Medicare Program; Prospective Payment System and Consolidated Billing for Skilled Nursing Facilities-Update

DEPARTMENT OF HEALTH AND HUMAN SERVICES

Health Care Financing Administration

42 CFR Parts 410, 411, 413, 424, 482, and 489

[HCFA-1163-P]

RIN 0938-AK47

Medicare Program; Prospective Payment System and Consolidated Billing for Skilled Nursing Facilities—Update

AGENCY:

Health Care Financing Administration (HCFA), HHS.

ACTION:

Proposed rule.

SUMMARY:

This proposed rule updates the payment rates used under the prospective payment system (PPS) for skilled nursing facilities (SNFs), for fiscal year (FY) 2002, as required by statute. Annual updates to the PPS rates are required by section 1888(e) of the Social Security Act (the Act), as amended by the Medicare, Medicaid, and SCHIP Balanced Budget Refinement Act of 1999 (BBRA 1999), and the Medicare, Medicaid, and SCHIP Benefits Improvement and Protection Act of 2000 (BIPA 2000), relating to Medicare payments and consolidated billing for SNFs. As part of this annual update, we are rebasing and revising the routine SNF market basket to reflect 1997 total cost data (the latest available complete data on the structure of SNF costs), and modifying certain variables for some of the cost categories. In addition, we propose to implement the transition of swing-bed facilities to the SNF PPS, as required by section 1888(e)(7) of the Act.

DATES:

We will consider comments if we receive them at the appropriate address, as provided below, no later than 5 p.m. on July 9, 2001.

ADDRESSES:

Mail written comments (one original and three copies) to the following address: Health Care Financing Administration, Department of Health and Human Services, Attention: HCFA-1163-P, P.O. Box 8013, Baltimore, MD 21244-8013.

If you prefer, you may deliver your written comments (one original and three copies) to one of the following addresses: Hubert H. Humphrey Building, Room 443-G, 200 Independence Avenue, SW., Washington, DC 20201, or Health Care Financing Administration, Room C5-15-03, 7500 Security Boulevard, Baltimore, MD 21244-8150.

Comments mailed to those addresses designated for courier delivery may be delayed and could be considered late. Because of staffing and resource limitations, we cannot accept comments by facsimile (FAX) transmission. Please refer to file code HCFA-1163-P on each comment. Comments received timely will be available for public inspection as they are received, generally beginning approximately 3 weeks after publication of this document, in Room C5-12-08 of the Health Care Financing Administration, 7500 Security Boulevard, Baltimore, Maryland, Monday through Friday of each week from 8:30 a.m. to 5 p.m. Please call (410) 786-7197 to make an appointment to view comments.

FOR FURTHER INFORMATION CONTACT:

Dana Burley, (410) 786-4547 or Sheila Lambowitz, (410) 786-7605 (for information related to the case-mix classification methodology)

John Davis, (410) 786-0008 (for information related to the Wage Index)

Bill Ullman, (410) 786-5667 (for information related to consolidated billing)

Susan Burris, (410) 786-6655 (for information related to payment)

Sheila Lambowitz, (410) 786-7605 (for information related to swing-bed providers)

Bill Ullman, (410) 786-5667 or Susan Burris, (410) 786-6655 (for general information)

SUPPLEMENTARY INFORMATION:

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.

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

Table of Contents

I. Background

A. Current System for Payment of Skilled Nursing Facility Services Under Part A of the Medicare Program

B. Requirements of the Balanced Budget Act of 1997 for Updating the Prospective Payment System for Skilled Nursing Facilities

C. The Medicare, Medicaid, and SCHIP Balanced Budget Refinement Act of 1999 (BBRA 1999)

D. The Medicare, Medicaid, and SCHIP Benefits Improvement and Protection Act of 2000 (BIPA 2000)

E. Skilled Nursing Facility Prospective Payment—General Overview

1. Payment Provisions—Federal Rates

2. Payment Provisions—Transition Period

F. Skilled Nursing Facility Market Basket Index

II. Update of Payment Rates Under the Prospective Payment System for Skilled Nursing Facilities

A. Federal Prospective Payment System

1. Costs and Services Covered by the Federal Rates

2. Methodology Used for the Calculation of the Federal Rates

B. Case-Mix Adjustment

C. Wage Index Adjustment to Federal Rates

D. Updates to the Federal Rates

E. Relationship of RUG-III Classification System to Existing Skilled Nursing Facility Level-of-Care Criteria

F. Three-year Transition Period

G. Example of Computation of Adjusted PPS Rates and SNF Payment

III. The Skilled Nursing Facility Market Basket Index

A. Background

B. Rebasing and Revising the SNF Market Basket

IV. Update Framework

A. The Need for an Update Framework

B. Factors Inherent in SNF Payments per Day

C. Defining Each Factor Inherent in SNF Costs per Day

1. Input Prices

2. Productivity

3. Real Case-Mix per Day

4. Case-Mix Constant Real Output Intensity per Day

D. Applying the Factors that Affect SNF Costs per Day in an Update Framework

E. Current HCFA Inpatient Hospital PPS and Illustrative SNF PPS Payment Update Frameworks

F. Additional Conceptual and Data Issues

V. Consolidated Billing

VI. Application of the SNF PPS to SNF Services Furnished by Swing-Bed Hospitals

A. Current System for Payment of Swing-Bed Facility Services Under Part A of the Medicare Program

B. Requirement of the Balanced Budget Act of 1997 for Swing-Bed Facility Services to be Paid under the Prospective Payment System for Skilled Nursing Facilities

C. Requirements of BBRA 1999 Affecting Swing-Bed Payment and Eligibility

D. Implications of Swing-Bed Facility Conversion to the SNF PPS

E. SNF PPS Rate Components

F. Implementation of the SNF PPS for Swing-Bed Facilities

G. Use of the Resident Assessment Instrument—Minimum Data Set (MDS 2.0)

H. Required Schedule for Completing the MDS

I. RUG-III “Grouper” Methodology and Software

J. Applicability of Consolidated Billing to SNF Services Furnished in Swing-Bed Facilities

K. Costs Associated with Automating the MDS: Preliminary Estimates

L. Provider Training

VII. Provisions of the Proposed Rule

VIII. Collection of Information Requirements

IX. Regulatory Impact Analysis

A. Background

B. Impact of the Proposed Rule

X. Federalism

Regulation Text

Appendix—Technical Features of the Proposed 1997-based Skilled Nursing Facility Market Basket Index

I. Synopsis of Structural Changes Adopted in the Proposed Revised and Rebased 1997 Skilled Nursing Facility Market Basket

II. Methodology for Developing the Cost Category Weights

III. Price Proxies Used to Measure Cost Category Growth

A. Wages and Salaries

B. Employee Benefits

C. All Other Expenses

D. Capital-Related Expenses

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

ADL Activity of Daily Living

AHE Average Hourly Earnings

ARD Assessment Reference Date

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

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

BEA (U.S.) Bureau of Economic Analysis

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

BES (U.S.) Business Expenditures Survey

BLS (U.S.) Bureau of Labor Statistics

CAH Critical Access Hospital

CFR Code of Federal Regulations

CPI Consumer Price Index

CPI-U Consumer Price Index-All Urban Consumers

CPT (Physicians') Current Procedural Terminology

DRG Diagnosis Related Group

ECI Employment Cost Index

FI Fiscal Intermediary

FR Federal Register

FY Fiscal Year

GAO General Accounting Office

HCFA Health Care Financing Administration

HCPCS HCFA Common Procedure Coding System

ICD-9-CM International Classification of Diseases, Ninth Edition, Clinical Modification

