accordingly.

Comment: One commenter requested that CMS calculate the IRF PPS market basket estimates using more current market basket data. This commenter stated that the FY 2009 market basket estimate is based on data from FY 2002, and that the FY 2002 data underestimate the increase in costs, especially labor costs, that IRFs have experienced. The commenter suggested that CMS use Medicare cost report data to compute the market basket estimate, rather than data from the Bureau of Labor Statistics, in order to make the estimate more current.

Response: The IRF PPS market basket, which is a fixed weight, Laspeyres-type price index, is constructed in three steps. First, a base period is selected (FY 2002 in the current market basket) and total base period expenditures are estimated for a set of mutually exclusive and exhaustive spending categories based upon type of expenditure. The proportion of total operating costs that each category represents is called a cost or expenditure weight.

Medicare Cost Report (MCR) data are used to derive the primary cost weights for the market basket. We monitor the stability of these cost weights and have determined that they do not tend to fluctuate over short periods of time (such as a period of less than 5 years). In general, we have typically rebased (recalculated market basket cost weights) approximately every 5 years. We note that we last revised and rebased the market basket in the FY 2006 IRF PPS final rule (70 FR 47880, 47915 through 47917).

Second, the FY 2002 expenditure weight for each cost category is matched to an appropriate price or wage variable, referred to as a price proxy. These price proxies are selected to reflect the rate-of-price change for each expenditure category and are primarily obtained from the Bureau of Labor Statistics (BLS).

Finally, each FY 2002 cost weight is multiplied by the level of its respective price proxy. The sum of these products (that is, the expenditure weights multiplied by their price levels) for all cost categories yields the composite index level of the market basket in a given period. Repeating this step for other periods produces a series of market basket levels over time.

The final IRF market basket update for FY 2009 is calculated using the market basket levels from the second quarter of 2008 (2008Q2) forecast prepared by Global Insight, Inc. (GII). These levels reflect the most recent price data available (historical price data through 2008Q1 and forecasted price data for 2008Q2 and beyond).

Given the methodology described above, the current market basket estimate is not based solely on FY 2002 data, but rather is calculated by applying the most recent available price data for each quarter to the FY 2002 cost weights. Thus, the current FY 2009 market basket estimate does in fact reflect recent price increases experienced by IRFs.

Comment: Several commenters expressed concern about the methodology for computing the labor-related share. One commenter requested that we begin updating the labor-related share more frequently using the most recent available data. The commenter stated that the current calculation of the labor-related share is based on 2002 data. Another commenter said that the methodology does not adequately reflect the difficulty IRFs have in recruiting a skilled labor force.

Response: The FY 2009 labor-related share is intended to reflect those costs that are related to, influenced by, or vary with the local labor market. Accordingly, the share is calculated as the sum of the relative importance of the appropriate categories which include wages and salaries, fringe benefits, professional fees, labor-intensive services, and a portion of capital costs. We calculate this share based on the RPL market basket, which we believe adequately captures the current cost structures of Medicare-participating IRFs.

By following a four-step process to estimate the labor-related relative importance for FY 2009, we are making use of up-to-date data that reflect current trends. As a result, the labor-related share appropriately reflects current labor market price pressures experienced by IRFs. The process is as follows: First, we compute the FY 2009 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 2009 price index level for that cost category by the total market basket price index level. Third, we determine the FY 2009 relative importance for each cost category by multiplying this ratio by the base year (FY 2002) weight. Finally, we sum the FY 2009 relative importance for each of the labor-related categories to produce the FY 2009 labor-related relative importance.

The price proxies that move the different cost categories in the market basket do not necessarily change at the same rate, and the relative importance captures these potential differential growth rates. Accordingly, the relative importance figure more closely reflects the cost share weights for FY 2009 when compared to the base year weights from the 2002-based RPL market basket. We revised and rebased the market basket and labor-related share in FY 2006 and expect to conduct additional updates on a regular basis.

Final Decision: We will continue to apply a zero percent increase factor to the IRF Federal prospective payment rates for FY 2009, in accordance with section 115 of the MMSEA. Further, we will continue to update the IRF labor-related share using our current methodology, which reflects the most recent available data. Thus, for this final rule, the labor-related share is 75.464 percent. This is based on the GII's forecast for the second quarter of 2008 (2008Q2) with historical data through the first quarter of 2008 (2008Q1).

B. Area Wage Adjustment

Section 1886(j)(6) of the Act requires the Secretary to adjust the proportion (as estimated by the Secretary from time to time) of rehabilitation facilities' costs attributable to wages and wage-related costs by a factor (established by the Secretary) reflecting the relative hospital wage level in the geographic area of the rehabilitation facility compared to the national average wage level for those facilities. The Secretary is required to update the IRF PPS wage index on the basis of information available to the Secretary on the wages and wage-related costs to furnish rehabilitation services. Any adjustments or updates made under section 1886(j)(6) of the Act for a FY are made in a budget neutral manner.

In the FY 2008 IRF PPS final rule (72 FR 44284 at 44299), we maintained the methodology described in the FY 2006 IRF PPS final rule to determine the wage index, labor market area definitions, and hold harmless policy consistent with the rationale outlined in the FY 2006 IRF PPS final rule (70 FR 47880, 47917 through 47933).

For FY 2009, we proposed to and will maintain the policies and methodologies described in the FY 2008 IRF PPS final rule relating to the labor market area definitions and the wage index methodology for areas with wage data. Therefore, this final rule continues to use the Core-Based Statistical Area (CBSA) labor market area definitions and the pre-reclassification and pre-floor hospital wage index data based on 2004 cost report data.

When adopting new labor market designations made by the Office of Management and Budget (OMB), we identified some geographic areas where there were no hospitals and, thus, no hospital wage index data on which to base the calculation of the IRF PPS wage index. We continue to use the same methodology discussed in the FY 2008 IRF PPS final rule (72 FR 44284 at 44299) to address those geographic areas where there are no hospitals and, thus, no hospital wage index data on which to base the calculation of the FY 2009 IRF PPS wage index.

Additionally, this final rule incorporates the CBSA changes published in the most recent OMB bulletin that applies to the hospital wage data used to determine the current IRF PPS wage index. The changes were nomenclature and did not represent substantive changes to the CBSA-based designations. Specifically, OMB added or deleted certain CBSA numbers and revised certain titles. The OMB bulletins are available online at http://www.whitehouse.gov/​omb/​bulletins/​index.html.

1. Clarification of New England Deemed Counties

We are taking this opportunity to address the change in the treatment of “New England deemed counties” (that is, those counties in New England listed in § 412.64(b)(1)(ii)(B) of the regulations that were deemed to be parts of urban areas under section 601(g) of the Social Security Amendments of 1983) that was made in the FY 2008 Inpatient Prospective Payment System (IPPS) final rule with comment period (72 FR 47337). These counties include the following: Litchfield County, CT; York County, ME; Sagadahoc County, ME; Merrimack County, NH; and Newport County, RI. Of these five “New England deemed counties,” three (York County, ME, Sagadahoc County, ME, and Newport County, RI) are also included in metropolitan statistical areas (MSAs) defined by OMB and are considered urban under both the current IPPS and IRF PPS labor market area definitions in § 412.64(b)(1)(ii)(A). The remaining two, Litchfield County, CT and Merrimack County, NH, are geographically located in areas that are considered rural under the current IPPS (and IRF PPS) labor market area definitions, but have been previously deemed urban under the IPPS in certain circumstances, as discussed below.

In the FY 2008 IPPS final rule with comment period, (72 FR 47337 through 47338), § 412.64(b)(1)(ii)(B) was revised that the two “New England deemed counties” that are still considered rural under the OMB definitions (Litchfield County, CT and Merrimack County, NH), are no longer considered urban, effective for discharges occurring on or after October 1, 2007, and, therefore, are considered rural in accordance with § 412.64(b)(1)(ii)(C). However, for purposes of payment under the IPPS, acute care hospitals located within those areas are treated as being reclassified to their deemed urban area effective for discharges occurring on or after October 1, 2007 (see 72 FR 47337 through 47338). We note that the IRF PPS does not provide for geographic reclassification. Also, in the FY 2008 IPPS final rule with comment period (72 FR 47338), we explained that we limited this policy change for the “New England deemed counties” only to IPPS hospitals, and any change to non-IPPS provider wage indexes would be addressed in the respective payment system rules.

Accordingly, as stated above, we are taking this opportunity to clarify the treatment of “New England deemed counties” under the IRF PPS in this final rule.

As discussed above, the IRF PPS has consistently used the IPPS definition of “urban” and “rural” with regard to the wage index used in the IRF PPS. Under existing § 412.602, an IRF's wage index is determined based on the location of the IRF in an urban or rural area as defined in §§ 412.64(b)(1)(ii)(A) through (C).

Historical changes to the labor market area/geographic classifications and annual updates to the wage index values under the IRF PPS are made effective October 1 each year. When we established the most recent IRF PPS payment rate update, effective for discharges occurring on or after October 1, 2007 through September 30, 2008, we considered the “New England deemed counties” (including Litchfield County, CT and Merrimack County, NH) as urban for FY 2008, as evidenced by the inclusion of Litchfield County, CT as one of the constituent counties of urban CBSA 25540 (Hartford-West Hartford-East Hartford, CT), and the inclusion of Merrimack County, NH as one of the constituent counties of urban CBSA 31700 (Manchester-Nashua, NH).

As noted above, § 412.602 indicates that the terms “rural” and “urban” are defined according to the definitions of those terms in §§ 412.64(b)(1)(ii)(A) through (C). Applying the IPPS definitions, Litchfield County, CT and Merrimack County, NH are not considered “urban” under §§ 412.64(b)(1)(ii)(A) and (B) as revised under the FY 2008 IPPS final rule and, therefore, are considered “rural” under § 412.64(b)(1)(ii)(C). Accordingly, reflecting our policy to use the IPPS definitions of “urban” and “rural”, these two counties would be considered “rural” under the IRF PPS effective with the next update of the IRF PPS payment rates, October 1, 2008, and would no longer be included in urban CBSA 25540 (Hartford-West Hartford-East Hartford, CT) and urban CBSA 31700 (Manchester-Nashua, NH), respectively. We note that this policy is consistent with our policy of not taking into account IPPS geographic reclassifications in determining payments under the IRF PPS. We do not need to make any changes to our regulations to effectuate this change.

There is one IRF (in Merrimack County, NH) that greatly benefits from treating these counties as rural. This IRF would begin to receive a higher wage index value and the 21.3 percent adjustment that is applied to IRF PPS payments for rural facilities. Currently, there are no IRFs in the following areas: Litchfield County, CT; rural Connecticut; or rural New Hampshire.

2. Multi-Campus Hospital Wage Index Data

In the FY 2008 IRF PPS final rule (72 FR 44284, August 7, 2007), we established IRF PPS wage index values for FY 2008 calculated from the same data (collected from cost reports submitted by hospitals for cost reporting periods beginning during FY 2003) used to compute the FY 2007 acute care hospital inpatient wage index, without taking into account geographic reclassification under sections 1886(d)(8) and (d)(10) of the Act. The IRF PPS wage index values applicable for discharges occurring on or after October 1, 2007 through September 30, 2008 are shown in Table 1 (for urban areas) and Table 2 (for rural areas) in the addendum to the FY 2008 IRF PPS final rule (72 FR 44284, 44312 through 44335).

We are continuing to use IPPS wage data for the FY 2009 IRF PPS Wage Index, because we believe that using the hospital inpatient wage data is appropriate and reasonable for the IRF PPS. We note that the IPPS wage data used to determine the FY 2009 IRF wage index values reflect our policy that was adopted under the IPPS beginning in FY 2008. The wage data for multi-campus hospitals located in different labor market areas (CBSAs) are apportioned to each CBSA where the campuses are located (see the FY 2008 IPPS final rule with comment period (72 FR 47317 through 47320)). We computed the FY 2009 IRF PPS wage index values presented in this final rule consistent with our pre-reclassified IPPS wage index policy (that is, our historical policy of not taking into account IPPS geographic reclassifications in determining payments under the IRF PPS).

For the FY 2009 IRF PPS, we computed the wage index from IPPS wage data (submitted by hospitals for cost reporting periods beginning in FY 2004 and used in the FY 2008 IPPS wage index), which allocated salaries and hours to the campuses of two multi-campus hospitals with campuses that are located in different labor areas, one in Massachusetts and another in Illinois. Thus, the FY 2009 IRF PPS wage index values for the following CBSAs are affected by this policy: Boston-Quincy, MA (CBSA 14484), Providence-New Bedford-Falls River, RI-MA (CBSA 39300), Chicago-Naperville-Joliet, IL (CBSA 16974) and Lake County-Kenosha County, IL-WI (CBSA 29404) (please refer to Table 1 in the addendum of this final rule).

3. Methodology for Applying the Revisions to the Area Wage Adjustment for FY 2009 in a Budget-Neutral Manner

To calculate the wage-adjusted facility payment for the payment rates set forth in this final rule, we multiply the unadjusted Federal prospective payment by the FY 2009 RPL labor-related share (75.464 percent) to determine the labor-related portion of the Federal prospective payments. We then multiply this labor-related portion by the applicable IRF wage index shown in Table 1 for urban areas and Table 2 for rural areas in the addendum.

Adjustments or updates to the IRF wage index made under section 1886(j)(6) of the Act must be made in a budget neutral manner; therefore, we calculated a budget neutral wage adjustment factor as established in the FY 2004 IRF PPS final rule (68 FR 45674 at 45689), codified at § 412.624(e)(1), and described in the steps below. We proposed to use (and have used for this final rule) the following steps to ensure that the FY 2009 IRF standard payment conversion factor reflects the update to the proposed wage indexes (based on the FY 2004 pre-reclassified and pre-floor hospital wage data) and the labor-related share in a budget neutral manner:

Step 1. Determine the total amount of the estimated FY 2008 IRF PPS rates, using the FY 2008 standard payment conversion factor and the labor-related share and the wage indexes from FY 2008 (as published in the FY 2008 IRF PPS final rule (72 FR 44284 at 44301, 44298, and 44312 through 44335, respectively)).

Step 2. Calculate the total amount of estimated IRF PPS payments, using the FY 2008 standard payment conversion factor and the FY 2009 labor-related share and CBSA urban and rural wage indexes.

Step 3. Divide the amount calculated in step 1 by the amount calculated in step 2, which equals the final FY 2009 budget neutral wage adjustment factor of 1.0003. (Note that this final budget neutral wage adjustment factor differs from the one we proposed in the proposed rule (1.0004) because of the use of updated data to calculate the labor-related share for this final rule and the use of updated FY 2007 IRF claims data for this final rule.)

Step 4. Apply the FY 2009 budget neutral wage adjustment factor from step 3 to the FY 2008 IRF PPS standard payment conversion factor after the application of the estimated market basket update to determine the FY 2009 standard payment conversion factor.

We received 4 comments on the proposed FY 2009 IRF PPS wage index, which are summarized below.

Comment: Several commenters recommended that we consider wage index policies under the acute IPPS because IRFs compete in a similar labor pool as acute care hospitals. The IPPS wage index policies would allow IRFs to benefit from the IPPS reclassification and/or floor policies. Several commenters also recommended that CMS conduct further analysis of the wage index methodology to ensure that fluctuations in the annual wage index for hospitals are minimized, that all future updates match the costs of labor in the market, that IRF's occupational mix is appropriately recognized, and that payments are “smoothed” across geography and across time. Further, one provider requested that the same wage index policies be used for all healthcare providers, to maintain consistency.

Response: We do not believe IPPS wage index policies should be applied to IRFs. We note the IRF PPS does not account for geographic reclassification under sections 1886(d)(8) and (d)(10) of the Act and does not apply the “rural floor” under section 4410 of Public Law 105-33(BBA). Because we do not have an IRF specific wage index we are unable to determine at this time the degree, if any, to which a geographic reclassification adjustment under the IRF PPS is appropriate. Furthermore, we believe the “rural floor” is applicable only to the acute care hospital payment system. The rationale for our current wage index policies is fully described in the FY 2006 final rule (70 FR 47880, 47926 through 47928).

