07-3789. Medicare Program; Inpatient Rehabilitation Facility Prospective Payment System for Federal Fiscal Year 2008

AGENCY:

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

ACTION:

Final rule.

SUMMARY:

This final rule will update the prospective payment rates for inpatient rehabilitation facilities (IRFs) for Federal fiscal year (FY) 2008 (for discharges occurring on or after October 1, 2007 and on or before September 30, 2008) 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:

The regulatory changes to 42 CFR part 412 are effective October 1, 2007. The updated IRF prospective payment rates are applicable for discharges on or after October 1, 2007 and on or before September 30, 2008.

FOR FURTHER INFORMATION CONTACT:

Pete Diaz, [phone], for information regarding the 75 percent rule.

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

Zinnia Ng, [phone], for information regarding the wage index and prospective payment rate calculation.

SUPPLEMENTARY INFORMATION:

Table of Contents

I. Background

A. Historical Overview of the Inpatient Rehabilitation Facility Prospective Payment System (IRF PPS) for Fiscal Years (FYs) 2002 Through 2007

B. Requirements for Updating the IRF PPS Rates

C. Operational Overview of the Current IRF PPS

II. Provisions of the Proposed Regulations

III. Analysis of and Responses to Public Comments

IV. 75 Percent Rule Policy

V. Classification System for the Inpatient Rehabilitation Facility Prospective Payment System

VI. FY 2008 IRF PPS Federal Prospective Payment Rates

A. FY 2008 IRF Market Basket Increase Factor and Labor-Related Share

B. Area Wage Adjustment

C. Description of the IRF Standard Payment Conversion Factor and Payment Rates for FY 2008

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

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

A. Update to the Outlier Threshold Amount for FY 2008

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

VIII. Clarification to the Regulations Text for Special Payment Provisions for Patients That Are Transferred

IX. Miscellaneous Comments Outside the Scope of the Proposed Rule

X. Provisions of the Final Regulation

XI. Collection of Information Requirement

XII. Regulatory Impact Analysis

A. Overall Impact

B. Anticipated Effects of the Final Rule

C. Anticipated Effects of the 75 Percent Rule Policy

D. Alternatives Considered

E. Accounting Statement

F. Conclusion

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 of 2002, Pub. L. 107-105

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

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

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

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, Pub. L. 109-171

DSH Disproportionate Share Hospital

ECI Employment Cost Indexes

FI Fiscal Intermediary

FR Federal Register

FY Federal Fiscal Year

HHH Hubert H. Humphrey Building

HIPAA Health Insurance Portability and Accountability Act, Pub. L. 104-191

IFMC Iowa Foundation for Medical Care

IOM Internet-Only Manual

IPPS Inpatient Prospective Payment System

IRF Inpatient Rehabilitation Facility

IRF-PAI Inpatient Rehabilitation Facility-Patient Assessment Instrument

IRF PPS Inpatient Rehabilitation Facility Prospective Payment System

IRVEN Inpatient Rehabilitation Validation and Entry

LIP Low-Income Percentage

MEDPAR Medicare Provider Analysis and Review

MMA Medicare Prescription Drug, Improvement, and Modernization Act of 2003 (Pub. L. 108-173)

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

RAC Recovery Audit Contractor

RFA Regulatory Flexibility Act, Pub. L. 96-354

RIA Regulation 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, Pub. L. 97-248

I. Background

A. Historical Overview of the Inpatient Rehabilitation Facility Prospective Payment System (IRF PPS) for Fiscal Years (FYs) 2002 Through 2007

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

Payments under the IRF PPS encompass inpatient operating and capital costs of furnishing covered rehabilitation services (that is, routine, ancillary, and capital costs) but not costs of approved educational activities, bad debts, and other services or items outside the scope of the IRF PPS. Although a complete discussion of the IRF PPS provisions appears in the August 7, 2001 final rule (66 FR 41316) as revised in the FY 2006 IRF PPS final rule (70 FR 47880, August 15, 2005), we are providing below a general description of the IRF PPS for fiscal years (FYs) 2002 through 2005.

Under the IRF PPS from FY 2002 through FY 2005, as described in the August 7, 2001 final rule, 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 August 1, 2003 final rule (68 FR 45674, 45684 through 45685). In the FY 2006 IRF PPS final rule, 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, we then applied adjustments for geographic variations in wages (wage index), the percentage of low-income patients, and location in a rural area (if applicable) to the IRF's unadjusted Federal prospective payment rates. In addition, we made adjustments to account for short-stay transfer cases, interrupted stays, and high cost outliers.

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 to propose refinements to the IRF PPS. We finalized the refinements described in this section in the FY 2006 IRF PPS final rule. The provisions of the FY 2006 IRF PPS final rule became effective for discharges beginning on or after October 1, 2005. We published correcting amendments to the FY 2006 IRF PPS final rule in the Federal Register on September 30, 2005 (70 FR 57166). Any reference to the FY 2006 IRF PPS final rule in this final rule also includes the provisions effective in the correcting amendments.

In the FY 2006 final rule (70 FR 47880 and 70 FR 57166), 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 were based on analyses by the RAND Corporation (RAND), a non-partisan economic and social policy research group, using calendar year 2002 and FY 2003 data. These were the first significant refinements to the IRF PPS since its implementation. In conducting the analysis, RAND used claims and clinical data for services furnished after the IRF PPS implementation. These newer data sets were more complete, and reflected improved coding of comorbidities and patient severity by IRFs. The researchers were able to use new data sources for imputing missing values and more advanced statistical approaches to complete their analyses. The RAND reports supporting the refinements made to the IRF PPS are available on the CMS Web site at: http://www.cms.hhs.gov/​InpatientRehabFacPPS/​09_​Research.asp.

The final key policy changes, effective for discharges occurring on or after October 1, 2005, are discussed in detail in the FY 2006 IRF PPS final rule (70 FR 47880 and 70 FR 57166). The following is a brief summary of the key policy changes:

• Adopted the Office of Management and Budget's (OMB's) Core-Based Statistical Area (CBSA) market area definitions in a budget neutral manner.
• Implemented a budget-neutral 3-year hold harmless policy for IRFs that had been classified as rural in FY 2005, but became urban in FY 2006.
• Implemented a payment adjustment to account for changes in coding that did not reflect real changes in case mix. We reduced the standard payment amount by 1.9 percent to account for such changes in coding following implementation of the IRF PPS.
• Modified the CMGs, tier comorbidities, and relative weights in a budget-neutral manner. The five special CMGs remained the same as they had been before FY 2006 and continued to account for very short stays and for patients who expire in the IRF.
• Implemented a teaching status adjustment in a budget neutral manner for IRFs, similar to the one adopted for inpatient psychiatric facilities.
• Revised and rebased the market basket and labor-related share to reflect the operating and capital cost structures for rehabilitation, psychiatric, and long-term care (RPL) hospitals to update IRF payment rates.
• Updated the rural adjustment from 19.14 percent to 21.3 percent in a budget neutral manner.
• Updated the low-income percentage (LIP) adjustment from an exponent of 0.484 to an exponent of 0.6229 in a budget neutral manner.
• Updated the outlier threshold amount from $11,211 to $5,129.

As noted above, a detailed discussion of the final key policy changes for FY 2006 appears in the FY 2006 IRF PPS final rule (70 FR 47880 and 70 FR 57166).

In the FY 2007 final rule (71 FR 48354) we made the following revisions and updates:

• Updated the relative weight and average length of stay tables based on re-analysis of the data by CMS and our contractor, the RAND Corporation.
• Reduced the standard payment amount by 2.6 percent to account more fully for coding changes that do not reflect real changes in case mix.
• Updated the IRF PPS payment rates by the FY 2007 estimates of the market basket and the labor-related share.
• Updated the IRF PPS payment rates by the FY 2007 wage indexes.
• Applied the second year of the hold harmless policy in a budget neutral manner.
• Updated the outlier threshold from $5,129 to $5,534.
• Updated the urban and rural national cost-to-charge ratio ceilings for the purposes of determining outlier payments under the IRF PPS and clarified the methodology described in the regulations text.
• Revised the regulation text in § 412.23(b)(2)(i) and § 412.23(b)(2)(ii) to reflect the statutory changes in section 5005 of the Deficit Reduction Act of 2005 (DRA, Pub. L. 109-171). The regulation text change prolongs the overall duration of the phased transition to the full 75 percent threshold established in § 412.23(b)(2)(i) and § 412.23(b)(2)(ii), by extending the transition's 60 percent phase for an additional 12 months. In addition to the above DRA requirements pertaining to the applicable compliance percentage requirements under § 412.23(b)(2), we also permitted a comorbidity that meets the criteria as specified in § 412.23(b)(2)(i) to continue to be used before the 75 percent compliance threshold must be met.

B. Requirements for Updating the IRF PPS Rates

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

Section 1886(j)(5) of the Act and § 412.628 of the regulations require the Secretary to publish in the Federal Register, on or before the August 1 that precedes the start of each new FY, the classifications and weighting factors for the IRF CMGs and a description of the methodology and data used in computing the prospective payment rates for the upcoming FY. On August 1, 2002, we published a notice in the Federal Register (67 FR at 49928) to update the IRF Federal prospective payment rates from FY 2002 to FY 2003 using the methodology as described in § 412.624. As stated in the August 1, 2002 notice, we used the same classifications and weighting factors for the IRF CMGs that were set forth in the August 7, 2001 final rule to update the IRF Federal prospective payment rates from FY 2002 to FY 2003. We continued to update the prospective payment rates in accordance with the methodology set forth in the August 7, 2001 final rule for each succeeding FY up to and including FY 2005. For FY 2006, however, we published a final rule that revised several IRF PPS policies (70 FR 47880). The provisions of the FY 2006 IRF PPS final rule became effective for discharges occurring on or after October 1, 2005. We published correcting amendments to the FY 2006 IRF PPS final rule in the Federal Register (70 FR 57166). Any reference to the FY 2006 IRF PPS final rule in this final rule includes the provisions effective in the correcting amendments.

In the final rule for FY 2007, we updated the IRF Federal prospective payment rates. In addition, we updated the cost-to-charge ratio ceilings and the outlier threshold. We implemented a 2.6 percent reduction to the FY 2007 standard payment amount to account more fully for changes in coding practices that do not reflect real changes in case mix. We revised the tier comorbidities and the relative weights to ensure that IRF PPS payments reflect, as closely as possible, the costs of caring for patients in IRFs. The final FY 2007 Federal prospective payment rates were effective for discharges occurring on or after October 1, 2006 and on or before September 30, 2007.

C. Operational Overview of the Current IRF PPS

As described in the August 7, 2001 final rule, upon the admission and discharge of a Medicare Part A fee-for-service patient, the IRF is required to complete the appropriate sections of a patient assessment instrument, the Inpatient Rehabilitation Facility-Patient Assessment Instrument (IRF-PAI). All required data must be electronically encoded into the IRF-PAI software product. Generally, the software product includes patient grouping programming called the GROUPER software. The GROUPER software uses specific Patient Assessment Instrument (PAI) data elements to classify (or group) 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 completes the Medicare claim (UB-92 or its equivalent) using the five-digit CMG number and sends it to the appropriate Medicare fiscal intermediary (FI). Claims submitted to Medicare must comply with both the Administrative Simplification Compliance Act (ASCA, Pub. L. 107-105), and the Health Insurance Portability and Accountability Act of 1996 (HIPAA, Pub. L. 104-191). Section 3 of 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 two types of cases and may also waive such denial “in such unusual cases as the Secretary finds appropriate.” See also the final rule on 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 as 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 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 the Internet-Only Manual (IOM) at Pub. 100-04 published by CMS at: http://www.cms.hhs.gov/​Manuals/​IOM/​list.asp). Instructions for the limited number of claims submitted to Medicare on paper are published by CMS at: http://www.cms.hhs.gov/​manuals/​downloads/​clm104c25.pdf.

The Medicare FI 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 Regulation

As discussed in the FY 2008 IRF PPS proposed rule (72 FR 26230), we proposed to make revisions to the regulation text in order to implement policy changes for IRFs for FY 2008 and subsequent fiscal years. Specifically, we proposed to make conforming changes in 42 CFR part 412. We discuss these proposed revisions and others in detail below.

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

We proposed to revise the current regulations text in paragraph (f)(2)(v) to clarify that we determine whether a high-cost outlier payment would be applicable for transfer cases. We emphasize that this is not a change to our current methodology for determining whether a high-cost outlier payment applies to transfer cases.

B. Additional Proposed Changes

• Update the FY 2008 IRF PPS payment rates by the market basket, as discussed in section IV.A of the FY 2008 IRF PPS proposed rule (72 FR 26320).
• Update the FY 2008 IRF PPS payment rates by the proposed wage index and the labor related share in a budget neutral manner, as discussed in section IV.A and B of the FY 2008 IRF PPS proposed rule (72 FR 26320).
• 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 IV.B of the FY 2008 IRF PPS proposed rule (72 FR 26320).
• Revise the wage index policy for rural areas without hospital wage data by imputing an average wage index from all contiguous CBSAs to represent a reasonable proxy for the rural area within a State, as discussed in section IV.B of the proposed rule (72 FR 26320).
• Implement the final year of the 3-year hold harmless policy adopted in the FY 2006 IRF PPS final rule (70 FR 47880, 447923 through 47926) in a budget neutral manner, as discussed in section IV.B of the FY 2008 IRF PPS proposed rule (72 FR 26320).
• Update the outlier threshold amount for FY 2008 to $7,522, as discussed in section V.A of the FY 2008 IRF PPS proposed rule (72 FR 26320).
• 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 V.B of the FY 2008 IRF PPS proposed rule (72 FR 26320).

III. Analysis of and Responses to Public Comments

We received approximately 40 timely items of correspondence containing multiple comments on the FY 2008 proposed rule (72 FR 26230) from the public. We received comments from a university, 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. 75 Percent Rule Policy

In order to be excluded from the acute care inpatient hospital PPS specified in § 412.1(a)(1) and instead be paid under the IRF PPS, a hospital or rehabilitation unit of an acute care hospital must meet the requirements for classification as an IRF stipulated in subpart B of part 412. As discussed in previous Federal Register publications 68 FR 26786 (May 16, 2003), 68 FR 53266 (September 9, 2003), 69 FR 25752 (May 7, 2004), 70 FR 36640 (June 24, 2005), and 71 FR 48354 (August 18, 2006)), § 412.23(b)(2) specifies one criterion that Medicare uses for classifying a hospital or unit of a hospital as an IRF. The criterion is that a minimum percentage of a facility's total inpatient population must require intensive rehabilitative services for the treatment of at least one of 13 medical conditions listed in § 412.23(b)(2)(iii) in order for the facility to be classified as an IRF. The minimum percentage is known as the “compliance threshold.” In addition, for cost reporting periods beginning on or after July 1, 2004, and before July 1, 2008, a patient's comorbidity, as defined at § 412.602, as well as the patient's principal diagnosis, may be included when determining the medical conditions of the inpatient population that count toward the required applicable percentage, if certain requirements are met.

Prior to the May 7, 2004 final rule (69 FR 25752), § 412.23(b)(2) stipulated that the compliance threshold was 75 percent. Therefore, the compliance threshold was commonly referred to as the “75 percent rule.” In addition, prior to the May 7, 2004 final rule, the regulation only specified 10 medical conditions. However, in the May 7, 2004 final rule, we revised § 412.23(b)(2) to increase the number of medical conditions to 13. We also temporarily lowered the compliance threshold, while at the same time specifying a transition period at the end of which IRFs would once again have to meet a compliance threshold of 75 percent. Also, as described below, the revised regulation specified that during the compliance threshold transition period, a patient's comorbidity may be used to determine whether a provider met the compliance threshold, provided certain applicable requirements were met.

The regulations at § 412.602 define a comorbidity as a specific patient condition that is secondary to the patient's principal diagnosis. A patient's principal diagnosis is the primary reason a patient is admitted to an IRF, and this diagnosis is used to determine whether the patient had a medical condition that can be counted toward meeting the compliance threshold. As specified in the May 7, 2004 final rule, in order for an inpatient with a certain comorbidity to be included in the inpatient population that counts toward the applicable percentage, the following criteria must be met:

• The patient is admitted for inpatient rehabilitation for a condition that is not one of the conditions listed in § 412.23(b)(2)(iii).
• The patient also has a comorbidity that falls within one of the conditions listed in § 412.23(b)(2)(iii).
• The comorbidity has caused significant decline in functional ability in the individual such that, even in the absence of the admitting condition, the individual would require the intensive rehabilitation treatment that is unique to inpatient rehabilitation facilities paid under the IRF PPS and that cannot be appropriately performed in another Medicare-covered care setting.

In accordance with the May 7, 2004 final rule, IRFs would have had to meet a compliance threshold of 75 percent for cost reporting periods starting on or after July 1, 2007. However, section 5005 of the Deficit Reduction Act of 2005 (DRA, Pub. L. 109-171) modified the applicable time periods when the various compliance thresholds, as originally specified in the May 7, 2004 final rule, must be met. The net effect of the DRA was extension of the compliance threshold transition period. Due to the DRA, the transition period was extended to include cost reporting periods starting on or after July 1, 2004, and before July 1, 2008. Therefore, in order to conform the regulations to the DRA, we revised § 412.23(b)(2) by stipulating that an IRF must meet the full 75 percent compliance threshold as of its first cost reporting period that starts on or after July 1, 2008, rather than on or after July 1, 2007. In addition, we also permitted a comorbidity that meets the criteria as specified in paragraph (b)(2)(i) of § 412.23 to continue to be used, along with principal diagnosis, to determine the compliance threshold for cost reporting periods beginning before July 1, 2008, rather than before July 1, 2007. (For a complete description of all of the changes, see the FY 2007 IRF PPS final rule (71 FR 48354)).

Under existing policy, for cost reporting periods beginning on or after July 1, 2008, comorbidities will not be eligible for inclusion in the calculations used to determine whether the provider meets the 75 percent compliance threshold specified in § 412.23(b)(2)(ii). However, in the May 7, 2004 final rule (69 FR 25762), we encouraged research evaluating the continued use of comorbidities in determining compliance with the 75 percent rule. Therefore, in the May 8, 2007 proposed rule (72 FR 26230), we solicited comments supporting current policy or other options, including use of some or all of the existing comorbidities in calculating the compliance percentage for an additional fixed period of one or more years or to integrate the inclusion of some or all of the existing comorbidities on a permanent basis. In addition, we solicited comments that include clinical data based on scientifically sound research that provide evidence to support these and other options.

We received many comments on this proposal, which are summarized below.

Comment: Commenters cited our acknowledgement, made during a conference on Medicare and Medicaid payment issues held March 2007 in Baltimore, Maryland, that approximately 7 percent of inpatients from July 2005 through June 2006 were counted toward the compliance threshold because they met the medical conditions listed in § 412.23(b)(2)(iii) only because of the patient's comorbidities. They argued that eliminating use of comorbidities to determine the compliance percentage would be equivalent to adding an additional 7 percent to the compliance threshold.

Response: One method that we use to determine compliance with the requirements specified at § 412.23(b)(2) is analysis of the impairment group and etiologic diagnosis codes, as well as the comorbidity codes, recorded on the IRF-PAI. It is true that IRF-PAI data from July 1, 2005, to June 30, 2006, indicates that approximately 7 percent of IRF cases met the compliance standards based on the IRF-PAI comorbidity codes alone rather than on the IRF-PAI impairment group or etiologic diagnosis codes. However, this does not mean that the cases were evenly distributed across providers or that 7 percent of IRFs met the compliance threshold solely because of the comorbid conditions of their inpatients. The commenters offer no evidence that IRFs needed to rely on those 7 percent of cases in order to meet the compliance threshold. Also, our rules already provide that up to 25 percent of the cases do not have to be admitted because of a qualifying diagnosis. It does not follow that, because 7 percent of the IRF cases met the compliance standards only because of the comorbidities recorded on the IRF-PAIs, using just the principal diagnoses to determine compliance would result in a higher “effective” compliance threshold. For example, although an IRF may have had a certain percentage of cases that presumptively met a medical condition listed in § 412.23(b)(2)(iii) only because of the comorbid conditions recorded on the IRF-PAI, the IRF may also have a sufficient number of other cases with impairment group or etiologic codes that meet one of the medical conditions identified in § 412.23(b)(2)(iii), and these other cases by themselves could allow the IRF to meet the compliance threshold.

In addition, there is a second method of verifying compliance, which is the FI analyzing a random sample of medical records. Consequently, although the IRF may fail to meet the compliance threshold by an analysis of its IRF-PAI data, the IRF may meet the compliance threshold when the medical records are analyzed. The medical records identify the principal diagnoses, as well as the information supporting the principal diagnoses, which is much more detailed than the list of codes recorded on the IRF-PAIs. Thus, the medical record of a patient may indicate the presence of a qualifying condition that meets the 75 percent rule when the IRF data does not.

The medical conditions that we believe are most appropriate for treatment in an IRF are listed in § 412.23(b)(2)(iii). However, these medical conditions are not specific diagnoses, but broad medical categories. In addition, we acknowledge that there may be atypical patients with medical conditions not listed in § 412.23(b)(2)(iii) who may occasionally also require treatment in an IRF. Therefore, § 412.23(b)(2) has always allowed the IRF the flexibility to admit a percentage of patients with medical conditions not listed in this section of the regulations without losing its classification status as an IRF and the higher reimbursement rate than would be paid to hospitals under the IPPS.