IFC Interim Final Rule with Comment Period

MDS Minimum Data Set

MEDPAR Medicare Provider Analysis and Review File

MIP Medicare Integrity Program

MSA Metropolitan Statistical Area

NECMA New England County Metropolitan Area

OIG Office of the Inspector General

OMRA Other Medicare Required Assessment

PCE Personal Care Expenditures

PPI Producer Price Index

PPS Prospective Payment System

PRM Provider Reimbursement Manual

RAI Resident Assessment Instrument

RAP Resident Assessment Protocol

RAVEN Resident Assessment Validation Entry

RUG Resource Utilization Groups

SCHIP State Children's Health Insurance Program

SNF Skilled Nursing Facility

STM Staff Time Measure

I. Background

On July 31, 2000, we published in the

Federal Register

(65 FR 46770), a final rule that set forth updates to the payment rates used under the prospective payment system (PPS) for skilled nursing facilities (SNFs), for fiscal year (FY) 2001. Annual updates to the PPS rates are required by section 1888(e) of the Social Security Act (the Act), as amended by the Medicare, Medicaid, and SCHIP Balanced Budget Refinement Act of 1999 (BBRA 1999) and the Medicare, Medicaid, and SCHIP Benefits Improvement and Protection Act of 2000 (BIPA 2000), relating to Medicare payments and consolidated billing for SNFs.

A. Current System for Payment of Skilled Nursing Facility Services Under Part A of the Medicare Program

Section 4432 of the Balanced Budget Act of 1997 (BBA 1997) amended section 1888 of the Act to provide for the implementation of a per diem PPS for SNFs, covering all costs (routine, ancillary, and capital) of covered SNF services furnished to beneficiaries under Part A of the Medicare program, effective for cost reporting periods beginning on or after July 1, 1998. We propose to update the per diem payment rates for SNFs, for FY 2002. Major elements of the SNF PPS include:

•

Rates.

Per diem Federal rates were established for urban and rural areas using allowable costs from FY 1995 cost reports. These rates also included an estimate of the cost of services that, before July 1, 1998, had been paid under Part B but furnished to Medicare beneficiaries in a SNF during a Part A covered stay. The rates were adjusted annually using a SNF market basket index. Rates were case-mix adjusted using a classification system (Resource Utilization Groups, version III (RUG-III)) based on beneficiary assessments (using the Minimum Data Set (MDS) 2.0). The rates were also adjusted by the hospital wage index to account for geographic variation in wages. (In section II.C of this preamble, we discuss the wage index adjustment in detail, including an examination of the feasibility of developing a wage index based on SNF-specific wage data.) At this time, data for the FY 2002 hospital wage index are not yet available; therefore, the index applied in this proposed rule is the same index used in the July 31, 2000 final rule. A correction notice was published on January 16, 2001 (66 FR 3497) that announced corrections to several of the wage factors. Additionally, as noted in the July 31, 2000 final rule (65 FR 46770), section 101 of BBRA 1999 also affects the payment rate. Finally, sections 311, 312, and 314 of BIPA 2000 affect the Part A PPS payment rates for SNFs. These new provisions are discussed in detail in section I.D. of this proposed rule.

•

Transition.

The SNF PPS includes an initial 3-year, phased transition that blended a facility-specific payment rate with the Federal case-mix adjusted rate. For each cost reporting period after a facility migrated to the new system, the facility-specific portion of the blend decreased and the Federal portion increased in 25 percentage point increments. For most facilities, the facility-specific rate was based on allowable costs from FY 1995; however, since the last year of the transition is FY 2001, all facilities will be paid at the full Federal rate by the coming fiscal year (FY 2002), for which we are now proposing updated rates. Therefore, unlike previous years, this proposed rule does not include adjustment factors related to facility-specific rates for the coming fiscal year.

•

Coverage.

Medicare's fundamental requirements for SNF coverage were not changed by BBA 1997; however, because RUG-III classification is based, in part, on the beneficiary's need for skilled nursing care and therapy, we have attempted, where possible, to coordinate claims review procedures with the outputs of beneficiary assessment and RUG-III classifying activities.

•

Consolidated Billing.

BBA 1997 included a billing provision that required a SNF to submit consolidated Medicare bills for its residents for almost all services that are covered under either Part A or Part B (the statute excluded a small list of services, primarily those of physicians and certain other types of practitioners). With the exception of physical therapy, occupational therapy, and speech-language therapy, section 313 of BIPA 2000 has now limited the scope of this

provision to apply only to those services that are furnished during the course of a resident's covered Part A stay in the SNF, as discussed later in this proposed rule.

•

Application of the SNF PPS to SNF services furnished by swing-bed hospitals.

Section 1883 of the Act permits certain small, rural hospitals to enter into a Medicare swing-bed agreement, under which the hospital can use its beds to provide either acute or SNF care, as needed. Part A currently pays for SNF services furnished by swing-bed hospitals on a cost-related basis. Section 1888(e)(7) of the Act requires the SNF PPS to encompass these services no earlier than cost reporting periods beginning on July 1, 1999, and no later than the end of the SNF PPS transition period described in section 1888(e)(2)(E) of the Act.

B. Requirements of the Balanced Budget Act of 1997 for Updating the Prospective Payment System for Skilled Nursing Facilities

Section 1888(e)(4)(H) of the Act requires that we publish in the

Federal Register:

1. The unadjusted Federal per diem rates to be applied to days of covered SNF services furnished during the FY.

2. The case-mix classification system to be applied with respect to these services during the FY.

3. The factors to be applied in making the area wage adjustment with respect to these services.

In the July 30, 1999 final rule (64 FR 41670), we indicated that we would announce any changes to the guidelines for Medicare level of care determinations related to modifications in the RUG-III classification structure.

Along with a number of other revisions discussed later in this preamble, this proposed rule provides the annual updates to the Federal rates as mandated by the Act.

C. The Medicare, Medicaid, and SCHIP Balanced Budget Refinement Act of 1999 (BBRA 1999)

There were several provisions in BBRA 1999 that resulted in adjustments to the PPS for SNFs. The provisions were described in the final rule that we published on July 31, 2000 (65 FR 46770). In particular, section 101 provided for a temporary, 20 percent increase in the per diem adjusted payment rates for 15 specified RUG-III groups (SE3, SE2, SE1, SSC, SSB, SSA, CC2, CC1, CB2, CB1, CA2, CA1, RHC, RMC, and RMB). Section 101 also included a 4 percent across-the-board increase in the adjusted Federal per diem payment rates each year for FYs 2001 and 2002, exclusive of the 20 percent increase.

We included further information on all of the provisions of BBRA 1999 in Program Memorandums A-99-53 and A-99-61 (December 1999), and Program Memorandum AB-00-18 (March 2000).

D. The Medicare, Medicaid, and SCHIP Benefits Improvement and Protection Act of 2000 (BIPA 2000)

The following highlights the major provisions in BIPA 2000 that result in adjustments to the PPS for SNFs:

•

Section 203—Exemption of Critical Access Hospital (CAH) Swing-beds from SNF PPS.

This provision exempts swing-beds in CAHs from section 1888(e)(7) of the Act (as enacted by section 4432(a) of BBA 1997) which applies the SNF PPS to SNF services furnished by swing-bed hospitals. Accordingly, this provision enables CAHs to be paid for their swing-bed SNF services on a reasonable cost basis. This provision is effective with cost reporting periods beginning on or after December 21, 2000, the date of the enactment of this Act. We include further information on this provision in Program Memorandum A-01-09 (January 16, 2001).