In addition, we reviewed the Medicare Payment Advisory Commission's (MedPAC) wage index recommendations as discussed in MedPAC's June 2007 report titled, “Report to Congress: Promoting Greater Efficiency in Medicare.” Although some commenters recommended that we adopt the IPPS wage index policies such as reclassification and floor policies, we note that MedPAC's June 2007 report to Congress recommends that Congress “repeal the existing hospital wage index statute, including reclassification and exceptions, and give the Secretary authority to establish new wage index systems.” We believe that adopting the IPPS wage index policies, such as reclassification or floor, would not be prudent at this time because MedPAC suggests that the reclassification and exception policies in the IPPS wage index alters the wage index values for one-third of IPPS hospitals. In addition, MedPAC found that the exceptions may lead to anomalies in the wage index. By adopting the IPPS reclassification and exceptions at this time, the IRF PPS wage index may be vulnerable to similar issues that MedPAC identified in their June 2007 Report to Congress. However, we will continue to review and consider MedPAC's recommendations on a refined or an alternative wage index methodology for the IRF PPS in future years.

We would also like to inform the commenter about our current research with respect to wage index methodology, including the issues the commenter mentioned about ensuring that the wage index minimizes fluctuations, matches the costs of labor in the market, and provides for a single wage index policy. Section 106(b)(2) of the MIEA-TRHCA instructed the Secretary of Health and Human Services, to take into account MedPAC's recommendations on the Medicare wage index classification system, to include in the FY 2009 IPPS proposed rule one or more proposals to revise the wage index adjustment applied under section 1886(d)(3)(E) of the Act for purposes of the IPPS. The proposal (or proposals) must consider each of the following:

• Problems associated with the definition of labor markets for the wage index adjustment.
• The modification or elimination of geographic reclassifications and other adjustments.
• The use of Bureau of Labor of Statistics data or other data or methodologies to calculate relative wages for each geographic area.
• Minimizing variations in wage index adjustments between and within MSAs and statewide rural areas.
• The feasibility of applying all components of CMS's proposal to other settings.
• Methods to minimize the volatility of wage index adjustments while maintaining the principle of budget neutrality.
• The effect that the implementation of the proposal would have on health care providers on each region of the country.
• Methods for implementing the proposal(s) including methods to phase in such implementations.
• Issues relating to occupational mix such as staffing practices and any evidence on quality of care and patient safety including any recommendation for alternative calculations to the occupational mix.

To assist us in meeting the requirements of section 106(b)(2) of Public Law 109-432, in February 2008, we awarded a Task Order under its Expedited Research and Demonstration Contract, to Acumen, LLC. A comparison of the current IPPS wage index and MedPAC's recommendations will be presented in the FY 2009 IPPS final rule. We plan to monitor these efforts and the impact or influence they may have to the IRF PPS wage index.

Comment: One commenter requested that the IRF wage index values for FY 2009 be capped at plus or minus 2 percent of the IRF wage index values for FY 2008 to provide for more stable, and thus more predictable, changes in the IRF wage index between FY 2008 and FY 2009.

Response: We will take the commenter's suggestion into account for the future. However, we do not believe that the IRF wage index would accurately reflect geographic variations in the costs of labor, which is the purpose of the IRF wage index, if we were to constrain changes in the wage index adjustment from year to year. Thus, we believe it is best at this point to continue the analysis of the wage index methodology, as described above, and to consider developing wage index policies that are consistent across settings as noted in the previous response.

Final Decision: We will continue to use the policies and methodologies described in the FY 2008 IRF PPS final rule relating to the labor market area definitions and the wage index methodology for areas with wage data. Therefore, this final rule continues to use the Core-Based Statistical Area (CBSA) labor market area definitions and the pre-reclassification and pre-floor hospital wage index data based on 2004 cost report data. We discuss the final standard payment conversion factor for FY 2009 in the next section below.

C. Description of the IRF Standard Payment Conversion Factor and Payment Rates for FY 2009

To calculate the standard payment conversion factor for FY 2009, as illustrated in Table 4 below, we begin with the standard payment conversion factor for FY 2008. To explain how we determined the standard payment conversion factor for FY 2008, we include Table 3 below. The final FY 2008 IRF standard payment conversion factor that we show in Tables 3 and 4 below is different than the IRF standard payment conversion factor that we published in the FY 2008 IRF PPS final rule (72 FR 44284 at 44301) due to a legislative change. We adjusted the IRF standard payment conversion factor for IRF discharges occurring on or after April 1, 2008 to reflect the changes codified in section 115 of the MMSEA that require the Secretary to apply a zero percent increase factor for FYs 2008 and 2009, effective for discharges occurring on or after April 1, 2008.

In the FY 2008 IRF PPS final rule (72 FR 44284, 44300 through 44301), we used the RPL market basket estimate described in that final rule (3.2 percent) to update the IRF standard payment conversion factor. As shown in Table 3 of the FY 2008 IRF PPS final rule (72 FR 44284 at 44301), applying this market basket estimate to the standard payment amount resulted in a final standard payment conversion factor for FY 2008 of $13,451.

However, section 115 of the MMSEA had the effect of changing the increase factor for FY 2008 from 3.2 percent to zero percent for discharges occurring on or after April 1, 2008. This, in turn, had the effect of decreasing the IRF standard payment conversion factor for discharges occurring on or after April 1, 2008.

As shown in Table 3 below, to develop the FY 2008 standard payment conversion factor for discharges beginning on or after April 1, 2008, we started with the FY 2007 standard payment conversion factor that was finalized in the FY 2007 IRF PPS final rule (71 FR 48354 at 48378). We then multiplied this by the zero percent increase factor, as described above. Then, we applied the same FY 2008 budget neutrality factor (1.0041) for the Wage Index, Labor-Related Share, and the Hold Harmless Provision that was published in the FY 2008 IRF PPS Final Rule (72 FR 44284 at 44301). This resulted in the final FY 2008 standard payment conversion factor, effective for discharges occurring on or after April 1, 2008, of $13,034.

Table 3—Calculations To Determine the FY 2008 IRF Standard Payment Conversion Factor for Discharges Beginning on or After April 1, 2008

Explanation for adjustment	Calculations
FY 2007 Standard Payment Conversion Factor (published in the FY 2007 IRF PPS Final Rule (71 FR 48354))	$12,981
Zero Percent Increase Factor for Discharges Occurring on or after April 1, 2008	× 1.0000
Budget Neutrality Factor for the Wage Index, Labor-Related Share, and the Hold Harmless Provision that was published in the FY 2008 IRF PPS Final Rule (72 FR 44284)	× 1.0041
Standard Payment Conversion Factor for Discharges Occurring on or after April 1, 2008	= $13,034

As a result, the IRF standard payment conversion factor changed from $13,451 for discharges occurring on or after October 1, 2007 to $13,034 for discharges occurring on or after April 1, 2008.

Further, as required by section 115 of the MMSEA, we apply an increase factor of zero percent to the standard payment conversion factor for FY 2009, meaning that it does not change from the current value of $13,034. Next, we apply the combined final budget neutrality factor for the FY 2009 wage index and labor related share of 1.0003, which results in a standard payment amount of $13,038. Finally, we apply the final budget neutrality factor for the revised CMG relative weights of 0.9939, which results in the final FY 2009 standard payment conversion factor of $12,958.

As stated previously, we note that the budget neutrality factor for the FY 2009 wage index and labor related share changed from 1.0004 in the proposed rule to 1.0003 in this final rule due to the use of updated FY 2007 IRF claims data in this final rule and the update to the FY 2009 labor-related share for this final rule using the most recent available data. Similarly, the budget neutrality factor used to update the CMG relative weights and average length of stay values changed from 0.9969 in the proposed rule to 0.9939 in this final rule due to the use of updated FY 2007 IRF claims data in this final rule. Furthermore, the methodology that we used to compute the final budget neutrality factors for this final rule is the same methodology (as discussed above and in section IV of this final rule) that we used to compute the proposed budget neutrality factors in the proposed rule (73 FR 22674 at 22677 and 22683).

Table 4—Calculations To Determine the FY 2009 Standard Payment Conversion Factor

Explanation for adjustment	Calculations
Standard Payment Conversion Factor for Discharges Occurring on or after April 1, 2008	$13,034
Zero Percent Increase Factor for FY 2009	× 1.0000
Budget Neutrality Factor for the Wage Index and Labor-Related Share	× 1.0003
Budget Neutrality Factor for the Revisions to the CMG Relative Weights	× 0.9939
FY 2009 Standard Payment Conversion Factor	= $12,958

After the application of the CMG relative weights described in section IV of this final rule, the resulting unadjusted IRF prospective payment rates for FY 2009 are shown below in Table 5, “FY 2009 Payment Rates.”

Table 5—FY 2009 Payment Rates

CMG	Payment rate tier 1	Payment rate tier 2	Payment rate tier 3	Payment rate no comorbidity
0101	$9,993.21	$9,210.55	$8,268.50	$7,851.25
0102	12,561.49	11,579.27	10,393.61	9,870.11
0103	14,873.19	13,709.56	12,304.92	11,685.52
0104	15,798.39	14,562.20	13,070.73	12,412.47
0105	18,555.86	17,103.26	15,352.64	14,579.05
0106	21,551.75	19,864.61	17,831.50	16,932.22
0107	24,581.33	22,657.06	20,337.58	19,312.60
0108	29,537.76	27,226.05	24,438.79	23,207.78
0109	28,230.30	26,020.96	23,356.80	22,180.21
0110	35,267.79	32,507.73	29,178.82	27,709.39
0201	9,791.06	8,376.05	7,538.96	6,861.26
0202	13,353.22	11,425.07	10,282.17	9,358.27
0203	14,884.85	12,735.12	11,462.65	10,432.49
0204	16,759.88	14,339.32	12,904.87	11,745.13
0205	20,394.60	17,449.24	15,703.80	14,292.67
0206	25,306.97	21,651.52	19,487.54	17,735.61
0207	34,088.61	29,165.87	26,249.02	23,890.66
0301	14,362.65	12,061.31	10,830.30	9,912.87
0302	18,296.70	15,364.30	13,796.38	12,628.87
0303	21,948.26	18,431.46	16,549.96	15,149.20
0304	29,971.85	25,169.62	22,600.05	20,688.74
0401	11,992.63	10,214.79	10,019.13	8,508.22
0402	18,054.38	15,378.55	15,083.11	12,810.28
0403	29,574.04	25,190.35	24,707.02	20,984.19
0404	51,528.78	43,891.34	43,049.07	36,561.00
0405	39,323.64	33,496.43	32,853.71	27,901.17
0501	10,505.05	8,289.23	7,703.53	6,796.47
0502	14,246.03	11,241.07	10,446.74	9,217.03
0503	18,549.38	14,637.36	13,602.01	12,000.40
0504	22,325.34	17,617.70	16,371.14	14,444.28
0505	26,382.49	20,818.32	19,346.29	17,069.57
0506	36,703.54	28,962.43	26,913.77	23,745.54
0601	11,979.67	9,778.11	9,296.07	8,477.12
0602	16,023.86	13,079.81	12,434.50	11,338.25
0603	20,425.70	16,671.76	15,850.23	14,453.35
0604	27,065.37	22,092.09	21,002.33	19,151.92
0701	11,904.51	10,032.08	9,459.34	8,504.34
0702	15,699.91	13,228.82	12,474.67	11,215.15
0703	19,237.45	16,210.46	15,286.55	13,743.25
0704	24,612.43	20,739.28	19,557.51	17,582.71
0801	9,070.60	7,391.24	6,701.88	6,108.40
0802	12,154.60	9,903.80	8,981.19	8,185.57
0803	17,341.69	14,130.70	12,814.17	11,679.05
0804	15,219.17	12,402.10	11,246.25	10,249.78
0805	18,997.72	15,480.92	14,037.40	12,794.73
0806	23,504.52	19,151.92	17,367.61	15,828.20
0901	11,123.15	9,814.39	8,849.02	7,827.93
0902	14,866.71	13,116.09	11,826.77	10,462.29
0903	19,229.67	16,965.91	15,298.21	13,532.04
0904	25,423.60	22,430.30	20,224.85	17,891.11
1001	12,123.50	11,741.24	10,103.35	9,248.12
1002	16,226.01	15,714.17	13,521.67	12,377.48
1003	23,574.49	22,830.70	19,645.62	17,981.82
1101	15,350.05	12,764.93	12,764.93	11,089.46
1102	22,401.79	18,629.72	18,629.72	16,184.54
1201	13,371.36	12,527.79	10,992.27	9,771.63
1202	16,889.46	15,824.31	13,884.50	12,342.50
1203	21,223.91	19,885.35	17,447.95	15,509.43
1301	14,231.77	12,794.73	11,013.00	9,910.28
1302	19,164.88	17,228.96	14,830.43	13,345.44
1303	24,801.61	22,298.13	19,193.39	17,271.72
1401	10,370.29	9,356.97	8,277.57	7,343.30
1402	14,376.90	12,970.96	11,475.60	10,179.80
1403	17,594.37	15,874.85	14,043.88	12,459.12
1404	22,842.36	20,609.70	18,233.20	16,175.47
1501	12,443.57	10,866.58	9,605.77	9,119.84
1502	15,934.45	13,915.60	12,302.33	11,679.05
1503	20,266.31	17,698.04	15,645.49	14,853.76
1504	25,300.50	22,094.69	19,531.59	18,542.90
1601	14,375.61	11,620.73	9,934.90	9,158.71
1602	19,408.49	15,689.55	13,412.83	12,365.82
1603	24,992.09	20,201.52	17,270.42	15,921.49
1701	13,546.29	11,907.11	10,963.76	9,613.54
1702	17,852.24	15,692.14	14,449.47	12,670.33
1703	21,466.22	18,868.14	17,374.09	15,234.72
1704	26,921.54	23,662.60	21,788.88	19,105.28
1801	15,794.51	12,477.26	11,719.22	10,051.52
1802	23,840.13	18,831.86	17,688.97	15,171.23
1803	40,742.54	32,185.08	30,229.72	25,927.66
1901	15,007.96	12,035.39	12,035.39	11,379.72
1902	30,332.09	24,324.76	24,324.76	22,999.15
1903	46,576.24	37,351.44	37,351.44	35,315.73
2001	11,428.96	9,436.02	8,570.42	7,681.50
2002	15,385.03	12,702.73	11,537.80	10,340.48
2003	19,736.33	16,294.69	14,800.63	13,265.10
2004	26,386.38	21,784.99	19,788.16	17,734.32
2101	30,666.40	30,666.40	27,835.08	22,616.89
5001	0.00	0.00	0.00	1,912.60
5101	0.00	0.00	0.00	8,789.41
5102	0.00	0.00	0.00	19,996.79
5103	0.00	0.00	0.00	9,182.04
5104	0.00	0.00	0.00	25,379.54

We received 3 comments on the proposed standard payment conversion factor and the proposed unadjusted IRF prospective payment rates for FY 2009, which are summarized below.

Comment: One commenter recommended that CMS use the most recent available data in computing the FY 2009 CMG relative weights, because these have an impact on the FY 2009 IRF prospective payment rates and the budget neutrality factors used in computing the FY 2009 standard payment conversion factor.

Response: We agree that we should use the most recent available data in computing the FY 2009 CMG relative weights. We typically update the data we use in our analysis each year between the proposed and final rules in order to ensure that we are using the most current available data. Specifically, in the proposed rule (73 FR 22674 at 22677), we proposed to update our analysis for this final rule using more current data. Thus, we updated our data analysis using FY 2007 IRF claims data for the final rule, whereas we had used FY 2006 IRF claims data in conducting the analysis for the FY 2009 IRF PPS proposed rule (73 FR 22674 at 22677). As discussed in detail in section IV of this final rule, we did not use IRF-PAI data for this final rule because the CMG information on the FY 2007 IRF claims data incorporated all of the most recent changes to the IRF classification system that were implemented in the FY 2007 IRF PPS final rule (71 FR 48354). Moreover, we did not implement any changes to the IRF classification system in the FY 2008 IRF PPS final rule (72 FR 44284).

The revised final budget neutrality factors for FY 2009 reflect the updated FY 2009 IRF labor-related share and the revised CMG relative weights and average length of stay values described above.

Comment: Several commenters requested that we keep the same standard payment conversion factor of $13,034 for FY 2009 that was used for determining IRF PPS payments in FY 2008, for discharges occurring on or after April 1, 2008. In effect, we believe that these commenters were asking us not to apply the combined budget neutrality factor for the wage index and labor-related share or the budget neutrality factor for the revisions to the CMG relative weights to the FY 2008 standard payment conversion factor in determining the FY 2009 standard payment conversion factor. Another commenter asked us to provide a more extensive explanation of the methodology that we use to compute the budget neutrality factors, including any background studies on the methodology and calculations for the budget neutrality factors.