It is important to note that even when the compliance threshold increases to 75 percent, an IRF may admit up to 25 percent of patients who have medical needs that meet the IRF medical necessity criteria but do not have as a principal diagnosis one of the 13 medical conditions used to classify a provider as an IRF. Thus, an IRF may admit up to 25 percent of patients not meeting the 75 percent rule and still be eligible to be paid under the IRF PPS. In other words, when the compliance threshold increases to 75 percent, as many as 1 in every 4 patients may still be admitted with a principal diagnosis that is not one of the medical conditions listed in § 412.23(b)(2)(iii), as long as the patient requires an IRF level of care. Therefore, if an IRF believes that the clinical status of some patients involves principal diagnoses or comorbidities that are so unusually medically and functionally complex as to demonstrate medical necessity to be admitted the IRF, then the IRF may admit these atypical cases as part of the percentage of cases that do not have to meet the 75 percent rule.

Comment: Many commenters urged CMS to permanently continue to use a patient's comorbidities to determine whether a provider met the 75 percent rule. Some commenters stated that terminating the use of comorbidities would decrease the number of IRFs that can achieve compliance as they are adapting their admissions policies and operating procedures. Several commenters urged us to continue the use of comorbidities in the compliance calculations until we can refine the way we identify patients that are most appropriate for an IRF-level of care, or until such time as we have sufficient data to reassess all the provisions of the 75 percent rule. These commenters state that the simple diagnosis-based criteria used in the 75 percent rule is insensitive to the special needs of individual patients, and encouraged CMS to move toward more patient-specific criteria. These commenters also urged CMS to modernize the classifying conditions. Several commenters argued that comorbidities should be retained for use in compliance calculations at a minimum until further research examining the use of comorbidities is conducted, such as assessing the potential negative patient outcomes that may result from the discontinued use. Commenters believed that expiration of the comorbidity provision would change provider behavior, and specifically change admission patterns, in ways that cannot be evaluated using historical data.

Response: We believe a patient's principal diagnosis most accurately identifies the medical condition that required intensive inpatient rehabilitation. A patient's principal diagnosis is determined from the combination of items and services the IRF furnished to the inpatient as documented in the patient's medical record, including the data derived from medical tests, lab tests, procedures, and therapy, as well as the notes of the IRF's clinicians. Medical conditions that are secondary to the patient's principal reason for the inpatient rehabilitation stay are comorbid medical conditions.

It is not unusual for patients admitted to an IRF to have more than one ailment for which the patient exhibited a need for medical treatment. However, it is the patient's principal diagnosis that most accurately denotes whether a patient had a medical condition listed in § 412.23(b)(2)(iii) that required intensive inpatient rehabilitation because of how, as described previously, the principal diagnosis is determined. In other words, the data used to determine the principal diagnosis makes it the most accurate diagnosis that identifies the medical condition which required intensive inpatient rehabilitation. Additionally, as stated above, § 412.23(b)(2) has always allowed the IRF the flexibility to admit a percentage of patients with medical conditions not listed in this regulation section, as long as the patient requires an IRF level of care, without jeopardizing the IRF's classification and eligibility for payment under the IRF PPS.

We believe it is essential that we maintain appropriate criteria to ensure that only facilities providing medically necessary intensive inpatient rehabilitation are classified as IRFs. Thus, it is imperative to identify medical conditions that would typically require intensive inpatient rehabilitation in IRFs, because rehabilitation in general can be delivered in a variety of settings, such as acute care hospitals, SNFs, and outpatient settings. The most appropriate method we can use to identify the medical condition of an inpatient is to determine the impairment that led to admission of the patient to the IRF. It is the principal diagnosis that best identifies the impairment which resulted in the patient's admission providing the principal diagnosis was made in accordance with acceptable medical practice and appropriate clinical coding standards.

The inclusion of comorbidities in determining provider compliance with IRF classification requirements was established as a temporary policy in our May 7, 2004 final rule (69 FR 25752), and the revised regulation continues to be commonly referred to as the 75 percent rule. After careful review of a large volume of comments, we stated in the May 7, 2004 final rule (69 FR 25752, 25762) that we recognized IRFs could need additional time in order to adjust to the revised regulations. Therefore, in order to give IRFs flexibility to adapt we implemented a phase-in to meeting the 75 percent compliance threshold. Similarly, the intent of the comorbidity provision was to provide flexibility that would help providers adapt to the phase-in of enforcement of the compliance threshold.

Originally the transition time period, which provided for a phase-in of the compliance percentage and included the use of comorbid conditions in compliance calculations, was 3 years. However, in accordance with the DRA, the transition time period was extended one additional year. We also decided to extend the use of comorbidities for one additional year as well to maintain consistency with our current approach with respect to the counting of comorbidities before the 75 percent threshold applies. Therefore, providers will have had 4 years to adjust their case-mixes and adapt their operations in order to comply with the 75 percent rule.

As stated in the May 7, 2004 final rule (69 FR 25752, 25762) we have encouraged stakeholders to conduct research studies that could assist us in evaluating IRF compliance criteria. (Elsewhere in this preamble we describe our research efforts.) While we are aware that some studies have been initiated, they have not yet yielded results. The commenters urging the continuation of comorbidities did not support their arguments with sound clinical evidence on the value of including comorbidities when calculating the compliance percentage. In the absence of such evidence, we do not believe it would be appropriate to convert what was always intended to be a temporary accommodation during the phase-in period to a permanent policy. Similarly, we think it would be inappropriate to adopt an extension of indefinite duration because we have no way to estimate when and if sufficient data will become available to reevaluate the IRF classification criteria. However, we will examine our policies as the results of well-designed, rigorous, scientific studies become available and continue to encourage the industry and academics to conduct rehabilitation research. We will continue to evaluate the 75 percent rule and as appropriate will consider improvements to the criteria identifying appropriate IRF admissions that are supported by high-quality research and/or our data analysis.

Miscellaneous 75 Percent Rule Comments

Although it is difficult to separate comments on our comorbidity policy and comments on the other provisions of the 75 percent rule, we believe that the following comments were generally about the other aspects of the 75 percent rule.

Comment: Commenters stated that the 75 percent rule jeopardized the care of patients who required treatment in an IRF by restricting access to treatment. They believe that patients with medical conditions not listed in § 412.23(b)(2)(iii) should be admitted to IRFs because IRFs provide better care for these types of patients. One commenter further stated that the 75 percent rule, by restricting access to care, is denying patients with disabilities access to the comprehensive, coordinated rehabilitation services in an IRF. Another commenter referenced research that the commenter believes shows the length of stay (LOS) of patients with single joint replacements was less in an IRF as opposed to a SNF.

Response: In this rule, we did not propose changes to the 13 qualifying conditions considered to be appropriate for IRF care. However, in the May 7, 2004 final rule (69 FR 25752) we responded to similar comments. We continue to believe that an IRF is appropriately characterized as an inpatient hospital setting designed to provide the specialized, intensive, and interdisciplinary rehabilitation level of care that certain types of patients need. Although we remain committed to maintaining access to rehabilitation care for all Medicare beneficiaries, not all patients require the intensive degree of rehabilitation services that an IRF furnishes. We believe that those specific patients with certain medical conditions requiring intensive inpatient physical therapy, occupational therapy, and, if necessary, speech and language therapy are the patients most appropriate for treatment in an IRF.

We do not believe that the 75 percent rule jeopardizes access to an appropriate level of rehabilitation care, nor do we have data to support that perspective. In addition, although an IRF is capable of extensive medical management of patients by virtue of its inpatient hospital status, as we stated in the May 7, 2004 final rule (69 FR 25752, 25764) “patients who require medical management but not intensive, interdisciplinary rehabilitation can be cared for in another setting.” The fact that care in an IRF may be preferred by some patients and/or their physicians does not make it the most appropriate clinical treatment setting or the most optimal use of intensive rehabilitation resources uniquely provided by IRFs. As part of our ongoing efforts to evaluate the impact of the requirements at § 412.23(b)(2) since we revised the regulations, we have analyzed the available data extensively. Our most recent analysis of this data is available at the following Web site: http://www.cms.hhs.gov/​InpatientRehabFacPPS/​Downloads/​IRF_​PPS_​75_​percent_​Rule_​060807.pdf.

As the IRF industry has noted, the reduced claims volume identified since 2004, which shows the decrease in the inpatient population of IRFs, is almost entirely attributable to cases in one of these five IRF PPS rehabilitation impairment categories (RICs): Lower extremity joint replacement, cardiac, osteoarthritis, pain syndrome, and the miscellaneous category. These five RICs are precisely the types of medical conditions that the 75 percent rule was designed to screen out, because they are not generally thought to require the intensive rehabilitation services provided by IRFs. The clinical experts that CMS consulted prior to publishing the May 7, 2004 final rule (69 FR 25752) indicated that the vast majority of patients with these medical conditions could typically be cared for appropriately in other less intensive settings. In addition, while we have and are continuing to encourage research studies, these studies have not yet been completed. In the absence of findings generated from well-designed scientific studies, we have no evidence showing that the medical conditions in these 5 RICs require treatment in an IRF as opposed to receiving treatment at another treatment setting. Therefore, we do not agree that without a more complete analysis of the patient characteristics and care needs of patients served in the different settings that a shortened length of stay for single joint replacement cases is, in itself, a compelling reason for these cases to be treated in an IRF.

In addition, as more fully described in the analysis, which is available on the previously identified Web site, our examination of the data indicates that patients requiring post-acute rehabilitation care for four common conditions (total knee replacement, total hip replacement, hip fracture, and stroke) have access to and are receiving services in different settings. Therefore, we believe that the data indicate beneficiaries have access to care and are receiving the appropriate level of care at an appropriate cost to the Medicare program. Further, we believe the 75 percent rule promotes equal access to those who require an IRF level of care.

The IRF classification polices are used to identify those patients who have a need for a more intensive level of rehabilitation than is generally required by most patients. Recent industry reports emphasize only a very selective subset of the CMS data, using as their starting point the highest level of utilization and then focusing on the relative decreases that follow. It is important to note, however, that the highest historical level of utilization is not necessarily the most appropriate or even the most typical level of utilization, and that patients who need rehabilitation services have continued access to these services in other settings, as shown by the data in the analysis on the previously referenced Web site. For example:

• Although the proportion of total knee replacement and total hip replacement patients receiving care in IRFs has dropped significantly since 2004, our data show that the proportions of these patients receiving care in the other post-acute care settings are increasing.
• The SNFs, particularly, are now better able to manage patients with musculoskeletal conditions with the introduction of 9 new resource utilization group payment categories beginning in FY 2006. These new payment categories compensate SNFs more fully for patients who have both significant rehabilitation and medical needs—precisely the type of patient who may need some level of medical monitoring but does not require the intense level of inpatient rehabilitation services provided in an IRF setting.

The analyses described above are part of our ongoing evaluation of our IRF classification policies. However, although we have encouraged research to be undertaken that would contribute to improving the criteria for identifying appropriate IRF admissions, we have not received results of well-designed scientific studies that would support such changes at this time.

Comment: Several commenters stated that we should suspend increasing the compliance percentage until we have implemented a single post-acute assessment instrument. One commenter stated that we should devise a price-neutral payment system to pay for care that could be furnished in either a SNF or an IRF. Although the commenter was not clear, we believe that by “price-neutral payment system” the commenter means payments that are basically the same regardless of the setting where the services were furnished. We refer to such a payment system as being site-neutral. Another commenter stated that instead of the broad 13 medical conditions we should use facility characteristics to define a provider as an IRF. Many commenters recommended that the medical conditions listed at § 412.23(b)(2)(iii) should be updated. Other commenters suggested that we should use more specific patient-centered criteria than the broad 13 medical conditions in order to identify which patients should receive care in an IRF. Similarly, a commenter stated that a patient's overall function should be used to determine compliance. Another commenter encouraged us to better identify patients who “typically” are in need of inpatient rehabilitation. This commenter urged CMS to consider that the comorbidity in combination with the primary diagnosis establishes the need for inpatient rehabilitation. Some commenters stated that the 75 percent rule is insensitive and inadequate as a tool to determine a patient's need for IRF care.

Response: While these recommendations address issues that are beyond the scope of this rule because they concern issues about which we did not make any proposals, we will address them briefly because they generally pertain to the 75 percent rule. We agree that future data analysis and the results of well-designed scientific studies may inform policy decisions regarding the IRF classification criteria. With input from all our stakeholders, we will continue our efforts to make these refinements as quickly as possible. In attempting to promote research that better identifies the types of patients whose treatment needs require an IRF setting, CMS has collaborated with several crucial stakeholders to create a framework for future research. We describe some of these efforts below.

• At CMS's request, the National Center for Medical Rehabilitation Research at the National Institute of Child Health and Human Development (NCMRR/NICHD) at the National Institutes of Health (NIH) convened a panel in February 2005 to develop a research agenda on appropriate settings for rehabilitation.
• Recently, NCMRR/NICHD also issued a notice on the NIH Web site recognizing the need to enhance the evidence base for clinical practice, with a commitment to work with providers and research groups to encourage the design of clinical studies that meet NIH standards. We also intend to work with researchers conducting NIH-approved studies so that they can meet their study objectives within the overall framework of the Medicare program benefit.
• Over the past year, we have been actively participating in various NIH panel discussions to foster research in the area of medical rehabilitation, with the goal to better identify typical characteristics of patients in need of the intensive rehabilitative services that only IRFs can provide. In the course of attending these meetings, we have established connections with many of the researchers conducting the research in this area and have been helping them to identify the appropriate resources within CMS.
• We strongly support industry research efforts by serving on project advisory boards and by participating in industry-sponsored meetings and research conferences.

We also want to express our support for our integrated post-acute payment system demonstration project. As part of that demonstration, we are developing an assessment instrument that can be used to assess patients in different treatment settings. We expect that the demonstration will generate much needed data on differences in patient characteristics and treatment outcomes across settings that will be extremely useful in our ongoing evaluation of the IRF PPS. Further, in an effort to try to move toward a site-neutral payment system as suggested by a commenter, the proposed FY 2008 President's Budget includes a proposal to reduce the difference in payment between IRFs and SNFs for total knee and hip replacements. We will continue to look for opportunities to propose policies which move the program in the direction of our ultimate goal of PAC payment reform.

In summary, we will continue to examine our IRF classification polices and the criteria for identifying appropriate IRF admissions using sound data analysis or well-designed scientific studies.

Comment: A commenter believes that our CMG data should be used to identify the concentrations of typical conditions treated in an IRF and use that data instead of or in combination with the 13 medical conditions listed in the regulations as the criteria to classify a provider as an IRF.

Response: We addressed a similar comment in the May 7, 2004 final rule (69 FR 25752, 25758-25759) regarding why it would be inappropriate to use the RICs to classify a provider as an IRF. The CMGs are derived from the RICs and, thus, using CMGs to classify a provider as an IRF would also be inappropriate. The payment system, which is based on the RICs, was devised to pay for all the patients an IRF admits, including the patients not counted as part of the compliance percentage the IRF must meet. Thus, a PPS created to pay for IRF cases is different than a classification system that specifies the percentage of patients that must have certain medical conditions. We refer the commenter to the May 7, 2004 final rule for a more detailed explanation.

Comment: A commenter suggested that we modify our medical review policies to assume that any claim with a qualifying diagnosis or a comorbidity code used in the 75 percent rule calculations can be deemed to meet Medicare's medical necessity provisions. Another commenter stated that FIs were incorrectly performing medical necessity reviews. The same commenter expressed concerns regarding how the Recovery Audit Contractors (RACs) are performing their reviews. Another commenter stated that the 75 percent rule is being used as a crude measure of medical necessity. A few commenters suggested all local coverage determination polices be suspended until we fully examine the issues associated with medical necessity for IRF level of care. Another commenter requested that we use the criteria specified in the Health Care Financing Administration (HCFA) ruling 85-2 as the sole determinant for the medical necessity of an IRF admission, and implement a moratorium on new rehabilitation programs participating in Medicare until we revise the 75 percent rule. One commenter requested that CMS expand our policy to include additional complicating conditions as comorbidities, which count toward compliance with the 75 percent rule.

Response: These comments relate to regulatory policies or operational issues that are outside the scope of the rule. Nevertheless, we address them briefly here. First, the purpose of the comorbidity policy has been to recognize patients with one of the 13 qualifying conditions, even when that qualifying condition is not the primary reason for the IRF admission. The effect of adding new codes would be to inappropriately expand the set of qualifying conditions without any clinical evidence or review. Second, our medical review protocols and IRF compliance criteria were designed to perform two distinct oversight functions. For example, medical review protocols are used to ensure that claims are paid appropriately, but our IRF classification criteria are used to ensure that only facilities that provide intensive inpatient rehabilitation services are paid under the IRF PPS. While we continue to work diligently to improve consistency between the review protocols where appropriate, we realize that there will always be some differences that reflect differences in statutory, regulatory and operational priorities and the two distinct oversight functions. Third, regarding the reviews performed by our contractors, it should be noted that we believe these reviews are necessary to ensure the integrity of the Medicare trust fund. As part of this oversight function, we continuously review the performance of our contractors to ensure that they are functioning in accordance with our policies and guidance. Finally, we believe that implementing a moratorium on new rehabilitation programs participating in Medicare could result in restricting access to care and therefore is not appropriate at this time.

Comment: A commenter stated that the impact of the 75 percent rule combined with reviews being performed by FIs and RACs have decreased IRF admissions well beyond the estimates we envisioned in the May 7, 2004 final rule (69 FR 25752). In addition, the commenter appeared to indicate that the significant drop in IRF admissions as a result of the 75 percent rule and the contractor reviews calls into question the validity of the revisions to § 412.23(b)(2) that we made in the May 7, 2004 final rule.

Response: In evaluating the potential effect of an impending rule change, the regulatory impact analysis represents our best effort to project the economic impact of the change, based on the data available at the time of publication. It is important to note that such projections are estimates, and that they consider only the potential effect of the change itself. Moreover, we do not use such projections as program targets or benchmarks, but rather, conduct reviews and analyses of program data after the change is implemented in order to evaluate its actual impact.

In order to put a proposed change in perspective, a regulatory impact analysis generally is projected on the assumption that all other variables remain constant. Thus, the projections in a regulatory impact analysis take historical data on provider behavior, utilization of services, and expenditure levels and simply trend them forward, in order to show more clearly the effect of the single policy change under review.

When we imposed the temporary moratorium on enforcing the 75 percent rule in June 2002, we assumed that provider case-mix and utilization would remain stable while we took steps to standardize the provider classification procedures. However, our data indicate that during the period when the moratorium was in effect, there was actually a pronounced increase in the volume of IRF cases involving certain specific categories of conditions. In general, the medical conditions in these particular rehabilitation impairment categories—lower extremity joint replacement, cardiac, osteoarthritis, pain syndrome, and miscellaneous—are unlikely to require intensive rehabilitation in IRFs. According to the clinical experts that CMS consulted in revising the 75 percent rule criteria prior to publishing the May 7, 2004 final rule, the vast majority of patients with these medical conditions can typically be appropriately cared for in other less intensive settings. In addition, we have not received reports from well-designed scientific studies showing that these medical conditions are typically appropriate for treatment in an IRF. Thus, we continue to believe that these medical conditions are appropriately treatable in other, less intensive settings.

When we resumed enforcement of the 75 percent rule, the volume of these less intensive IRF cases decreased, accompanied by a concomitant increase in the volume of cases involving conditions that typically do require intensive rehabilitation: brain injury and certain nervous system conditions. This phenomenon would appear to indicate that:

• The 75 percent rule accurately identifies as IRFs those facilities serving patients who genuinely need intensive rehabilitation; and
• Significant behavior changes occurred among IRFs in response to both the initial imposition and the subsequent lifting of the moratorium, underscoring the inappropriateness of utilizing the 2004 final rule's regulatory impact analysis projections (which were not designed to take possible behavior changes into account) as a benchmark in analyzing subsequent utilization patterns.

We do not believe that the decline in IRF utilization levels for certain conditions in the period since we lifted the moratorium is an indication that beneficiaries are being denied access to needed care in this setting. As explained above, we believe that the moratorium itself may well have triggered aberrant IRF utilization patterns, which were skewed toward certain conditions that generally do not require the exceptionally intensive type of rehabilitation that characterizes the IRF setting. As a consequence, what would appear to be a relative decline in IRF utilization since that time may, in fact, represent a return to more normal utilization patterns, which better reflect the actual prevalence of patient need for the kind of intensive rehabilitation that the IRF setting is intended to provide.

We will continue to review Medicare claim and patient assessment data closely as part of our ongoing effort to monitor Medicare beneficiary access to rehabilitation services in IRFs.

Comment: A commenter stated that the 75 percent rule is negatively affecting the financial operations of IRFs because the 75 percent rule and other IRF policies have resulted in more severely ill patients being treated in IRFs, which is not being reflected in IRF PPS payment rates.

Response: We agree that IRF utilization patterns have changed since we began enforcing the 75 percent rule in 2004. The CMS data show a shift in the pattern of admissions away from lower acuity cases such as unilateral knee replacements to more severe conditions. However, we do not agree that the IRF PPS rates do not cover the cost of treating these more severely ill patients, in fact, comparisons of IRF payments and costs, as calculated by both CMS and MedPAC, showed double digit profit margins from the start of the IRF PPS in 2002 through 2005. The IRF profit margins are expected to decline in FY 2008, but should still remain positive. Based on this profitability analysis, we believe that the existing IRF PPS rate structure adequately accounts for the full range of IRF patients. Further, these analyses support our understanding that the IRF case-mix system was specifically designed to reflect the needs and costs of a unique segment of the post acute population requiring both intensive rehabilitation and medical management.