•

Section 311—Elimination of Reduction in SNF Market Basket Update in 2001.

This provision eliminates the one percent reduction reflected in the update formula for the Federal rates for FY 2001 that was required by BBA 1997. In implementing this change, this provision modifies the schedule and rates according to which Federal per diem payments are updated. For FY 2002 and FY 2003, the updates would be the market basket index increase minus 0.5 percentage points. This provision also provides a special rule that, for purposes of making payments under the SNF PPS for FY 2001, for the first half of FY 2001 (the period beginning October 1, 2000, and ending March 31, 2001), the market basket update remains at market basket minus 1, and for the second half of the fiscal year (the period beginning on April 1, 2001, and ending on September 30, 2001), the market basket update changes from market basket minus 1 to market basket plus 1.

In addition, this provision requires the General Accounting Office (GAO) to submit a report to Congress by July 1, 2002, on the adequacy of SNF payment rates. It also requires the Secretary to conduct a study of the different systems for categorizing patients in SNFs in a manner that accounts for the relative resource utilization of different patient types, and to submit a report to Congress not later than January 1, 2005.

•

Section 312—Increase in Nursing Component of PPS Federal Rate.

This provision requires the Secretary to increase by 16.66 percent the nursing component of the case-mix adjusted Federal rate specified in the July 31, 2000 final rule (65 FR 46770) for services furnished on or after April 1, 2001, and before October 1, 2002. This provision also requires the GAO to conduct an audit of SNF nursing staff ratios, and to submit a report to Congress by August 1, 2002, including a recommendation on whether the temporary 16.66 percent increase in the nursing component should be continued.

•

Section 313—Application of SNF Consolidated Billing Requirement Limited to Part A Covered Stays.

This provision repeals the consolidated billing requirement for services (other than physical therapy, occupational therapy, and speech-language therapy) furnished to those SNF residents who are in non-covered stays, effective January 1, 2001. It also directs the Secretary to monitor Part B payments for such services, in order to guard against duplicate billing and the excessive provision of services.

•

Section 314—Adjustment of Rehabilitation RUGs to Correct Anomaly in Payment Rates.

For services furnished from April 1, 2001, until the date that RUG refinements are implemented, this provision requires the Secretary to increase by 6.7 percent the adjusted Federal per diem rate for all of the following RUG-III rehabilitation groups: RUC, RUB, RUA, RVC, RVB, RVA, RHC, RHB, RHA, RMC, RMB, RMA, RLB, and RLA. This provision amends section 101(b) of BBRA 1999 and supersedes the 20 percent increase that BBRA 1999 had previously established for the RHC, RMC, and RMB rehabilitation groups, and corrects the resulting anomaly under which the payment rates for these particular groups were actually higher than the rates for some other, more intensive rehabilitation RUGs. This provision also requires the Office of Inspector General (OIG) to review whether the RUG payment structure in effect under BBRA 1999 included incentives for the delivery of inadequate care and report to the Congress by October 1, 2001.

•

Section 315—Establishment of Process for Geographic Reclassification.

This provision explicitly permits the Secretary to establish a geographic reclassification procedure that is specific to SNFs, for purposes of payment for covered SNF services under the PPS. The Secretary may not implement this procedure until the

Secretary has collected data necessary to establish a SNF wage index that is based on wage data from nursing homes.

We include further information on several of these provisions in Program Memorandum A-01-08 (January 16, 2001).

E. Skilled Nursing Facility Prospective Payment—General Overview

The Medicare SNF PPS was implemented for cost reporting periods beginning on or after July 1, 1998. Under the PPS, SNFs are paid through prospective, case-mix adjusted per diem payment rates applicable to all covered SNF services. These payment rates cover all the costs of furnishing covered skilled nursing services (routine, ancillary, and capital-related costs) other than costs associated with approved educational activities. Covered SNF services include post-hospital services for which benefits are provided under Part A and all items and services that, before July 1, 1998, had been paid under Part B (other than physician and certain other services specifically excluded under BBA 1997) but furnished to Medicare beneficiaries in a SNF during a Part A covered stay. A complete discussion of these provisions appears in the May 12, 1998 interim final rule (63 FR 26252).

1. Payment Provisions—Federal Rate

The PPS uses per diem Federal payment rates based on mean SNF costs in a base year updated for inflation to the first effective period of the PPS. We developed the Federal payment rates using allowable costs from hospital-based and freestanding SNF cost reports for reporting periods beginning in FY 1995. The data used in developing the Federal rates also incorporated an estimate of the amounts that would be payable under Part B for covered SNF services furnished to individuals who were receiving Part A covered services in a SNF.

In developing the rates for the initial period, we updated costs to the first effective year of PPS (15-month period beginning July 1, 1998) using a SNF market basket index, and then standardized for the costs of facility differences in case-mix and for geographic variations in wages. Providers that received new provider exemptions from the routine cost limits were excluded from the database used to compute the Federal payment rates, as well as costs related to payments for exceptions to the routine cost limits. In accordance with the formula prescribed in BBA 1997, we set the Federal rates at a level equal to the weighted mean of freestanding costs plus 50 percent of the difference between the freestanding mean and weighted mean of all SNF costs (hospital-based and freestanding) combined. We computed and applied separately the payment rates for facilities located in urban and rural areas. In addition, we adjusted the portion of the Federal rate attributable to wage-related costs by a wage index.

The Federal rate also incorporates adjustments to account for facility case-mix, using a classification system that accounts for the relative resource utilization of different patient types. This classification system, RUG-III, utilizes beneficiary assessment data from the Minimum Data Set (MDS) completed by SNFs to assign beneficiaries to one of 44 groups. The May 12, 1998 interim final rule (63 FR 26252) included a complete and detailed description of the RUG-III classification system.

The Federal rates in this proposed rule reflect an update to the rates in the July 31, 2000 update notice (65 FR 46770) equal to the SNF market basket index minus 0.5 percent, as well as the elimination of the 1 percent reduction reflected in the update formula for the FY 2001 payment rates under section 311 of BIPA 2000. According to section 311 of BIPA 2000, for FY 2002, we will update the rate by adjusting the current rates by the SNF market basket change minus 0.5 percent.

2. Payment Provisions—Transition Period

The SNF PPS includes an initial, phased transition from a facility-specific rate (which reflects the individual facility's historical cost experience) to the Federal case-mix adjusted rate. The transition extends through the facility's first three cost reporting periods under the PPS, up to and including the one that begins in FY 2001. Accordingly, starting with cost reporting periods that begin in FY 2002, we will base payments entirely on the Federal rates.

F. Skilled Nursing Facility Market Basket Index

Section 1888(e)(5) of the Act requires the Secretary to establish a SNF market basket index that reflects changes over time in the prices of an appropriate mix of goods and services included in the covered SNF services. The SNF market basket index is used to update the Federal rates on an annual basis. We are proposing a revised and rebased SNF market basket index that consists of the most commonly used cost categories for SNF routine services, ancillary services, and capital-related expenses. A complete discussion concerning the design and application of the proposed SNF market basket index is presented in Section III.

II. Update of Payment Rates Under the Prospective Payment System for Skilled Nursing Facilities

A. Federal Prospective Payment System

This proposed rule sets forth a schedule of Federal prospective payment rates applicable to Medicare Part A SNF services beginning October 1, 2001. The schedule incorporates per diem Federal rates that provide Part A payment for all costs of services furnished to a beneficiary in a SNF during a Medicare-covered stay.