Response: Section 1886(j)(6) of the Act requires CMS to make any adjustments or updates to the IRF wage index in a budget neutral manner. To do this, we ensure that estimated aggregate payments to IRFs in the FY are not greater or less than estimated aggregate payments would have been without such adjustments or updates to the wage index. Thus, in accordance with the statute and using the same general methodology that was described and finalized in the FY 2004 IRF PPS final rule (68 FR 45674 at 45689), we are required to adjust the FY 2008 standard payment conversion factor of $13,034 by the combined final budget neutrality factor for the FY 2009 wage index and labor related share of 1.0003, which results in a standard payment amount of $13,038.

Further, in accordance with the regulations at § 412.624(d)(4), as discussed in the FY 2006 IRF PPS final rule (70 FR 47880 at 47937), we apply an additional budget neutrality factor to make the updates to the CMG relative weights and average length of stay values budget neutral. The final budget neutrality factor used to update the CMG relative weights and average length of stay values for this final rule is 0.9939, which results in a standard payment amount of $12,958. As discussed above, the budget neutrality factor used to update the CMG relative weights and average length of stay values changed from 0.9969 in the proposed rule to 0.9939 in this final rule due to the use of updated FY 2007 IRF claims data in this final rule. Although the standard payment conversion factor for FY 2009 of $12,958 is lower than the standard payment conversion factor applicable for discharges occurring on or after April 1, 2008, of $13,034, estimated aggregate IRF payments for FY 2009, excluding outlier payments, are the same. This is because we estimate that aggregate IRF payments would have increased by about $37 million, due to the update to the CMG relative weights for FY 2009, if we had not applied the budget-neutrality factor used to update the CMG relative weights and average length of stay values.

We have consistently implemented any revisions to the IRF classification and weighting factors in a budget-neutral manner, such that estimated aggregate payments to IRFs remain the same with and without the revisions. The methodology for computing the budget neutrality factor is the same general methodology that we have consistently used to ensure that the changes to the classification and weighting factors that we implemented in the FY 2006 IRF PPS final rule (70 FR 47880) and in the FY 2007 IRF PPS final rule (71 FR 48354) were done in a budget-neutral manner. (Note that we did not implement any changes to the IRF classification or weighting factors in the FY 2008 IRF PPS final rule (72 FR 44284)). The methodology that we are using in this final rule to compute the budget neutrality factor for the updates to the CMG relative weights is the same general methodology that we have used to ensure that updates to the IRF wage index are implemented in a budget-neutral manner, as discussed above and as finalized in the FY 2004 IRF PPS final rule (68 FR 45674 at 45689). The methodology, as proposed in the FY 2009 IRF PPS proposed rule (73 FR 22674 at 22677) and finalized in this final rule, applied to the update to the CMG relative weights for FY 2009 involves the following steps:

Step 1. Calculate the estimated total amount of IRF PPS payments for FY 2009 (with no changes to the CMG relative weights).

Step 2. Apply the changes to the CMG relative weights (as discussed in section IV of this final rule) to calculate the estimated total amount of IRF PPS payments for FY 2009 (with the changes).

Step 3. Divide the amount calculated in step 1 ($6,003,947,007) by the amount calculated in step 2 ($6,040,824,839) to determine the factor (0.9939) that maintains the same total estimated aggregate payments in FY 2009 with and without the changes to the CMG relative weights.

Step 4. Apply the final budget neutrality factor (0.9939) to the FY 2008 IRF PPS standard payment amount after the application of the budget-neutral wage adjustment factor.

The FY 2004 IRF PPS final rule (68 FR 45674 at 45689) contains additional information on the methodology for computing the budget neutrality factor for the IRF wage index and labor-related share, and the FY 2006 IRF PPS final rule (70 FR 47880, 47937 through 47938) contains additional information on the methodology for computing the budget neutrality factor for the updates to the CMG relative weights and average length of stay values.

Final Decision: After reviewing the comments that we received on the proposed methodology for calculating the budget neutrality factors for the wage index and labor-related share and for the CMG relative weights and average length of stay values, we are finalizing the proposed methodology. We are also finalizing the FY 2009 standard payment conversion factor at $12,958. This differs from the standard payment conversion factor of $12,999 that we had proposed in the proposed rule because of the use of updated FY 2007 IRF claims data for analyzing the final CMG relative weights and average length of stay values for this final rule, as discussed in section IV of this final rule.

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

Table 6 illustrates the methodology for adjusting the Federal prospective payments (as described in sections III.A through III.C of the FY 2009 proposed rule (73 FR 22674, 22680 through 22685)). The examples below are based on two hypothetical Medicare beneficiaries, both classified into CMG 0110 (without comorbidities). The unadjusted Federal prospective payment rate for CMG 0110 (without comorbidities) appears in Table 5 above.

One beneficiary is in Facility A, an IRF located in rural Spencer County, Indiana, and another beneficiary is in Facility B, an IRF located in urban Harrison County, Indiana. Facility A, a non-teaching hospital, has a disproportionate share hospital (DSH) percentage of 5 percent (which results in a low-income percentage (LIP) adjustment of 1.0309), a wage index of 0.8576, and an applicable rural adjustment of 21.3 percent. Facility B, a teaching hospital, has a DSH percentage of 15 percent (which results in a LIP adjustment of 1.0910), a wage index of 0.9065, and an applicable teaching status adjustment of 0.109.

To calculate each IRF's labor and non-labor portion of the Federal prospective payment, we begin by taking the unadjusted Federal prospective payment rate for CMG 0110 (without comorbidities) from Table 5 above. Then, we multiply the estimated labor-related share (75.464) described in section V.A of this final rule by the unadjusted Federal prospective payment rate. To determine the non-labor portion of the Federal prospective payment rate, we subtract the labor portion of the Federal payment from the unadjusted Federal prospective payment.

To compute the wage-adjusted Federal prospective payment, we multiply the result of the labor portion of the Federal payment by the appropriate wage index found in the addendum in Tables 1 and 2, which would result in the wage-adjusted amount. Next, we compute the wage-adjusted Federal payment by adding the wage-adjusted amount to the non-labor portion.

Adjusting the Federal prospective payment by the facility-level adjustments involves several steps. First, we take the wage-adjusted Federal prospective payment and multiply it by the appropriate rural and LIP adjustments (if applicable). Second, to determine the appropriate amount of additional payment for the teaching status adjustment (if applicable), we multiply the teaching status adjustment (0.109, in this example) by the wage-adjusted and rural-adjusted amount (if applicable). Finally, we add the additional teaching status payments (if applicable) to the wage, rural, and LIP-adjusted Federal prospective payment rates. Table 6 illustrates the components of the adjusted payment calculation.

Table 6—Example of Computing an IRF FY 2009 Federal Prospective Payment

Steps	Rural facility A (Spencer Co., IN)	Urban Facility B (Harrison Co., IN)
1. Unadjusted Federal Prospective Payment	$27,709.39	$27,709.39
2. Labor Share	× 0.75464	× 0.75464
3. Labor Portion of Federal Payment	= $20,910.61	= $20,910.61
4. CBSA Based Wage Index (shown in the Addendum, Tables 1 and 2)	× 0.8576	× 0.9065
5. Wage-Adjusted Amount	= $17,932.94	= $18,955.47
6. Non-labor Amount	+ $6,798.78	+ $6,798.78
7. Wage-Adjusted Federal Payment	= $24,731.72	= $25,754.25
8. Rural Adjustment	× 1.213	× 1.000
9. Wage- and Rural-Adjusted Federal Payment	= $29,999.57	= $25,754.25
10. LIP Adjustment	× 1.0309	× 1.0910
11. FY 2009 Wage-, Rural- and LIP-Adjusted Federal Prospective Payment Rate	= $30,926.56	= $28,097.88
12. FY 2009 Wage- and Rural-Adjusted Federal Prospective Payment	$29,999.57	$25,754.25
13. Teaching Status Adjustment	× 0.000	× 0.109
14. Teaching Status Adjustment Amount	= $0.00	= $2,807.21
15. FY 2009 Wage-, Rural-, and LIP-Adjusted Federal Prospective Payment Rate	+ $30,926.56	+ $28,097.88
16. Total FY 2009 Adjusted Federal Prospective Payment	= $30,926.56	= $30,905.10

Thus, the adjusted payment for Facility A would be $30,926.56 and the adjusted payment for Facility B would be $30,905.10.

VI. Update to Payments for High-Cost Outliers Under the IRF PPS

A. Update to the Outlier Threshold Amount for FY 2009

Section 1886(j)(4) of the Act provides the Secretary with the authority to make payments in addition to the basic IRF prospective payments for cases incurring extraordinarily high costs. A case qualifies for an outlier payment if the estimated cost of the case exceeds the adjusted outlier threshold. We calculate the adjusted outlier threshold by adding the IRF PPS payment for the case (that is, the CMG payment adjusted by all of the relevant facility-level adjustments) and the adjusted threshold amount (also adjusted by all of the relevant facility-level adjustments). Then, we calculate the estimated cost of a case by multiplying the IRF's overall CCR by the Medicare allowable covered charge. If the estimated cost of the case is higher than the adjusted outlier threshold, we make an outlier payment for the case equal to 80 percent of the difference between the estimated cost of the case and the outlier threshold.

In the FY 2002 IRF PPS final rule (66 FR 41316, 41362 through 41363), we discussed our rationale for setting the outlier threshold amount for the IRF PPS so that estimated outlier payments would equal 3 percent of total estimated payments. Subsequently, we updated the IRF outlier threshold amount in the FYs 2006, 2007, and 2008 IRF PPS final rules (70 FR 47880, 70 FR 57166, 71 FR 48354, and 72 FR 44284, respectively) to maintain estimated outlier payments at 3 percent of total estimated payments. We also stated that we would continue to analyze the estimated outlier payments for subsequent years and adjust the outlier threshold amount as appropriate to maintain the 3 percent target.

As was proposed, for this final rule, we used updated data for calculating the high-cost outlier threshold amount. Specifically, we performed an updated analysis using FY 2007 claims data using the same methodology that we used to set the initial outlier threshold amount in the FY 2002 IRF PPS final rule (66 FR 41316, 41362 through 41363), which is also the same methodology that we used to update the outlier threshold amounts for FYs 2006, 2007, and 2008. (Note: the methodology that we use to calculate the appropriate outlier threshold amount for each FY requires us to simulate Medicare payments for that FY, using the most recent available IRF claims data from a previous FY. If the previous FY's data that we are using for the analysis does not contain exactly the same CMGs as the future FY for which we are calculating the update to the outlier threshold, then we cannot rely on the CMGs from the previous FY's IRF claims data and must instead use IRF-PAI data to assign the appropriate CMG for each IRF claim.) The CMGs and tiers in effect for FY 2009 would be slightly different than those that were in effect for FY 2006, due to revisions that were implemented in the FY 2007 IRF PPS final rule (71 FR 48354, 48360 through 48370). Use of the IRF-PAI data was no longer necessary when we used the updated FY 2007 IRF claims data for this final rule because the CMG information on the FY 2007 IRF claims data incorporated all of the changes to the IRF classification system that were implemented in the FY 2007 IRF PPS final rule (71 FR 48354, 48360 through 48370). We did not implement any changes to the IRF classification system in the FY 2008 IRF PPS final rule (72 FR 44284).

For FY 2009, based on an analysis of updated FY 2007 claims data, we estimate that IRF outlier payments as a percentage of total estimated payments would be 4.2 percent without the change to the outlier threshold amount. The need to revise the high-cost outlier threshold is discussed in detail in section IV.A of the FY 2009 proposed rule (73 FR 22674, 22686 through 22687). Generally, we note that the zero percent IRF increase factor for FYs 2008 and 2009, for discharges occurring on or after April 1, 2008, implemented by section 115 of the MMSEA resulted in lower IRF PPS payments for FYs 2008 and 2009 than would otherwise have been implemented. In addition, IRF charges found in the FY 2007 IRF claims data were higher than those in the FY 2006 IRF claims data, resulting in higher estimated outlier payments for FY 2009.

Based on the updated analysis of FY 2007 claims data (for the reasons discussed previously, IRF-PAI data was not needed in this analysis), we are updating the outlier threshold amount to $10,250 to maintain estimated outlier payments at 3 percent of total estimated aggregate IRF payments for FY 2009.

B. Update to the IRF Cost-to-Charge Ratio Ceilings

In accordance with the methodology stated in the FY 2004 IRF PPS final rule (68 FR 45674, 45692 through 45694), we apply a ceiling to IRFs' CCRs. Using the methodology described in that final rule, as discussed in more detail in section IV.B of the FY 2009 proposed rule (73 FR 22674 at 22687), we are updating the national urban and rural CCRs for IRFs. As was proposed, the national average rural and urban CCRs and our estimate of the national CCR ceiling are changing in this final rule based on the analysis of updated data. We apply the national urban and rural CCRs in the following situations:

• New IRFs that have not yet submitted their first Medicare cost report.
• IRFs whose overall CCR is in excess of the national CCR ceiling for FY 2009, as discussed below.
• Other IRFs for which accurate data to calculate an overall CCR are not available.

Specifically, for FY 2009, we estimate a national average CCR of 0.619 for rural IRFs and 0.490 for urban IRFs based on the most recent available IRF cost report data. For this final rule, we have used FY 2006 IRF cost report data, updated through March 31, 2008. If, for any IRF, the FY 2006 cost report was missing or had an “as submitted” status, we use data from a previous fiscal year's report for that IRF. However, we do not use cost report data from before FY 2003 for any IRF. For new IRFs, we use these national CCRs until the facility's actual CCR can be computed using the first settled cost report (either tentative or final, whichever is earlier).

In addition, we estimate the national CCR ceiling at 1.60 for FY 2009. This means that, if an individual IRF's CCR exceeds this ceiling of 1.60 for FY 2009, we would replace the IRF's CCR with the appropriate national average CCR (either rural or urban, depending on the geographic location of the IRF). For a complete description of the methodology used to calculate the national CCR ceiling for this final rule, see section IV.B of the FY 2009 proposed rule (73 FR 22674 at 22687).

We received seven comments on the proposed high-cost outlier updates under the IRF PPS, which are summarized below.

Comment: Most commenters supported our proposal to increase the outlier threshold amount to maintain estimated outlier payments at 3 percent of total estimated payments. However, several other commenters expressed concerns that the change would mean that fewer cases would qualify for outlier payments and that it would affect IRFs' ability to provide care to Medicare beneficiaries. Several commenters asked that we further explain the reasons behind the increase in the IRF outlier threshold amount and provide proof that we would be paying more than 3 percent in outliers without the change. Finally, one commenter said that the increases in the outlier threshold amount in recent years appear excessive and recommended that CMS look more closely to determine if there are anomalies in the IRF outlier data or institutional practices that may be causing the changes.

Response: Based on our analysis of FY 2007 IRF claims and FY 2006 IRF cost report data (as previously discussed, we did not need to use IRF-PAI data in conjunction with the FY 2007 IRF claims data), we need to increase the IRF outlier threshold amount to maintain estimated outlier payments at 3 percent of total estimated payments for FY 2009 for the following reasons. First, as discussed in detail in the FY 2009 IRF PPS proposed rule (73 FR 22674, 22686 through 22687), section 115 of the MMSEA, which amended section 1886(j)(3)(C) of the Social Security Act, required the Secretary to apply a zero percent increase factor for FYs 2008 and 2009, effective for discharges occurring on or after April 1, 2008. The effect of this change was to decrease projected IRF PPS payments. As a direct result of a zero percent update, we would exceed our projected 3 percent target for the proportion of estimated IRF outlier payment to estimated IRF total payments.

Second, because the average charges per case in the FY 2007 data are significantly higher than the average charges per case in the FY 2006 data, we believe that our increase to the outlier threshold amount for FY 2009 is warranted. Specifically, higher charges directly result in more cases being estimated to qualify for outlier payments and higher estimated outlier payments, which in turn lead to higher estimates of outlier payments as a percentage of total estimated payments. In this case, higher charges result in estimated outlier payments as a percentage of total estimated payments in FY 2009 of 4.2 percent, well above the 3 percent target. To decrease estimated outlier payments as a percentage of total estimated payments from 4.2 percent to 3 percent, we must increase the outlier threshold.

The higher charges in the FY 2007 may be due to several factors, including the “75 percent” rule and the IRF medical review activities, which have led to declines in the number of IRF discharges and may have led to increases in the complexity of IRF cases. Thus, based on our analysis of updated data (that is, FY 2007 IRF claims data), we now project that estimated IRF outlier payments as a percentage of total estimated payments for FY 2008 increased from 3.0 percent to 3.7 percent.