Final Decision: After carefully considering the comments, we are maintaining the comorbidity policy specified in § 412.23(b)(2). Therefore, for cost reporting periods beginning on or after July 1, 2007, and before July 1, 2008, the compliance threshold remains 65 percent and we will continue to include comorbidities when calculating the compliance percentage. However, for cost reporting periods beginning on or after July 1, 2008, the compliance threshold will increase to 75 percent, but the comorbidities will not be used to determine whether a provider met the 75 percent of the compliance threshold.

V. Classification System for the Inpatient Rehabilitation Facility Prospective Payment System

For the FY 2008 IRF PPS, we will use the same case-mix classification system that we used for FY 2007, as set forth in the FY 2007 IRF PPS final rule (71 FR 48354). Table 1 below, “Relative Weights and Average Lengths of Stay for Case-Mix Groups”, presents the CMGs, the comorbidity tiers, the corresponding relative weights, and the average length of stay value for each CMG and tier. The average length of stay for each CMG is used to determine when an IRF discharge meets the definition of a short-stay transfer, which results in a per diem case level adjustment. Because these data elements are not changing, Table 1 shown below is identical to Table 4 that was published in the FY 2007 IRF PPS final rule (71 FR 48354, 48364 through 48370). The methodology we used to construct the data elements in Table 1 is described in detail in the FY 2007 IRF PPS final rule (71 FR 48354).

We received a few comments on the proposed classification system for FY 2008, which are summarized below.

Comment: A few commenters expressed concerns about the proposed CMG relative weight and average length of stay values for FY 2008, noting that they are based on FY 2003 data and that these data do not reflect the changes in IRF cost structures that may be occurring in response to the renewed enforcement of the 75 percent rule. These commenters requested that CMS use the latest available data to update the CMG relative weights and average length of stay values for FY 2008 and future years. One commenter suggested that CMS update the CMG definitions regularly to reflect changes in clinical practice that affect resource use.

Response: We agree with the commenters that it is important to update the CMG relative weights, average length of stay values, and CMG definitions regularly to reflect changes in IRF admission patterns and cost structures, using the most recent available data. We are analyzing the data carefully to prepare to update the IRF classification system, as appropriate, in the future. However, we also believe it is important to balance the need to update these elements with the benefits derived from maintaining stability within the IRF classification system and payment rates. In the FY 2006 IRF PPS final rule (70 FR 47880, 47886 through 47904), we implemented major changes to the IRF classification system, including revising the CMG definitions and recalibrating the CMG relative weights and average length of stay values. Given that these major changes to the classification system took effect less than 2 years ago, we believe that, in the interest of fostering stability in the IRF PPS, we should allow more time to pass before we implement more changes to the system. By waiting at least one additional year before making further changes to the system, we will ensure that we have sufficient time to analyze the effects of the FY 2006 revisions and the impact they are having on providers, which will improve the accuracy of future IRF PPS refinements. We also believe that further analysis of the FY 2006 data is needed to determine how the changes to the classification system, as well as the changes to the facility-level adjustments and the other changes we adopted in the FY 2006 final rule, are affecting providers. Now that the FY 2006 claims data are available, we are analyzing them and will propose updates to the system as appropriate in the future.

Although we believe that it is best to delay updating the CMG relative weights and average length of stay values, we have conducted an analysis of these components of the IRF classification system using FY 2006 data. This analysis shows that updating these elements of the classification system would not materially change payments for the vast majority of IRF discharges. From this analysis, we found that payments for about 90 percent of the cases in our data would change by less than 4 percent. CMGs for which payments would change by more than 4 percent contain a small number of cases. Based on our analysis, we believe that it is more appropriate to update the CMG relative weights and average length of stay values after we conduct careful analysis of the FY 2006 data and analyze IRFs' responses to the changes that we implemented to the system in FY 2006. We believe that the results that we will obtain from this analysis of the effects of the FY 2006 revisions on providers will improve the accuracy of future revisions to the IRF PPS.

Comment: One commenter suggested that CMS should review the FY 2006 revisions to the classification system with more recent data to determine whether the revisions caused a 2.2 percent decrease in aggregate IRF payments and whether further revisions to the system are needed to account for this.

Response: Since this comment is on revisions that we implemented for FY 2006, and we did not propose additional revisions to the IRF classification system for FY 2008, this comment is outside the scope of this final rule. Further, we responded to a very similar comment in the FY 2007 IRF PPS final rule (71 FR 48373 through 48374). However, our analysis of the data continues to show that the FY 2006 refinements to the IRF classification system did not cause a reduction in aggregate IRF payments. We are continuing to work with the industry to understand its concerns, and we are analyzing the FY 2006 IRF claims data in detail to identify any unanticipated effects of the FY 2006 revisions to the classification system on IRF payments. However, our analysis of the data 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 did not increase or decrease as a result of these refinements. Although our preliminary data do not show any decrease in IRF aggregate payments for FY 2006 resulting from the FY 2006 revisions to the IRF classification system, we will continue to analyze the FY 2006 data to determine whether additional refinements to the IRF classification system are necessary in the future.

Final Decision: After carefully reviewing the comments that we received on the proposed changes to the CMG relative weights and average length of stay values, we proposed and will finalize our decision to update the CMG relative weights and the average length of stay values for FY 2008, as shown in Table 1.

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

CMG	CMG description (M=motor, C=cognitive, A=age)	Relative weights				Average length of stay
		Tier 1	Tier 2	Tier 3	None	Tier 1	Tier 2	Tier 3	None
0101	Stroke
	M>51.05	0.7707	0.7303	0.6572	0.6347	8	11	9	9
0102	Stroke
	M>44.45 and M<51.05 and C>18.5	0.9493	0.8995	0.8095	0.7818	11	15	11	10
0103	Stroke
	M>44.45 and M<51.05 and C<18.5	1.1192	1.0605	0.9544	0.9218	14	13	12	12
0104	Stroke
	M>38.85 and M<44.45	1.1885	1.1260	1.0134	0.9787	13	14	13	13
0105	Stroke
	M>34.25 and M<38.85	1.4261	1.3512	1.2161	1.1745	16	17	16	15
0106	Stroke
	M>30.05 and M<34.25	1.6594	1.5722	1.4150	1.3666	18	20	18	18
0107	Stroke
	M>26.15 and M<30.05	1.9150	1.8145	1.6330	1.5771	21	23	21	20
0108	Stroke
	M<26.15 and A>84.5	2.2160	2.0997	1.8897	1.8250	28	29	25	24
0109	Stroke
	M>22.35 and M<26.15 and A<84.5	2.1998	2.0843	1.8758	1.8116	23	26	24	23
0110	Stroke
	M<22.35 and A<84.5	2.6287	2.4907	2.2416	2.1649	30	33	28	27
0201	Traumatic brain injury
	M>53.35 and C>23.5	0.8143	0.6806	0.6080	0.5647	10	9	9	8
0202	Traumatic brain injury
	M>44.25 and M<53.35 and C>23.5	1.0460	0.8743	0.7810	0.7254	12	10	11	9
0203	Traumatic brain injury
	M>44.25 and C<23.5	1.2503	1.0450	0.9335	0.8671	15	15	12	12
0204	Traumatic brain injury
	M>40.65 and M<44.25	1.3390	1.1192	0.9998	0.9287	15	16	13	13
0205	Traumatic brain injury
	M>28.75 and M<40.65	1.6412	1.3718	1.2254	1.1382	17	18	16	15
0206	Traumatic brain injury
	M>22.05 and M<28.75	2.1445	1.7924	1.6011	1.4873	23	22	21	20
0207	Traumatic brain injury
	M<22.05	2.7664	2.3122	2.0655	1.9185	35	29	26	25
0301	Non-traumatic brain injury
	M>41.05	1.1394	0.9533	0.8552	0.7772	12	12	11	10
0302	Non-traumatic brain injury
	M>35.05 and M<41.05	1.4875	1.2446	1.1164	1.0147	14	16	14	13
0303	Non-traumatic brain injury
	M>26.15 and M<35.05	1.7701	1.4810	1.3285	1.2074	20	19	17	16
0304	Non-traumatic brain injury
	M<26.15	2.4395	2.0410	1.8309	1.6640	32	25	23	21
0401	Traumatic spinal cord injury
	M>48.45	0.9587	0.8456	0.7722	0.6858	12	12	11	10
0402	Traumatic spinal cord injury
	M>30.35 and M<48.45	1.3256	1.1691	1.0676	0.9482	18	16	14	13
0403	Traumatic spinal cord injury
	M>16.05 and M<30.35	2.3069	2.0347	1.8580	1.6502	22	24	24	22
0404	Traumatic spinal cord injury
	M<16.05 and A>63.5	4.1542	3.6639	3.3458	2.9717	51	46	41	37
0405	Traumatic spinal cord injury
	M<16.05 and A<63.5	3.1371	2.7668	2.5266	2.2441	33	37	33	28
0501	Non-traumatic spinal cord injury
	M>51.35	0.7648	0.6455	0.5687	0.5071	9	8	8	7
0502	Non-traumatic spinal cord injury
	M>40.15 and M<51.35	1.0262	0.8661	0.7630	0.6804	13	12	11	9
0503	Non-traumatic spinal cord injury
	M>31.25 and M<40.15	1.3596	1.1476	1.0109	0.9014	15	15	13	12
0504	Non-traumatic spinal cord injury
	M>29.25 and M<31.25	1.6984	1.4335	1.2628	1.1260	21	19	16	15
0505	Non-traumatic spinal cord injury
	M>23.75 and M<29.25	2.0171	1.7025	1.4997	1.3373	23	22	19	18
0506	Non-traumatic spinal cord injury
	M<23.75	2.7402	2.3128	2.0374	1.8167	29	28	26	23
0601	Neurological
	M>47.75	0.8991	0.7330	0.7019	0.6522	11	10	9	9
0602	Neurological
	M>37.35 and M<47.75	1.1968	0.9757	0.9342	0.8682	13	13	13	12
0603	Neurological
	M>25.85 and M<37.35	1.5326	1.2495	1.1965	1.1118	17	17	15	15
0604	Neurological
	M<25.85	1.9592	1.5973	1.5295	1.4213	22	20	21	19
0701	Fracture of lower extremity
	M>42.15	0.9028	0.7717	0.7338	0.6617	12	11	10	9
0702	Fracture of lower extremity
	M>34.15 and M<42.15	1.1736	1.0033	0.9539	0.8602	13	14	13	12
0703	Fracture of lower extremity
	M>28.15 and M<34.15	1.4629	1.2506	1.1890	1.0722	16	17	16	14
0704	Fracture of lower extremity
	M<28.15	1.7969	1.5361	1.4605	1.3170	20	20	19	18
0801	Replacement of lower extremity joint
	M>49.55	0.6537	0.5504	0.5131	0.4607	7	7	7	6
0802	Replacement of lower extremity joint
	M>37.05 and M<49.55	0.8542	0.7193	0.6704	0.6020	10	10	9	8
0803	Replacement of lower extremity joint
	M>28.65 and M<37.05 and A>83.5	1.2707	1.0700	0.9974	0.8956	15	15	13	12
0804	Replacement of lower extremity joint
	M>28.65 and M<37.05 and A<83.5	1.1040	0.9296	0.8665	0.7781	13	12	12	10
0805	Replacement of lower extremity joint
	M>22.05 and M<28.65	1.3927	1.1727	1.0931	0.9816	17	16	14	13
0806	Replacement of lower extremity joint
	M<22.05	1.6723	1.4082	1.3126	1.1787	18	19	17	15
0901	Other orthopedic
	M>44.75	0.8425	0.7641	0.6868	0.6120	10	11	10	9
0902	Other orthopedic
	M>34.35 and M<44.75	1.1088	1.0057	0.9039	0.8056	13	13	12	11
0903	Other orthopedic
	M>24.15 and M<34.35	1.4638	1.3277	1.1934	1.0635	18	19	16	15
0904	Other orthopedic
	M<24.15	1.8341	1.6636	1.4952	1.3325	25	23	21	19
1001	Amputation, lower extremity
	M>47.65	0.9625	0.8879	0.7957	0.7361	11	11	11	10
1002	Amputation, lower extremity
	M>36.25 and M<47.65	1.2709	1.1724	1.0507	0.9719	14	15	14	13
1003	Amputation, lower extremity
	M<36.25	1.7876	1.6491	1.4779	1.3671	19	22	19	18
1101	Amputation, non-lower extremity
	M>36.35	1.2554	1.0482	0.9225	0.8496	14	15	12	11
1102	Amputation, non-lower extremity
	M<36.35	1.8824	1.5717	1.3832	1.2739	19	19	18	17
1201	Osteoarthritis
	M>37.65	1.0177	0.8785	0.8182	0.7405	11	12	11	10
1202	Osteoarthritis
	M>30.75 and M<37.65	1.3168	1.1367	1.0586	0.9581	15	16	14	13
1203	Osteoarthritis
	M<30.75	1.6241	1.4020	1.3057	1.1817	21	19	17	16
1301	Rheumatoid, other arthritis
	M>36.35	1.0354	0.9636	0.8511	0.7429	12	13	11	10
1302	Rheumatoid, other arthritis
	M>26.15 and M<36.35	1.4321	1.3327	1.1772	1.0275	15	18	15	14
1303	Rheumatoid, other arthritis
	M<26.15	1.8250	1.6984	1.5002	1.3094	22	21	20	18
1401	Cardiac
	M>48.85	0.8160	0.7351	0.6534	0.5861	10	9	9	8
1402	Cardiac
	M>38.55 and M<48.85	1.1038	0.9944	0.8839	0.7928	12	13	12	11
1403	Cardiac
	M>31.15 and M<38.55	1.3705	1.2347	1.0975	0.9844	16	16	14	13
1404	Cardiac
	M<31.15	1.7370	1.5649	1.3910	1.2477	21	20	18	16
1501	Pulmonary
	M>49.25	0.9986	0.8870	0.7793	0.7399	11	13	10	10
1502	Pulmonary
	M>39.05 and M<49.25	1.2661	1.1246	0.9880	0.9381	13	15	12	12
1503	Pulmonary
	M>29.15 and M<39.05	1.5457	1.3730	1.2062	1.1453	16	16	15	15
1504	Pulmonary
	M<29.15	2.0216	1.7957	1.5775	1.4979	26	21	20	18
1601	Pain syndrome
	M>37.15	1.0070	0.8550	0.7774	0.6957	12	11	10	10
1602	Pain syndrome
	M>26.75 and M<37.15	1.3826	1.1739	1.0673	0.9552	15	17	14	13
1603	Pain syndrome
	M<26.75	1.7025	1.4455	1.3143	1.1762	19	19	18	16
1701	Major multiple trauma without brain or spinal cord injury
	M>39.25	0.9818	0.9641	0.8479	0.7368	12	12	11	10
1702	Major multiple trauma without brain or spinal cord injury
	M>31.05 and M<39.25	1.2921	1.2688	1.1158	0.9696	14	16	15	13
1703	Major multiple trauma without brain or spinal cord injury
	M>25.55 and M<31.05	1.5356	1.5080	1.3262	1.1524	17	20	18	16
1704	Major multiple trauma without brain or spinal cord injury
	M<25.55	1.9246	1.8899	1.6620	1.4443	26	26	22	19
1801	Major multiple trauma with brain or spinal cord injury
	M>40.85	1.1920	0.9866	0.8243	0.7342	15	13	13	10
1802	Major multiple trauma with brain or spinal cord injury
	M>23.05 and M<40.85	1.9058	1.5774	1.3179	1.1738	19	21	18	16
1803	Major multiple trauma with brain or spinal cord injury
	M<23.05	3.4302	2.8391	2.3721	2.1127	43	33	30	27
1901	Guillian Barre
	M>35.95	1.2399	1.0986	1.0965	0.9350	14	13	14	12
1902	Guillian Barre
	M>18.05 and M<35.95	2.3194	2.0552	2.0512	1.7491	27	25	25	23
1903	Guillian Barre
	M<18.05	3.3464	2.9651	2.9593	2.5235	37	39	31	33
2001	Miscellaneous
	M>49.15	0.8734	0.7381	0.6735	0.6084	10	10	9	8
2002	Miscellaneous
	M>38.75 and M<49.15	1.1447	0.9674	0.8827	0.7975	12	13	12	11
2003	Miscellaneous
	M>27.85 and M<38.75	1.4777	1.2488	1.1395	1.0294	16	16	15	14
2004	Miscellaneous
	M<27.85	1.9716	1.6662	1.5204	1.3735	25	22	20	18
2101	Burns
	M>0	2.1842	2.1842	1.6606	1.4587	27	24	20	17
5001	Short-stay cases, length of stay is 3 days or fewer				0.2201				2
5101	Expired, orthopedic, length of stay is 13 days or fewer				0.6351				8
5102	Expired, orthopedic, length of stay is 14 days or more				1.5985				22
5103	Expired, not orthopedic, length of stay is 15 days or fewer				0.7203				8
5104	Expired, not orthopedic, length of stay is 16 days or more				1.8784				24

VI. FY 2008 IRF PPS Federal Prospective Payment Rates

A. FY 2008 IRF PPS Market Basket Increase Factor and Labor-Related Share

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. In updating the FY 2008 payment rates outlined in this final rule, CMS applied an appropriate increase factor to the FY 2007 IRF PPS payment rates that is based on the rehabilitation, psychiatric, and long-term care hospital (RPL) market basket. In constructing the RPL market basket, we used the methodology set forth in the FY 2006 IRF PPS final rule (70 FR 47880, 47908 through 47915).

As discussed in that final rule, the RPL market basket primarily uses the Bureau of Labor Statistics' (BLS) data as price proxies, which are grouped in one of the three BLS categories: Producer Price Indexes (PPI), Consumer Price Indexes (CPI), and Employment Cost Indexes (ECI). We evaluated and selected these particular price proxies using the criteria of reliability, timeliness, availability, and relevance, and believe they continue to be the best measures of price changes for the cost categories.

As discussed in the FY 2007 IRF PPS proposed rule, beginning April 2006 with the publication of March 2006 data, the BLS’ ECI has used a different classification system, the North American Industrial Classification System (NAICS), instead of the Standard Industrial Codes (SIC). We have consistently used the ECI as the data source for our wages and salaries and other price proxies in the RPL market basket and did not propose to make any changes to the data source in the proposed rule. This final rule's estimated FY 2008 IRF market basket increase factor and labor-related share is based on the most recent data available from the BLS.

We will use the same methodology described in the FY 2006 IRF PPS final rule to compute the FY 2008 IRF market basket increase factor and labor-related share. For this final rule, the FY 2008 IRF market basket increase factor is 3.2 percent. This is based on Global Insight, Inc.’s (GII) forecast of price proxies for the second quarter of 2007 (2007Q2) with historical data through the first quarter of 2007 (2007Q1).

In addition, we have used the methodology described in the FY 2006 IRF PPS final rule to update the labor-related share for FY 2008. As discussed in the FY 2006 IRF PPS final rule (70 FR 47880, 47915 through 47917), we rebased and revised the market basket for FY 2006 using the 2002-based cost structures for IRFs, inpatient psychiatric hospitals, and long-term care hospitals to determine the FY 2006 labor-related share. For FY 2007, we used the same methodology discussed in the FY 2006 IRF PPS final rule (70 FR 47880, 47908 through 47917) to determine the FY 2007 IRF labor-related share. For FY 2008, we continue to use the same methodology discussed in the FY 2006 IRF PPS final rule. As shown in Table 2, the total FY 2008 RPL labor-related share is 75.818 percent in this final rule.

Table 2.—FY 2008 IRF Labor-Related Share Relative Importance

Cost category	FY 2008 IRF labor-related relative importance
Wages and salaries	52.640
Employee benefits	14.125
Professional fees	2.907
All other labor intensive services	2.144
Subtotal	71.816
Labor-related share of capital costs	4.002
Total	75.818
Source: Global Insight, Inc, 2nd Qtr, 2007; @USMACRO/CONTROL0507@CISSIM/TL0507.SIM, Historical Data through 1st QTR, 2007.

We received two comments on the proposed FY 2008 IRF PPS market basket and labor-related share, which are summarized below.

Comment: One commenter requested that the IRF PPS market basket adjustments be calculated using more current market basket data, stating that the inflation factors for FY 2008 are based upon data that are 5 years old (FY 2002). The commenter suggested that this may result in an underestimation of the labor cost inflation experienced by IRFs.

Response: We disagree with the comment that the inflation factors used in the market basket are based upon data that are 5 years old. To derive the IRF market basket, we use FY 2002 data to derive the relative cost weights for the base year. While these cost weights remain fixed until the market basket is rebased to a new base year, data for the respective price proxies are frequently updated to reflect more recent data as they become available. The final IRF market basket update for FY 2008 is based on GII's forecast for the second quarter of 2007 (2007Q2). This forecast reflects historical data for the various inflation factors through the first quarter of 2007 (2007Q1).

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 on an annual basis in FY 2009 using the most recent available data. The commenter stated that the current calculation of the labor-related share is based on 2002 data and expressed concern that this time lag is distorting actual labor cost trends being experienced by IRFs. Another commenter said that the methodology does not adequately reflect the difficulty IRFs have in recruiting a skilled labor force.

Response: We disagree with the commenters' view that the methodology does not reflect accurate labor-related costs for IRFs. The FY 2008 labor-related share is calculated as the sum of the relative importance of those costs that are related to, influenced by, or vary with the local labor market. This includes wages and salaries, fringe benefits, professional fees, labor-intensive services, and a portion of capital costs. We calculate this share based on the cost weights associated with the 2002-based RPL market basket, which is constructed using Medicare Cost Reports submitted by IRFs.

Further, we believe these weights adequately reflect the current cost structures of Medicare-participating IRFs given our methodology for calculating the labor-related relative importance for FY 2008. First, we compute the FY 2008 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 2008 price index level for that cost category by the total market basket price index level. Third, we determine the FY 2008 relative importance for each cost category by multiplying this ratio by the base year (FY 2002) weight. Finally, we sum the FY 2008 relative importance for each of the labor-related categories to produce the FY 2008 labor-related relative importance.