1. Costs and Services Covered by the Federal Rates

The Federal rates apply to all costs (routine, ancillary, and capital-related costs) of covered SNF services other than costs associated with approved educational activities as defined in § 413.85. Under section 1888(e)(2) of the Act, covered SNF services include post-hospital SNF services for which benefits are provided under Part A (the hospital insurance program), as well as all items and services (other than those services excluded by statute) that, before July 1, 1998, were paid under Part B (the supplementary medical insurance program) but furnished to Medicare beneficiaries in a SNF during a Part A covered stay. (These excluded service categories are discussed in greater detail in section V.B.2. of the May 12, 1998 interim final rule (63 FR 26295-97)).

2. Methodology Used for the Calculation of the Federal Rates

The proposed FY 2002 rates would reflect an update using the latest market basket index minus 0.5 percentage point. The FY 2002 market basket update factor is 2.9 percent, and subtracting 0.5 percentage points yields an update of 2.4 percent. For a complete description of the multi-step process, see the May 12, 1998 interim final rule (63 FR 26252). In accordance with section 101 of BBRA 1999 and section 314 of BIPA 2000, we have provided for a temporary increase in the per diem adjusted payment rates of 20 percent for certain specified RUGs, and 6.7 percent for certain others. These temporary increases of 20 percent and 6.7 percent for certain specified RUGs will continue until implementation of case-mix refinements, as described in section 101 of BBRA 1999 and section 314 of BIPA 2000. Also, in accordance with section 101 of BBRA 1999, we are providing a 4 percent increase in the adjusted Federal rate for FY 2002. These temporary adjustments (that is, 20

percent, 6.7 percent, or 4 percent) are not reflected in the rate tables (Tables 1, 2, 3, 4, 5, and 6 of this proposed rule). Rather, in accordance with the statute, they are applied only after all other adjustments (wage and case-mix) have been made. Further, several provisions of BIPA 2000 affect the payment rates for SNFs, as described in the previous section.

We used the SNF market basket to adjust each per diem component of the Federal rates forward to reflect cost increases occurring between the midpoint of the Federal FY beginning October 1, 2000, and the midpoint of the Federal FY beginning October 1, 2001 and ending September 30, 2002, to which the payment rates apply. In accordance with section 311 of BIPA 2000, the payment rates are updated for FY 2002 by a factor equal to the annual market basket index percentage increase minus 0.5 percentage point. However, we note that section 311 of BIPA 2000 has also eliminated the one percent reduction in the market basket associated with the establishment of the FY 2001 payment rates. Therefore, in establishing the payment rates for FY 2002, we would update from the FY 2001 payment rates determined using the full market basket amount for that year rather than the rates as they appeared in the July 31, 2000 final rule (65 FR 46770), that were determined using the one percent reduction. As modified in this manner to reflect section 311 of BIPA 2000, the FY 2001 rates would be updated using the latest market basket minus 0.5 percentage point to determine the payment rates for FY 2002. The nursing case-mix component of the proposed rates, both urban and rural, includes the 16.66 percent increase provided by section 312 of BIPA 2000. The rates are further adjusted by a wage index budget neutrality factor, described later in this section. Tables 1 and 2 reflect the updated components of the unadjusted Federal rates (including both the market basket adjustment and the 16.66 percent increase in the nursing case-mix component).

Table 1.—Unadjusted Federal Rate Per Diem, Urban

Rate component

Nursing—

case-mix

Therapy—

case-mix

Therapy—

non-case-mix

Non-case-mix

Per Diem Amount

$137.89

$89.03

$11.73

$60.33

Table 2.—Unadjusted Federal Rate Per Diem, Rural

Rate component

Nursing—

case-mix

Therapy—

case-mix

Therapy—

non-case-mix

Non-case-mix

Per Diem Amount

$131.76

$102.67

$12.53

$61.44

B. Case-Mix Adjustment

For FY 2002, we are not proposing to modify the case-mix classification system. The payment rates set forth in this proposed rule reflect the continued use of the existing 44-group RUG-III classification system discussed in the May 12, 1998 interim final rule (63 FR 26252). Consequently, we will also maintain the add-ons to the Federal rates for specified RUG-III groups, as required by section 101 of BBRA 1999 and subsequently modified by section 314 of BIPA 2000. The case-mix adjusted payment rates are listed separately for urban and rural SNFs in Tables 3 and 4, with the corresponding case-mix index values. These tables do not reflect the add-ons (that is, 20 percent, 6.7 percent, or 4 percent) provided for in BBRA 1999 and BIPA 2000, which are applied only after all other adjustments (wage and case-mix) have been made.

Table 3.—Case-Mix Adjusted Federal Rates and Associated Indexes Urban

RUG III category

Nursing

index

Therapy

index

Nursing

component

Therapy

component

Non-case mix

therapy comp.