Thus, given the recent changes in IRF aggregate payments resulting from section 115 of the MMSEA and recent increases in IRFs' charges that are being reflected in the IRF claims data for FY 2007, we believe that it is necessary to adjust the outlier threshold amount for FY 2009 to maintain estimated IRF outlier payments equal to 3 percent of estimated total payments.

As several of the commenters suggested, increasing the outlier threshold amount for FY 2009 would mean that fewer cases would qualify for IRF outlier payments. As discussed above, this is necessary to maintain estimated IRF outlier payments at 3 percent of estimated total payments. However, we do not believe that this will affect IRFs' ability to provide care to Medicare beneficiaries because the IRF outlier policy is designed to reduce the financial risk to IRFs, which could be substantial for many smaller IRFs, of admitting unusually high-cost cases. The additional IRF outlier payments reduce the financial losses caused by treating these patients and, therefore, reduce the incentives to underserve these patients. As discussed at length in the FY 2002 IRF PPS final rule (66 FR 41316 at 41362), we considered various options for setting the target percentage of estimated outlier payments as a percentage of total payments. In that final rule, we finalized our proposal to set an outlier policy of 3 percent of total estimated payments because we believed (and continue to believe) that this option optimizes the extent to which we protect vulnerable IRFs for treating unusually high-cost cases, while still providing adequate payment for all other IRF cases. If we were to increase the percentage of total estimated IRF payments that we paid in IRF outlier payments, then we would have to reduce IRF PPS payments for all other IRF cases in order to implement this change in a budget neutral manner. This could negatively affect the adequacy of IRF PPS payments for other, non-outlier IRF cases. Thus, we continue to believe that the 3 percent outlier policy ensures that all IRF cases, outlier and non-outlier, continue to be reimbursed appropriately.

As one of the commenters suggested, we will continue to analyze IRF outliers to determine if there are any anomalies in the IRF outlier data or any institutional practices which may be affecting our analysis of IRF outliers. To the extent that we find any such anomalies, we would propose to implement future refinements to the IRF outlier policies to ensure that IRF outlier payments continue to fulfill their intended purpose of reducing the risks to IRFs of treating unusually high-cost cases and ensuring access to care for all patients who require and can benefit from an IRF level of care.

Comment: One commenter recommended that we continue to refine our methodology for calculating the outlier threshold amount, and that we use the most accurate CCR data available.

Response: The CCR data that we use in our analyses comes directly from the Medicare cost reports submitted to Medicare by IRFs and is continually updated each time a more recent cost report is tentatively settled. Therefore, we believe that it is the most accurate and most recent CCR data available. However, we agree with the commenter about the need to continually examine our methodology and the CCR data to ensure that we are setting the IRF outlier threshold at the appropriate level to maintain estimated outlier payments at 3 percent of total estimated payments.

Comment: One commenter requested that we conduct an analysis of IRF outlier payments to ensure that we are not rewarding IRFs with outlier payments for the “wrong” reasons, such as the cost effects of declines in patient volume. This commenter suggested that we should either “hold back” outlier payments from facilities if we find that the outlier payments were paid for the “wrong” reasons, or that we should reduce the outlier pool from 3 percent to 1.5 percent.

Response: We are continuing to analyze IRF outlier payments to ensure that they continue to compensate IRFs for treating unusually high-cost patients and promote access to care for patients who are likely to require unusually high-cost care. At this time, we do not have indications to suggest that any IRF outlier payments are being paid for the “wrong” reasons. Further, we do not have indications to suggest that the outlier pool would be better set at 1.5 percent than at 3 percent. However, we will carefully consider this commenter's suggestions, and will consider proposing additional refinements to the IRF outlier policies in the future if we find that such refinements are necessary.

Comment: Several commenters requested that CMS provide additional data and information to the public to allow the IRF industry and external researchers to conduct a more thorough review of CMS's proposed updates to the outlier threshold amount and to verify our estimates of outlier payments as a percentage of total payments for FY 2009. Specifically, one commenter asked that we provide information on actual charge increases and CCR declines that have been utilized in the outlier threshold calculation, a discussion of the data sources and time periods used in computing the outlier threshold, an IRF Medpar file (including total payments, outlier payments, and actual, estimated, and proposed CMGs), historical information on IRF facility-level payment factors (specifically CCRs), and actual levels and percentages of outlier payments. The commenter also asked that we provide data on actual outlier payments and the percentage of outlier payments by FY.

Response: We will carefully consider all of the commenter's suggestions in updating the IRF rate setting files that we post on the IRF PPS Web site in conjunction with each IRF PPS proposed and final rule. These files are available for download from the IRF PPS Web site at http://www.cms.hhs.gov/​InpatientRehabFacPPS/​07_​DataFiles.asp#TopOfPage. These files already contain much of the facility-level payment data requested by the commenter, including the CCRs used to compute the IRF outlier threshold amount. For this final rule, we used FY 2007 IRF claims data to conduct patient-level payment simulations to estimate the outlier threshold amount for FY 2009. This data file contains information that can be used to identify individual Medicare beneficiaries and is therefore not publicly available. We obtained the provider-level CCR data used in this analysis from the Provider-Specific Files, which contain historical CCR data and are available for download from the CMS Web site at http://www.cms.hhs.gov/​ProspMedicareFeeSvcPmtGen/​03_​psf.asp.

The modified Medpar data files that CMS provides to IPPS hospitals already contain IRF stay data. However, we have recently discovered that these files do not include the CMGs, and we recognize that there may be other limitations to the usefulness of these files for analyzing IRF payments. Based on the commenters' requests, we will carefully consider the usefulness and feasibility of including additional variables, such as actual IRF outlier payments and the percentage of outlier payments, on the Medpar file in the future to facilitate IRF analyses.

Comment: One commenter suggested that CMS utilize the same concepts that the IPPS uses for modeling charge increases and cost-to-charge ratio (CCR) changes in estimating the outlier threshold amount, as noted in the methodology implemented for IPPS hospitals in the FY 2007 IPPS final rule (71 FR 47870, 48150 through 48151).

Response: We considered proposing the same methodology described in the FY 2007 IPPS final rule (71 FR 47870, 48150 through 48151) for projecting cost and charge growth in estimating the FY 2008 and FY 2009 IRF outlier threshold amount. However, we discovered that the accuracy of the projections depends on the case mix of patients in the facilities remaining similar from year to year, as it does in IPPS hospitals. With the recent phase in of the enforcement of the 75 percent rule criteria and increases in IRF medical review activities, we find evidence of relatively large changes in the case mix of patients in IRFs, especially in recent years (FYs 2004 through 2007). In performing our analysis, we noted that, if we based future projections of cost and charge growth on data from years in which IRFs were experiencing abnormal fluctuations in case mix, the results appeared dramatically skewed. Rather than implementing an outlier threshold amount for FY 2009 based on such skewed results, we thought a better approach would be to wait until we could further analyze the interactions between case mix changes and IRF cost and charge growth.

We are encouraged that IRF case mix may stabilize in the near future now that the IRF compliance percentage is set at 60 percent for FY 2009. However, as recently as FY 2007, we are still observing large shifts in IRFs' patient populations, and we believe it is prudent at this time to defer adopting a methodology for projecting cost and charge growth in IRFs until the patient populations have stabilized.

Final Decision: Based on careful consideration of the comments that we received on the proposed update to the outlier threshold amount for FY 2009 and based on updated analysis of the FY 2007 data explained previously in this section and for the reasons explained in the proposed rule (73 FR 22674, 22686 through 22687), we are finalizing our decision to update the outlier threshold amount for FY 2009. Based on our proposed policy, the outlier threshold amount for FY 2009 is $10,250. In addition, we did not receive any comments on the IRF cost-to-charge ratio ceiling. Based on our proposed policy and the reasons set forth in the proposed rule (73 FR 22674 at 22687), we are finalizing the national average urban CCR at 0.490 and the national average rural CCR at 0.619. We are also finalizing our estimate of the IRF national CCR ceiling at 1.60 for FY 2009.

VII. Revisions to the Regulation Text in Response to the Medicare, Medicaid, and SCHIP Extension Act of 2007

Section 115 of the MMSEA amended section 5005 of the Deficit Reduction Act of 2005 (DRA, Pub. L. 109-171) to revise the following elements of the 75 percent rule that are used to classify IRFs:

• The compliance rate that IRFs must meet to be excluded from the IPPS and to be paid under the IRF PPS shall be no greater than the 60 percent compliance rate that became effective for cost reporting periods beginning on or after July 1, 2006.
• Patient comorbidities that satisfy the criteria specified in 42 CFR 412.23(b)(2)(i) shall be included in the calculations used to determine whether an IRF meets the 60 percent compliance percentage for cost reporting periods beginning on or after July 1, 2007.

Although section 115 of the MMSEA grants the Secretary broad discretion to implement compliance criteria up to 60 percent, we are setting the compliance rate at 60 percent, the highest level possible within current statutory authority, for the reasons discussed in detail in the proposed rule (73 FR 22674, 22687 through 22688). Generally, we are setting the compliance rate at 60 percent because we believe that it implements the provisions of the statute with minimal disruption to IRF operations, thus allowing us to more effectively analyze changes in IRF operations and admissions patterns over time as well as helping us to ensure that IRFs predominantly treat patients who benefit most from this level of care.

Specifically, we proposed the following revisions to the regulation text in § 412.23(b). We proposed to remove the following phrases from the first sentence of § 412.23(b)(2)(i):

• “and before July 1, 2007;” and
• “and for cost reporting periods beginning on or after July 1, 2007 and before July 1, 2008, the hospital has served an inpatient population of whom at least 65 percent,”

We also proposed to remove § 412.23(b)(2)(ii) in its entirety, redesignate the existing § 412.23(b)(2)(iii) to § 412.23(b)(2)(ii), and revise all references to the previously numbered § 412.23(b)(2)(iii) accordingly.

We received 3 comments on the proposed revisions to the regulation text in response to section 115 of the MMSEA, which are summarized below.

Comment: Although several commenters supported the revisions to the regulation text in response to section 115 of the MMSEA, one commenter was concerned that CMS was confusing the 75 percent rule policies, hereinafter referred to as the 60 percent rule policies, and the IRF medical necessity policies.

Response: We agree with the commenter that the IRF 60 percent rule policies and the IRF medical necessity policies are different.

While both policies relate to ensuring that patients who need the intensive rehabilitation services provided in IRFs have access to this level of care, the two policies serve different functions and are applied differently.

The Medicare statute excludes payment for services that “* * * are not reasonable and necessary” (see section 1862(a) of the Social Security Act). This applies to all Medicare settings of care, including IRFs, and it applies to all Medicare beneficiaries receiving treatment in those settings. Thus, all IRF discharges for which providers seek payment from Medicare must meet the criteria for establishing the medical necessity of the treatment, regardless of whether the patient's condition is one of the conditions listed in § 412.23(b)(2)(iii), herein redesignated as § 412.23(b)(2)(ii), or not. CMS has specifically instructed its contractors to make medical review determinations based on reviews of individual medical records by qualified clinicians, not on the basis of diagnosis alone. In addition, we do not believe that the 60 percent rule should be used to make individual medical review claim determinations.

Conversely, the IRF 60 percent rule is intended to distinguish IRFs from other inpatient hospital settings of care, including acute care hospitals and traditional post-acute care settings (such as skilled nursing facilities). The 60 percent rule specifies that an IRF's patient population must consist of at least 60 percent of the patients who need intensive rehabilitation services for one or more of 13 specified conditions. The remaining 40 percent of patients in an IRF may be admitted for treatment of conditions not included on the list of qualifying conditions. We recognize that the list of 13 conditions does not identify all possible conditions for which it would generally be considered reasonable and necessary for a patient to be treated in an IRF, and thus we believe that it is appropriate to allow some percentage of an IRF's patient population to be made up of patients with other conditions. However, every patient must meet the medical necessity criteria.

We believe that it is particularly important to ensure that all patients being treated in IRFs meet the medical necessity criteria, so that the data on which we base IRF PPS payments is as accurate as possible.

Comment: One commenter expressed a number of concerns about Medicare's policies concerning IRF medical necessity. This commenter indicated that IRFs are confused about the interpretation of the medical necessity policies. The commenter also expressed concerns that the data that CMS uses to analyze and update IRF PPS payment rates may not be as accurate as it could be because it may include patients who do not meet medical necessity requirements for receiving care in IRFs. The commenter suggested that this could lead to inaccuracies in CMS's rate setting for IRFs.

Response: We note that we did not propose anything regarding the IRF medical necessity policies in the proposed rule. However, we will carefully consider the commenter's concerns and suggestions and will consider refinements to the IRF medical necessity criteria in the future.

Comment: Several commenters requested that CMS implement changes to the operational policies used in determining IRFs' compliance with the 60 percent rule, to correspond with the statutory changes to the compliance percentage and the continued use of comorbidites. For example, several commenters asked CMS to revise its policies to include Medicare Advantage patients in determining whether at least 50 percent of an IRF's patient population is made up of Medicare patients. In addition, one commenter asked that CMS revise its policies to allow individual IRFs to view the same IRF-PAI database information that the fiscal intermediaries use in determining the IRFs' compliance using the presumptive methodology.

Response: We appreciate the suggestions provided by the commenters and are considering making future changes to some of the operational policies for determining compliance with the 60 percent rule, including changes to some of the policies mentioned by the commenters. We are currently evaluating whether we could include Medicare Advantage patients in determining whether 50 percent of an IRF's patient population is made up of Medicare patients, including our statutory authority for doing so. We are also currently evaluating whether modifications to the current system for collecting and compiling IRF-PAI data could be made to allow individual IRFs to view copies of the reports that the Medicare contractors use in determining the individual IRF's compliance using the presumptive methodology. Our goal is to continue to ensure that the 60 percent rule compliance determinations are as transparent and equitable as possible both for providers and for Medicare contractors. We are continuing to work toward this end.

Comment: One commenter suggested that we remove the phrase “(b)(2)(ii)” from the end of the paragraph in the regulations at § 412.23(b)(2), as the original § 412.23(b)(2)(ii) to which the paragraph referred will no longer exist.

Response: We agree with the commenter's suggestion and will make the suggested revision.

Final Decision: As all of the commenters supported the proposed revisions to the regulation text, we are finalizing our revisions to the regulation text at § 412.23(b) by removing the following phrases from the first sentence of § 412.23(b)(2)(i):

• “and before July 1, 2007;” and
• “and for cost reporting periods beginning on or after July 1, 2007 and before July 1, 2008, the hospital has served an inpatient population of whom at least 65 percent,”

We are also removing § 412.23(b)(2)(ii) in its entirety, redesignating the existing § 412.23(b)(2)(iii) to § 412.23(b)(2)(ii), and revising all references to the previously numbered § 412.23(b)(2)(iii) accordingly. In response to a comment, we are also deleting the phrase “or (b)(2)(ii)” from the end of the paragraph in section § 412.23(b)(2).

VIII. Post Acute Care Payment Reform

In the proposed rule, we discussed our ongoing examination of possible steps toward achieving a more seamless system for the delivery and payment of post-acute care (PAC) services in various care settings. These include the PAC Payment Reform Demonstration (PAC-PRD) and its standardized patient assessment tool, the Continuity Assessment Record and Evaluation (CARE) tool. In the related area of value-based purchasing (VBP) initiatives, we described the IPPS preventable hospital-acquired conditions (HAC) payment provision, which is designed to ensure that the occurrence of selected, preventable conditions during hospitalization does not have the unintended effect of generating higher Medicare payments under the IPPS. We then discussed the potential application of this same underlying principle to other care settings in addition to IPPS hospitals. For a full and complete discussion of this issue as it pertains to the IRF setting, please refer to the FY 2009 IRF PPS proposed rule (73 FR 22674, 22688 through 22689).

We received 12 responses to our request for comments on the post acute care payment reform.

Comment: We received several comments concerning the use of the CARE tool. While most of these comments acknowledged that the CARE tool holds long-term promise in terms of potentially facilitating the efficient flow of secure electronic patient information, they also cautioned that it would be far too premature at this point in time to draw any definitive conclusions about its use, given the very early stage of the research currently being conducted in this area.

Response: We agree with the commenters' observations about the CARE tool, both in terms of its significant future potential and the need to await the results of ongoing research before reaching any specific conclusions about its use. We will continue to evaluate the CARE tool closely during the remainder of the current demonstration, and we plan to keep the commenters' concerns in mind as we proceed with our research in this area.