The price proxies that move the different cost categories in the market basket do not necessarily change at the same rate, and the relative importance captures these changes. Accordingly, the relative importance figure more closely reflects the cost share weights for FY 2008 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 update the IRF PPS payment rates using our current methodology, which reflects the most recent available data. For this final rule, the FY 2008 IRF market basket increase factor is 3.2 percent and the labor-related share is 75.818 percent. This is based on GII's forecast for the second quarter of 2007 (2007Q2) with historical data through the first quarter of 2007 (2007Q1).

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 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 2007 IRF PPS final rule, 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 that final rule (70 FR 47880, 47917 through 47933). In the FY 2006 IRF PPS final rule, we adopted a 3-year hold harmless policy specifically for rural IRFs whose labor market designations changed from rural to urban under the CBSA-based labor market area designations. This policy specifically applied to IRFs that had been previously designated rural and which, effective for discharges on or after October 1, 2005, would otherwise have become ineligible for the 19.14 percent rural adjustment. For FY 2008, the third and final year of the 3-year phase-out of the budget neutral hold harmless policy, we will no longer apply an adjustment for IRFs that meet the criteria described in the FY 2006 final rule (70 FR 47880, 47923 through 47926).

For FY 2008, we will maintain the policies and methodologies described in the FY 2007 IRF PPS final rule relating to the labor market area definitions, the wage index methodology for areas with wage data, and hold harmless policy consistent with the rationale outlined in the FY 2006 IRF PPS final rule (70 FR 47880, 47917 through 47933). Therefore, this final rule continues to use the CBSA labor market area definitions and the pre-reclassification and pre-floor hospital wage index based on 2003 cost report data. In addition, the budget neutral hold harmless policy established in the FY 2006 final rule will expire for discharges occurring on or after October 1, 2007.

In adopting the CBSA geographic designations in FY 2006, we provided a 1-year transition with a blended wage index for all providers. For FY 2006, the wage index for each provider consisted of a blend of 50 percent of the FY 2006 metropolitan statistical area (MSA)-based wage index and 50 percent of the FY 2006 CBSA-based wage index (both using FY 2001 hospital data). We referred to the blended wage index as the FY 2006 IRF PPS transition wage index. As discussed in the FY 2006 IRF PPS final rule (70 FR 47880, 47926), subsequent to the expiration of this 1-year transition on September 30, 2006, we used the full CBSA-based wage index values as published in the Addendum of the FY 2007 IRF PPS final rule (71 FR 48354) and in the Addendum of this final rule.

When adopting OMB's new labor market designations, 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 (70 FR 47880).

In this final rule, we are revising our methodology to determine a proxy for rural areas without hospital wage data. Under the CBSA labor market areas, there are no rural hospitals in rural Massachusetts and rural Puerto Rico. Because there was no rural proxy for more recent rural data within those areas, we used the FY 2006 wage index value in both FY 2006 and FY 2007 for rural Massachusetts and rural Puerto Rico.

Due to the use of the same wage index value (from FY 2006) for these areas for two fiscal years, we believe it is appropriate at this point to consider alternatives in our methodology to update the wage index for rural areas without rural hospital wage index data. We believe that the best imputed proxy would (1) use pre-floor, pre-reclassified hospital data, (2) be easy to evaluate, (3) use the most local data, and (4) be easily updateable from year-to-year. Since the implementation of the IRF PPS, we have used the pre-floor, pre-reclassified hospital wage data that is easy to evaluate and is updatable from year-to-year. In addition, the IRF PPS wage index is based on hospitals' cost report data, which reflects local available data. Therefore, we believe the imputed proxy for a rural area without hospital wage data is consistent with our past methodology and other post-acute PPS wage index policy. Although our current methodology uses rural pre-floor, pre-reclassified hospital wage data, this method is not updateable from year-to-year.

Therefore, in cases where there is a rural area without rural hospital wage data, we are finalizing the use of the average wage index from all contiguous CBSAs to represent a reasonable proxy for the rural area within a State. While this approach does not use rural data, it does use pre-floor, pre-reclassified hospital wage data, it is easy to evaluate, it is updateable from year-to-year, and it uses the most local data available.

In determining an imputed rural wage index, we interpret the term “contiguous” to mean sharing a border. For example, in the case of Massachusetts, the entire rural area consists of Dukes and Nantucket counties. We have determined that the borders of Dukes and Nantucket counties are local and contiguous with Barnstable and Bristol counties. Under this methodology, the wage indexes for the counties of Barnstable (CBSA 12700: 1.2539) and Bristol (CBSA 39300: 1.0783) are averaged, resulting in an imputed rural wage index of 1.1661 for rural Massachusetts for FY 2008. We believe that this policy could be readily applied to other rural areas that lack hospital wage data (possibly due to hospitals converting to a different provider type, such as a critical access hospital, that does not submit the appropriate wage data), and we may re-examine this policy should a similar situation arise in the future.

However, we do not believe that this policy is appropriate for Puerto Rico. There are sufficient economic differences between hospitals in the United States and those in Puerto Rico (including the payment of hospitals in Puerto Rico using blended Federal/Commonwealth-specific rates) that a separate and distinct policy for Puerto Rico is necessary. Consequently, any alternative methodology for imputing a wage index for rural Puerto Rico would need to take into account these economic differences and the payment rates hospitals receive in Puerto Rico. Our policy of imputing a rural wage index based on the wage index(es) of CBSAs contiguous to the rural area in question does not recognize the unique circumstances of Puerto Rico. While we have not yet identified an alternative methodology for imputing a wage index for rural Puerto Rico, we will continue to evaluate the feasibility of using existing hospital wage data and, possibly, wage data from other sources. By maintaining our current policy for Puerto Rico, we will maintain consistency with other post-acute care PPS wage index policies. Accordingly, we will continue using the most recent wage index previously available for Puerto Rico; that is, a wage index of 0.4047.

In the FY 2006 IRF PPS final rule (70 FR 47880, 47920), we notified the public that the Office of Management and Budget (OMB) published a bulletin that changed the titles of certain CBSAs after the publication of our FY 2006 IRF PPS proposed rule (70 FR 30186). Since the publication of the FY 2006 IRF PPS final rule, OMB published additional bulletins that updated the CBSAs. Specifically, OMB added or deleted certain CBSA numbers and revised certain titles. Accordingly, in this final rule, we are clarifying that this and all subsequent IRF PPS rules and notices are considered to incorporate the CBSA changes published in the most recent OMB bulletin that applies to the hospital wage data used to determine the current IRF PPS wage index. The OMB bulletins may be accessed online at http://www.whitehouse.gov/​omb/​bulletins/​index.html.

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 2008 RPL labor-related share (75.818 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 August 1, 2003 final rule and codified at § 412.624(e)(1), and described in the steps below. We use the following steps to ensure that the FY 2008 IRF standard payment conversion factor reflects the update to the wage indexes (based on the FY 2003 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 2007 IRF PPS rates, using the FY 2007 standard payment conversion factor and the labor-related share and the wage indexes from FY 2007 (as published in the FY 2007 IRF PPS final rule).

Step 2. Calculate the total amount of estimated IRF PPS payments, using the FY 2007 standard payment conversion factor and the FY 2008 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 FY 2008 budget neutral wage adjustment factor of 1.0028.

Step 4. Apply the FY 2008 budget neutral wage adjustment factor from step 3 to the FY 2007 IRF PPS standard payment conversion factor after the application of the estimated market basket update to determine the FY 2008 standard payment conversion factor.

We received a few comments on the proposed IRF PPS wage index, which are summarized below.

Comment: A few commenters recommended that we revise the urban IRF PPS wage index policies to stabilize the wage index from one year to the next. The commenters stated that the FY 2008 IRF PPS proposed wage indexes would be lower than other IRFs or acute care hospitals in their local market area. In addition, the variability of the wage index from one year to the next causes unpredictable annual revenue swings that make it difficult to retain staff. Thus, it is difficult for these IRFs to compete for healthcare personnel in the same market area as other local IRFs and acute care hospitals. The wage index recommendations varied from a general change to the urban wage index to specific criteria an IRF must meet in order to qualify for the commenter's recommended wage index policy.

We also received a few public comments that recommend 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. (A discussion of the IPPS reclassification and floor policies may be found on our Web site at http://www.cms.hhs.gov/​AcuteInpatientPPS/​01_​overview.asp.)

In addition, commenters recommended that we conduct further analysis and discussions with the industry regarding alternative wage index methodologies that would minimize fluctuations in the wage index and better reflect the costs of IRF labor in the market areas.

Response: For FY 2008, we proposed a revision to our methodology to determine a proxy for rural areas without hospital wage data. This proxy would be applied to rural geographic areas in a State where there is no hospital wage data. We did not propose changes in the IRF PPS methodology for urban areas with available hospital wage data nor did we propose to revise our current wage index policies to adopt the reclassification or floor provisions used in the IPPS. For this reason, we are not making changes at this time to wage index policies beyond what we discussed in the FY 2008 IRF PPS proposed rule (72 FR 26230).

A few commenters recommended alternative approaches to the IRF PPS wage index that we would like to further analyze and may consider in the future. For example, we received recommendations ranging from a general change to the urban wage index and wage data to specific criteria an IRF must meet in order to qualify for the commenter's recommended wage index policy. We met in 2006 and 2007 with industry representatives that recommended several different approaches to the IRF PPS wage index that they believe would minimize the shifts in the wage index from one year to the next. However, we agree with the commenters that urged us to conduct further analysis. For this reason, we believe that it is prudent to refrain from acting on these recommendations at this time so that we can consider, if appropriate, these recommended approaches and provide the public the opportunity in future rulemaking to evaluate and comment upon any alternatives we may propose.

We reviewed 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 recommend 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.

Therefore, we will only revise the methodology for computing a wage index for rural areas without hospital wage data by computing an average wage index from all contiguous CBSAs to represent a reasonable proxy for the rural area within a State (as discussed above). We may consider the commenters' recommended alternative wage index policies and methodology in the future.

Comment: We received a comment that supports the expiration of the hold-harmless policy implemented in FY 2006 for IRFs that were rural in FY 2005 and became urban based on the CBSAs. Specifically, the budget neutral hold harmless policy established in the FY 2006 final rule will expire for discharges occurring on or after October 1, 2007.

Response: As discussed above and in the FY 2006 IRF PPS final rule (70 FR 47880), the hold harmless policy was implemented in FY 2006 and, as recommended by the commenter, will expire for discharges occurring on or after October 1, 2007.

Final Decision: Although we solicited public comments on revising the wage index for rural areas without hospital wage data, we did not receive any comments regarding the use of an imputed wage index for rural areas without wage data within a State. Therefore, we proposed and will finalize in this rule the methodology for computing a wage index for rural areas without hospital wage data by computing an average wage index from all contiguous CBSAs to represent a reasonable proxy for the rural area within a State (as discussed above), as proposed in the FY 2008 proposed rule. In addition, the wage index tables for the IRF PPS in this and all subsequent IRF PPS rules and notices are considered to incorporate the CBSA changes published in the most recent OMB bulletin (see Web site at http://www.whitehouse.gov/​omb/​bulletins/​index.html) that applies to the hospital wage data used to determine the current IRF PPS wage index.

C. Description of the IRF Standard Payment Conversion Factor and Payment Rates for FY 2008

To calculate the standard payment conversion factor for FY 2008 and as illustrated in Table 3 below, we begin by applying the estimated market basket increase factor (3.2 percent) to the standard payment conversion factor for FY 2007 ($12,981), which equals $13,396. We then apply the combined budget neutrality factor for the wage index and labor related share and final year of the hold harmless policy of 1.0041 (1.0028 * 1.0013 = 1.0041), which would result in a standard payment conversion factor of $13,451.

Table 3.—Calculations To Determine the FY 2008 Standard Payment Conversion Factor

Explanation for adjustment	Calculations
FY 2007 Standard Payment Conversion Factor	12,981
FY 2008 Market Basket Increase Factor	× 1.032
Subtotal	= 13,396
Budget Neutrality Factor for the Wage Index, Labor-Related Share, and the Hold Harmless Provision	× 1.0041
FY 2008 Standard Payment Conversion Factor	= $13,451

After the application of the relative weights, the resulting unadjusted IRF prospective payment rates for FY 2008 are shown below in Table 4, “FY 2008 Payment Rates.”

Table 4.—FY 2008 Payment Rates

CMG	Payment rate tier 1	Payment rate tier 2	Payment rate tier 3	Payment rate no comorbidity
0101	$10,366.69	$9,823.27	$8,840.00	$8,537.35
0102	12,769.03	12,099.17	10,888.58	10,515.99
0103	15,054.36	14,264.79	12,837.63	12,399.13
0104	15,986.51	15,145.83	13,631.24	13,164.49
0105	19,182.47	18,174.99	16,357.76	15,798.20
0106	22,320.59	21,147.66	19,033.17	18,382.14
0107	25,758.67	24,406.84	21,965.48	21,213.57
0108	29,807.42	28,243.06	25,418.35	24,548.08
0109	29,589.51	28,035.92	25,231.39	24,367.83
0110	35,358.64	33,502.41	30,151.76	29,120.07
0201	10,953.15	9,154.75	8,178.21	7,595.78
0202	14,069.75	11,760.21	10,505.23	9,757.36
0203	16,817.79	14,056.30	12,556.51	11,663.36
0204	18,010.89	15,054.36	13,448.31	12,491.94
0205	22,075.78	18,452.08	16,482.86	15,309.93
0206	28,845.67	24,109.57	21,536.40	20,005.67
0207	37,210.85	31,101.40	27,783.04	25,805.74
0301	15,326.07	12,822.84	11,503.30	10,454.12
0302	20,008.36	16,741.11	15,016.70	13,648.73
0303	23,809.62	19,920.93	17,869.65	16,240.74
0304	32,813.71	27,453.49	24,627.44	22,382.46
0401	12,895.47	11,374.17	10,386.86	9,224.70
0402	17,830.65	15,725.56	14,360.29	12,754.24
0403	31,030.11	27,368.75	24,991.96	22,196.84
0404	55,878.14	49,283.12	45,004.36	39,972.34
0405	42,197.13	37,216.23	33,985.30	30,185.39
0501	10,287.32	8,682.62	7,649.58	6,821.00
0502	13,803.42	11,649.91	10,263.11	9,152.06
0503	18,287.98	15,436.37	13,597.62	12,124.73
0504	22,845.18	19,282.01	16,985.92	15,145.83
0505	27,132.01	22,900.33	20,172.46	17,988.02
0506	36,858.43	31,109.47	27,405.07	24,436.43
0601	12,093.79	9,859.58	9,441.26	8,772.74
0602	16,098.16	13,124.14	12,565.92	11,678.16
0603	20,615.00	16,807.02	16,094.12	14,954.82
0604	26,353.20	21,485.28	20,573.30	19,117.91
0701	12,143.56	10,380.14	9,870.34	8,900.53
0702	15,786.09	13,495.39	12,830.91	11,570.55
0703	19,677.47	16,821.82	15,993.24	14,422.16
0704	24,170.10	20,662.08	19,645.19	17,714.97
0801	8,792.92	7,403.43	6,901.71	6,196.88
0802	11,489.84	9,675.30	9,017.55	8,097.50
0803	17,092.19	14,392.57	13,416.03	12,046.72
0804	14,849.90	12,504.05	11,655.29	10,466.22
0805	18,733.21	15,773.99	14,703.29	13,203.50
0806	22,494.11	18,941.70	17,655.78	15,854.69
0901	11,332.47	10,277.91	9,238.15	8,232.01
0902	14,914.47	13,527.67	12,158.36	10,836.13
0903	19,689.57	17,858.89	16,052.42	14,305.14
0904	24,670.48	22,377.08	20,111.94	17,923.46
1001	12,946.59	11,943.14	10,702.96	9,901.28
1002	17,094.88	15,769.95	14,132.97	13,073.03
1003	24,045.01	22,182.04	19,879.23	18,388.86
1101	16,886.39	14,099.34	12,408.55	11,427.97
1102	25,320.16	21,140.94	18,605.42	17,135.23
1201	13,689.08	11,816.70	11,005.61	9,960.47
1202	17,712.28	15,289.75	14,239.23	12,887.40
1203	21,845.77	18,858.30	17,562.97	15,895.05
1301	13,927.17	12,961.38	11,448.15	9,992.75
1302	19,263.18	17,926.15	15,834.52	13,820.90
1303	24,548.08	22,845.18	20,179.19	17,612.74
1401	10,976.02	9,887.83	8,788.88	7,883.63
1402	14,847.21	13,375.67	11,889.34	10,663.95
1403	18,434.60	16,607.95	14,762.47	13,241.16
1404	23,364.39	21,049.47	18,710.34	16,782.81
1501	13,432.17	11,931.04	10,482.36	9,952.39
1502	17,030.31	15,126.99	13,289.59	12,618.38
1503	20,791.21	18,468.22	16,224.60	15,405.43
1504	27,192.54	24,153.96	21,218.95	20,148.25
1601	13,545.16	11,500.61	10,456.81	9,357.86
1602	18,597.35	15,790.13	14,356.25	12,848.40
1603	22,900.33	19,443.42	17,678.65	15,821.07
1701	13,206.19	12,968.11	11,405.10	9,910.70
1702	17,380.04	17,066.63	15,008.63	13,042.09
1703	20,655.36	20,284.11	17,838.72	15,500.93
1704	25,887.79	25,421.04	22,355.56	19,427.28
1801	16,033.59	13,270.76	11,087.66	9,875.72
1802	25,634.92	21,217.61	17,727.07	15,788.78
1803	46,139.62	38,188.73	31,907.12	28,417.93
1901	16,677.89	14,777.27	14,749.02	12,576.69
1902	31,198.25	27,644.50	27,590.69	23,527.14
1903	45,012.43	39,883.56	39,805.54	33,943.60
2001	11,748.10	9,928.18	9,059.25	8,183.59
2002	15,397.36	13,012.50	11,873.20	10,727.17
2003	19,876.54	16,797.61	15,327.41	13,846.46
2004	26,519.99	22,412.06	20,450.90	18,474.95
2101	29,379.67	29,379.67	22,336.73	19,620.97
5001	0.00	0.00	0.00	2,960.57
5101	0.00	0.00	0.00	8,542.73
5102	0.00	0.00	0.00	21,501.42
5103	0.00	0.00	0.00	9,688.76
5104	0.00	0.00	0.00	25,266.36

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

Table 5 illustrates the methodology for adjusting the Federal prospective payments (as described in sections VI.A through VI.C of this final rule). 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) can be found in Table 4 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 LIP adjustment of 1.0309), a wage index of 0.8538, 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 0.9118, 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 4 above. Then, we multiply the estimated labor-related share (75.818) described in section VI.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 will 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.

To adjust the Federal prospective payment by the facility-level adjustments, there are several steps. First, we take the wage-adjusted Federal prospective payment and multiply it by the appropriate rural and LIP adjustments (if applicable). Then, 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 rate. Table 5 illustrates the components of the adjusted payment calculation.

Table 5.—Example of Computing an IRF's FY 2008 Federal Prospective Payment

Steps		Rural Facility A (Spencer Co., IN)	Urban Facility B (Harrison Co., IN)
1	Unadjusted Federal Prospective Payment	$29,120.07	$29,120.07
2	Labor Share	× 0.75818	× 0.75818
3	Labor Portion of Federal Payment	= $22,078.25	= $22,078.25
4	CBSA Based Wage Index (shown in the Addendum, Tables 1 and 2)	× 0.8538	× 0.9118
5	Wage-Adjusted Amount	= $18,850.41	= $20,130.95
6	Non-labor Amount	+ $7,041.82	+ $7,041.82
7	Wage-Adjusted Federal Payment	= $25,892.23	= $27,172.77
8	Rural Adjustment	× 1.213	× 1.000
9	Wage- and Rural-Adjusted Federal Payment	= $31,407.27	= $27,172.77
10	LIP Adjustment	× 1.0309	× 1.0910
11	FY2007 Wage-, Rural- and LIP-Adjusted Federal Prospective Payment Rate	= $32,377.76	= $29,645.49
12	FY2007 Wage- and Rural-Adjusted Federal Prospective Payment	$31,407.27	$27,172.77
13	Teaching Status Adjustment	× 0.000	× 0.109
14	Teaching Status Adjustment Amount	= $0.00	= $2,961.83
15	FY2007 Wage-, Rural-, and LIP-Adjusted Federal Prospective Payment Rate	+ $32,377.76	+ $29,645.49
16	Total FY2007 Adjusted Federal Prospective Payment	= $32,377.76	= $32,607.32

Thus, the adjusted payment for Facility A would be $32,377.76 and the adjusted payment for Facility B would be $32,607.32.

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

A. Update to the Outlier Threshold Amount for FY 2008

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 cost-to-charge ratio (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 August 7, 2001 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 and 2007 IRF PPS final rules (70 FR 47880 and 71 FR 48354) to maintain estimated outlier payments at 3 percent of total estimated payments, and 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.

For this final rule, we performed an updated analysis of FY 2006 claims and IRF-PAI data using the same methodology that we used to set the initial outlier threshold amount when we first implemented the IRF PPS in the August 7, 2001 final rule (66 FR 41316), which is also the same methodology that we used to update the outlier threshold amounts for FYs 2006 and 2007. Using the updated FY 2006 claims and IRF-PAI data, we estimate that IRF outlier payments as a percentage of total estimated payments for FY 2007 increased from 3 percent using the FY 2004 data to approximately 3.7 percent using the updated FY 2006 data.