Non-case mix

component

Total rate

RUC

1.30

2.25

179.26

200.32

60.33

439.91

RUB

0.95

2.25

131.00

200.32

60.33

391.65

RUA

0.78

2.25

107.55

200.32

60.33

368.20

RVC

1.13

1.41

155.82

125.53

60.33

341.68

RVB

1.04

1.41

143.41

125.53

60.33

329.27

RVA

0.81

1.41

111.69

125.53

60.33

297.55

RHC

1.26

0.94

173.74

83.69

60.33

317.76

RHB

1.06

0.94

146.16

83.69

60.33

290.18

RHA

0.87

0.94

119.96

83.69

60.33

263.98

RMC

1.35

0.77

186.15

68.55

60.33

315.03

RMB

1.09

0.77

150.30

68.55

60.33

279.18

RMA

0.96

0.77

132.37

68.55

60.33

261.25

RLB

1.11

0.43

153.06

38.28

60.33

251.67

RLA

0.80

0.43

110.31

38.28

60.33

208.92

SE3

1.70

234.41

11.73

60.33

306.47

SE2

1.39

191.67

11.73

60.33

263.73

SE1

1.17

161.33

11.73

60.33

233.39

SSC

1.13

155.82

11.73

60.33

227.88

SSB

1.05

144.78

11.73

60.33

216.84

SSA

1.01

139.27

11.73

60.33

211.33

CC2

1.12

154.44

11.73

60.33

226.50

CC1

0.99

136.51

11.73

60.33

208.57

CB2

0.91

125.48

11.73

60.33

197.54

CB1

0.84

115.83

11.73

60.33

187.89

CA2

0.83

114.45

11.73

60.33

186.51

CA1

0.75

103.42

11.73

60.33

175.48

IB2

0.69

95.14

11.73

60.33

167.20

IB1

0.67

92.39

11.73

60.33

164.45

IA2

0.57

78.60

11.73

60.33

150.66

IA1

0.53

73.08

11.73

60.33

145.14

BB2

0.68

93.77

11.73

60.33

165.83

BB1

0.65

89.63

11.73

60.33

161.69

BA2

0.56

77.22

11.73

60.33

149.28

BA1

0.48

66.19

11.73

60.33

138.25

PE2

0.79

108.93

11.73

60.33

180.99

PE1

0.77

106.18

11.73

60.33

178.24

PD2

0.72

99.28

11.73

60.33

171.34

PD1

0.70

96.52

11.73

60.33

168.58

PC2

0.65

89.63

11.73

60.33

161.69

PC1

0.64

88.25

11.73

60.33

160.31

PB2

0.51

70.32

11.73

60.33

142.38

PB1

0.50

68.95

11.73

60.33

141.01

PA2

0.49

67.57

11.73

60.33

139.63

PA1

0.46

63.43

11.73

60.33

135.49

Table 4.—Case-Mix Adjusted Federal Rates and Associated Indexes, Rural

RUG III category

Nursing

index

Therapy

index

Nursing

component

Therapy

component

Non-case mix

therapy comp

Non-case mix

component

Total rate

RUC

1.30

2.25

171.29

231.01

61.44

463.74

RUB

0.95

2.25

125.17

231.01

61.44

417.62

RUA

0.78

2.25

102.77

231.01

61.44

395.22

RVC

1.13

1.41

148.89

144.76

61.44

355.09

RVB

1.04

1.41

137.03

144.76

61.44

343.23

RVA

0.81

1.41

106.73

144.76

61.44

312.93

RHC

1.26

0.94

166.02

96.51

61.44

323.97

RHB

1.06

0.94

139.67

96.51

61.44

297.62

RHA

0.87

0.94

114.63

96.51

61.44

272.58

RMC

1.35

0.77

177.88

79.06

61.44

318.38

RMB

1.09

0.77

143.62

79.06

61.44

284.12

RMA

0.96

0.77

126.49

79.06

61.44

266.99

RLB

1.11

0.43

146.25

44.15

61.44

251.84

RLA

0.80

0.43

105.41

44.15

61.44

211.00

SE3

1.70

223.99

12.53

61.44

297.96

SE2

1.39

183.15

12.53

61.44

257.12

SE1

1.17

154.16

12.53

61.44

228.13

SSC

1.13

148.89

12.53

61.44

222.86

SSB

1.05

138.35

12.53

61.44

212.32

SSA

1.01

133.08

12.53

61.44

207.05

CC2

1.12

147.57

12.53

61.44

221.54

CC1

0.99

130.44

12.53

61.44

204.41

CB2

0.91

119.90

12.53

61.44

193.87

CB1

0.84

110.68

12.53

61.44

184.65

CA2

0.83

109.36

12.53

61.44

183.33

CA1

0.75

98.82

12.53

61.44

172.79

IB2

0.69

90.91

12.53

61.44

164.88

IB1

0.67

88.28

12.53

61.44

162.25

IA2

0.57

75.10

12.53

61.44

149.07

IA1

0.53

69.83

12.53

61.44

143.80

BB2

0.68

89.60

12.53

61.44

163.57

BB1

0.65

85.64

12.53

61.44

159.61

BA2

0.56

73.79

12.53

61.44

147.76

BA1

0.48

63.24

12.53

61.44

137.21

PE2

0.79

104.09

12.53

61.44

178.06

PE1

0.77

101.46

12.53

61.44

175.43

PD2

0.72

94.87

12.53

61.44

168.84

PD1

0.70

92.23

12.53

61.44

166.20

PC2

0.65

85.64

12.53

61.44

159.61

PC1

0.64

84.33

12.53

61.44

158.30

PB2

0.51

67.20

12.53

61.44

141.17

PB1

0.50

65.88

12.53

61.44

139.85

PA2

0.49

64.56

12.53

61.44

138.53

PA1

0.46

60.61

12.53

61.44

134.58

We remain committed to efforts to monitor the RUG-III classification system and to pursue refinements in SNF payment. In the proposed rule associated with the FY 2001 SNF PPS update published April 10, 2000 (65 FR 19188), we had discussed options for refinements to the RUG-III classification system to account more accurately for the services provided to medically complex patients. The refinement approaches discussed had a particular focus on ancillary services other than rehabilitation (physical, occupational, and speech-language therapy), such as prescription drugs and respiratory therapy. We described our ongoing research and analyses in this area and shared the initial results that we proposed be incorporated into the Medicare SNF PPS system effective October 1, 2000. In that proposed rule, we cautioned that the proposed RUG-III refinements were based on limited data from seven states from periods prior to the implementation of the SNF PPS (1996 and 1997). Consequently, we indicated our plan to validate the findings using more current data from a broad national sample before issuing a final rule.

As discussed in the final rule published on July 31, 2000 (65 FR 46770), we conducted the validation analyses to determine the predictive power of the proposed case-mix models in identifying variations in non-therapy ancillary costs, using national data from a current period (that is, after the implementation of the SNF PPS). Based on these analyses, we determined that the refinement models developed using the pre-PPS sample were not effective in predicting resource use in the post-PPS environment. We identified several important variations in the post-PPS volume and distribution of beneficiaries and ancillary services costs using the 1999 national data, which appear to have affected the performance of the case-mix refinement models described in the proposed rule. We noted our belief that the introduction of the PPS and consolidated billing provisions for covered Part A SNF stays may have caused changes in facility practice patterns and billing. These changes, as well as the use of the broader national data sample, likely diminished the effectiveness of the models. Accordingly, in the final rule, we indicated our decision not to proceed with the implementation of case-mix refinements for FY 2001.

However, this decision did not in any way reflect a lack of commitment to pursuing appropriate case-mix refinements, and we remain dedicated to achieving this objective as quickly as possible. While the language in section 101 of BBRA 1999 does not directly mandate that we make case-mix refinements, we believe it nonetheless reflects a clear expectation that refinements will occur, by establishing payment adjustments that will expire upon the implementation of case-mix refinements, and by characterizing those adjustments as temporary. Accordingly, we are continuing our active efforts in this area, with the expectation that we will, over the next 12 months, develop case-mix refinements.

The inability of the specific case-mix refinement models based on a pre-PPS study sample (as described in the FY 2001 proposed rule) to explain behavior adequately in the post-PPS data does not warrant the conclusion that further efforts to improve the payment system's ability to allocate payments based on expected ancillary use would be unproductive. In fact, we believe there may well be the potential to establish meaningful refinements in the short term based on the results of a deliberate, comprehensive analysis using the extensive MDS 2.0, claims, and other administrative data now available. Moreover, this research will also provide an important foundation for a longer term analysis which seeks to identify alternative classification approaches in the SNF setting. The analysis we propose to conduct will be included in the report to Congress mandated by section 311 of BIPA 2000. This section requires us to submit the report no later than January 1, 2005. This work may also support a longer term goal, supported by HCFA and MedPAC, of developing more integrated approaches for the payment and delivery system for Medicare post acute services generally.

Therefore, we are currently proceeding with efforts to develop refinements to the RUG-III system, and are in the process of initiating a research contract in this area. We plan to look broadly for alternative refinement approaches that will improve the payment system's ability to account for the variation in resources associated with SNF patients generally, as well as medically complex patients and non-therapy ancillary services more specifically. This may include further analysis to develop a non-therapy ancillary index, similar to that proposed in the FY 2001 proposed rule, as well as exploration of other potential refinement approaches that could utilize information related to service use, function, diagnosis, and co-morbidities. In exploring possible refinement approaches, it is necessary to consider the potential effect of the refinements on aggregate SNF payments, as well as on access to and quality of care. In addition, we recognize the utility of using administrative data (such as claims) in the construction of the case-mix indexes and may, as MedPAC has recommended in the past, examine the potential for using this data to accomplish the tasks we are undertaking. Such an approach would facilitate annual updates to the case-mix indexes similar to the inpatient hospital PPS. In continuing this research, we will carefully consider the comments we received pursuant to the FY 2001 proposed rule. In addition, we specifically solicit comments in this proposed rule regarding possible approaches to refining the case-mix system.

While we recognize the need to seek improvements in the payment system, we are not aware of any substantive findings that demonstrate, as has been

suggested at recent MedPAC meetings, that the RUG-III system has proven to be unworkable. In fact, several recent reports indicate that quality and access do not appear to be impaired. This may be more a function of overall revenues available to SNFs under the PPS, especially considering recent increases in funding under BBRA 1999 and BIPA 2000. Even though they do not affect the current case-mix classification structure, a number of these recent payment increases are nonetheless intended to ensure that facilities continue to be paid appropriately until RUG refinements can be made. We also note that it may be premature to make assumptions regarding the effect of case-mix on provider behavior based on currently available data (which, at this point, still reflect only payments made during the transition period when SNFs received a blend of the Federal rate and facility-specific rate), since provider behavior may change significantly once payment is made under the fully case-mix adjusted Federal rates.