Comment: A number of commenters stressed the need for external research in the area of PAC payment reform, as well as the importance of obtaining input from the stakeholder community.

Response: We agree with the commenters regarding the value of obtaining stakeholder input, and believe that this is, in fact, crucial to the success of our PAC payment reform efforts. We also recognize the importance of obtaining the benefit of findings from research that is currently underway. We note that our own activities in this regard primarily involve applied research through our demonstration projects and internal analysis of changes in program policy. However, while our limited resources in this area preclude us from sponsoring any external research projects on PAC payment reform, we strongly favor such activity and encourage interested parties to engage in it.

Comment: We received a number of comments regarding the HAC payment provision under the IPPS, and the possible adoption of a similar approach in care settings other than IPPS hospitals. The commenters urged us to conduct a thorough evaluation of the HAC policy's implementation under the IPPS to determine its actual impact and efficacy prior to considering whether to adopt this type of approach in other care settings. Some also questioned the legal authority under existing Medicare law to expand the HAC payment provision beyond the IPPS hospital setting. Others raised concerns about the specific implications of applying this type of policy to the IRF setting. They cited “falls” as an example of something that might be less appropriately characterized as “never events” in the IRF setting than in the acute care hospital setting. They also argued that it would be unfair to penalize an IRF financially for a condition that actually developed during the preceding hospital stay but was not detected until after transfer to the IRF. In addition, they indicated that it might be difficult to differentiate a preventable healthcare-acquired complication from a normal, unavoidable aspect of a terminal illness.

Response: We appreciate the commenters' thoughtful input about application of the principal embodied in the IPPS HAC payment provision to the IRF setting. While we acknowledge that “falls” are among the selected HACs in the IPPS acute care setting that potentially have significant implications for the IRF setting, we agree that these and other conditions may have different implications in the IRF setting. We agree with the commenters that it would be unfair to penalize an IRF financially for a condition that developed in another care setting. We note that the IPPS HAC payment provision uses Present on Admission (POA) indicator data to exclude from payment consequences conditions that develop outside of the IPPS acute care stay, and a similar mechanism would be needed to apply this type of payment provision to the IRF setting. Regarding the commenters' concerns about the difficulty in differentiating a preventable healthcare-acquired complication from a normal, unavoidable aspect of a terminal illness, we would expect to work closely with stakeholders to determine which conditions could reasonably be prevented through the application of evidence-based guidelines. Finally, with regard to the comments that questioned the existing legal authority for expanding the HAC payment provision beyond the IPPS hospital setting, we note that in this final rule, we are not establishing any new Medicare policies in this area. However, we will keep the commenters' concerns in mind as our implementation of value-based purchasing for all Medicare payment systems proceeds, and we look forward to working with stakeholders in continuing to explore possible ways to reduce the occurrence of these preventable conditions in various care settings.

IX. Miscellaneous Comments

Comment: One commenter recommended that CMS update the IRF facility-level adjustments, including the rural adjustment, the low-income percentage adjustment, and the teaching status adjustment, as these adjustments were last updated in FY 2006 based on analysis of FY 2003 data. This commenter also suggested a number of methodological changes to the way that CMS computes the facility-level adjustments, including standardizing cost-per-case by outlier payments and computing three-year moving averages of the adjustments to promote added stability and predictability in the payment system.

Response: We note that we did not propose any refinements to the IRF facility-level adjustment for FY 2009. However, we are in the process of analyzing the data to determine whether future updates to the IRF facility-level adjustments are needed. At the same time, we are also analyzing the commenter's suggested revisions to the methodology for computing these adjustments to determine whether these revisions would improve the precision of our estimates of the appropriate facility-level adjustment parameters. We will consider proposing to update the IRF facility-level adjustments in future rules if our analysis indicates that such updates are necessary to ensure that IRF PPS payments continue to reflect the costs of caring for IRF patients appropriately.

Comment: One commenter recommended that CMS re-examine the weights used to compute the weighted motor score for classifying IRF patients. The weights that are currently being used to compute patients' motor scores were finalized in the FY 2006 IRF PPS final rule (70 FR 47880 at 47900) and were based on FY 2003 data. The commenter expressed concerns that the appropriate weights may change over time and may need to be updated using more recent data.

Response: We did not propose any changes to the weighted motor score in the proposed rule. However, we will consider the commenter's suggestions for future updates to the weighted motor score methodology.

Comment: Several commenters expressed interest in assisting CMS in the development of the IRF Report to Congress that was mandated in section 115 of the MMSEA.

Response: We appreciate the commenters' interest in this important project and, as required by statute, we will consult with interested parties and stakeholders in developing this report.

Comment: Several commenters noted that we reported IRF spending estimates of $6.4 billion for FY 2008 in the proposed rule (73 FR 22674 at 22686) and IRF spending projections of $5.6 billion for FY 2009 in the press release that was issued in conjunction with the proposed rule. We believe that these commenters mistakenly interpreted these spending estimates to mean that a 12.5 percent decrease in IRF PPS payments is estimated to occur between FY 2008 and FY 2009.

Response: The IRF spending estimate of $6.4 billion for FY 2008 that was reported in the proposed rule (73 FR 22674 at 22686) did not account for any changes in IRF utilization that might occur between FYs 2006 and 2008. It was based on an analysis of simulated IRF payments using IRF claims data from FY 2006 (that is, the number and types of patients that were being treated in IRFs in FY 2006) and the policies that were being proposed for FY 2009 with IRF utilization held constant. The $6.4 billion spending estimate should not be compared with the $5.6 billion IRF spending projection developed by the Office of the Actuary for FY 2008, which accounts for expected changes in IRF utilization between FYs 2006 and 2008. The Office of the Actuary projects that total IRF spending for both FY 2008 and FY 2009 will be $5.6 billion under both the FY 2009 IRF PPS proposed and final rules. Thus, for this final rule, we estimate only a $40 million decrease in IRF PPS spending between FY 2008 and FY 2009, which is equal to only 0.7 percent of total estimated IRF PPS payments. We note that this is different than the $20 million decrease in IRF PPS spending that we had estimated for the proposed rule due to the use of updated data (that is, FY 2007 IRF claims data). The estimated $40 million decrease for this final rule is entirely due to the adjustment to the outlier threshold amount for FY 2009 to set estimated IRF outlier payments at 3 percent of total estimated payments, as discussed in detail in section XII of this final rule.

X. Provisions of the Final Rule

In this final rule, we are adopting the provisions as set forth in the FY 2009 IRF PPS proposed rule (73 FR 22674), except as noted elsewhere in the preamble. Specifically:

• We will update the pre-reclassified and pre-floor wage indexes based on the CBSA changes published in the most recent OMB bulletins that apply to the hospital wage data used to determine the current IRF PPS wage index, as discussed in section V.B of this final rule.
• We will update the FY 2009 IRF PPS relative weights and average length of stay values using the most current and complete Medicare claims and cost report data, as discussed in section IV of this final rule.
• We will update the FY 2009 IRF PPS payment rates by the wage index and labor related share in a budget neutral manner, as discussed in section V.A and B of this final rule.
• We will update the outlier threshold amount for FY 2009, as discussed in section VI.A of this final rule.
• We will update the cost-to-charge ratio ceiling and the national average urban and rural cost-to-charge ratios for purposes of determining outlier payments under the IRF PPS, as discussed in section VI.B of this final rule.
• With respect to § 412.23, we will revise the regulation text in paragraph (b)(2) and (b)(2)(i) and remove paragraph (b)(2)(ii) to reflect section 115 of the MMSEA, as discussed in section VII of this final rule.

XI. Collection of Information Requirements

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

XII. Regulatory Impact Statement

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

Executive Order 12866, as amended, directs agencies to assess all costs and benefits of available regulatory alternatives and, if regulation is necessary, to select regulatory approaches that maximize net benefits (including potential economic, environmental, public health and safety effects, distributive impacts, and equity). A regulatory impact analysis (RIA) must be prepared for major rules with economically significant effects ($100 million or more in any one year). This final rule does not reach the $100 million economic threshold and thus is not considered a major rule. We estimate that the total impact of the changes in this final rule would be a decrease of approximately $40 million or 0.7 percent of total IRF PPS payments (this reflects a $40 million decrease due to the update to the outlier threshold amount to decrease estimated outlier payments from approximately 3.7 percent in FY 2008 to 3 percent in FY 2009).

The RFA requires agencies to analyze options for regulatory relief of small entities. For purposes of the RFA, small entities include small businesses, nonprofit organizations, and small governmental jurisdictions. Most IRFs and most other providers and suppliers are small entities, either by nonprofit status or by having revenues of $6.5 million to $31.5 million in any one year. (For details, see the Small Business Administration's final rule that set forth size standards for health care industries, at 65 FR 69432, November 17, 2000.) Because we lack data on individual hospital receipts, we cannot determine the number of small proprietary IRFs or the proportion of IRFs' revenue that is derived from Medicare payments. Therefore, we assume that all IRFs (an approximate total of 1,200 IRFs, of which approximately 60 percent are nonprofit facilities) are considered small entities and that Medicare payment constitutes the majority of their revenues. The Department of Health and Human Services generally uses a revenue impact of 3 to 5 percent as a significance threshold under the RFA. Medicare fiscal intermediaries and carriers are not considered to be small entities. Individuals and States are not included in the definition of a small entity. The Secretary has determined that this final rule (which we estimate will result in a decrease in total estimated payments to IRFs of 0.7 percent) would not have a significant economic impact on a substantial number of small entities and therefore an analysis as outlined by the RFA was not prepared.

In addition, section 1102(b) of the Act requires us to prepare a regulatory impact analysis if a rule may have a significant impact on the operations of a substantial number of small rural hospitals. This analysis must conform to the provisions of section 604 of the RFA. For purposes of section 1102(b) of the Act, we define a small rural hospital as a hospital that is located outside of a Metropolitan Statistical Area and has fewer than 100 beds. The Secretary has determined that this final rule would not have a significant impact on the operations of a substantial number of small rural hospitals and therefore an analysis for section 1102(b) of the Act was not prepared.

Section 202 of the Unfunded Mandates Reform Act of 1995 (UMRA) also requires that agencies assess anticipated costs and benefits before issuing any rule whose mandates require spending in any one year of $100 million in 1995 dollars, updated annually for inflation. That threshold level is currently approximately $130 million. This final rule would not mandate any cost requirements on State, local, or tribal governments in the aggregate, or by the private sector, of $130 million.

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

We received one comment on the regulatory impact statement included in the proposed rule, which is summarized below.

Comment: One commenter expressed concern that the regulatory impact information provided in the proposed rule was not sufficient to calculate the projected impact to individual providers, and that data on FY 2007 actual payments, FY 2008 estimated payments, and FY 2009 proposed payments would be required to fully estimate the effects on individual IRFs. The commenter requested that CMS make information available to allow interested parties to recreate CMS's impact table and to make projections on a facility-specific basis.

Response: As discussed above, we did not prepare a regulatory impact analysis for this final rule (or for the proposed rule) because this final rule does not reach the $100 million economic threshold and thus is not considered a major rule. However, we provided an IRF rate setting file in conjunction with the proposed rule to allow interested parties to calculate the payment effects of the proposed policies for individual IRFs. In addition, we will carefully consider all of the commenter's suggestions in updating the final FY 2009 IRF rate setting file that will be posted on the IRF PPS Web site in conjunction with this final rule. This file will be available for download from the IRF PPS Web site soon after publication of this final rule at http://www.cms.hhs.gov/​InpatientRehabFacPPS/​07_​DataFiles.asp#TopOfPage. The IRF rate setting files posted in conjunction with each proposed and final rule already contain much of the facility-level payment data needed to allow interested parties to recreate CMS's analysis and to make projections on a facility-specific basis.

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

List of Subjects in 42 CFR Part 412

• Administrative practice and procedure
• Health facilities
• Medicare
• Puerto Rico
• Reporting and recordkeeping requirements

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

PART 412—PROSPECTIVE PAYMENT SYSTEMS FOR INPATIENT HOSPITAL SERVICES

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

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

Subpart B—Hospital Services Subject to and Excluded From the Prospective Payment Systems for Inpatient Operating Costs and Inpatient Capital—Related Costs

2. Section 412.23 is amended by—

A. Revising introductory text of paragraph (b)(2).

B. Revising introductory text of paragraph (b)(2)(i).

C. Revising paragraphs (b)(2)(i)(A) and (B).

D. Removing paragraph (b)(2)(ii).

E. Redesignating paragraph (b)(2)(iii) as (b)(2)(ii).

The revision reads as follows:

§ 412.23

Excluded hospitals: Classifications.

* * * * *

(b) * * *

(2) Except in the case of a newly participating hospital seeking classification under this paragraph as a rehabilitation hospital for its first 12-month cost reporting period, as described in paragraph (b)(8) of this section, a hospital must show that during its most recent, consecutive, and appropriate 12-month time period (as defined by CMS or the fiscal intermediary), it served an inpatient population that meets the criteria under paragraph (b)(2)(i) of this section.

(i) For cost reporting periods beginning on or after July 1, 2004 and before July 1, 2005, the hospital has served an inpatient population of whom at least 50 percent, and for cost reporting periods beginning on or after July 1, 2005, the hospital has served an inpatient population of whom at least 60 percent required intensive rehabilitation services for treatment of one or more of the conditions specified at paragraph (b)(2)(ii) of this section. A patient with a comorbidity, as defined at § 412.602, may be included in the inpatient population that counts toward the required applicable percentage if—

(A) The patient is admitted for inpatient rehabilitation for a condition that is not one of the conditions specified in paragraph (b)(2)(ii) of this section;

(B) The patient has a comorbidity that falls in one of the conditions specified in paragraph (b)(2)(ii) of this section; and

* * * * *

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

Dated: July 18, 2008.

Kerry Weems,

Acting Administrator, Centers for Medicare & Medicaid Services.

Approved: July 25, 2008.

Michael O. Leavitt,

Secretary.