Based on the updated analysis using FY 2006 data, and consistent with the broad statutory authority conferred upon the Secretary in sections 1886(j)(4)(A)(i) and 1886(j)(4)(A)(ii) of the Act, we are updating the outlier threshold amount to $7,362 to decrease estimated outlier payments from approximately 3.7 to 3 percent of total estimated aggregate IRF payments for FY 2008.

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

In accordance with the methodology stated in the August 1, 2003 final rule (68 FR 45692 through 45694), we apply a ceiling to IRFs' cost-to-charge ratios (CCRs). Using the methodology described in that final rule, we are updating the national urban and rural CCRs for IRFs. 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 3 standard deviations above the corresponding national geometric mean, which is set at 1.56 for FY 2008.
• Other IRFs for whom accurate data with which to calculate an overall CCR are not available.

Specifically, for FY 2008, we estimate a national CCR of 0.596 for rural IRFs and 0.476 for urban IRFs. For new facilities, we use these national ratios until the data become available for us to compute the facility's actual CCR using the first tentative settled or final settled cost report data, which we will then use for the subsequent cost reporting period.

C. Adjustment of IRF Outlier Payments

In the August 1, 2003 final rule (68 FR 45674, 45693 through 45694), we finalized a proposal to make IRF outlier payments subject to reconciliation when IRFs' cost reports are settled, consistent with the policy adopted for IPPS hospitals in the June 9, 2003 IPPS final rule (68 FR 34494, 34501). The revised methodology provides for retroactive adjustments to IRF outlier payments to account for differences between the CCRs from the latest settled cost report and the actual CCRs computed at the time the cost report that coincides with the date of discharge is settled using the cost and charge data from that cost report. This revised methodology addresses vulnerabilities found in the IPPS and the IRF outlier payment policies, which may have resulted in outlier payments that were too high or too low. Along these lines, we are analyzing IRF outlier payments from the beginning of the IRF PPS through FY 2005, obtained from IRFs' cost report filings, to identify specific payment vulnerabilities in the IRF outlier payment policy.

Under this policy, which is outlined in § 412.624(e)(5), which in turn references § 412.84(i) and § 412.84(m) of the IPPS regulations, outlier payments will be processed on an interim basis throughout the year using IRFs' CCRs based on the best information available at the time. When an IRF's cost report is settled, any reconciliation of outlier payments by fiscal intermediaries will be based on the relationship between an IRF's costs and charges at the time a particular discharge actually occurred. This revised methodology ensures that the final outlier payments reflect an accurate assessment of the actual costs that the IRF incurred for treating the case.

We have not yet issued instructions to the fiscal intermediaries regarding IRF outlier reconciliation because we have been analyzing the data and assessing the systems changes necessary to conduct the reconciliation. Thus, we will soon issue instructions to fiscal intermediaries to begin reconciling IRF outlier payments upon settlement of IRF cost reports.

We received several comments on the proposed high-cost outliers under the IRF PPS, which are summarized below.

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

Response: In response to the comment, we considered adopting 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 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. However, with the recent phase in of the enforcement of the 75 percent rule criteria, we find evidence of relatively large changes in the case mix of patients in IRFs, especially in the years immediately following the reinstatement of enforcement of the 75 percent rule (FYs 2004 through 2006). In performing our analysis, we discovered that we could get inaccurate results if we based future projections of cost and charge growth on data from years in which IRFs were experiencing abnormal fluctuations in case mix. Rather than implementing an outlier threshold amount for FY 2008 based on these potentially inaccurate 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. Our analysis of the data suggests that it is likely better to wait until the 75 percent rule has been fully phased in, and the IRF case mix has stabilized, before we attempt to project cost and charge growth using a new methodology. Otherwise, the substantial changes occurring in the system all at the same time, including changes in IRFs' charges, costs, and case mix, could compromise the accuracy of our results. For the reasons described above, our analysis shows that using the same methodology we used previously for updating the outlier threshold amount for FY 2008 is the best approach at this time. However, we will carefully consider the commenter's suggestions as we investigate alternative approaches for projecting IRF cost and charge growth in estimating future updates to the IRF outlier threshold amount.

Comment: One commenter requested that we use updated FY 2006 data to estimate the IRF outlier threshold amount for FY 2008, because the FY 2006 data better reflect changes in the volume of IRF cases due to the 75 percent rule.

Response: We agree with the commenter and we have updated our analysis for this final rule based on FY 2006 data using the same methodology that was described in the August 7, 2001 final rule (66 FR 41316), which was the same methodology used to calculate the proposed outlier threshold for the FY 2008 proposed rule (72 FR 26250).

Comment: In the proposed rule, we indicated that we would investigate the reasons for our finding that estimated FY 2007 outlier payments increased from 3.0 to 3.8 percent of total estimated payments when we updated the claims data used in the calculations from FY 2004 to FY 2005. Two commenters requested that we report the findings of our analysis and our rationale for increasing the outlier threshold amount in this final rule.

Response: Our analysis of the increase in estimated FY 2007 outlier payments using the updated FY 2005 claims data (compared with the FY 2004 claims data) shows that the increase was caused primarily by increases in IRF charges and cost-to-charge ratios (CCRs) between FY 2004 and FY 2005. As discussed above in section VII.C of this final rule, we are continuing to examine these changes closely to assess whether they indicate the presence of specific payment vulnerabilities in the IRF outlier payment policy. This is ongoing research, but we have already discovered large variations in charges and CCRs among IRFs from year to year since the implementation of the IRF PPS that we believe may be indicative of specific payment vulnerabilities in the IRF PPS outlier payment policy.

For this final rule, we used updated FY 2006 IRF claims data to analyze IRF outliers. Similar to the findings from the FY 2005 data, the FY 2006 data show that estimated IRF outlier payments would equal 3.7 percent of total estimated payments in FY 2007. Thus, based on the analysis of both the FYs 2005 and 2006 data, we believe that continuing to use the same outlier threshold amount for FY 2008 that we implemented for FY 2007 would result in an overpayment of IRF outlier payments, above the 3 percent outlier pool that we established when we first implemented the IRF PPS. For this reason, we are finalizing our decision to update the IRF outlier threshold amount for FY 2008 to $7,362, based on analysis of FY 2006 data.

Comment: Two commenters supported the proposed change to the IRF outlier threshold amount for FY 2008 to maintain estimated outlier payments at 3 percent of total estimated payments. One commenter indicated that the outlier threshold amount may have been set too low in FYs 2006 and 2007, which they said may have meant that the standard payment conversion factor in these years was also too low.

Response: We agree with these commenters that it is important to adjust the outlier threshold amount to maintain estimated outlier payments at 3 percent of total estimated payments for FY 2008. However, our calculation of the outlier threshold amount for a given FY has no effect on the amount of the standard payment conversion factor for that FY. Therefore, we disagree that the standard payment conversion factor was too low in FYs 2006 and 2007.

Comment: One commenter 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. Specifically, the commenter asked that we provide information on IRF charges and CCRs, 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.

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. 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 2006 IRF claims data, merged with FY 2006 IRF-PAI data, to conduct patient-level payment simulations to estimate the outlier threshold amount for FY 2008. 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 commenter's request, we will carefully consider the usefulness and feasibility of including additional variables on the Medpar file in the future to facilitate IRF analyses.

Comment: One commenter recommended that CMS consider placing a 10 percent upper limit on the amount of an IRF's outlier payments (as a percentage of total payments) to encourage IRFs to strengthen their management of cases that might become high-cost outlier cases. In addition, the commenter requested that CMS incorporate any unused funds from the 3 percent IRF outlier pool back into the IRF base rate to increase payments for all IRF discharges.

Response: We appreciate the commenter's suggestion to place a cap on an IRF's outlier payments, and will consider this approach in the future as we work to eliminate potential vulnerabilities in the IRF outlier payment policy. However, at this time, we believe that a better approach to mitigating the vulnerabilities in the IRF outlier payment methodology is to increase the accuracy of the IRF outlier payments. As discussed previously in section VII.C of this final rule, we will soon be issuing instructions to fiscal intermediaries to begin reconciling the IRF CCRs upon settlement of the cost reports. We believe that using the actual CCR computed from an IRF's cost report at the time the cost report is settled, rather than an older CCR, to compute the outlier payments on the discharges that coincide with that cost report will improve the accuracy of the outlier payment calculations. We expect that much of the variation in outlier payments (as a percentage of total payments) among IRFs will be reduced by this approach, because it will limit IRFs' ability to increase their outlier payments by increasing their charges.

As discussed in the August 7, 2001 final rule (66 FR 41316, 41362 through 41363), we believe that setting estimated outlier payments equal to 3 percent of total estimated payments effectively balances the need to encourage IRFs to continue admitting potential high-cost outlier cases, while simultaneously ensuring that adequate funds are available to reimburse IRFs for treating the non-high-cost outlier cases. As we discussed in response to comments that we received on the FY 2006 IRF PPS rule and other PPS rules, we do not make adjustments to IRF PPS payment rates to account for differences between the 3 percent target and actual outlier payments. (See 70 FR 47936 for the IRF PPS response and a list of the FRs addressing this issue for other PPS systems.) If outlier payments for a given year are higher than 3 percent, we do not recoup money from IRFs. Similarly, if outlier payments in a given year are below 3 percent, we do not increase IRF PPS payments to account for this. We believe that this policy is consistent with the statute and with the goals of the prospective payment systems.

Comment: Two commenters supported CMS's plan to instruct fiscal intermediaries to begin reconciling IRF outlier payments, in certain instances, upon settlement of the IRF cost reports. However, both commenters recommended that CMS limit the administrative burden of these reviews by conducting reconciliation on only those IRF providers whose outlier payments and cost-to-charge ratio fluctuations exceed certain thresholds, similar to the process for IPPS hospitals. Specifically, one commenter recommended that CMS structure the IRF outlier reconciliation policy so that it is similar to the reconciliation policies for IPPS and long-term care hospitals. In addition, one commenter suggested that CMS limit our reconciliation efforts to discharges that occurred on or after October 1, 2003, the effective date of recent improvements to the methodology for determining IRF outlier payments.

Response: We agree with the commenters that we should conduct outlier reconciliation to address vulnerabilities in IRF outlier payments, and we also agree that we should apply the outlier reconciliation policies used in the IPPS and long-term care hospital settings as closely as possible. To this end, we have been working closely with the CMS components that develop the outlier reconciliation policies for these facilities. We also agree that focusing our outlier reconciliation efforts on those IRFs whose outlier payments and cost-to-charge ratio fluctuations exceed certain thresholds, similar to the process for IPPS hospitals, would limit the administrative burden of the reconciliation process. We are in the process now of determining the appropriate thresholds to apply in the IRF setting, and will carefully consider the commenters' recommendations in this regard. We will issue the final thresholds in our instructions to the fiscal intermediaries. We will also consider the commenter's suggestions in deciding which years to review for outlier reconciliation.

Final Decision: Based on a careful review of the comments that we received on the proposed update to the outlier threshold amount for FY 2008 and based on updated analysis of the FY 2006 data, we are finalizing our decision to update the outlier threshold amount for FY 2008 to $7,362. In addition, we did not receive any comments on the IRF cost-to-charge ratio ceilings and are finalizing the national average urban CCR at 0.476 and the national average rural CCR at 0.596. We are also finalizing our estimate of 3 standard deviations above the corresponding national geometric mean, at 1.56 for FY 2008.

VIII. Clarification to the Regulation Text for Special Payment Provisions for Patients That Are Transferred

Section 125(a)(3) of the BBRA amended section 1886(j)(1) of the Act by adding a paragraph (E) that states “Construction relating to transfer authority—Nothing in this subsection shall be construed as preventing the Secretary from providing for an adjustment to payments to take into account the early transfer of a patient from a rehabilitation facility to another site of care.” In the FY 2002 proposed and final IRF PPS rules, we proposed and adopted the transfer payment policy under § 412.624(f). The transfer policy provides payments that more accurately reflect facility resources used and services delivered for patients that transfer to another site of care as discussed in the FY 2002 IRF PPS final rule (66 FR 41316, 41353 through 41355). We are revising our regulations text to clarify our existing policy under § 412.624(f).

In the FY 2002 IRF PPS final rule (66 FR 41316, 41353 through 41355), we discuss our rationale, criteria for defining a transfer case, and the methodology to determine the unadjusted Federal prospective payment for the transfer case. In addition, we discuss several adjustments that we apply to the unadjusted Federal prospective payment rate. The final adjustments described in the FY 2002 IRF PPS final rule (65 FR 66304, 66347 through 66357) include the area wage adjustment, rural adjustment, the LIP adjustment, and the high-cost outlier adjustment. In our FY 2006 IRF PPS final rule (70 FR 47880), we refined the facility level adjustments and also adopted a teaching status adjustment.

We define a “transfer” under § 412.602 to mean the release of a Medicare inpatient from an IRF to another IRF, a short-term, acute-care prospective payment hospital, a long-term care hospital as described in § 412.23(e), or a nursing home that qualifies to receive Medicare or Medicaid payment. In order to receive a transfer payment under § 412.624(f), a patient must be transferred to another site of care as defined in § 412.602 and must have been admitted to the IRF for less than the average length of stay for the CMG. Table 1 in this final rule presents the CMGs, the comorbidity tiers, the corresponding relative weights, and the average length of stay value for each CMG and tier. We use the average length of stay for each CMG to determine when an IRF discharge meets the definition of a transfer, which results in a per diem case level adjustment.

Since the implementation of the IRF PPS, a claim meets the high-cost outlier policy under § 412.624(e)(5), as revised in the FY 2007 IRF PPS final rule (71 FR 48354, 48382 through 48383), if the estimated cost of the case exceeds the adjusted outlier threshold. For a case that qualifies, we make an outlier payment equal to 80 percent of the difference between the estimated cost of the case and the outlier threshold. Since the implementation of the IRF PPS, we have provided an additional high-cost outlier payment to both transfer cases and full CMG cases when applicable. We proposed to clarify the regulations text to articulate the transfer policy more clearly. Specifically, we proposed to add the phrase “subject to paragraph (e)(5)” at the end of the paragraph under § 412.624(f)(2)(v). We proposed to revise § 412.624(f)(2)(v) to read, “[B]y applying the adjustment described in paragraphs (e)(1), (e)(2), (e)(3), (e)(4), and (e)(7) of this section to the unadjusted payment amount determined in paragraph (f)(2)(iv) of this section to equal the adjusted transfer payment amount, subject to paragraph (e)(5).”

We received a couple comments on the proposed clarification to the regulation text for special payment provisions for patients that are transferred, which are summarized below.

Comment: We received a comment supporting the revisions to the clarification to the regulation text for special payment provisions for patients that are transferred described above. Another commenter requested additional clarification to better understand the intent of the revision to the regulation text.

Response: In the past, we have received questions from the public about whether an outlier payment applies to cases that are transferred to another site of care as defined in § 412.602. As discussed in detail above in this section, we have provided an additional high-cost outlier payment to both transfer cases and full CMG cases when applicable. We reviewed § 412.624(f) and believe that a minor revision to the regulation text would clarify the existing policy. As we emphasized in the proposed rule, the revision to the regulation text will not change our current methodology for determining whether a high-cost outlier payment applies to transfer cases. Based on the comment, we believe the regulations text should be revised to make more clear that we will apply a high-cost outlier payment to a transfer case based on the methodology set forth in § 412.624(e)(5), which we use to determine whether a high-cost outlier payment. Therefore, we will add the phrase to the end of § 412.624(f)(2)(v) to read, “and making an outlier payment in accordance with (e)(5), if applicable.”

Final Decision: We are finalizing our change to the regulations text at § 412.624(f)(2)(v) by revising the paragraph to read, “[B]y applying the adjustment described in paragraphs (e)(1), (e)(2), (e)(3), (e)(4), and (e)(7) of this section to the unadjusted payment amount determined in paragraph (f)(2)(iv) of this section to equal the adjusted transfer payment amount and making an outlier payment in accordance with (e)(5), if applicable.”

IX. Miscellaneous Comments

Comment: One commenter requested that CMS work to define more precisely the requirements for other post acute care providers, such as skilled nursing facilities and long-term care hospitals that also provide rehabilitation services.

Response: Because this comment concerns the establishment of regulations for other Medicare post-acute care settings, the comment is outside the scope of this final rule. However, in the IRF PPS final rule for FY 2007 (71 FR 48354), we described our plans to explore refinements to the existing provider-oriented “silos” to create a more seamless system for payment and delivery of post-acute care (PAC) under Medicare. We expect that this new model will be characterized by more consistent payments for the same type of care across different sites of service, quality driven pay-for-performance incentives, and collection of uniform clinical assessment information to support quality and discharge planning functions. In the IRF PPS final rule for FY 2007 (71 FR 48354), we described how section 5008 of the DRA provides for a demonstration on uniform assessment and data collection across different sites of service. We are developing a standard, comprehensive assessment instrument to be completed at hospital discharge for use in the demonstration, which we expect to begin in 2008. We expect that the demonstration will enable us to test the usefulness of this instrument, and analyze cost and outcomes across different PAC sites.

Comment: A few commenters recommended that CMS implement additional refinements to the IRF PPS using more recent data that reflect changes in IRF case mix and volume occurring in response to the 75 percent rule compliance criteria and medical necessity reviews. Specifically, one commenter recommended changes to the IRF facility-level adjustments, including suggested revisions to CMS's methodology for determining the amount of the adjustments. A few commenters also suggested that CMS work with the IRF industry and researchers to develop an analytical framework for analyzing future payment adjustments to account for coding changes that do not reflect real changes in IRFs' case mix.

Response: Since we did not propose any additional refinements to the IRF PPS for FY 2008, these comments are outside the scope of this final rule. However, we are currently analyzing the FY 2006 data to determine whether any future revisions to the IRF PPS, including revisions to the facility-level adjustments and coding adjustments, would be appropriate. In conducting our analyses, we will carefully consider the suggestions offered by the commenters and will explore any new analytical frameworks that may be useful for developing future refinements.

X. Provisions of the Final Regulations

In this final rule we are adopting the provisions as set forth in the May 8, 2007 proposed rule (72 FR 26230) except as noted elsewhere in the preamble with the following revisions:

• 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 VI.B.
• We will revise the wage index policy for rural areas without hospital wage data by imputing an average wage index from all contiguous CBSAs to represent a reasonable proxy for the rural area within a State, as discussed in section VI.B of this final rule.
• We are updating the FY 2008 IRF PPS payment rates by the market basket (3.2 percent), as discussed in section VI.A of this final rule.
• We are updating the FY 2008 IRF PPS payment rates by the labor-related share (75.818 percent), the wage indexes, and the final year of the hold harmless policy in a budget neutral manner, as discussed in sections VI of this final rule.
• We are updating the outlier threshold amount for FY 2008 to $7,362, as discussed in section VII.A in this final rule.
• We are updating the urban and rural national cost-to-charge ratio ceilings for purposes of determining outlier payments under the IRF PPS, as discussed in section VII.B in this final rule.
• We are maintaining the comorbidity policy specified in § 412.23(b)(2). Therefore, for cost reporting periods beginning on or after July 1, 2007, and before July 1, 2008, the compliance threshold remains 65 percent and we will continue to include comorbidities when calculating the compliance percentage. However, for cost reporting periods beginning on or after July 1, 2008, the compliance threshold will increase to 75 percent, but the comorbidities will not be used to determine if a provider met the 75 percent of the compliance threshold.
• We are revising the regulation text at § 412.624(f)(2)(v) to clarify that we determine whether a high-cost outlier payment would be applicable for transfer cases.

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 Analysis

A. Overall Impact

We have examined the impacts of this final rule as required by Executive Order 12866 (September 1993, Regulatory Planning and Review), the Regulatory Flexibility Act (RFA, September 16, 1980, Pub. L. 96-354), section 1102(b) of the Social Security Act, the Unfunded Mandates Reform Act of 1995 (Pub. L. 104-4), and Executive Order 13132.

Executive Order 12866 (as amended by Executive Order 13258, which merely reassigns responsibility of duties) directs agencies to assess all costs and benefits of available regulatory alternatives and, if regulation is necessary, to select regulatory approaches that maximize net benefits (including potential economic, environmental, public health and safety effects, distributive impacts, and equity). A regulatory impact analysis (RIA) must be prepared for major rules with economically significant effects ($100 million or more in any one year). This final rule is a major rule, as defined in Title 5, United States Code, section 804(2), because we estimate the impact to the Medicare program, and the annual effects to the overall economy, will be more than $100 million. We estimate that the total impact of these changes for estimated FY 2008 payments compared to estimated FY 2007 payments will be an increase of approximately $150 million (this reflects a $195 million increase from the update to the payment rates and a $45 million decrease due to the update to the outlier threshold amount to decrease estimated outlier payments from approximately 3.7 percent in FY 2007 to 3 percent in FY 2008).

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 government jurisdictions. Most IRFs and most other providers and suppliers are considered small entities, either by nonprofit status or by having revenues of $6 million to $29 million in any 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. As shown in Table 6, we estimate that the net revenue impact of this final rule on all IRFs is to increase estimated payments by about 2.4 percent, with an estimated increase in payments of 3 percent or higher for some categories of IRFs (such as urban IRFs in the Mountain region and rural IRFs in the Middle Atlantic and East South Central regions). Thus, we anticipate that this final rule may have a significant impact on a substantial number of small entities. However, the estimated impact of this final rule is a net increase in revenues across all categories of IRFs, so we believe that this final rule will not impose a significant burden on small entities. 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.

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. As discussed in detail below, the rates and policies set forth in this final rule will not have an adverse impact on rural hospitals based on the data of the 198 rural units and 20 rural hospitals in our database of 1,220 IRFs for which data were available.