Further, it is worth noting that in research conducted to support the implementation of the SNF PPS, the RUG-III case-mix system was shown to predict approximately 55 percent of the overall variation in nursing and therapy staff time costs across total facility population (that includes both Medicare and Medicaid, as well as other patients). The level of variance explanation is somewhat less across the Medicare population due to its greater homogeneity. While we have not measured this directly, an examination of the 1997 staff time data focusing on patients in Medicare certified units that specialize in medically complex care or intensive rehabilitation found that RUG-III predicted 41 percent of nursing and rehabilitation staff time costs across total facility population (which includes Medicare, Medicaid, and private pay patients). We believe that it continues to be highly effective in this area. While we have found that pharmacy costs are correlated somewhat with the nursing case-mix indexes in RUG-III, it is important to note that such costs are, by and large, difficult to account for in case-mix systems because drug costs do not necessarily follow physical condition, resource use, or functional and clinical pathways.

We look forward to addressing this important issue through the study of alternative case-mix systems required under BIPA 2000, which provides an opportunity for a deliberate analytical approach to the question of how best to refine the current classification system or to redirect Medicare's payment system to produce more equitable payments for providers and best support access and quality of care for Medicare beneficiaries. Similarly, we look forward to the study required under section 545 of BIPA 2000 (required to be completed by January 1, 2005), which requires us to submit a report on the development of standard instruments for the assessment of the health and functional status of patients. We also invite comments on possible approaches to refining the current case-mix classification system, as well as on identifying and studying alternatives to the current system. With regard to the MDS 2.0, we continue to believe that the MDS is an accurate and effective assessment tool, which meets program objectives related to its major purposes of supporting quality of care and providing patient status and treatment information needed to support payment. We are currently engaged in a number of activities that support accurate completion of the MDS. These include expanded provider training, clearer definitions of certain MDS elements and coding instructions, and funding of program safeguard contractor activities to undertake auditing and verification of the MDS. We also note our concern that the OIG's recent reports related to the accuracy of the MDS contained a number of methodological limitations (as acknowledged in the reports) that limit their utility for drawing conclusions about the MDS.

However, we recognize the increased financial incentives that BIPA creates for the rehabilitation categories and the potential for upcoding under the SNF PPS to gain higher payments. In fact, the potential for inappropriate upcoding exists in any prospective payment system that uses coding of clinical information as the basis for determining payment amounts due to providers, and the SNF PPS (which bases payment amounts on the clinical information entered on the MDS) is no exception. In this context, we note that fiscal intermediaries (FIs) will continue reviewing SNF PPS bills. As with current practice, the FIs will focus on identifying instances in which inappropriate services were provided or where the beneficiary did not meet the requirements for Medicare Part A coverage in an SNF. As part of this review, the MDS and the medical record is assessed to verify that the reported information supports the RUG category billed.

We believe that the practice of FIs using a data driven approach to focus medical review efforts will help address the incentive for upcoding. Once bills have been targeted for review, the FIs will identify instances in which inappropriate services were provided or where the beneficiary did not meet the requirements for Medicare Part A coverage in a SNF. As part of this review, the medical record (which includes the MDS) is assessed to verify that the reported information supports the RUG category billed.

To lend further support to program safeguard efforts, we are in the process of awarding a contract to a Medicare Integrity Program (MIP) contractor to provide an ongoing centralized data surveillance process to assess the accuracy and reliability of MDS data particular to the health care furnished by SNFs, and payment for these services. This includes ensuring appropriate payment and payment denial decisions. The findings will produce evidence for further actions at national, regional, and State levels in addressing concerns in the areas of program integrity, beneficiary health and safety, and quality improvement. The contractor is also expected to perform monitoring and data analyses to determine if there are variations over time in the case-mix intensity, and whether those differences represent changes in actual or real case status of beneficiaries rather than changes that reflect improper provider behavior. Through the MIP contractor and the FIs, we will address instances of improper billing through recoupment of improper payments, intensified reviews, and provider education.

Further, in the context of our ongoing efforts to ensure accurate payment for appropriate care, we note a situation regarding rehabilitation therapy that is being provided in SNFs in a manner that conflicts with Medicare coverage guidelines. This issue involves providers that refuse to employ therapists who are unwilling to perform, on a routine basis, concurrent therapy. Concurrent therapy is the practice of one professional therapist treating more than one Medicare beneficiary at a time—in some cases, many more than one individual at a time.

Concurrent therapy is distinguished from group therapy, because all participants in group therapy are working on some common skill development and the ratio of participants to therapist may be no higher than 4 to 1. In addition, in the July 30, 1999 SNF PPS final rule (64 FR 41662), we specified that the minutes of group therapy received by the beneficiary may account for no more than 25 percent of the therapy (per discipline) received in a 7 day period. By contrast, a beneficiary who is receiving concurrent therapy with one or more other beneficiaries likely is not

receiving services that relate to those needed by any of the other participants. Although each beneficiary may be receiving care that is prescribed in his individual plan of treatment, it is not being delivered according to Medicare coverage guidelines; that is, the therapy is not being provided individually, and it is unlikely that the services being delivered are at the complex skill level required for coverage by Medicare.

The Medicare SNF benefit provides coverage of therapy services only when the services are of such a level of complexity and sophistication (or the beneficiary's condition is such) that the services can be safely and effectively performed only by or under the supervision of a qualified professional therapist. Therapy services that are concurrently being delivered by one treating therapist to many beneficiaries would not appear to meet these criteria. If the therapist or therapy assistant can provide distinct services to several beneficiaries at once, then it is unlikely that the services are sufficiently complex and sophisticated to qualify for coverage under the Medicare guidelines.

We note that there have always been isolated instances in which a professional therapist has been allowed to have some overlap in the time of concluding treatment to one individual and the time of commencing the treatment of another, even to the point of briefly providing therapy concurrently in certain cases. However, the key principle here is that Medicare relies on the professional judgment of the therapist to determine when, based on the complexity of the services to be delivered and the condition of the beneficiary, it is appropriate to deliver care to more than one beneficiary at the same time. Our concern now is that in some areas of the country, concurrent therapy is becoming a standard practice rather than the exception, and is being dictated by facility management personnel rather than according to the professional judgment of the therapists involved.

We believe that it is important to heighten the SNF and therapy industries' awareness of the applicable Medicare policy in this regard. Medicare policy has not, until now, specifically addressed coverage of skilled rehabilitation therapy in situations in which a single professional therapist (or therapy assistant under the supervision of the professional therapist) simultaneously provides different treatments to multiple beneficiaries. As noted above, we have relied on the professional therapist's judgment as to when it is appropriate for an individual therapist to provide services to more than one beneficiary. We now wish to advise the providers of care of our concern about the potentially adverse effect of this practice on the quality of the therapy provided to beneficiaries in Part A SNF stays, as well as our concern about the implications of making payments in such situations. We solicit public comments regarding the scope and magnitude of this problem, and possible approaches for addressing this issue.