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

Addendum

This addendum contains the tables referred to throughout the preamble of this final rule. The tables presented below are as follows:

Table 1.—Inpatient Rehabilitation Facility Wage Index for Urban Areas for Discharges Occurring from October 1, 2008 through September 30, 2009

Table 2.—Inpatient Rehabilitation Facility Wage Index for Rural Areas for Discharges Occurring from October 1, 2008 through September 30, 2009

Table 1—Inpatient Rehabilitation Facility Wage Index for Urban Areas for Discharges Occurring From October 1, 2008 Through September 30, 2009

CBSA code	Urban area (constituent counties)	Wage index
10180	Abilene, TX	0.7957
	Callahan County, TX
	Jones County, TX
	Taylor County, TX
10380	Aguadilla-Isabela-San Sebastián, PR	0.3448
	Aguada Municipio, PR
	Aguadilla Municipio, PR
	Añasco Municipio, PR
	Isabela Municipio, PR
	Lares Municipio, PR
	Moca Municipio, PR
	Rincón Municipio, PR
	San Sebastián Municipio, PR
10420	Akron, OH	0.8794
	Portage County, OH
	Summit County, OH
10500	Albany, GA	0.8514
	Baker County, GA
	Dougherty County, GA
	Lee County, GA
	Terrell County, GA
	Worth County, GA
10580	Albany-Schenectady-Troy, NY	0.8588
	Albany County, NY
	Rensselaer County, NY
	Saratoga County, NY
	Schenectady County, NY
	Schoharie County, NY
10740	Albuquerque, NM	0.9554
	Bernalillo County, NM
	Sandoval County, NM
	Torrance County, NM
	Valencia County, NM
10780	Alexandria, LA	0.7979
	Grant Parish, LA
	Rapides Parish, LA
10900	Allentown-Bethlehem-Easton, PA-NJ	0.9865
	Warren County, NJ
	Carbon County, PA
	Lehigh County, PA
	Northampton County, PA
11020	Altoona, PA	0.8618
	Blair County, PA
11100	Amarillo, TX	0.9116
	Armstrong County, TX
	Carson County, TX
	Potter County, TX
	Randall County, TX
11180	Ames, IA	1.0046
	Story County, IA
11260	Anchorage, AK	1.1913
	Anchorage Municipality, AK
	Matanuska-Susitna Borough, AK
11300	Anderson, IN	0.8827
	Madison County, IN
11340	Anderson, SC	0.9086
	Anderson County, SC
11460	Ann Arbor, MI	1.0539
	Washtenaw County, MI
11500	Anniston-Oxford, AL	0.7926
	Calhoun County, AL
11540	Appleton, WI	0.9598
	Calumet County, WI
	Outagamie County, WI
11700	Asheville, NC	0.9185
	Buncombe County, NC
	Haywood County, NC
	Henderson County, NC
	Madison County, NC
12020	Athens-Clarke County, GA	1.0517
	Clarke County, GA
	Madison County, GA
	Oconee County, GA
	Oglethorpe County, GA
12060	Atlanta-Sandy Springs-Marietta, GA	0.9828
	Barrow County, GA
	Bartow County, GA
	Butts County, GA
	Carroll County, GA
	Cherokee County, GA
	Clayton County, GA
	Cobb County, GA
	Coweta County, GA
	Dawson County, GA
	DeKalb County, GA
	Douglas County, GA
	Fayette County, GA
	Forsyth County, GA
	Fulton County, GA
	Gwinnett County, GA
	Haralson County, GA
	Heard County, GA
	Henry County, GA
	Jasper County, GA
	Lamar County, GA
	Meriwether County, GA
	Newton County, GA
	Paulding County, GA
	Pickens County, GA
	Pike County, GA
	Rockdale County, GA
	Spalding County, GA
	Walton County, GA
12100	Atlantic City, NJ	1.2198
	Atlantic County, NJ
12220	Auburn-Opelika, AL	0.8090
	Lee County, AL
12260	Augusta-Richmond County, GA-SC	0.9645
	Burke County, GA
	Columbia County, GA
	McDuffie County, GA
	Richmond County, GA
	Aiken County, SC
	Edgefield County, SC
12420	Austin-Round Rock, TX	0.9544
	Bastrop County, TX
	Caldwell County, TX
	Hays County, TX
	Travis County, TX
	Williamson County, TX
12540	Bakersfield, CA	1.1051
	Kern County, CA
12580	Baltimore-Towson, MD	1.0134
	Anne Arundel County, MD
	Baltimore County, MD
	Carroll County, MD
	Harford County, MD
	Howard County, MD
	Queen Anne's County, MD
	Baltimore City, MD
12620	Bangor, ME	0.9978
	Penobscot County, ME
12700	Barnstable Town, MA	1.2603
	Barnstable County, MA
12940	Baton Rouge, LA	0.8034
	Ascension Parish, LA
	East Baton Rouge Parish, LA
	East Feliciana Parish, LA
	Iberville Parish, LA
	Livingston Parish, LA
	Pointe Coupee Parish, LA
	St. Helena Parish, LA
	West Baton Rouge Parish, LA
	West Feliciana Parish, LA
12980	Battle Creek, MI	1.0179
	Calhoun County, MI
13020	Bay City, MI	0.8897
	Bay County, MI
13140	Beaumont-Port Arthur, TX	0.8531
	Hardin County, TX
	Jefferson County, TX
	Orange County, TX
13380	Bellingham, WA	1.1474
	Whatcom County, WA
13460	Bend, OR	1.0942
	Deschutes County, OR
13644	Bethesda-Gaithersburg-Frederick, MD	1.0511
	Frederick County, MD
	Montgomery County, MD
13740	Billings, MT	0.8666
	Carbon County, MT
	Yellowstone County, MT
13780	Binghamton, NY	0.8949
	Broome County, NY
	Tioga County, NY
13820	Birmingham-Hoover, AL	0.8898
	Bibb County, AL
	Blount County, AL
	Chilton County, AL
	Jefferson County, AL
	St. Clair County, AL
	Shelby County, AL
	Walker County, AL
13900	Bismarck, ND	0.7225
	Burleigh County, ND
	Morton County, ND
13980	Blacksburg-Christiansburg-Radford, VA	0.8192
	Giles County, VA
	Montgomery County, VA
	Pulaski County, VA
	Radford City, VA
14020	Bloomington, IN	0.8915
	Greene County, IN
	Monroe County, IN
	Owen County, IN
14060	Bloomington-Normal, IL	0.9325
	McLean County, IL
14260	Boise City-Nampa, ID	0.9465
	Ada County, ID
	Boise County, ID
	Canyon County, ID
	Gem County, ID
	Owyhee County, ID
14484	Boston-Quincy, MA	1.1792
	Norfolk County, MA
	Plymouth County, MA
	Suffolk County, MA
14500	Boulder, CO	1.0426
	Boulder County, CO
14540	Bowling Green, KY	0.8159
	Edmonson County, KY
	Warren County, KY
14740	Bremerton-Silverdale, WA	1.0904
	Kitsap County, WA
14860	Bridgeport-Stamford-Norwalk, CT	1.2735
	Fairfield County, CT
15180	Brownsville-Harlingen, TX	0.8914
	Cameron County, TX
15260	Brunswick, GA	0.9475
	Brantley County, GA
	Glynn County, GA
	McIntosh County, GA
15380	Buffalo-Niagara Falls, NY	0.9568
	Erie County, NY
	Niagara County, NY
15500	Burlington, NC	0.8747
	Alamance County, NC
15540	Burlington-South Burlington, VT	0.9660
	Chittenden County, VT
	Franklin County, VT
	Grand Isle County, VT
15764	Cambridge-Newton-Framingham, MA	1.1215
	Middlesex County, MA
15804	Camden, NJ	1.0411
	Burlington County, NJ
	Camden County, NJ
	Gloucester County, NJ
15940	Canton-Massillon, OH	0.8935
	Carroll County, OH
	Stark County, OH
15980	Cape Coral-Fort Myers, FL	0.9396
	Lee County, FL
16180	Carson City, NV	1.0003
	Carson City, NV
16220	Casper, WY	0.9385
	Natrona County, WY
16300	Cedar Rapids, IA	0.8852
	Benton County, IA
	Jones County, IA
	Linn County, IA
16580	Champaign-Urbana, IL	0.9392
	Champaign County, IL
	Ford County, IL
	Piatt County, IL
16620	Charleston, WV	0.8289
	Boone County, WV
	Clay County, WV
	Kanawha County, WV
	Lincoln County, WV
	Putnam County, WV
16700	Charleston-North Charleston, SC	0.9124
	Berkeley County, SC
	Charleston County, SC
	Dorchester County, SC
16740	Charlotte-Gastonia-Concord, NC-SC	0.9520
	Anson County, NC
	Cabarrus County, NC
	Gaston County, NC
	Mecklenburg County, NC
	Union County, NC
	York County, SC
16820	Charlottesville, VA	0.9277
	Albemarle County, VA
	Fluvanna County, VA
	Greene County, VA
	Nelson County, VA
	Charlottesville City, VA
16860	Chattanooga, TN-GA	0.8994
	Catoosa County, GA
	Dade County, GA
	Walker County, GA
	Hamilton County, TN
	Marion County, TN
	Sequatchie County, TN
16940	Cheyenne, WY	0.9308
	Laramie County, WY
16974	Chicago-Naperville-Joliet, IL	1.0715
	Cook County, IL
	DeKalb County, IL
	DuPage County, IL
	Grundy County, IL
	Kane County, IL
	Kendall County, IL
	McHenry County, IL
	Will County, IL
17020	Chico, CA	1.1290
	Butte County, CA
17140	Cincinnati-Middletown, OH-KY-IN	0.9784
	Dearborn County, IN
	Franklin County, IN
	Ohio County, IN
	Boone County, KY
	Bracken County, KY
	Campbell County, KY
	Gallatin County, KY
	Grant County, KY
	Kenton County, KY
	Pendleton County, KY
	Brown County, OH
	Butler County, OH
	Clermont County, OH
	Hamilton County, OH
	Warren County, OH
17300	Clarksville, TN-KY	0.8251
	Christian County, KY
	Trigg County, KY
	Montgomery County, TN
	Stewart County, TN
17420	Cleveland, TN	0.8052
	Bradley County, TN
	Polk County, TN
17460	Cleveland-Elyria-Mentor, OH	0.9339
	Cuyahoga County, OH
	Geauga County, OH
	Lake County, OH
	Lorain County, OH
	Medina County, OH
17660	Coeur d'Alene, ID	0.9532
	Kootenai County, ID
17780	College Station-Bryan, TX	0.9358
	Brazos County, TX
	Burleson County, TX
	Robertson County, TX
17820	Colorado Springs, CO	0.9719
	El Paso County, CO
	Teller County, CO
17860	Columbia, MO	0.8658
	Boone County, MO
	Howard County, MO
17900	Columbia, SC	0.8800
	Calhoun County, SC
	Fairfield County, SC
	Kershaw County, SC
	Lexington County, SC
	Richland County, SC
	Saluda County, SC
17980	Columbus, GA-AL	0.8729
	Russell County, AL
	Chattahoochee County, GA
	Harris County, GA
	Marion County, GA
	Muscogee County, GA
18020	Columbus, IN	0.9537
	Bartholomew County, IN
18140	Columbus, OH	1.0085
	Delaware County, OH
	Fairfield County, OH
	Franklin County, OH
	Licking County, OH
	Madison County, OH
	Morrow County, OH
	Pickaway County, OH
	Union County, OH
18580	Corpus Christi, TX	0.8588
	Aransas County, TX
	Nueces County, TX
	San Patricio County, TX
18700	Corvallis, OR	1.0959
	Benton County, OR
19060	Cumberland, MD-WV	0.8294
	Allegany County, MD
	Mineral County, WV
19124	Dallas-Plano-Irving, TX	0.9915
	Collin County, TX
	Dallas County, TX
	Delta County, TX
	Denton County, TX
	Ellis County, TX
	Hunt County, TX
	Kaufman County, TX
	Rockwall County, TX
19140	Dalton, GA	0.8760
	Murray County, GA
	Whitfield County, GA
19180	Danville, IL	0.8957
	Vermilion County, IL
19260	Danville, VA	0.8240
	Pittsylvania County, VA
	Danville City, VA
19340	Davenport-Moline-Rock Island, IA-IL	0.8830
	Henry County, IL
	Mercer County, IL
	Rock Island County, IL
	Scott County, IA
19380	Dayton, OH	0.9190
	Greene County, OH
	Miami County, OH
	Montgomery County, OH
	Preble County, OH
19460	Decatur, AL	0.7885
	Lawrence County, AL
	Morgan County, AL
19500	Decatur, IL	0.8074
	Macon County, IL
19660	Deltona-Daytona Beach-Ormond Beach, FL	0.9031
	Volusia County, FL
19740	Denver-Aurora, CO	1.0718
	Adams County, CO
	Arapahoe County, CO
	Broomfield County, CO
	Clear Creek County, CO
	Denver County, CO
	Douglas County, CO
	Elbert County, CO
	Gilpin County, CO
	Jefferson County, CO
	Park County, CO
19780	Des Moines-West Des Moines, IA	0.9226
	Dallas County, IA
	Guthrie County, IA
	Madison County, IA
	Polk County, IA
	Warren County, IA
19804	Detroit-Livonia-Dearborn, MI	0.9999
	Wayne County, MI
20020	Dothan, AL	0.7270
	Geneva County, AL
	Henry County, AL
	Houston County, AL
20100	Dover, DE	1.0099
	Kent County, DE
20220	Dubuque, IA	0.9058
	Dubuque County, IA
20260	Duluth, MN-WI	0.9975
	Carlton County, MN
	St. Louis County, MN
	Douglas County, WI
20500	Durham, NC	0.9816
	Chatham County, NC
	Durham County, NC
	Orange County, NC
	Person County, NC
20740	Eau Claire, WI	0.9475
	Chippewa County, WI
	Eau Claire County, WI
20764	Edison, NJ	1.1181
	Middlesex County, NJ
	Monmouth County, NJ
	Ocean County, NJ
	Somerset County, NJ
20940	El Centro, CA	0.8914
	Imperial County, CA
21060	Elizabethtown, KY	0.8711
	Hardin County, KY
	Larue County, KY
21140	Elkhart-Goshen, IN	0.9611
	Elkhart County, IN
21300	Elmira, NY	0.8264
	Chemung County, NY
21340	El Paso, TX	0.8989
	El Paso County, TX
21500	Erie, PA	0.8495
	Erie County, PA
21660	Eugene-Springfield, OR	1.0932
	Lane County, OR
21780	Evansville, IN-KY	0.8662
	Gibson County, IN
	Posey County, IN
	Vanderburgh County, IN
	Warrick County, IN
	Henderson County, KY
	Webster County, KY
21820	Fairbanks, AK	1.1050
	Fairbanks North Star Borough, AK
21940	Fajardo, PR	0.4375
	Ceiba Municipio, PR
	Fajardo Municipio, PR
	Luquillo Municipio, PR
22020	Fargo, ND-MN	0.8042
	Cass County, ND
	Clay County, MN
22140	Farmington, NM	0.9587
	San Juan County, NM
22180	Fayetteville, NC	0.9368
	Cumberland County, NC
	Hoke County, NC
22220	Fayetteville-Springdale-Rogers, AR-MO	0.8742
	Benton County, AR
	Madison County, AR
	Washington County, AR
	McDonald County, MO
22380	Flagstaff, AZ	1.1687
	Coconino County, AZ
22420	Flint, MI	1.1220
	Genesee County, MI
22500	Florence, SC	0.8249
	Darlington County, SC
	Florence County, SC
22520	Florence-Muscle Shoals, AL	0.7680
	Colbert County, AL
	Lauderdale County, AL
22540	Fond du Lac, WI	0.9667
	Fond du Lac County, WI
22660	Fort Collins-Loveland, CO	0.9897
	Larimer County, CO
22744	Fort Lauderdale-Pompano Beach-Deerfield Beach, FL	1.0229
	Broward County, FL
22900	Fort Smith, AR-OK	0.7933
	Crawford County, AR
	Franklin County, AR
	Sebastian County, AR
	Le Flore County, OK
	Sequoyah County, OK
23020	Fort Walton Beach-Crestview-Destin, FL	0.8743
	Okaloosa County, FL
23060	Fort Wayne, IN	0.9284
	Allen County, IN
	Wells County, IN
	Whitley County, IN
23104	Fort Worth-Arlington, TX	0.9693
	Johnson County, TX
	Parker County, TX
	Tarrant County, TX
	Wise County, TX
23420	Fresno, CA	1.0993
	Fresno County, CA
23460	Gadsden, AL	0.8159
	Etowah County, AL
23540	Gainesville, FL	0.9196
	Alachua County, FL
	Gilchrist County, FL
23580	Gainesville, GA	0.9216
	Hall County, GA
23844	Gary, IN	0.9224
	Jasper County, IN
	Lake County, IN
	Newton County, IN
	Porter County, IN
24020	Glens Falls, NY	0.8256
	Warren County, NY
	Washington County, NY
24140	Goldsboro, NC	0.9288
	Wayne County, NC
24220	Grand Forks, ND-MN	0.7881
	Polk County, MN
	Grand Forks County, ND
24300	Grand Junction, CO	0.9864
	Mesa County, CO
24340	Grand Rapids-Wyoming, MI	0.9315
	Barry County, MI
	Ionia County, MI
	Kent County, MI
	Newaygo County, MI
24500	Great Falls, MT	0.8675
	Cascade County, MT
24540	Greeley, CO	0.9658
	Weld County, CO
24580	Green Bay, WI	0.9727
	Brown County, WI
	Kewaunee County, WI
	Oconto County, WI
24660	Greensboro-High Point, NC	0.9010
	Guilford County, NC
	Randolph County, NC
	Rockingham County, NC
24780	Greenville, NC	0.9402
	Greene County, NC
	Pitt County, NC
24860	Greenville-Mauldin-Easley, SC	0.9860
	Greenville County, SC
	Laurens County, SC
	Pickens County, SC
25020	Guayama, PR	0.3064
	Arroyo Municipio, PR
	Guayama Municipio, PR
	Patillas Municipio, PR
25060	Gulfport-Biloxi, MS	0.8773
	Hancock County, MS
	Harrison County, MS
	Stone County, MS
25180	Hagerstown-Martinsburg, MD-WV	0.9013
	Washington County, MD
	Berkeley County, WV
	Morgan County, WV
25260	Hanford-Corcoran, CA	1.0499
	Kings County, CA
25420	Harrisburg-Carlisle, PA	0.9280
	Cumberland County, PA
	Dauphin County, PA
	Perry County, PA
25500	Harrisonburg, VA	0.8867
	Rockingham County, VA
	Harrisonburg City, VA
25540	Hartford-West Hartford-East Hartford, CT	1.0959
	Hartford County, CT
	Middlesex County, CT
	Tolland County, CT
25620	Hattiesburg, MS	0.7366
	Forrest County, MS
	Lamar County, MS
	Perry County, MS
25860	Hickory-Lenoir-Morganton, NC	0.9028
	Alexander County, NC
	Burke County, NC
	Caldwell County, NC
	Catawba County, NC
25980	Hinesville-Fort Stewart, GA 1	0.9187
	Liberty County, GA
	Long County, GA
26100	Holland-Grand Haven, MI	0.9006
	Ottawa County, MI
26180	Honolulu, HI	1.1556
	Honolulu County, HI
26300	Hot Springs, AR	0.9109
	Garland County, AR
26380	Houma-Bayou Cane-Thibodaux, LA	0.7892
	Lafourche Parish, LA
	Terrebonne Parish, LA
26420	Houston-Sugar Land-Baytown, TX	0.9939
	Austin County, TX
	Brazoria County, TX
	Chambers County, TX
	Fort Bend County, TX
	Galveston County, TX
	Harris County, TX
	Liberty County, TX
	Montgomery County, TX
	San Jacinto County, TX
	Waller County, TX
26580	Huntington-Ashland, WV-KY-OH	0.9041
	Boyd County, KY
	Greenup County, KY
	Lawrence County, OH
	Cabell County, WV
	Wayne County, WV
26620	Huntsville, AL	0.9146
	Limestone County, AL
	Madison County, AL
26820	Idaho Falls, ID	0.9264
	Bonneville County, ID
	Jefferson County, ID
26900	Indianapolis-Carmel, IN	0.9844
	Boone County, IN
	Brown County, IN
	Hamilton County, IN
	Hancock County, IN
	Hendricks County, IN
	Johnson County, IN
	Marion County, IN
	Morgan County, IN
	Putnam County, IN
	Shelby County, IN
26980	Iowa City, IA	0.9568
	Johnson County, IA
	Washington County, IA
27060	Ithaca, NY	0.9630
	Tompkins County, NY
27100	Jackson, MI	0.9329
	Jackson County, MI
27140	Jackson, MS	0.8011
	Copiah County, MS
	Hinds County, MS
	Madison County, MS
	Rankin County, MS
	Simpson County, MS
27180	Jackson, TN	0.8676
	Chester County, TN
	Madison County, TN
27260	Jacksonville, FL	0.9021
	Baker County, FL
	Clay County, FL
	Duval County, FL
	Nassau County, FL
	St. Johns County, FL
27340	Jacksonville, NC	0.8079
	Onslow County, NC
27500	Janesville, WI	0.9702
	Rock County, WI
27620	Jefferson City, MO	0.8478
	Callaway County, MO
	Cole County, MO
	Moniteau County, MO
	Osage County, MO
27740	Johnson City, TN	0.7677
	Carter County, TN
	Unicoi County, TN
	Washington County, TN
27780	Johnstown, PA	0.7543
	Cambria County, PA
27860	Jonesboro, AR	0.7790
	Craighead County, AR
	Poinsett County, AR
27900	Joplin, MO	0.8951
	Jasper County, MO
	Newton County, MO
28020	Kalamazoo-Portage, MI	1.0433
	Kalamazoo County, MI
	Van Buren County, MI
28100	Kankakee-Bradley, IL	1.0238
	Kankakee County, IL
28140	Kansas City, MO-KS	0.9504
	Franklin County, KS
	Johnson County, KS
	Leavenworth County, KS
	Linn County, KS
	Miami County, KS
	Wyandotte County, KS
	Bates County, MO
	Caldwell County, MO
	Cass County, MO
	Clay County, MO
	Clinton County, MO
	Jackson County, MO
	Lafayette County, MO
	Platte County, MO
	Ray County, MO
28420	Kennewick-Richland-Pasco, WA	1.0075
	Benton County, WA
	Franklin County, WA
28660	Killeen-Temple-Fort Hood, TX	0.8249
	Bell County, TX
	Coryell County, TX
	Lampasas County, TX
28700	Kingsport-Bristol-Bristol, TN-VA	0.7658
	Hawkins County, TN
	Sullivan County, TN
	Bristol City, VA
	Scott County, VA
	Washington County, VA
28740	Kingston, NY	0.9556
	Ulster County, NY
28940	Knoxville, TN	0.8036
	Anderson County, TN
	Blount County, TN
	Knox County, TN
	Loudon County, TN
	Union County, TN
29020	Kokomo, IN	0.9591
	Howard County, IN
	Tipton County, IN
29100	La Crosse, WI-MN	0.9685
	Houston County, MN
	La Crosse County, WI
29140	Lafayette, IN	0.8869
	Benton County, IN
	Carroll County, IN
	Tippecanoe County, IN
29180	Lafayette, LA	0.8247
	Lafayette Parish, LA
	St. Martin Parish, LA
29340	Lake Charles, LA	0.7777
	Calcasieu Parish, LA
	Cameron Parish, LA
29404	Lake County-Kenosha County, IL-WI	1.0603
	Lake County, IL
	Kenosha County, WI
29420	Lake Havasu City-Kingman, AZ	0.9333
	Mohave County, AZ
29460	Lakeland, FL	0.8661
	Polk County, FL
29540	Lancaster, PA	0.9252
	Lancaster County, PA
29620	Lansing-East Lansing, MI	1.0119
	Clinton County, MI
	Eaton County, MI
	Ingham County, MI
29700	Laredo, TX	0.8093
	Webb County, TX
29740	Las Cruces, NM	0.8676
	Dona Ana County, NM
29820	Las Vegas-Paradise, NV	1.1799
	Clark County, NV
29940	Lawrence, KS	0.8227
	Douglas County, KS
30020	Lawton, OK	0.8025
	Comanche County, OK
30140	Lebanon, PA	0.8192
	Lebanon County, PA
30300	Lewiston, ID-WA	0.9454