Section 202 of the Unfunded Mandates Reform Act of 1995 (Pub. L. 104-4) also requires that agencies assess anticipated costs and benefits before issuing any rule whose mandates require spending in any one year of $100 million in 1995, updated annually for inflation. That threshold level is currently approximately $120 million. This final rule will not mandate any requirements for State, local, or tribal governments, nor will it affect private sector costs.

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

B. Anticipated Effects of the Final Rule

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

1. Basis and Methodology of Estimates

This final rule sets forth updates of the IRF PPS rates contained in the FY 2007 final rule, updates the outlier threshold for high-cost cases, and establishes an adjustment to the wage index methodology.

Based on the above, we estimate that the FY 2008 impact will be a net increase of $150 million in payments to IRF providers (this reflects a $195 million estimated increase from the update to the payment rates and a $45 million estimated decrease due to the update to the outlier threshold amount to decrease the estimated outlier payments from approximately 3.7 percent in FY 2007 to 3 percent in FY 2008). The impact analysis in Table 6 of this final rule represents the projected effects of the policy changes in the IRF PPS for FY 2008 compared with estimated IRF PPS payments in FY 2007 without the policy changes. We estimate the effects by estimating payments while holding all other payment variables constant. We use the best data available, but we do not attempt to predict behavioral responses to these changes, and we do not make adjustments for future changes in such variables as number of discharges or case-mix.

We note that certain events may combine to limit the scope or accuracy of our impact analysis, because such an analysis is future-oriented and, thus, susceptible to forecasting errors because of other changes in the forecasted impact time period. Some examples could be legislative changes made by the Congress to the Medicare program that will impact program funding, or changes specifically related to IRFs. In addition, changes to the Medicare program may continue to be made as a result of the BBA, the BBRA, the BIPA, the MMA, the DRA, or new statutory provisions. Although these changes may not be specific to the IRF PPS, the nature of the Medicare program is such that the changes may interact, and the complexity of the interaction of these changes could make it difficult to predict accurately the full scope of the impact upon IRFs.

In updating the rates for FY 2008, we are implementing a number of standard annual revisions and clarifications mentioned elsewhere in this final rule (for example, the update to the wage and market basket indexes used to adjust the Federal rates). We estimate that these revisions will increase payments to IRFs by approximately $195 million.

The aggregate change in estimated payments associated with this final rule is estimated to be an increase in payments to IRFs of $150 million for FY 2008. The market basket increase of $195 million and the $45 million decrease due to the update to the outlier threshold amount to decrease estimated outlier payments from approximately 3.7 percent in FY 2007 to 3.0 percent in FY 2008 will result in a net change in estimated payments from FY 2007 to FY 2008 of $150 million.

The effects of the changes that affect IRF PPS payment rates are shown in Table 6. The following changes that affect the IRF PPS payment rates are discussed separately below:

• The effects of the update to the outlier threshold amount to decrease total estimated outlier payments from approximately 3.7 to 3 percent of total estimated payments for FY 2008, consistent with section 1886(j)(4) of the Act.
• The effects of the annual market basket update (using the RPL market basket) to IRF PPS payment rates, as required by sections 1886(j)(3)(A)(i) and 1886(j)(3)(C) of the Act.
• The effects of applying the budget neutral labor-related share and wage index adjustment, including revisions to our methodology for determining a proxy for rural areas without hospital wage data (as described in section VI of this final rule), as required under section 1886(j)(6) of the Act.
• The effects of the final year of the 3-year budget neutral hold-harmless policy for IRFs that were rural under § 412.602 during FY 2005, but are urban under § 412.602 beginning in FY 2006 and lose the rural adjustment, resulting in a decrease in the estimated IRF PPS payments if not for the hold harmless policy.
• The total change in estimated payments based on the FY 2008 policies relative to estimated FY 2007 payments without the policies.

2. Description of Table 6

The table below categorizes IRFs by geographic location, including urban or rural location, and location with respect to CMS's nine census divisions (as defined on the cost report) of the country. In addition, the table divides IRFs into those that are separate rehabilitation hospitals (otherwise called freestanding hospitals in this section), those that are rehabilitation units of a hospital (otherwise called hospital units in this section), rural or urban facilities, ownership (otherwise called for-profit, non-profit, and government), and by teaching status. The top row of the table shows the overall impact on the 1,220 IRFs included in the analysis.

The next 12 rows of Table 6 contain IRFs categorized according to their geographic location, designation as either a freestanding hospital or a unit of a hospital, and by type of ownership; all urban, which is further divided into urban units of a hospital, urban freestanding hospitals, and by type of ownership; and all rural, which is further divided into rural units of a hospital, rural freestanding hospitals, and by type of ownership. There are 1,002 IRFs located in urban areas included in our analysis. Among these, there are 806 IRF units of hospitals located in urban areas and 196 freestanding IRF hospitals located in urban areas. There are 218 IRFs located in rural areas included in our analysis. Among these, there are 198 IRF units of hospitals located in rural areas and 20 freestanding IRF hospitals located in rural areas. There are 406 for-profit IRFs. Among these, there are 328 IRFs in urban areas and 78 IRFs in rural areas. There are 745 non-profit IRFs. Among these, there are 622 urban IRFs and 123 rural IRFs. There are 69 government-owned IRFs. Among these, there are 52 urban IRFs and 17 rural IRFs.

The remaining three parts of Table 6 show IRFs grouped by their geographic location within a region, and the last part groups IRFs by teaching status. First, IRFs located in urban areas are categorized with respect to their location within a particular one of the nine CMS geographic regions. Second, IRFs located in rural areas are categorized with respect to their location within a particular one of the nine CMS geographic regions. In some cases, especially for rural IRFs located in the New England, Mountain, and Pacific regions, the number of IRFs represented is small. Finally, IRFs are grouped by teaching status, including non-teaching IRFs, IRFs with an intern and resident to average daily census (ADC) ratio less than 10 percent, IRFs with an intern and resident to ADC ratio greater than or equal to 10 percent and less than or equal to 19 percent, and IRFs with an intern and resident to ADC ratio greater than 19 percent.

The estimated impact of each change to the facility categories listed above are shown in the columns of Table 6. The description of each column is as follows:

Column (1) shows the facility classification categories described above.

Column (2) shows the number of IRFs in each category in our FY 2006 analysis file.

Column (3) shows the number of cases in each category in our FY 2006 analysis file.

Column (4) shows the estimated effect of the adjustment to the outlier threshold amount so that estimated outlier payments decrease from approximately 3.7 percent in FY 2007 to 3 percent of total estimated payments for FY 2008.

Column (5) shows the estimated effect of the market basket update to the IRF PPS payment rates.

Column (6) shows the estimated effect of the update to the IRF labor-related share, wage index, and the final year of the hold harmless policy, in a budget neutral manner.

Column (7) compares our estimates of the payments per discharge, incorporating all of the changes reflected in this final rule for FY 2008, to our estimates of payments per discharge in FY 2007 (without these changes).

The average estimated increase for all IRFs is approximately 2.4 percent. This estimated increase includes the effects of the 3.2 percent market basket update. It also includes the 0.7 percent overall estimated decrease in estimated IRF outlier payments from the update to the outlier threshold amount. Because we are making the remainder of the changes outlined in this final rule in a budget neutral manner, they will not affect total estimated IRF payments in the aggregate. However, as described in more detail in each section, they will affect the estimated distribution of payments among providers.

Table 6.—Projected Impact on the IRF PPS for FY 2008

Facility classification (1)	Number of IRFs in FY 2006 (2)	Number of cases in FY 2006 (3)	Outlier (4) (percent)	Market basket (5) (percent)	FY08 CBSA wage index, labor-related share, and hold harmless (6) (percent)	Total change (7) (percent)
Total	1,220	404,331	−0.7	3.2	0	2.4
Urban unit	806	225,170	−1.0	3.2	0.2	2.4
Rural unit	198	35,612	−0.8	3.2	0.2	2.7
Urban hospital	196	137,865	−0.4	3.2	−0.3	2.5
Rural hospital	20	5,684	−0.4	3.2	0.1	2.9
Urban For-Profit	328	137,349	−0.6	3.2	−0.2	2.4
Rural For-Profit	78	14,824	−0.6	3.2	0.1	2.7
Urban Non-Profit	622	210,708	−0.8	3.2	0.1	2.5
Rural Non-Profit	123	23,686	−0.7	3.2	0.3	2.7
Urban Government	52	14,978	−0.9	3.2	−0.2	2.0
Rural Government	17	2,786	−1.2	3.2	0.3	2.3
Urban	1,002	363,035	−0.7	3.2	0.0	2.4
Rural	218	41,296	−0.7	3.2	0.2	2.7
Urban by region:
Urban New England	32	15,634	−0.7	3.2	−0.4	2.0
Urban Middle Atlantic	155	63,821	−0.5	3.2	0.1	2.8
Urban South Atlantic	134	61,794	−0.7	3.2	−0.6	1.8
Urban East North Central	195	62,561	−0.9	3.2	0.6	2.8
Urban East South Central	53	26,084	−0.5	3.2	−0.8	1.9
Urban West North Central	72	19,076	−0.9	3.2	0.2	2.4
Urban West South Central	180	64,823	−0.7	3.2	−0.4	2.1
Urban Mountain	75	22,942	−0.9	3.2	0.7	3.0
Urban Pacific	106	26,300	−1.0	3.2	0.5	2.6
Rural by region:
Rural New England	5	1,078	−1.4	3.2	−0.8	1.0
Rural Middle Atlantic	19	3,706	−0.4	3.2	0.7	3.4
Rural South Atlantic	26	6,175	−0.5	3.2	−0.1	2.6
Rural East North Central	36	6,804	−0.7	3.2	0.3	2.7
Rural East South Central	22	4,357	−0.6	3.2	0.5	3.1
Rural West North Central	37	6,334	−1.0	3.2	0.5	2.7
Rural West South Central	58	11,392	−0.6	3.2	0.1	2.7
Rural Mountain	9	946	−1.8	3.2	−0.2	1.1
Rural Pacific	6	504	−1.2	3.2	0.3	2.3
Teaching Status:
Non-teaching	1,103	352,896	−0.8	3.2	0.0	2.4
Resident to ADC less than 10%	59	32,718	−0.6	3.2	0.1	2.9
Resident to ADC 10%-19%	41	15,597	−0.6	3.2	0.1	2.7
Resident to ADC greater than 19%	17	3,120	−0.7	3.2	0.1	2.8

3. Impact of the Update to the Outlier Threshold Amount (Column 4, Table 6)

In the FY 2007 IRF PPS final rule (71 FR 48354), we used FY 2004 patient-level claims data (the best, most complete data available at that time) to set the outlier threshold amount for FY 2007 so that estimated outlier payments would equal 3 percent of total estimated payments for FY 2007. For this final rule, we are updating our analysis using FY 2006 data. Using the updated FY 2006 data, we now estimate that IRF outlier payments as a percentage of total estimated payments for FY 2007 increased from 3 percent using the FY 2004 data to approximately 3.7 percent using the updated FY 2006 data. Thus, we are adjusting the outlier threshold amount for FY 2008 to $7,362 to set total estimated outlier payments equal to 3 percent of total estimated payments in FY 2008. The estimated change in total payments between FY 2007 and FY 2008, therefore, includes a 0.7 percent overall estimated decrease in payments because the estimated outlier portion of total payments is estimated to decrease from approximately 3.7 percent to 3 percent.

The impact of this update (as shown in column 4 of Table 6) is to decrease estimated overall payments to IRFs by 0.7 percent. We do not estimate that any group of IRFs would experience an increase in payments from this update. We estimate the largest decrease in payments to be a 1.8 percent decrease in estimated payments to rural IRFs in the Mountain region.

4. Impact of the Market Basket Update to the IRF PPS Payment Rates (Column 5, Table 6)

In column 5 of Table 6, we present the estimated effects of the market basket update to the IRF PPS payment rates. In the aggregate, and across all hospital groups, the update will result in a 3.2 percent increase in overall estimated payments to IRFs.

5. Impact of the CBSA Wage Index, Labor-Related Share, and the Hold Harmless Policy for FY 2008 (Column 6, Table 6)

In column 6 of Table 6, we present the effects of the budget neutral update of the wage index, labor-related share, and the final year of the hold harmless policy. In FY 2006, we provided a 1-year blended wage index and a 3-year phase out of the rural adjustment for IRFs that changed designation because of the change from MSAs to CBSAs (referenced as the hold harmless policy). We applied the blended wage index to all IRFs and the hold harmless policy to those IRFs that qualify, as described in § 412.624(e)(7), in order to mitigate the impact of the change from the MSA-based labor area definitions to the CBSA-based labor area definitions for IRFs.

As discussed in the FY 2007 IRF PPS final rule (71 FR 48345), the blended wage index expired in FY 2007 and will not be applied for discharges occurring on or after October 1, 2006. In addition, FY 2008 is the third and final year of the hold harmless policy, and we are continuing to apply this policy as described in the FY 2006 final rule in a budget neutral manner.

As discussed in this final rule, we are revising our methodology to impute a rural wage index value for rural areas without hospital wage data and update the wage index based on the CBSA-based labor market area definitions in a budget neutral manner. We are also applying the third and final year of the hold harmless policy in a budget neutral manner. Thus, in the aggregate, the estimated impact of the update to the wage index and labor-related share is zero percent.

In the aggregate and for all urban IRFs, we do not estimate that these changes will affect overall estimated payments to IRFs. However, we estimate that these changes will have small distributional effects. We estimate a 0.2 percent increase in estimated payments to rural IRFs. We estimate the largest increase in payments to be a 0.7 percent increase for urban IRFs in the Mountain region and for rural IRFs in the Middle Atlantic region. We estimate the largest decrease in payments to be a 0.8 percent decrease for urban IRFs in the East South Central region and for rural IRFs in the New England region.

C. Anticipated Effects of the 75 Percent Rule Policy

The existing policy for classifying a facility as an IRF, on the basis of its meeting the compliance threshold, which is described in § 412.23(b)(2), allows the inclusion of comorbidities meeting certain requirements in the calculations used to determine the compliance percentage for cost reporting periods beginning on or after July 1, 2004, and before July 1, 2008. However, for cost reporting periods beginning on or after July 1, 2008, the existing regulations indicate that comorbidities will not be eligible for inclusion in the calculations used to determine whether the provider meets the 75 percent compliance threshold. As discussed in section IV of this final rule, we are not changing the existing policy. On or after July 1, 2008, we anticipate that IRFs will make adjustments to their admission and coding practices to continue to meet the compliance threshold. Data limitations and two important sources of uncertainty prevent a precise estimate of the effect of this policy at this time. One source of uncertainty is what proportion of patients who would no longer be treated in IRFs would instead be treated by other, lower-cost post-acute care settings such as skilled nursing facilities or home health agencies. Another source of uncertainty is determining how providers will make adjustments on or after July 1, 2008. While we cannot make a precise estimate at this time, we anticipate modest decreases in Medicare payments beginning on or after July 1, 2008.

D. Alternatives Considered

Because we have determined that this final rule will have a significant economic impact on IRFs and on a substantial number of small entities, we will discuss alternative changes to the IRF PPS that we considered.

Section 1886(j)(3)(C) of the Act requires the Secretary to update the IRF PPS payment rates by 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. As discussed above, we estimate the RPL market basket increase factor for FY 2008 to be 3.2 percent. This increase factor represents the majority of the impact on IRF providers shown in Table 6. Thus, we believe this estimated net increase in payments across all categories of IRFs represents a benefit to IRF providers and, thus, to IRFs that are small entities.

We considered maintaining the existing outlier threshold amount for FY 2008 because updating the outlier threshold amount has an estimated negative impact on IRF providers and, therefore, on small entities. If we were to maintain the FY 2007 outlier threshold amount, more outlier cases would have qualified for the additional outlier payments in FY 2008. However, analysis of updated FY 2006 data indicates that estimated outlier payments would not equal 3 percent of total estimated payments for FY 2008 unless we updated the outlier threshold amount. Also, we estimate that the overall effect of this policy on estimated payments to IRFs is small (less than 1 percent).

We considered two other options regarding the use of comorbidities in determining compliance with the 75 percent rule, in addition to the one that we are finalizing to maintain the existing policy regarding use of the comorbidities. First, we considered retaining the use of the comorbidities for one additional year, for cost reporting periods beginning before July 1, 2009. We considered this option in order to extend the phase in of the 75 percent rule for one additional year and to separate the increase in the compliance percentage (to 75 percent) from the expiration of the use of comorbidities. However, providers have already had 4 years to adjust their case-mixes and adapt their operations in order to comply with the 75 percent rule.

The second alternative option that we considered was to continue the use of the comorbidities in determining compliance with the 75 percent rule on a permanent basis. However, we believe that, in the absence of sound clinical data, it would be premature to convert a temporary transition policy into a permanent part of the compliance requirements. Thus, we believe that continuing the existing policy, which expires the use of comorbidities in determining compliance with the 75 percent rule for cost reporting periods beginning on or after July 1, 2008, is the best approach.

E. Accounting Statement

As required by OMB Circular A-4 (available at http://www.whitehouse.gov/​omb/​circulars/​a004/​a-4.pdf), in Table 7 below, we have prepared an accounting statement showing the classification of the expenditures associated with the provisions of this final rule. This table provides our best estimate of the increase in Medicare payments under the IRF PPS as a result of the changes presented in this final rule based on the data for 1,220 IRFs in our database. All estimated expenditures are classified as transfers to Medicare providers (that is, IRFs).

Table 7.—Accounting Statement: Classification of Estimated Expenditures, from the 2007 IRF PPS Rate Year to the 2008 IRF PPS Rate Year

[In millions]

Category	Transfers
Annualized Monetized Transfers	$150 million.
From Whom To Whom?	Federal Government to IRF Medicare Providers.

F. Conclusion (Column 7, Table 6)

Overall, the estimated payments per discharge for IRFs in FY 2008 are projected to increase by 2.4 percent, compared with those in FY 2007, as reflected in column 7 of Table 6. We estimate that IRFs in urban areas will experience a 2.4 percent increase in estimated payments per discharge compared with FY 2007. We estimate that IRFs in rural areas will experience a 2.7 percent increase in estimated payments per discharge compared with FY 2007. We estimate that rehabilitation units in urban areas will experience a 2.4 percent increase in estimated payments per discharge and that freestanding rehabilitation hospitals in urban areas will experience a 2.5 percent increase in estimated payments per discharge. We estimate that rehabilitation units in rural areas will experience a 2.7 percent increase in estimated payments per discharge, while freestanding rehabilitation hospitals in rural areas will experience a 2.9 percent increase in estimated payments per discharge.

Overall, we estimate that the largest payment increase will be 3.4 percent among rural IRFs in the Middle Atlantic region. We do not estimate that any group of IRFs will experience an overall decrease in payments from the changes in this final rule.

Comment: One commenter expressed concerns about the total number of IRFs (Column 2, Table 6) and the total number of IRF discharges (Column 3, Table 6) reflected in table 6 of the proposed rule. The commenter noted that a recent report released by CMS on June 8, 2007 projected an estimated number of IRF discharges of approximately 412,000 in 2006, whereas table 6 of the proposed rule shows 427,419 IRF discharges in the FY 2005 claims data. The commenter questioned why CMS based its impact analysis on the higher number of discharges rather than the more recent, lower number.

Response: For the proposed rule, we analyzed the most current and complete IRF claims data available at that time, FY 2005, to estimate the impact of the proposed policies. The FY 2005 claims data show that there were 427,419 Medicare discharges from IRFs in that year. However, we have updated our analysis for this final rule using FY 2006 IRF claims data. This data show that there were 404,331 Medicare discharges from IRFs in FY 2006. Note that both of these numbers were calculated on a FY basis, whereas the 412,000 Medicare discharges reported in the June 8, 2007 report were estimated on a calendar year basis.

As discussed above, we use the best data available in estimating the impact of the policies contained in this final rule, but we do not attempt to predict behavioral responses to these changes and we do not make adjustments for future changes in such variables as number of discharges or case-mix. Thus, the number of Medicare discharges reflected in table 6 represents the actual number of discharges for which we have IRF claims in the FY 2006 data, and we have not attempted to predict how many discharges would be expected to occur in FY 2008.

We are confident that the impact analysis, based on FY 2006 data, provides our best estimate of the payment impact of the policies contained in this final rule.

Comment: One commenter requested that CMS provide additional information, including detailed payment information, to allow interested parties to recreate CMS's impact table, make projections on a facility-level basis, and review the proposed policies in more detail.

Response: We will carefully consider the commenter's suggestions in updating the IRF PPS rate setting files that we post 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. Some of the payment information that the commenter requested is already contained in these files, and we will consider the possibility of adding additional information to the file.

We believe the public should have as much information as possible to be able to review our proposed policies and evaluate the impacts of these policies. However, to recreate the detailed payment simulations used in preparing the impact analysis, the public would need detailed patient-level data, such as claims and IRF-PAI data. Some of these data files are available to the public through CMS's standard data distribution systems. More information on CMS's data distribution policies is available on CMS's Web site at http://www.cms.hhs.gov/​researchers/​statsdata.asp.

We will continue to work with researchers and with industry groups to determine the best ways of providing data that will be useful in reviewing and analyzing our IRF PPS payment policies.

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

Subpart P—Prospective Payment for Inpatient Rehabilitation Hospitals and Rehabilitation Units

2. Section 412.624 is amended by revising paragraph (f)(2)(v) to read as follows:

§ 412.624

Methodology for calculating the Federal prospective payment rates.