C. Wage Index Adjustment to Federal Rates

Section 1888(e)(4)(G)(ii) of the Act requires that we adjust the Federal rates to account for differences in area wage levels, using an appropriate wage index, as determined by the Secretary. Section 315 of BIPA 2000 authorizes the Secretary to establish a reclassification system for SNFs, similar to the hospital methodology. This reclassification system cannot be implemented until the Secretary has collected data necessary to establish an area wage index for SNFs based on wage data from such facilities. Pursuant to section 106(a) of the Social Security Act Amendments of 1994 (P.L. 103-432), the Secretary was directed to begin to collect data on employee compensation and paid hours of employment in SNFs for the purpose of constructing a SNF wage index. Since the inception of a PPS for SNFs, we have utilized hospital wage data in developing a wage index to be applied to SNFs.

The computation of the proposed wage index is similar to past years because we incorporate the latest data and methodology used to construct the hospital wage index (see the discussion in the May 12, 1998 interim final rule (63 FR 26274)). The wage index adjustment is applied to the proposed labor-related portion of the Federal rate, which is 75.374 percent of the total rate. This percentage reflects the labor-related relative importance for FY 2002. The labor-related relative importance is calculated from the SNF market basket, and approximates the labor-related portion of the total costs after taking into account historical and projected price changes between the base year and FY 2002. 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 2002 than the base year weights from the SNF market basket.

We calculate the labor-related relative importance for FY 2002 in four steps. First, we compute the FY 2002 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 2002 price index level for that cost category by the total market basket price index level. Third, we determine the FY 2002 relative importance for each cost category by multiplying this ratio by the base year (FY 1997) weight. Finally, we sum the FY 2002 relative importance for each of the labor-related cost categories (that is, wages and salaries; employee benefits; nonmedical professional fees; labor-intensive services; and, capital-related) to produce the FY 2002 labor-related relative importance. Tables 5 and 6 show the Federal rates by labor-related and non-labor-related components.

Table 5.—Case-Mix Adjusted Federal Rates for Urban SNFs by Labor and Non-Labor Component

RUG III

category

Total

rate

Labor

portion

Non-labor

portion

RUC

439.91

331.58

108.33

RUB

391.65

295.20

96.45

RUA

368.20

277.53

90.67

RVC

341.68

257.54

84.14

RVB

329.27

248.18

81.09

RVA

297.55

224.28

73.27

RHC

317.76

239.51

78.25

RHB

290.18

218.72

71.46

RHA

263.98

198.97

65.01

RMC

315.03

237.45

77.58

RMB

279.18

210.43

68.75

RMA

261.25

196.91

64.34

RLB

251.67

189.69

61.98

RLA

208.92

157.47

51.45

SE3

306.47

231.00

75.47

SE2

263.73

198.78

64.95

SE1

233.39

175.92

57.47

SSC

227.88

171.76

56.12

SSB

216.84

163.44

53.40

SSA

211.33

159.29

52.04

CC2

226.50

170.72

55.78

CC1

208.57

157.21

51.36

CB2

197.54

148.89

48.65

CB1

187.89

141.62

46.27

CA2

186.51

140.58

45.93

CA1

175.48

132.27

43.21

IB2

167.20

126.03

41.17

IB1

164.45

123.95

40.50

IA2

150.66

113.56

37.10

IA1

145.14

109.40

35.74

BB2

165.83

124.99

40.84

BB1

161.69

121.87

39.82

BA2

149.28

112.52

36.76

BA1

138.25

704.20

34.05

PE2

780.99

136.42

44.57

PE1

178.24

134.35

43.89

PD2

171.34

129.15

42.19

PD1

168.58

127.07

41.51

PC2

161.69

121.87

39.82

PC1

160.31

120.83

39.48

PB2

142.38

107.32

35.06

PB1

141.01

106.28

34.73

PA2

139.63

105.24

34.39

PA1

135.49

102.12

33.37

Table 6.—Case-Mix Adjusted Federal Rates for Rural SNFs by Labor and Non-Labor Component

RUG III

category

Total

rate

Labor

portion

Non-labor

portion

RUC

463.74

349.54

114.20

RUB

417.62

314.78

102.84

RUA

395.22

297.89

97.33

RVC

355.09

267.65

87.44

RVB

343.23

258.71

84.52

RVA

312.93

235.87

77.06

RHC

323.97

244.19

79.78

RHB

297.62

224.33

73.29

RHA

272.58

205.45

67.13

RMC

318.38

239.98

78.40

RMB

284.12

214.15

69.97

RMA

266.99

201.24

65.75

RLB

251.84

189.82

62.02

RLA

211.00

159.04

51.96

SE3

297.96

224.58

73.38

SE2

257.12

193.80

63.32

SE1

228.13

171.95

56.18

SSC

222.86

167.98

54.88

SSB

212.32

160.03

52.29

SSA

207.05

156.06

50.99

CC2

221.54

166.98

54.56

CC1

204.41

154.07

50.34

CB2

193.87

146.13

47.74

CB1

184.65

139.18

45.47

CA2

183.33

138.18

45.15

CA1

172.79

130.24

42.55

IB2

164.88

124.28

40.60

IB1

162.25

122.29

39.96

IA2

149.07

112.36

36.71

IA1

143.80

108.39

35.41

BB2

163.57

123.29

40.28

BB1

159.61

120.30

39.31

BA2

147.76

111.37

36.39

BA1

137.21

103.42

33.79

PE2

178.06

134.21

43.85

PE1

175.43

132.23

43.20

PD2

168.84

127.26

41.58

PD1

166.20

125.27

40.93

PC2

159.61

120.30

39.31

PC1

158.30

119.32

38.98

PB2

141.17

106.41

34.76

PB1

139.85

105.41

34.44

PA2

138.53

104.42

34.11

PA1

134.58

101.44

33.14

Section 1888(e)(4)(G)(ii) of the Act also requires that the application of this wage index be made in a manner that does not result in aggregate payments that are greater or lesser than would otherwise be made in the absence of the wage adjustment. In this fourth PPS year (Federal rates effective October 1, 2001), we are updating the wage index applicable to SNF payments using the most recent hospital wage data and applying an adjustment to fulfill the budget neutrality requirement. This requirement will be met by multiplying each of the components of the unadjusted Federal rates by a factor equal to the ratio of the volume weighted mean wage adjustment factor (using the wage index from the previous year) to the volume weighted mean wage adjustment factor, using the wage index for the FY beginning October 1, 2001. The same volume weights are used in both the numerator and denominator and will be derived from 1997 Medicare Provider Analysis and Review File (MEDPAR) data. The wage adjustment factor used in this calculation is defined as the labor share of the rate component multiplied by the wage index plus the non-labor share. The proposed budget neutrality factor for FY 2002 is .99939.

Over the past few years, we have received many comments asking that we evaluate a SNF-specific wage index, which would be based solely on wage and hourly data from SNFs. To develop this analysis, a schedule was added to the cost report to gather wage and hourly data from each SNF. In this proposed rule we are publishing a wage index prototype based on SNF data, along with the wage index based on the hospital wage data that was used in the FY 2001 final rule published July 31, 2000 in the

Federal Register

(65 FR 46770).

The wage index computations for the SNF prototype were done in the same manner as the current wage index based on hospital data, except that SNFs use one of three cost reports to report their data: Freestanding SNFs use the HCFA-2540, Worksheet S-3; hospital-based SNFs use the HCFA-2552, Worksheet S-3; and low-volume SNF providers use the HCFA-2540-S, Worksheet S-3.

The SNF-specific wage indexes illustrated in Table 7 include the following categories of data associated with costs paid under the SNF PPS:

• Salaries and hours from freestanding and hospital-based SNFs.

• Home office costs and hours.

• Certain contract labor costs and hours.

• Wage-related costs.