	Nez Perce County, ID
	Asotin County, WA
30340	Lewiston-Auburn, ME	0.9193
	Androscoggin County, ME
30460	Lexington-Fayette, KY	0.9191
	Bourbon County, KY
	Clark County, KY
	Fayette County, KY
	Jessamine County, KY
	Scott County, KY
	Woodford County, KY
30620	Lima, OH	0.9424
	Allen County, OH
30700	Lincoln, NE	1.0051
	Lancaster County, NE
	Seward County, NE
30780	Little Rock-North Little Rock-Conway, AR	0.8863
	Faulkner County, AR
	Grant County, AR
	Lonoke County, AR
	Perry County, AR
	Pulaski County, AR
	Saline County, AR
30860	Logan, UT-ID	0.9183
	Franklin County, ID
	Cache County, UT
30980	Longview, TX	0.8717
	Gregg County, TX
	Rusk County, TX
	Upshur County, TX
31020	Longview, WA	1.0827
	Cowlitz County, WA
31084	Los Angeles-Long Beach-Santa Ana, CA	1.1771
	Los Angeles County, CA
31140	Louisville-Jefferson County, KY-IN	0.9065
	Clark County, IN
	Floyd County, IN
	Harrison County, IN
	Washington County, IN
	Bullitt County, KY
	Henry County, KY
	Meade County, KY
	Nelson County, KY
	Oldham County, KY
	Shelby County, KY
	Spencer County, KY
	Trimble County, KY
31180	Lubbock, TX	0.8680
	Crosby County, TX
	Lubbock County, TX
31340	Lynchburg, VA	0.8732
	Amherst County, VA
	Appomattox County, VA
	Bedford County, VA
	Campbell County, VA
	Bedford City, VA
	Lynchburg City, VA
31420	Macon, GA	0.9541
	Bibb County, GA
	Crawford County, GA
	Jones County, GA
	Monroe County, GA
	Twiggs County, GA
31460	Madera, CA	0.8069
	Madera County, CA
31540	Madison, WI	1.0935
	Columbia County, WI
	Dane County, WI
	Iowa County, WI
31700	Manchester-Nashua, NH	1.0273
	Hillsborough County, NH
31900	Mansfield, OH 1	0.9271
	Richland County, OH
32420	Mayagüez, PR	0.3711
	Hormigueros Municipio, PR
	Mayagüez Municipio, PR
32580	McAllen-Edinburg-Mission, TX	0.9123
	Hidalgo County, TX
32780	Medford, OR	1.0318
	Jackson County, OR
32820	Memphis, TN-MS-AR	0.9250
	Crittenden County, AR
	DeSoto County, MS
	Marshall County, MS
	Tate County, MS
	Tunica County, MS
	Fayette County, TN
	Shelby County, TN
	Tipton County, TN
32900	Merced, CA	1.2120
	Merced County, CA
33124	Miami-Miami Beach-Kendall, FL	1.0002
	Miami-Dade County, FL
33140	Michigan City-La Porte, IN	0.8914
	LaPorte County, IN
33260	Midland, TX	1.0017
	Midland County, TX
33340	Milwaukee-Waukesha-West Allis, WI	1.0214
	Milwaukee County, WI
	Ozaukee County, WI
	Washington County, WI
	Waukesha County, WI
33460	Minneapolis-St. Paul—Bloomington, MN-WI	1.1093
	Anoka County, MN
	Carver County, MN
	Chisago County, MN
	Dakota County, MN
	Hennepin County, MN
	Isanti County, MN
	Ramsey County, MN
	Scott County, MN
	Sherburne County, MN
	Washington County, MN
	Wright County, MN
	Pierce County, WI
	St. Croix County, WI
33540	Missoula, MT	0.8953
	Missoula County, MT
33660	Mobile, AL	0.8033
	Mobile County, AL
33700	Modesto, CA	1.1962
	Stanislaus County, CA
33740	Monroe, LA	0.7832
	Ouachita Parish, LA
	Union Parish, LA
33780	Monroe, MI	0.9414
	Monroe County, MI
33860	Montgomery, AL	0.8088
	Autauga County, AL
	Elmore County, AL
	Lowndes County, AL
	Montgomery County, AL
34060	Morgantown, WV	0.8321
	Monongalia County, WV
	Preston County, WV
34100	Morristown, TN	0.7388
	Grainger County, TN
	Hamblen County, TN
	Jefferson County, TN
34580	Mount Vernon-Anacortes, WA	1.0529
	Skagit County, WA
34620	Muncie, IN	0.8214
	Delaware County, IN
34740	Muskegon-Norton Shores, MI	0.9836
	Muskegon County, MI
34820	Myrtle Beach-Conway-North Myrtle Beach, SC	0.8634
	Horry County, SC
34900	Napa, CA	1.4476
	Napa County, CA
34940	Naples-Marco Island, FL	0.9487
	Collier County, FL
34980	Nashville-Davidson-Murfreesboro-Franklin, TN	0.9689
	Cannon County, TN
	Cheatham County, TN
	Davidson County, TN
	Dickson County, TN
	Hickman County, TN
	Macon County, TN
	Robertson County, TN
	Rutherford County, TN
	Smith County, TN
	Sumner County, TN
	Trousdale County, TN
	Williamson County, TN
	Wilson County, TN
35004	Nassau-Suffolk, NY	1.2640
	Nassau County, NY
	Suffolk County, NY
35084	Newark-Union, NJ-PA	1.1862
	Essex County, NJ
	Hunterdon County, NJ
	Morris County, NJ
	Sussex County, NJ
	Union County, NJ
	Pike County, PA
35300	New Haven-Milford, CT	1.1871
	New Haven County, CT
35380	New Orleans-Metairie-Kenner, LA	0.8897
	Jefferson Parish, LA
	Orleans Parish, LA
	Plaquemines Parish, LA
	St. Bernard Parish, LA
	St. Charles Parish, LA
	St. John the Baptist Parish, LA
	St. Tammany Parish, LA
35644	New York-White Plains-Wayne, NY-NJ	1.3115
	Bergen County, NJ
	Hudson County, NJ
	Passaic County, NJ
	Bronx County, NY
	Kings County, NY
	New York County, NY
	Putnam County, NY
	Queens County, NY
	Richmond County, NY
	Rockland County, NY
	Westchester County, NY
35660	Niles-Benton Harbor, MI	0.9141
	Berrien County, MI
35980	Norwich-New London, CT	1.1432
	New London County, CT
36084	Oakland-Fremont-Hayward, CA	1.5685
	Alameda County, CA
	Contra Costa County, CA
36100	Ocala, FL	0.8627
	Marion County, FL
36140	Ocean City, NJ	1.0988
	Cape May County, NJ
36220	Odessa, TX	1.0042
	Ector County, TX
36260	Ogden-Clearfield, UT	0.9000
	Davis County, UT
	Morgan County, UT
	Weber County, UT
36420	Oklahoma City, OK	0.8815
	Canadian County, OK
	Cleveland County, OK
	Grady County, OK
	Lincoln County, OK
	Logan County, OK
	McClain County, OK
	Oklahoma County, OK
36500	Olympia, WA	1.1512
	Thurston County, WA
36540	Omaha-Council Bluffs, NE-IA	0.9561
	Harrison County, IA
	Mills County, IA
	Pottawattamie County, IA
	Cass County, NE
	Douglas County, NE
	Sarpy County, NE
	Saunders County, NE
	Washington County, NE
36740	Orlando-Kissimmee, FL	0.9226
	Lake County, FL
	Orange County, FL
	Osceola County, FL
	Seminole County, FL
36780	Oshkosh-Neenah, WI	0.9551
	Winnebago County, WI
36980	Owensboro, KY	0.8652
	Daviess County, KY
	Hancock County, KY
	McLean County, KY
37100	Oxnard-Thousand Oaks-Ventura, CA	1.1852
	Ventura County, CA
37340	Palm Bay-Melbourne-Titusville, FL	0.9325
	Brevard County, FL
37380	Palm Coast, FL	0.8945
	Flagler County, FL
37460	Panama City-Lynn Haven, FL	0.8313
	Bay County, FL
37620	Parkersburg-Marietta-Vienna, WV-OH	0.8105
	Washington County, OH
	Pleasants County, WV
	Wirt County, WV
	Wood County, WV
37700	Pascagoula, MS	0.8647
	George County, MS
	Jackson County, MS
37764	Peabody, MA	1.0650
	Essex County, MA
37860	Pensacola-Ferry Pass-Brent, FL	0.8281
	Escambia County, FL
	Santa Rosa County, FL
37900	Peoria, IL	0.9299
	Marshall County, IL
	Peoria County, IL
	Stark County, IL
	Tazewell County, IL
	Woodford County, IL
37964	Philadelphia, PA	1.0925
	Bucks County, PA
	Chester County, PA
	Delaware County, PA
	Montgomery County, PA
	Philadelphia County, PA
38060	Phoenix-Mesa-Scottsdale, AZ	1.0264
	Maricopa County, AZ
	Pinal County, AZ
38220	Pine Bluff, AR	0.7839
	Cleveland County, AR
	Jefferson County, AR
	Lincoln County, AR
38300	Pittsburgh, PA	0.8525
	Allegheny County, PA
	Armstrong County, PA
	Beaver County, PA
	Butler County, PA
	Fayette County, PA
	Washington County, PA
	Westmoreland County, PA
38340	Pittsfield, MA	1.0091
	Berkshire County, MA
38540	Pocatello, ID	0.9465
	Bannock County, ID
	Power County, ID
38660	Ponce, PR	0.4450
	Juana Díaz Municipio, PR
	Ponce Municipio, PR
	Villalba Municipio, PR
38860	Portland-South Portland-Biddeford, ME	1.0042
	Cumberland County, ME
	Sagadahoc County, ME
	York County, ME
38900	Portland-Vancouver-Beaverton, OR-WA	1.1498
	Clackamas County, OR
	Columbia County, OR
	Multnomah County, OR
	Washington County, OR
	Yamhill County, OR
	Clark County, WA
	Skamania County, WA
38940	Port St. Lucie, FL	1.0016
	Martin County, FL
	St. Lucie County, FL
39100	Poughkeepsie-Newburgh-Middletown, NY	1.0982
	Dutchess County, NY
	Orange County, NY
39140	Prescott, AZ	1.0020
	Yavapai County, AZ
39300	Providence-New Bedford-Fall River, RI-MA	1.0574
	Bristol County, MA
	Bristol County, RI
	Kent County, RI
	Newport County, RI
	Providence County, RI
	Washington County, RI
39340	Provo-Orem, UT	0.9557
	Juab County, UT
	Utah County, UT
39380	Pueblo, CO	0.8851
	Pueblo County, CO
39460	Punta Gorda, FL	0.9254
	Charlotte County, FL
39540	Racine, WI	0.9498
	Racine County, WI
39580	Raleigh-Cary, NC	0.9839
	Franklin County, NC
	Johnston County, NC
	Wake County, NC
39660	Rapid City, SD	0.8811
	Meade County, SD
	Pennington County, SD
39740	Reading, PA	0.9356
	Berks County, PA
39820	Redding, CA	1.3541
	Shasta County, CA
39900	Reno-Sparks, NV	1.0715
	Storey County, NV
	Washoe County, NV
40060	Richmond, VA	0.9425
	Amelia County, VA
	Caroline County, VA
	Charles City County, VA
	Chesterfield County, VA
	Cumberland County, VA
	Dinwiddie County, VA
	Goochland County, VA
	Hanover County, VA
	Henrico County, VA
	King and Queen County, VA
	King William County, VA
	Louisa County, VA
	New Kent County, VA
	Powhatan County, VA
	Prince George County, VA
	Sussex County, VA
	Colonial Heights City, VA
	Hopewell City, VA
	Petersburg City, VA
	Richmond City, VA
40140	Riverside-San Bernardino-Ontario, CA	1.1100
	Riverside County, CA
	San Bernardino County, CA
40220	Roanoke, VA	0.8691
	Botetourt County, VA
	Craig County, VA
	Franklin County, VA
	Roanoke County, VA
	Roanoke City, VA
	Salem City, VA
40340	Rochester, MN	1.0755
	Dodge County, MN
	Olmsted County, MN
	Wabasha County, MN
40380	Rochester, NY	0.8858
	Livingston County, NY
	Monroe County, NY
	Ontario County, NY
	Orleans County, NY
	Wayne County, NY
40420	Rockford, IL	0.9814
	Boone County, IL
	Winnebago County, IL
40484	Rockingham County, NH	1.0111
	Rockingham County, NH
	Strafford County, NH
40580	Rocky Mount, NC	0.9001
	Edgecombe County, NC
	Nash County, NC
40660	Rome, GA	0.9042
	Floyd County, GA
40900	Sacramento—Arden-Arcade—Roseville, CA	1.3505
	El Dorado County, CA
	Placer County, CA
	Sacramento County, CA
	Yolo County, CA
40980	Saginaw-Saginaw Township North, MI	0.8812
	Saginaw County, MI
41060	St. Cloud, MN	1.0549
	Benton County, MN
	Stearns County, MN
41100	St. George, UT	0.9358
	Washington County, UT
41140	St. Joseph, MO-KS	0.8762
	Doniphan County, KS
	Andrew County, MO
	Buchanan County, MO
	DeKalb County, MO
41180	St. Louis, MO-IL	0.9024
	Bond County, IL
	Calhoun County, IL
	Clinton County, IL
	Jersey County, IL
	Macoupin County, IL
	Madison County, IL
	Monroe County, IL
	St. Clair County, IL
	Crawford County, MO
	Franklin County, MO
	Jefferson County, MO
	Lincoln County, MO
	St. Charles County, MO
	St. Louis County, MO
	Warren County, MO
	Washington County, MO
	St. Louis City, MO
41420	Salem, OR	1.0572
	Marion County, OR
	Polk County, OR
41500	Salinas, CA	1.4775
	Monterey County, CA
41540	Salisbury, MD	0.8994
	Somerset County, MD
	Wicomico County, MD
41620	Salt Lake City, UT	0.9399
	Salt Lake County, UT
	Summit County, UT
	Tooele County, UT
41660	San Angelo, TX	0.8579
	Irion County, TX
	Tom Green County, TX
41700	San Antonio, TX	0.8834
	Atascosa County, TX
	Bandera County, TX
	Bexar County, TX
	Comal County, TX
	Guadalupe County, TX
	Kendall County, TX
	Medina County, TX
	Wilson County, TX
41740	San Diego-Carlsbad-San Marcos, CA	1.1492
	San Diego County, CA
41780	Sandusky, OH	0.8822
	Erie County, OH
41884	San Francisco-San Mateo-Redwood City, CA	1.5195
	Marin County, CA
	San Francisco County, CA
	San Mateo County, CA
41900	San Germán-Cabo Rojo, PR	0.4729
	Cabo Rojo Municipio, PR
	Lajas Municipio, PR
	Sabana Grande Municipio, PR
	San Germán Municipio, PR
41940	San Jose-Sunnyvale-Santa Clara, CA	1.5735
	San Benito County, CA
	Santa Clara County, CA
41980	San Juan-Caguas-Guaynabo, PR	0.4528
	Aguas Buenas Municipio, PR
	Aibonito Municipio, PR
	Arecibo Municipio, PR
	Barceloneta Municipio, PR
	Barranquitas Municipio, PR
	Bayamón Municipio, PR
	Caguas Municipio, PR
	Camuy Municipio, PR
	Canóvanas Municipio, PR
	Carolina Municipio, PR
	Cataño Municipio, PR
	Cayey Municipio, PR
	Ciales Municipio, PR
	Cidra Municipio, PR
	Comerío Municipio, PR
	Corozal Municipio, PR
	Dorado Municipio, PR
	Florida Municipio, PR
	Guaynabo Municipio, PR
	Gurabo Municipio, PR
	Hatillo Municipio, PR
	Humacao Municipio, PR
	Juncos Municipio, PR
	Las Piedras Municipio, PR
	Loíza Municipio, PR
	Manatí Municipio, PR
	Maunabo Municipio, PR
	Morovis Municipio, PR
	Naguabo Municipio, PR
	Naranjito Municipio, PR
	Orocovis Municipio, PR
	Quebradillas Municipio, PR
	Río Grande Municipio, PR
	San Juan Municipio, PR
	San Lorenzo Municipio, PR
	Toa Alta Municipio, PR
	Toa Baja Municipio, PR
	Trujillo Alto Municipio, PR
	Vega Alta Municipio, PR
	Vega Baja Municipio, PR
	Yabucoa Municipio, PR
42020	San Luis Obispo-Paso Robles, CA	1.2488
	San Luis Obispo County, CA
42044	Santa Ana-Anaheim-Irvine, CA	1.1766
	Orange County, CA
42060	Santa Barbara-Santa Maria-Goleta, CA	1.1714
	Santa Barbara County, CA
42100	Santa Cruz-Watsonville, CA	1.6122
	Santa Cruz County, CA
42140	Santa Fe, NM	1.0734
	Santa Fe County, NM
42220	Santa Rosa-Petaluma, CA	1.4696
	Sonoma County, CA
42260	Sarasota-Bradenton-Venice, FL	0.9933
	Manatee County, FL
	Sarasota County, FL
42340	Savannah, GA	0.9131
	Bryan County, GA
	Chatham County, GA
	Effingham County, GA
42540	Scranton—Wilkes-Barre, PA	0.8457
	Lackawanna County, PA
	Luzerne County, PA
	Wyoming County, PA
42644	Seattle-Bellevue-Everett, WA	1.1572
	King County, WA
	Snohomish County, WA
42680	Sebastian-Vero Beach, FL	0.9412
	Indian River County, FL
43100	Sheboygan, WI	0.8975
	Sheboygan County, WI
43300	Sherman-Denison, TX	0.8320
	Grayson County, TX
43340	Shreveport-Bossier City, LA	0.8476
	Bossier Parish, LA
	Caddo Parish, LA
	De Soto Parish, LA
43580	Sioux City, IA-NE-SD	0.9251
	Woodbury County, IA
	Dakota County, NE
	Dixon County, NE
	Union County, SD
43620	Sioux Falls, SD	0.9563
	Lincoln County, SD
	McCook County, SD
	Minnehaha County, SD
	Turner County, SD
43780	South Bend-Mishawaka, IN-MI	0.9617
	St. Joseph County, IN
	Cass County, MI
43900	Spartanburg, SC	0.9422
	Spartanburg County, SC
44060	Spokane, WA	1.0455
	Spokane County, WA
44100	Springfield, IL	0.8944
	Menard County, IL
	Sangamon County, IL
44140	Springfield, MA	1.0366
	Franklin County, MA
	Hampden County, MA
	Hampshire County, MA
44180	Springfield, MO	0.8695
	Christian County, MO
	Dallas County, MO
	Greene County, MO
	Polk County, MO
	Webster County, MO
44220	Springfield, OH	0.8694
	Clark County, OH
44300	State College, PA	0.8768
	Centre County, PA
44700	Stockton, CA	1.1855
	San Joaquin County, CA
44940	Sumter, SC	0.8599
	Sumter County, SC
45060	Syracuse, NY	0.9910
	Madison County, NY
	Onondaga County, NY
	Oswego County, NY
45104	Tacoma, WA	1.1055
	Pierce County, WA
45220	Tallahassee, FL	0.9025
	Gadsden County, FL
	Jefferson County, FL
	Leon County, FL
	Wakulla County, FL
45300	Tampa-St. Petersburg-Clearwater, FL	0.9020
	Hernando County, FL
	Hillsborough County, FL
	Pasco County, FL
	Pinellas County, FL
45460	Terre Haute, IN	0.8805
	Clay County, IN
	Sullivan County, IN
	Vermillion County, IN
	Vigo County, IN
45500	Texarkana, TX-Texarkana, AR	0.7770
	Miller County, AR
	Bowie County, TX
45780	Toledo, OH	0.9431
	Fulton County, OH
	Lucas County, OH
	Ottawa County, OH
	Wood County, OH
45820	Topeka, KS	0.8538
	Jackson County, KS
	Jefferson County, KS
	Osage County, KS
	Shawnee County, KS
	Wabaunsee County, KS
45940	Trenton-Ewing, NJ	1.0699
	Mercer County, NJ
46060	Tucson, AZ	0.9245
	Pima County, AZ
46140	Tulsa, OK	0.8340
	Creek County, OK
	Okmulgee County, OK
	Osage County, OK
	Pawnee County, OK
	Rogers County, OK
	Tulsa County, OK
	Wagoner County, OK
46220	Tuscaloosa, AL	0.8303
	Greene County, AL
	Hale County, AL
	Tuscaloosa County, AL
46340	Tyler, TX	0.9114
	Smith County, TX
46540	Utica-Rome, NY	0.8486
	Herkimer County, NY
	Oneida County, NY
46660	Valdosta, GA	0.8098
	Brooks County, GA
	Echols County, GA
	Lanier County, GA
	Lowndes County, GA
46700	Vallejo-Fairfield, CA	1.4666
	Solano County, CA
47020	Victoria, TX	0.8302
	Calhoun County, TX
	Goliad County, TX
	Victoria County, TX
47220	Vineland-Millville-Bridgeton, NJ	1.0133
	Cumberland County, NJ
47260	Virginia Beach-Norfolk-Newport News, VA-NC	0.8818
	Currituck County, NC
	Gloucester County, VA
	Isle of Wight County, VA
	James City County, VA
	Mathews County, VA
	Surry County, VA
	York County, VA
	Chesapeake City, VA
	Hampton City, VA
	Newport News City, VA
	Norfolk City, VA
	Poquoson City, VA
	Portsmouth City, VA
	Suffolk City, VA
	Virginia Beach City, VA
	Williamsburg City, VA
47300	Visalia-Porterville, CA	1.0091
	Tulare County, CA
47380	Waco, TX	0.8518
	McLennan County, TX
47580	Warner Robins, GA	0.9128
	Houston County, GA
47644	Warren-Troy-Farmington Hills, MI	1.0001
	Lapeer County, MI
	Livingston County, MI
	Macomb County, MI
	Oakland County, MI
	St. Clair County, MI
47894	Washington-Arlington-Alexandria, DC-VA-MD-WV	1.0855
	District of Columbia, DC
	Calvert County, MD
	Charles County, MD
	Prince George's County, MD
	Arlington County, VA
	Clarke County, VA
	Fairfax County, VA
	Fauquier County, VA
	Loudoun County, VA
	Prince William County, VA
	Spotsylvania County, VA
	Stafford County, VA
	Warren County, VA
	Alexandria City, VA
	Fairfax City, VA
	Falls Church City, VA
	Fredericksburg City, VA
	Manassas City, VA
	Manassas Park City, VA
	Jefferson County, WV
47940	Waterloo-Cedar Falls, IA	0.8519
	Black Hawk County, IA
	Bremer County, IA
	Grundy County, IA
48140	Wausau, WI	0.9679
	Marathon County, WI
48260	Weirton-Steubenville, WV-OH	0.7924
	Jefferson County, OH
	Brooke County, WV
	Hancock County, WV
48300	Wenatchee, WA	1.1469
	Chelan County, WA
	Douglas County, WA
48424	West Palm Beach-Boca Raton-Boynton Beach, FL	0.9728
	Palm Beach County, FL
48540	Wheeling, WV-OH	0.6961
	Belmont County, OH
	Marshall County, WV
	Ohio County, WV
48620	Wichita, KS	0.9062
	Butler County, KS
	Harvey County, KS
	Sedgwick County, KS
	Sumner County, KS
48660	Wichita Falls, TX	0.7920
	Archer County, TX
	Clay County, TX
	Wichita County, TX
48700	Williamsport, PA	0.8043
	Lycoming County, PA
48864	Wilmington, DE-MD-NJ	1.0824
	New Castle County, DE
	Cecil County, MD
	Salem County, NJ
48900	Wilmington, NC	0.9410
	Brunswick County, NC
	New Hanover County, NC
	Pender County, NC
49020	Winchester, VA-WV	0.9913
	Frederick County, VA
	Winchester City, VA
	Hampshire County, WV
49180	Winston-Salem, NC	0.9118
	Davie County, NC
	Forsyth County, NC
	Stokes County, NC
	Yadkin County, NC
49340	Worcester, MA	1.1287
	Worcester County, MA
49420	Yakima, WA	1.0267
	Yakima County, WA
49500	Yauco, PR	0.3284
	Guánica Municipio, PR
	Guayanilla Municipio, PR
	Peñuelas Municipio, PR
	Yauco Municipio, PR
49620	York-Hanover, PA	0.9359
	York County, PA
49660	Youngstown-Warren-Boardman, OH-PA	0.9002
	Mahoning County, OH
	Trumbull County, OH
	Mercer County, PA
49700	Yuba City, CA	1.0756
	Sutter County, CA
	Yuba County, CA
49740	Yuma, AZ	0.9488
	Yuma County, AZ
1 At this time, there are no hospitals located in this urban area on which to base a wage index.