* * * * *

(f) * * *

(2) * * *

(v) By applying the adjustment described in paragraphs (e)(1), (e)(2), (e)(3), (e)(4), and (e)(7) of this section to the unadjusted payment amount determined in paragraph (f)(2)(iv) of this section to equal the adjusted transfer payment amount and making a payment in accordance with paragraph (e)(5) of this section, if applicable.

(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, 2007.

Leslie V. Norwalk,

Acting Administrator, Centers for Medicare & Medicaid Services.

Approved: July 24, 2007.

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, 2007 Through September 30, 2008

Table 2.—Inpatient Rehabilitation Facility Wage Index for Rural Areas for Discharges Occurring From October 1, 2007 Through September 30, 2008

Table 1.—Inpatient Rehabilitation Facility Wage Index for Urban Areas for Discharges Occurring From October 1, 2007 Through September 30, 2008

CBSA code	Urban area (constituent counties)	Wage index
10180	Abilene, TX	0.8000
	Callahan County, TX
	Jones County, TX
	Taylor County, TX
10380	Aguadilla-Isabela-San Sebastián, PR	0.3915
	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	0.8654
	Portage County, OH
	Summit County, OH
10500	Albany, GA	0.8991
	Baker County, GA
	Dougherty County, GA
	Lee County, GA
	Terrell County, GA
	Worth County, GA
10580	Albany-Schenectady-Troy, NY	0.8720
	Albany County, NY
	Rensselaer County, NY
	Saratoga County, NY
	Schenectady County, NY
	Schoharie County, NY
10740	Albuquerque, NM	0.9458
	Bernalillo County, NM
	Sandoval County, NM
	Torrance County, NM
	Valencia County, NM
10780	Alexandria, LA	0.8006
	Grant Parish, LA
	Rapides Parish, LA
10900	Allentown-Bethlehem-Easton, PA-NJ	0.9947
	Warren County, NJ
	Carbon County, PA
	Lehigh County, PA
	Northampton County, PA
11020	Altoona, PA	0.8812
	Blair County, PA
11100	Amarillo, TX	0.9169
	Armstrong County, TX
	Carson County, TX
	Potter County, TX
	Randall County, TX
11180	Ames, IA	0.9760
	Story County, IA
11260	Anchorage, AK	1.2023
	Anchorage Municipality, AK
	Matanuska-Susitna Borough, AK
11300	Anderson, IN	0.8681
	Madison County, IN
11340	Anderson, SC	0.9017
	Anderson County, SC
11460	Ann Arbor, MI	1.0826
	Washtenaw County, MI
11500	Anniston-Oxford, AL	0.7770
	Calhoun County, AL
11540	Appleton, WI	0.9455
	Calumet County, WI
	Outagamie County, WI
11700	Asheville, NC	0.9216
	Buncombe County, NC
	Haywood County, NC
	Henderson County, NC
	Madison County, NC
12020	Athens-Clarke County, GA	0.9856
	Clarke County, GA
	Madison County, GA
	Oconee County, GA
	Oglethorpe County, GA
12060	Atlanta-Sandy Springs-Marietta, GA	0.9762
	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	1.1831
	Atlantic County, NJ
12220	Auburn-Opelika, AL	0.8096
	Lee County, AL
12260	Augusta-Richmond County, GA-SC	0.9667
	Burke County, GA
	Columbia County, GA
	McDuffie County, GA
	Richmond County, GA
	Aiken County, SC
	Edgefield County, SC
12420	Austin-Round Rock, TX	0.9344
	Bastrop County, TX
	Caldwell County, TX
	Hays County, TX
	Travis County, TX
	Williamson County, TX
12540	Bakersfield, CA	1.0725
	Kern County, CA
12580	Baltimore-Towson, MD	1.0088
	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	0.9711
	Penobscot County, ME
12700	Barnstable Town, MA	1.2539
	Barnstable County, MA
12940	Baton Rouge, LA	0.8084
	Ascension Parish, LA
	East Baton Rouge Parish, LA
	East Feliciana Parish, LA
	Iberville Parish, LA
	Livingston Parish, LA
	Pointe Coupee Parish, LA
	St. Helena Parish, LA
	West Baton Rouge Parish, LA
	West Feliciana Parish, LA
12980	Battle Creek, MI	0.9762
	Calhoun County, MI
13020	Bay City, MI	0.9251
	Bay County, MI
13140	Beaumont-Port Arthur, TX	0.8595
	Hardin County, TX
	Jefferson County, TX
	Orange County, TX
13380	Bellingham, WA	1.1104
	Whatcom County, WA
13460	Bend, OR	1.0743
	Deschutes County, OR
13644	Bethesda-Frederick-Gaithersburg, MD	1.0903
	Frederick County, MD
	Montgomery County, MD
13740	Billings, MT	0.8712
	Carbon County, MT
	Yellowstone County, MT
13780	Binghamton, NY	0.8786
	Broome County, NY
	Tioga County, NY
13820	Birmingham-Hoover, AL	0.8894
	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	0.7240
	Burleigh County, ND
	Morton County, ND
13980	Blacksburg-Christiansburg-Radford, VA	0.8213
	Giles County, VA
	Montgomery County, VA
	Pulaski County, VA
	Radford City, VA
14020	Bloomington, IN	0.8533
	Greene County, IN
	Monroe County, IN
	Owen County, IN
14060	Bloomington-Normal, IL	0.8944
	McLean County, IL
14260	Boise City-Nampa, ID	0.9401
	Ada County, ID
	Boise County, ID
	Canyon County, ID
	Gem County, ID
	Owyhee County, ID
14484	Boston-Quincy, MA	1.1679
	Norfolk County, MA
	Plymouth County, MA
	Suffolk County, MA
14500	Boulder, CO	1.0350
	Boulder County, CO
14540	Bowling Green, KY	0.8148
	Edmonson County, KY
	Warren County, KY
14740	Bremerton-Silverdale, WA	1.0913
	Kitsap County, WA
14860	Fairfield County, CT	1.2659
	Bridgeport-Stamford-Norwalk, CT
15180	Brownsville-Harlingen, TX	0.9430
	Cameron County, TX
15260	Brunswick, GA	1.0164
	Brantley County, GA
	Glynn County, GA
	McIntosh County, GA
15380	Buffalo-Niagara Falls, NY	0.9424
	Erie County, NY
	Niagara County, NY
15500	Burlington, NC	0.8674
	Alamance County, NC
15540	Burlington-South Burlington, VT	0.9474
	Chittenden County, VT
	Franklin County, VT
	Grand Isle County, VT
15764	Cambridge-Newton-Framingham, MA	1.0970
	Middlesex County, MA
15804	Camden, NJ	1.0392
	Burlington County, NJ
	Camden County, NJ
	Gloucester County, NJ
15940	Canton-Massillon, OH	0.9031
	Carroll County, OH
	Stark County, OH
15980	Cape Coral-Fort Myers, FL	0.9342
	Lee County, FL
16180	Carson City, NV	1.0025
	Carson City, NV
16220	Casper, WY	0.9145
	Natrona County, WY
16300	Cedar Rapids, IA	0.8888
	Benton County, IA
	Jones County, IA
	Linn County, IA
16580	Champaign-Urbana, IL	0.9644
	Champaign County, IL
	Ford County, IL
	Piatt County, IL
16620	Charleston, WV	0.8542
	Boone County, WV
	Clay County, WV
	Kanawha County, WV
	Lincoln County, WV
	Putnam County, WV
16700	Charleston-North Charleston, SC	0.9145
	Berkeley County, SC
	Charleston County, SC
	Dorchester County, SC
16740	Charlotte-Gastonia-Concord, NC-SC	0.9554
	Anson County, NC
	Cabarrus County, NC
	Gaston County, NC
	Mecklenburg County, NC
	Union County, NC
	York County, SC
16820	Charlottesville, VA	1.0125
	Albemarle County, VA
	Fluvanna County, VA
	Greene County, VA
	Nelson County, VA
	Charlottesville City, VA
16860	Chattanooga, TN-GA	0.8948
	Catoosa County, GA
	Dade County, GA
	Walker County, GA
	Hamilton County, TN
	Marion County, TN
	Sequatchie County, TN
16940	Cheyenne, WY	0.9060
	Laramie County, WY
16974	Chicago-Naperville-Joliet, IL	1.0751
	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	1.1053
	Butte County, CA
17140	Cincinnati-Middletown, OH-KY-IN	0.9601
	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	0.8436
	Christian County, KY
	Trigg County, KY
	Montgomery County, TN
	Stewart County, TN
17420	Cleveland, TN	0.8109
	Bradley County, TN
	Polk County, TN
17460	Cleveland-Elyria-Mentor, OH	0.9400
	Cuyahoga County, OH
	Geauga County, OH
	Lake County, OH
	Lorain County, OH
	Medina County, OH
17660	Coeur d'Alene, ID	0.9344
	Kootenai County, ID
17780	College Station-Bryan, TX	0.9045
	Brazos County, TX
	Burleson County, TX
	Robertson County, TX
17820	Colorado Springs, CO	0.9701
	El Paso County, CO
	Teller County, CO
17860	Columbia, MO	0.8542
	Boone County, MO
	Howard County, MO
17900	Columbia, SC	0.8933
	Calhoun County, SC
	Fairfield County, SC
	Kershaw County, SC
	Lexington County, SC
	Richland County, SC
	Saluda County, SC
17980	Columbus, GA-AL	0.8239
	Russell County, AL
	Chattahoochee County, GA
	Harris County, GA
	Marion County, GA
	Muscogee County, GA
18020	Columbus, IN	0.9318
	Bartholomew County, IN
18140	Columbus, OH	1.0107
	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	0.8564
	Aransas County, TX
	Nueces County, TX
	San Patricio County, TX
18700	Corvallis, OR	1.1546
	Benton County, OR
19060	Cumberland, MD-WV	0.8446
	Allegany County, MD
	Mineral County, WV
19124	Dallas-Plano-Irving, TX	1.0075
	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	0.9093
	Murray County, GA
	Whitfield County, GA
19180	Danville, IL	0.9266
	Vermilion County, IL
19260	Danville, VA	0.8451
	Pittsylvania County, VA
	Danville City, VA
19340	Davenport-Moline-Rock Island, IA-IL	0.8846
	Henry County, IL
	Mercer County, IL
	Rock Island County, IL
	Scott County, IA
19380	Dayton, OH	0.9037
	Greene County, OH
	Miami County, OH
	Montgomery County, OH
	Preble County, OH
19460	Decatur, AL	0.8159
	Lawrence County, AL
	Morgan County, AL
19500	Decatur, IL	0.8172
	Macon County, IL
19660	Deltona-Daytona Beach-Ormond Beach, FL	0.9263
	Volusia County, FL
19740	Denver-Aurora, CO	1.0930
	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	0.9214
	Dallas County, IA
	Guthrie County, IA
	Madison County, IA
	Polk County, IA
	Warren County, IA
19804	Detroit-Livonia-Dearborn, MI	1.0281
	Wayne County, MI
20020	Dothan, AL	0.7381
	Geneva County, AL
	Henry County, AL
	Houston County, AL
20100	Dover, DE	0.9847
	Kent County, DE
20220	Dubuque, IA	0.9133
	Dubuque County, IA
20260	Duluth, MN-WI	1.0042
	Carlton County, MN
	St. Louis County, MN
	Douglas County, WI
20500	Durham, NC	0.9826
	Chatham County, NC
	Durham County, NC
	Orange County, NC
	Person County, NC
20740	Eau Claire, WI	0.9630
	Chippewa County, WI
	Eau Claire County, WI
20764	Edison, NJ	1.1190
	Middlesex County, NJ
	Monmouth County, NJ
	Ocean County, NJ
	Somerset County, NJ
20940	El Centro, CA	0.9076
	Imperial County, CA
21060	Elizabethtown, KY	0.8697
	Hardin County, KY
	Larue County, KY
21140	Elkhart-Goshen, IN	0.9426
	Elkhart County, IN
21300	Elmira, NY	0.8240
	Chemung County, NY
21340	El Paso, TX	0.9053
	El Paso County, TX
21500	Erie, PA	0.8827
	Erie County, PA
21604	Essex County, MA	1.0418
	Essex County, MA
21660	Eugene-Springfield, OR	1.0876
	Lane County, OR
21780	Evansville, IN-KY	0.9071
	Gibson County, IN
	Posey County, IN
	Vanderburgh County, IN
	Warrick County, IN
	Henderson County, KY
	Webster County, KY
21820	Fairbanks, AK	1.1059
	Fairbanks North Star Borough, AK
21940	Fajardo, PR	0.4036
	Ceiba Municipio, PR
	Fajardo Municipio, PR
	Luquillo Municipio, PR
22020	Fargo, ND-MN	0.8250
	Cass County, ND
	Clay County, MN
22140	Farmington, NM	0.8589
	San Juan County, NM
22180	Fayetteville, NC	0.8945
	Cumberland County, NC
	Hoke County, NC
22220	Fayetteville-Springdale-Rogers, AR-MO	0.8865
	Benton County, AR
	Madison County, AR
	Washington County, AR
	McDonald County, MO
22380	Flagstaff, AZ	1.1601
	Coconino County, AZ
22420	Flint, MI	1.0969
	Genesee County, MI
22500	Florence, SC	0.8388
	Darlington County, SC
	Florence County, SC
22520	Florence-Muscle Shoals, AL	0.7843
	Colbert County, AL
	Lauderdale County, AL
22540	Fond du Lac, WI	1.0063
	Fond du Lac County, WI
22660	Fort Collins-Loveland, CO	0.9544
	Larimer County, CO
22744	Fort Lauderdale-Pompano Beach-Deerfield Beach, FL	1.0133
	Broward County, FL
22900	Fort Smith, AR-OK	0.7731
	Crawford County, AR
	Franklin County, AR
	Sebastian County, AR
	Le Flore County, OK
	Sequoyah County, OK
23020	Fort Walton Beach-Crestview-Destin, FL	0.8643
	Okaloosa County, FL
23060	Fort Wayne, IN	0.9517
	Allen County, IN
	Wells County, IN
	Whitley County, IN
23104	Fort Worth-Arlington, TX	0.9569
	Johnson County, TX
	Parker County, TX
	Tarrant County, TX
	Wise County, TX
23420	Fresno, CA	1.0943
	Fresno County, CA
23460	Gadsden, AL	0.8066
	Etowah County, AL
23540	Gainesville, FL	0.9277
	Alachua County, FL
	Gilchrist County, FL
23580	Gainesville, GA	0.8958
	Hall County, GA
23844	Gary, IN	0.9334
	Jasper County, IN
	Lake County, IN
	Newton County, IN
	Porter County, IN
24020	Glens Falls, NY	0.8324
	Warren County, NY
	Washington County, NY
24140	Goldsboro, NC	0.9171
	Wayne County, NC
24220	Grand Forks, ND-MN	0.7949
	Polk County, MN
	Grand Forks County, ND
24300	Grand Junction, CO	0.9668
	Mesa County, CO
24340	Grand Rapids-Wyoming, MI	0.9455
	Barry County, MI
	Ionia County, MI
	Kent County, MI
	Newaygo County, MI
24500	Great Falls, MT	0.8598
	Cascade County, MT
24540	Greeley, CO	0.9602
	Weld County, CO
24580	Green Bay, WI	0.9787
	Brown County, WI
	Kewaunee County, WI
	Oconto County, WI
24660	Greensboro-High Point, NC	0.8866
	Guilford County, NC
	Randolph County, NC
	Rockingham County, NC
24780	Greenville, NC	0.9432
	Greene County, NC
	Pitt County, NC
24860	Greenville, SC	0.9804
	Greenville County, SC
	Laurens County, SC
	Pickens County, SC
25020	Guayama, PR	0.3235
	Arroyo Municipio, PR
	Guayama Municipio, PR
	Patillas Municipio, PR
25060	Gulfport-Biloxi, MS	0.8915
	Hancock County, MS
	Harrison County, MS
	Stone County, MS
25180	Hagerstown-Martinsburg, MD-WV	0.9038
	Washington County, MD
	Berkeley County, WV
	Morgan County, WV
25260	Hanford-Corcoran, CA	1.0282
	Kings County, CA
25420	Harrisburg-Carlisle, PA	0.9402
	Cumberland County, PA
	Dauphin County, PA
	Perry County, PA
25500	Harrisonburg, VA	0.9073
	Rockingham County, VA
	Harrisonburg City, VA
25540	Hartford-West Hartford-East Hartford, CT	1.0894
	Hartford County, CT
	Litchfield County, CT
	Middlesex County, CT
	Tolland County, CT
25620	Hattiesburg, MS	0.7430
	Forrest County, MS
	Lamar County, MS
	Perry County, MS
25860	Hickory-Lenoir-Morganton, NC	0.9010
	Alexander County, NC
	Burke County, NC
	Caldwell County, NC
	Catawba County, NC
25980	Hinesville-Fort Stewart, GA1	0.9178
	Liberty County, GA
	Long County, GA
26100	Holland-Grand Haven, MI	0.9163
	Ottawa County, MI
26180	Honolulu, HI	1.1096
	Honolulu County, HI
26300	Hot Springs, AR	0.8782
	Garland County, AR
26380	Houma-Bayou Cane-Thibodaux, LA	0.8082
	Lafourche Parish, LA
	Terrebonne Parish, LA
26420	Houston-Sugar Land-Baytown, TX	1.0008
	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	0.8997
	Boyd County, KY
	Greenup County, KY
	Lawrence County, OH
	Cabell County, WV
	Wayne County, WV
26620	Huntsville, AL	0.9007
	Limestone County, AL
	Madison County, AL
26820	Idaho Falls, ID	0.9088
	Bonneville County, ID
	Jefferson County, ID
26900	Indianapolis-Carmel, IN	0.9895
	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	0.9714
	Johnson County, IA
	Washington County, IA
27060	Ithaca, NY	0.9928
	Tompkins County, NY
27100	Jackson, MI	0.9560
	Jackson County, MI
27140	Jackson, MS	0.8271
	Copiah County, MS
	Hinds County, MS
	Madison County, MS
	Rankin County, MS
	Simpson County, MS
27180	Jackson, TN	0.8853
	Chester County, TN
	Madison County, TN
27260	Jacksonville, FL	0.9165
	Baker County, FL
	Clay County, FL
	Duval County, FL
	Nassau County, FL
	St. Johns County, FL
27340	Jacksonville, NC	0.8231
	Onslow County, NC
27500	Janesville, WI	0.9655
	Rock County, WI
27620	Jefferson City, MO	0.8332
	Callaway County, MO
	Cole County, MO
	Moniteau County, MO
	Osage County, MO
27740	Johnson City, TN	0.8043
	Carter County, TN
	Unicoi County, TN
	Washington County, TN
27780	Johnstown, PA	0.8620
	Cambria County, PA
27860	Jonesboro, AR	0.7662
	Craighead County, AR
	Poinsett County, AR
27900	Joplin, MO	0.8605
	Jasper County, MO
	Newton County, MO
28020	Kalamazoo-Portage, MI	1.0704
	Kalamazoo County, MI
	Van Buren County, MI
28100	Kankakee-Bradley, IL	1.0083
	Kankakee County, IL
28140	Kansas City, MO-KS	0.9495
	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	1.0343
	Benton County, WA
	Franklin County, WA
28660	Killeen-Temple-Fort Hood, TX	0.8901
	Bell County, TX
	Coryell County, TX
	Lampasas County, TX
28700	Kingsport-Bristol-Bristol, TN-VA	0.7985
	Hawkins County, TN
	Sullivan County, TN
	Bristol City, VA
	Scott County, VA
	Washington County, VA
28740	Kingston, NY	0.9367
	Ulster County, NY
28940	Knoxville, TN	0.8249
	Anderson County, TN
	Blount County, TN
	Knox County, TN
	Loudon County, TN
	Union County, TN
29020	Kokomo, IN	0.9669
	Howard County, IN
	Tipton County, IN
29100	La Crosse, WI-MN	0.9426
	Houston County, MN
	La Crosse County, WI
29140	Lafayette, IN	0.8931
	Benton County, IN
	Carroll County, IN
	Tippecanoe County, IN
29180	Lafayette, LA	0.8289
	Lafayette Parish, LA
	St. Martin Parish, LA
29340	Lake Charles, LA	0.7914
	Calcasieu Parish, LA
	Cameron Parish, LA
29404	Lake County-Kenosha County, IL-WI	1.0570
	Lake County, IL
	Kenosha County, WI
29460	Lakeland, FL	0.8879
	Polk County, FL
29540	Lancaster, PA	0.9589
	Lancaster County, PA
29620	Lansing-East Lansing, MI	1.0088
	Clinton County, MI
	Eaton County, MI
	Ingham County, MI
29700	Laredo, TX	0.7811
	Webb County, TX
29740	Las Cruces, NM	0.9273
	Dona Ana County, NM
29820	Las Vegas-Paradise, NV	1.1430
	Clark County, NV
29940	Lawrence, KS	0.8365
	Douglas County, KS
30020	Lawton, OK	0.8065
	Comanche County, OK
30140	Lebanon, PA	0.8679
	Lebanon County, PA
30300	Lewiston, ID-WA	0.9853
	Nez Perce County, ID
	Asotin County, WA
30340	Lewiston-Auburn, ME	0.9126
	Androscoggin County, ME
30460	Lexington-Fayette, KY	0.9181
	Bourbon County, KY
	Clark County, KY
	Fayette County, KY
	Jessamine County, KY
	Scott County, KY
	Woodford County, KY
30620	Lima, OH	0.9042
	Allen County, OH
30700	Lincoln, NE	1.0092
	Lancaster County, NE
	Seward County, NE
30780	Little Rock-North Little Rock, AR	0.8890
	Faulkner County, AR
	Grant County, AR
	Lonoke County, AR
	Perry County, AR
	Pulaski County, AR
	Saline County, AR
30860	Logan, UT-ID	0.9022
	Franklin County, ID
	Cache County, UT
30980	Longview, TX	0.8788
	Gregg County, TX
	Rusk County, TX
	Upshur County, TX
31020	Longview, WA	1.0011
	Cowlitz County, WA
31084	Los Angeles-Long Beach-Glendale, CA	1.1760
	Los Angeles County, CA
31140	Louisville, KY-IN	0.9118
	Clark County, IN
	Floyd County, IN
	Harrison County, IN
	Washington County, IN
	Bullitt County, KY
	Henry County, KY
	Jefferson County, KY
	Meade County, KY
	Nelson County, KY
	Oldham County, KY
	Shelby County, KY
	Spencer County, KY
	Trimble County, KY
31180	Lubbock, TX	0.8613
	Crosby County, TX
	Lubbock County, TX
31340	Lynchburg, VA	0.8694
	Amherst County, VA
	Appomattox County, VA
	Bedford County, VA
	Campbell County, VA
	Bedford City, VA
	Lynchburg City, VA
31420	Macon, GA	0.9519
	Bibb County, GA
	Crawford County, GA
	Jones County, GA
	Monroe County, GA
	Twiggs County, GA
31460	Madera, CA	0.8154
	Madera County, CA
31540	Madison, WI	1.0840
	Columbia County, WI
	Dane County, WI
	Iowa County, WI
31700	Manchester-Nashua, NH	1.0243
	Hillsborough County, NH
	Merrimack County, NH
31900	Mansfield, OH	0.9271
	Richland County, OH
32420	Mayagüez, PR	0.3848
	Hormigueros Municipio, PR
	Mayagüez Municipio, PR
32580	McAllen-Edinburg-Pharr, TX	0.8773
	Hidalgo County, TX
32780	Medford, OR	1.0818
	Jackson County, OR
32820	Memphis, TN-MS-AR	0.9373
	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	1.1471
	Merced County, CA
33124	Miami-Miami Beach-Kendall, FL	0.9812
	Miami-Dade County, FL
33140	Michigan City-La Porte, IN	0.9118
	LaPorte County, IN
33260	Midland, TX	0.9786
	Midland County, TX
33340	Milwaukee-Waukesha-West Allis, WI	1.0218
	Milwaukee County, WI
	Ozaukee County, WI
	Washington County, WI
	Waukesha County, WI
33460	Minneapolis-St. Paul-Bloomington, MN-WI	1.0946
	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	0.8928
	Missoula County, MT
33660	Mobile, AL	0.7913
	Mobile County, AL
33700	Modesto, CA	1.1729
	Stanislaus County, CA
33740	Monroe, LA	0.7997
	Ouachita Parish, LA
	Union Parish, LA
33780	Monroe, MI	0.9707
	Monroe County, MI
33860	Montgomery, AL	0.8009
	Autauga County, AL
	Elmore County, AL
	Lowndes County, AL
	Montgomery County, AL
34060	Morgantown, WV	0.8423
	Monongalia County, WV
	Preston County, WV
34100	Morristown, TN	0.7933
	Grainger County, TN
	Hamblen County, TN
	Jefferson County, TN
34580	Mount Vernon-Anacortes, WA	1.0517
	Skagit County, WA
34620	Muncie, IN	0.8562
	Delaware County, IN
34740	Muskegon-Norton Shores, MI	0.9941
	Muskegon County, MI
34820	Myrtle Beach-Conway-North Myrtle Beach, SC	0.8810
	Horry County, SC
34900	Napa, CA	1.3374
	Napa County, CA
34940	Naples-Marco Island, FL	0.9941
	Collier County, FL
34980	Nashville-Davidson-Murfreesboro, TN	0.9847
	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	1.2662
	Nassau County, NY
	Suffolk County, NY
35084	Newark-Union, NJ-PA	1.1892
	Essex County, NJ
	Hunterdon County, NJ
	Morris County, NJ
	Sussex County, NJ
	Union County, NJ
	Pike County, PA
35300	New Haven-Milford, CT	1.1953
	New Haven County, CT
35380	New Orleans-Metairie-Kenner, LA	0.8831
	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-Wayne-White Plains, NY-NJ	1.3177
	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	0.8915
	Berrien County, MI
35980	Norwich-New London, CT	1.1932
	New London County, CT
36084	Oakland-Fremont-Hayward, CA	1.5819
	Alameda County, CA
	Contra Costa County, CA
36100	Ocala, FL	0.8867
	Marion County, FL
36140	Ocean City, NJ	1.0472
	Cape May County, NJ
36220	Odessa, TX	1.0073
	Ector County, TX
36260	Ogden-Clearfield, UT	0.8995
	Davis County, UT
	Morgan County, UT
	Weber County, UT
36420	Oklahoma City, OK	0.8843
	Canadian County, OK
	Cleveland County, OK
	Grady County, OK
	Lincoln County, OK
	Logan County, OK
	McClain County, OK
	Oklahoma County, OK
36500	Olympia, WA	1.1081
	Thurston County, WA
36540	Omaha-Council Bluffs, NE-IA	0.9450
	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, FL	0.9452
	Lake County, FL
	Orange County, FL
	Osceola County, FL
	Seminole County, FL
36780	Oshkosh-Neenah, WI	0.9315
	Winnebago County, WI
36980	Owensboro, KY	0.8748
	Daviess County, KY
	Hancock County, KY
	McLean County, KY
37100	Oxnard-Thousand Oaks-Ventura, CA	1.1546
	Ventura County, CA
37340	Palm Bay-Melbourne-Titusville, FL	0.9443
	Brevard County, FL
37460	Panama City-Lynn Haven, FL	0.8027
	Bay County, FL
37620	Parkersburg-Marietta, WV-OH	0.7977
	Washington County, OH
	Pleasants County, WV
	Wirt County, WV
	Wood County, WV
37700	Pascagoula, MS	0.8215
	George County, MS
	Jackson County, MS
37860	Pensacola-Ferry Pass-Brent, FL	0.8000
	Escambia County, FL
	Santa Rosa County, FL
37900	Peoria, IL	0.8982
	Marshall County, IL
	Peoria County, IL
	Stark County, IL
	Tazewell County, IL
	Woodford County, IL
37964	Philadelphia, PA	1.0996
	Bucks County, PA
	Chester County, PA
	Delaware County, PA
	Montgomery County, PA
	Philadelphia County, PA
38060	Phoenix-Mesa-Scottsdale, AZ	1.0287
	Maricopa County, AZ
	Pinal County, AZ
38220	Pine Bluff, AR	0.8383
	Cleveland County, AR
	Jefferson County, AR
	Lincoln County, AR
38300	Pittsburgh, PA	0.8674
	Allegheny County, PA
	Armstrong County, PA
	Beaver County, PA
	Butler County, PA
	Fayette County, PA
	Washington County, PA
	Westmoreland County, PA
38340	Pittsfield, MA	1.0266
	Berkshire County, MA
38540	Pocatello, ID	0.9400
	Bannock County, ID
	Power County, ID
38660	Ponce, PR	0.4842
	Juana Díaz Municipio, PR
	Ponce Municipio, PR
	Villalba Municipio, PR
38860	Portland-South Portland-Biddeford, ME	0.9908
	Cumberland County, ME
	Sagadahoc County, ME
	York County, ME
38900	Portland-Vancouver-Beaverton, OR-WA	1.1416
	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-Fort Pierce, FL	0.9833
	Martin County, FL
	St. Lucie County, FL
39100	Poughkeepsie-Newburgh-Middletown, NY	1.0911
	Dutchess County, NY
	Orange County, NY
39140	Prescott, AZ	0.9836
	Yavapai County, AZ
39300	Providence-New Bedford-Fall River, RI-MA	1.0783
	Bristol County, MA
	Bristol County, RI
	Kent County, RI
	Newport County, RI
	Providence County, RI
	Washington County, RI
39340	Provo-Orem, UT	0.9537
	Juab County, UT
	Utah County, UT
39380	Pueblo, CO	0.8753
	Pueblo County, CO
39460	Punta Gorda, FL	0.9405
	Charlotte County, FL
39540	Racine, WI	0.9356
	Racine County, WI
39580	Raleigh-Cary, NC	0.9864
	Franklin County, NC
	Johnston County, NC
	Wake County, NC
39660	Rapid City, SD	0.8833
	Meade County, SD
	Pennington County, SD
39740	Reading, PA	0.9622
	Berks County, PA
39820	Redding, CA	1.3198
	Shasta County, CA
39900	Reno-Sparks, NV	1.1963
	Storey County, NV
	Washoe County, NV
40060	Richmond, VA	0.9177
	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	1.0904
	Riverside County, CA
	San Bernardino County, CA
40220	Roanoke, VA	0.8647
	Botetourt County, VA
	Craig County, VA
	Franklin County, VA
	Roanoke County, VA
	Roanoke City, VA
	Salem City, VA
40340	Rochester, MN	1.1408
	Dodge County, MN
	Olmsted County, MN
	Wabasha County, MN
40380	Rochester, NY	0.8994
	Livingston County, NY
	Monroe County, NY
	Ontario County, NY
	Orleans County, NY
	Wayne County, NY
40420	Rockford, IL	0.9989
	Boone County, IL
	Winnebago County, IL
40484	Rockingham County-Strafford County, NH	1.0159
	Rockingham County, NH
	Strafford County, NH
40580	Rocky Mount, NC	0.8854
	Edgecombe County, NC
	Nash County, NC
40660	Rome, GA	0.9193
	Floyd County, GA
40900	Sacramento-Arden-Arcade-Roseville, CA	1.3372
	El Dorado County, CA
	Placer County, CA
	Sacramento County, CA
	Yolo County, CA
40980	Saginaw-Saginaw Township North, MI	0.8874
	Saginaw County, MI
41060	St. Cloud, MN	1.0362
	Benton County, MN
	Stearns County, MN
41100	St. George, UT	0.9265
	Washington County, UT
41140	St. Joseph, MO-KS	1.0118
	Doniphan County, KS
	Andrew County, MO
	Buchanan County, MO
	DeKalb County, MO
41180	St. Louis, MO-IL	0.9005
	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	1.0438
	Marion County, OR
	Polk County, OR
41500	Salinas, CA	1.4337
	Monterey County, CA
41540	Salisbury, MD	0.8953
	Somerset County, MD
	Wicomico County, MD
41620	Salt Lake City, UT	0.9402
	Salt Lake County, UT
	Summit County, UT
	Tooele County, UT
41660	San Angelo, TX	0.8362
	Irion County, TX
	Tom Green County, TX
41700	San Antonio, TX	0.8844
	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	1.1354
	San Diego County, CA
41780	Sandusky, OH	0.9302
	Erie County, OH
41884	San Francisco-San Mateo-Redwood City, CA	1.5165
	Marin County, CA
	San Francisco County, CA
	San Mateo County, CA
41900	San Germán-Cabo Rojo, PR	0.4885
	Cabo Rojo Municipio, PR
	Lajas Municipio, PR
	Sabana Grande Municipio, PR
	San Germán Municipio, PR
41940	San Jose-Sunnyvale-Santa Clara, CA	1.5543
	San Benito County, CA
	Santa Clara County, CA
41980	San Juan-Caguas-Guaynabo, PR	0.4452
	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	1.1598
	San Luis Obispo County, CA
42044	Santa Ana-Anaheim-Irvine, CA	1.1473
	Orange County, CA
42060	Santa Barbara-Santa Maria-Goleta, CA	1.1091
	Santa Barbara County, CA
42100	Santa Cruz-Watsonville, CA	1.5457
	Santa Cruz County, CA
42140	Santa Fe, NM	1.0824
	Santa Fe County, NM
42220	Santa Rosa-Petaluma, CA	1.4464
	Sonoma County, CA
42260	Sarasota-Bradenton-Venice, FL	0.9868
	Manatee County, FL
	Sarasota County, FL
42340	Savannah, GA	0.9351
	Bryan County, GA
	Chatham County, GA
	Effingham County, GA
42540	Scranton-Wilkes-Barre, PA	0.8347
	Lackawanna County, PA
	Luzerne County, PA
	Wyoming County, PA
42644	Seattle-Bellevue-Everett, WA	1.1434
	King County, WA
	Snohomish County, WA
42680	Sebastian-Vero Beach, FL	0.9573
	Indian River County, FL
43100	Sheboygan, WI	0.9026
	Sheboygan County, WI
43300	Sherman-Denison, TX	0.8502
	Grayson County, TX
43340	Shreveport-Bossier City, LA	0.8865
	Bossier Parish, LA
	Caddo Parish, LA
	De Soto Parish, LA
43580	Sioux City, IA-NE-SD	0.9200
	Woodbury County, IA
	Dakota County, NE
	Dixon County, NE
	Union County, SD
43620	Sioux Falls, SD	0.9559
	Lincoln County, SD
	McCook County, SD
	Minnehaha County, SD
	Turner County, SD
43780	South Bend-Mishawaka, IN-MI	0.9842
	St. Joseph County, IN
	Cass County, MI
43900	Spartanburg, SC	0.9174
	Spartanburg County, SC
44060	Spokane, WA	1.0447
	Spokane County, WA
44100	Springfield, IL	0.8890
	Menard County, IL
	Sangamon County, IL
44140	Springfield, MA	1.0079
	Franklin County, MA
	Hampden County, MA
	Hampshire County, MA
44180	Springfield, MO	0.8469
	Christian County, MO
	Dallas County, MO
	Greene County, MO
	Polk County, MO
	Webster County, MO
44220	Springfield, OH	0.8593
	Clark County, OH
44300	State College, PA	0.8784
	Centre County, PA
44700	Stockton, CA	1.1442
	San Joaquin County, CA
44940	Sumter, SC	0.8083
	Sumter County, SC
45060	Syracuse, NY	0.9691
	Madison County, NY
	Onondaga County, NY
	Oswego County, NY
45104	Tacoma, WA	1.0789
	Pierce County, WA
45220	Tallahassee, FL	0.8942
	Gadsden County, FL
	Jefferson County, FL
	Leon County, FL
	Wakulla County, FL
45300	Tampa-St. Petersburg-Clearwater, FL	0.9144
	Hernando County, FL
	Hillsborough County, FL
	Pasco County, FL
	Pinellas County, FL
45460	Terre Haute, IN	0.8765
	Clay County, IN
	Sullivan County, IN
	Vermillion County, IN
	Vigo County, IN
45500	Texarkana, TX-Texarkana, AR	0.8104
	Miller County, AR
	Bowie County, TX
45780	Toledo, OH	0.9586
	Fulton County, OH
	Lucas County, OH
	Ottawa County, OH
	Wood County, OH
45820	Topeka, KS	0.8730
	Jackson County, KS
	Jefferson County, KS
	Osage County, KS
	Shawnee County, KS
	Wabaunsee County, KS
45940	Trenton-Ewing, NJ	1.0835
	Mercer County, NJ
46060	Tucson, AZ	0.9202
	Pima County, AZ
46140	Tulsa, OK	0.8103
	Creek County, OK
	Okmulgee County, OK
	Osage County, OK
	Pawnee County, OK
	Rogers County, OK
	Tulsa County, OK
	Wagoner County, OK
46220	Tuscaloosa, AL	0.8542
	Greene County, AL
	Hale County, AL
	Tuscaloosa County, AL
46340	Tyler, TX	0.8811
	Smith County, TX
46540	Utica-Rome, NY	0.8396
	Herkimer County, NY
	Oneida County, NY
46660	Valdosta, GA	0.8369
	Brooks County, GA
	Echols County, GA
	Lanier County, GA
	Lowndes County, GA
46700	Vallejo-Fairfield, CA	1.5137
	Solano County, CA
47020	Victoria, TX	0.8560
	Calhoun County, TX
	Goliad County, TX
	Victoria County, TX
47220	Vineland-Millville-Bridgeton, NJ	0.9832
	Cumberland County, NJ
47260	Virginia Beach-Norfolk-Newport News, VA-NC	0.8790
	Currituck County, NC
	Gloucester County, VA
	Isle of Wight County, VA
	James City County, VA
	Mathews County, VA
	Surry County, VA
	York County, VA
	Chesapeake City, VA
	Hampton City, VA
	Newport News City, VA
	Norfolk City, VA
	Poquoson City, VA
	Portsmouth City, VA
	Suffolk City, VA
	Virginia Beach City, VA
	Williamsburg City, VA
47300	Visalia-Porterville, CA	0.9968
	Tulare County, CA
47380	Waco, TX	0.8633
	McLennan County, TX
47580	Warner Robins, GA	0.8380
	Houston County, GA
47644	Warren-Troy-Farmington Hills, MI	1.0054
	Lapeer County, MI
	Livingston County, MI
	Macomb County, MI
	Oakland County, MI
	St. Clair County, MI
47894	Washington-Arlington-Alexandria, DC-VA-MD-WV	1.1054
	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	0.8408
	Black Hawk County, IA
	Bremer County, IA
	Grundy County, IA
48140	Wausau, WI	0.9722
	Marathon County, WI
48260	Weirton-Steubenville, WV-OH	0.8063
	Jefferson County, OH
	Brooke County, WV
	Hancock County, WV
48300	Wenatchee, WA	1.0346
	Chelan County, WA
	Douglas County, WA
48424	West Palm Beach-Boca Raton-Boynton Beach, FL	0.9649
	Palm Beach County, FL
48540	Wheeling, WV-OH	0.7010
	Belmont County, OH
	Marshall County, WV
	Ohio County, WV
48620	Wichita, KS	0.9063
	Butler County, KS
	Harvey County, KS
	Sedgwick County, KS
	Sumner County, KS
48660	Wichita Falls, TX	0.8311
	Archer County, TX
	Clay County, TX
	Wichita County, TX
48700	Williamsport, PA	0.8139
	Lycoming County, PA
48864	Wilmington, DE-MD-NJ	1.0684
	New Castle County, DE
	Cecil County, MD
	Salem County, NJ
48900	Wilmington, NC	0.9835
	Brunswick County, NC
	New Hanover County, NC
	Pender County, NC
49020	Winchester, VA-WV	1.0091
	Frederick County, VA
	Winchester City, VA
	Hampshire County, WV
49180	Winston-Salem, NC	0.9276
	Davie County, NC
	Forsyth County, NC
	Stokes County, NC
	Yadkin County, NC
49340	Worcester, MA	1.0722
	Worcester County, MA
49420	Yakima, WA	0.9847
	Yakima County, WA
49500	Yauco, PR	0.3854
	Guánica Municipio, PR
	Guayanilla Municipio, PR
	Peñuelas Municipio, PR
	Yauco Municipio, PR
49620	York-Hanover, PA	0.9397
	York County, PA
49660	Youngstown-Warren-Boardman, OH-PA	0.8802
	Mahoning County, OH
	Trumbull County, OH
	Mercer County, PA
49700	Yuba City, CA	1.0730
	Sutter County, CA
	Yuba County, CA
49740	Yuma, AZ	0.9109
	Yuma County, AZ
1 At this time, there are no hospitals located in this CBSA-based urban area on which to base a wage index. Therefore, the wage index value is based on the methodology described in the August 15, 2005 final rule (70 FR 47880). The wage index value for this area is the average wage index for all urban areas within the state.