Table 2—Inpatient Rehabilitation Facility Wage Index for Rural Areas for Discharges Occurring From October 1, 2008 Through September 30, 2009

CBSA code	Nonurban area	Wage index
1	Alabama	0.7533
2	Alaska	1.2109
3	Arizona	0.8479
4	Arkansas	0.7371
5	California	1.2023
6	Colorado	0.9704
7	Connecticut	1.1119
8	Delaware	0.9727
10	Florida	0.8465
11	Georgia	0.7659
12	Hawaii	1.0612
13	Idaho	0.7920
14	Illinois	0.8335
15	Indiana	0.8576
16	Iowa	0.8566
17	Kansas	0.7981
18	Kentucky	0.7793
19	Louisiana	0.7373
20	Maine	0.8476
21	Maryland	0.9034
22	Massachusetts 1	1.1589
23	Michigan	0.8953
24	Minnesota	0.9079
25	Mississippi	0.7700
26	Missouri	0.7930
27	Montana	0.8379
28	Nebraska	0.8849
29	Nevada	0.9272
30	New Hampshire	0.0470
31	New Jersey 1	—
32	New Mexico	0.8940
33	New York	0.8268
34	North Carolina	0.8603
35	North Dakota	0.7182
36	Ohio	0.8714
37	Oklahoma	0.7492
38	Oregon	0.9906
39	Pennsylvania	0.8385
40	Puerto Rico 1	0.4047
41	Rhode Island 1	—
42	South Carolina	0.8656
43	South Dakota	0.8549
44	Tennessee	0.7723
45	Texas	0.7968
46	Utah	0.8116
47	Vermont	0.9919
48	Virgin Islands	0.6830
49	Virginia	0.7896
50	Washington	1.0259
51	West Virginia	0.7454
52	Wisconsin	0.9667
53	Wyoming	0.9287
65	Guam	0.9611
1 All counties within the State are classified as urban, with the exception of Massachusetts and Puerto Rico. Massachusetts and Puerto Rico have areas designated as rural; however, no short-term, acute care hospitals are located in the area(s) for FY 2009. The rural Massachusetts wage index is calculated as the average of all contiguous CBSAs. The Puerto Rico wage index is the same as FY 2008.