Table 2.—Inpatient Rehabilitation Facility Wage Index for Rural Areas for Discharges Occurring From October 1, 2007 Through September 30, 2008

CBSA code	Nonurban area	Wage index
01	Alabama	0.7591
02	Alaska	1.0661
03	Arizona	0.8908
04	Arkansas	0.7307
05	California	1.1454
06	Colorado	0.9325
07	Connecticut	1.1709
08	Delaware	0.9705
10	Florida	0.8594
11	Georgia	0.7593
12	Hawaii	1.0448
13	Idaho	0.8120
14	Illinois	0.8320
15	Indiana	0.8538
16	Iowa	0.8681
17	Kansas	0.7998
18	Kentucky	0.7768
19	Louisiana	0.7438
20	Maine	0.8443
21	Maryland	0.8926
22	Massachusetts 2	1.1661
23	Michigan	0.9062
24	Minnesota	0.9153
25	Mississippi	0.7738
26	Missouri	0.7927
27	Montana	0.8590
28	Nebraska	0.8677
29	Nevada	0.8944
30	New Hampshire	1.0853
31	New Jersey 1
32	New Mexico	0.8332
33	New York	0.8232
34	North Carolina	0.8588
35	North Dakota	0.7215
36	Ohio	0.8658
37	Oklahoma	0.7629
38	Oregon	0.9753
39	Pennsylvania	0.8320
40	Puerto Rico 3	0.4047
41	Rhode Island 1
42	South Carolina	0.8566
43	South Dakota	0.8480
44	Tennessee	0.7827
45	Texas	0.7965
46	Utah	0.8140
47	Vermont	0.9744
48	Virgin Islands	0.8467
49	Virginia	0.7940
50	Washington	1.0263
51	West Virginia	0.7607
52	Wisconsin	0.9553
53	Wyoming	0.9295
65	Guam	0.9611
1 All counties within the State are classified as urban.
2 Massachusetts has areas designated as rural; however, no short-term, acute care hospitals are located in the area(s) for FY 2008. As discussed in the preamble in Section VI.B, we will impute a wage index value for rural Massachusetts based on the average wage index from all contiguous CBSAs.
3 Puerto Rico has areas designated as rural; however, no short-term, acute care hospitals are located in the area(s) for FY 2008. As discussed in the preamble in Section VI.B, we will continue to use the most recent wage index previously available for Puerto Rico as discussed in the FY 2006 IRF PPS final rule (70 FR 47880).