Consistent with the wage index methodology used in the development of the hospital wage index, the wage indexes published here would also continue to exclude the direct and overhead costs of salaries and hours for services not paid through the SNF PPS, such as home health services, and other sub-provider components that are not subject to the PPS. In addition, as is done in computing the hospital wage index, we would phase out costs associated with graduate medical education (GME) (teaching physicians and residents). For purposes of illustrating the wage indexes shown in Table 7, the SNF wage index is based on a blend of 60 percent of an average hourly wage including the GME costs, and 40 percent of an average hourly wage excluding these costs.

Table 7 shows a side by side comparison of the wage index. Column A shows the Metropolitan Statistical Area (MSA); Column B shows the wage index, utilizing data derived from SNFs with cost reporting periods ending during FY 1998; Column C shows the wage index developed using SNF data from cost reporting periods ending during FY 1999; and Column D shows the wage index from the FY 2001 final rule, as revised by the correction notice published on January 16, 2001 (66 FR 3497).

Table 7.—Wage Index For Urban Areas

Urban Area (Constituent Counties or County Equivalents)

Wage Index

SNF98

SNF99

HOSP

Col. A

Col. B

Col. C

Col. D

0040 Abilene, TX

0.7354

0.8162

0.8240

Taylor, TX

0060 Aguadilla, PR

0.0000

0.0000

0.4391

Aguada, PR

Aguadilla, PR

Moca, PR

0080 Akron, OH

0.9636

1.0553

0.9736

Portage, OH

Summit, OH

0120 Albany, GA

0.6203

0.7460

0.9933

Dougherty, GA

Lee, GA

0160 Albany-Schenectady-Troy, NY

1.0860

1.0809

0.8549

Albany, NY

Montgomery, NY

Rensselaer, NY

Saratoga, NY

Schenectady, NY

Schoharie, NY

0200 Albuquerque, NM

0.7892

0.7980

0.9136

Bernalillo, NM

Sandoval, NM

Valencia, NM

0220 Alexandria, LA

0.7849

0.6318

0.8123

Rapides, LA

0240 Allentown-Bethlehem-Easton, PA

1.1553

1.0749

0.9925

Carbon, PA

Lehigh, PA

Northampton, PA

0280 Altoona, PA

0.9559

0.9712

0.9346

Blair, PA

0320 Amarillo, TX

0.8377

0.8338

0.8715

Potter, TX

Randall, TX

0380 Anchorage, AK

1.5003

1.4716

1.2793

Anchorage, AK

0440 Ann Arbor, MI

1.0845

1.1059

1.1254

Lenawee, MI

Livingston, MI

Washtenaw, MI

0450 Anniston, AL

0.7619

0.9226

0.8284

Calhoun, AL

0460 Appleton-Oshkosh-Neenah, WI

1.0962

1.0662

0.9052

Calumet, WI

Outagamie, WI

Winnebago, WI

0470 Arecibo, PR

0.0000

0.0000

0.4525

Arecibo, PR

Camuy, PR

Hatillo, PR

0480 Asheville, NC

0.9090

0.9482

0.9516

Buncombe, NC

Madison, NC

0500 Athens, GA

0.9653

0.9264

0.9739

Clarke, GA

Madison, GA

Oconee, GA

0520 Atlanta, GA

0.9733

0.9474

1.0096

Barrow, GA

Bartow, GA

Carroll, GA

Cherokee, GA

Clayton, GA

Cobb, GA

Coweta, GA

De Kalb, GA

Douglas, GA

Fayette, GA

Forsyth, GA

Fulton, GA

Gwinnett, GA

Henry, GA

Newton, GA

Paulding, GA

Pickens, GA

Rockdale, GA

Spalding, GA

Walton, GA

0560 Atlantic City-Cape May, NJ

1.1443

1.1406

1.1182

Atlantic City, NJ

Cape May, NJ

0580 Auburn-Opelika, AL

0.9892

0.8857

0.8106

Lee, AL

0600 Augusta-Aiken, GA-SC

0.7831

0.7898

0.9160

Columbia, GA

McDuffie, GA

Richmond, GA

Aiken, SC

Edgefield, SC

0640 Austin-San Marcos, TX

0.8694

0.8826

0.9577

Bastrop, TX

Caldwell, TX

Hays, TX

Travis, TX

Williamson, TX

0680 Bakersfield, CA

1.0005

1.0059

0.9678

Kern, CA

0720 Baltimore, MD

1.0144

0.9797

0.9365

Anne Arundel, MD

Baltimore, MD

Baltimore City, MD

Carroll, MD

Harford, MD

Howard, MD

Queen Annes, MD

0733 Bangor, ME

1.0358

0.8851

0.9561

Penobscot, ME

0743 Barnstable-Yarmouth, MA

1.2663

1.2722

1.3839

Barnstable, MA

0760 Baton Rouge, LA

0.7459

0.7803

0.8842

Ascension, LA

East Baton Rouge, LA

Livingston, LA

West Baton Rouge, LA

0840 Beaumont-Port Arthur, TX

0.8049

0.7895

0.8744

Hardin, TX

Jefferson, TX

Orange, TX

0860 Bellingham, WA

0.9121

0.8984

1.1439

Whatcom, WA

0870 Benton Harbor, MI

0.8766

0.9098

0.8671

Berrien, MI

0875 Bergen-Passaic, NJ

1.3811

1.2739

1.1848

Bergen, NJ

Passaic, NJ

0880 Billings, MT

0.9429

0.9017

0.9585

Yellowstone, MT

0920 Biloxi-Gulfport-Pascagoula, MS

0.8023

0.9676

0.8236

Hancock, MS

Harrison, MS

Jackson, MS

0960 Binghamton, NY

0.9400

0.9231

0.8690

Broome, NY

Tioga, NY

1000 Birmingham, AL

0.8846

0.9155

0.8452

Blount, AL

Jefferson, AL

St. Clair, AL

Shelby, AL

1010 Bismarck, ND

0.8939

0.8745

0.7705

Burleigh, ND

Morton, ND

1020 Bloomington, IN

0.8272

0.9108

0.8733

Monroe, IN

1040 Bloomington-Normal, IL

0.8547

0.9268

0.9095

McLean, IL

1080 Boise City, ID

1.0779

0.9592

0.9006

Ada, ID

Canyon, ID

1123 Boston-Worcester-Lawrence-Lowell-Brockton, MA-NH

1.2273

1.1947

1.1160

Bristol, MA

Essex, MA

Middlesex, MA

Norfolk, MA

Plymouth, MA

Suffolk, MA

Worcester, MA

Hillsborough, NH

Merrimack, NH

Rockingham, NH

Strafford, NH

1125 Boulder-Longmont, CO

1.1414

0.9062

0.9731

Boulder, CO

1145 Brazoria, TX

0.7869

0.7187

0.8658

Brazoria, TX

1150 Bremerton, WA

0.9945

0.9732

1.0975

Kitsap, WA

1240 Brownsville-Harlingen-San Benito, TX

0.8226

0.7991

0.8722

Cameron, TX

1260 Bryan-College Station, TX

0.8326

0.6742

0.8237

Brazos, TX

1280 Buffalo-Niagara Falls, NY

1.0114

0.9494

0.9580

Erie, NY

Niagara, NY

1303 Burlington, VT

1.0690

1.0145

1.0735

Chittenden, VT

Franklin, VT

Grand Isle, VT

1310 Caguas, PR

0.0000

0.0000

0.4562

Caguas, PR

Cayey, PR

Cidra, PR

Gurabo, PR

San Lorenzo, PR

1320 Canton-Massillon, OH

0.9343

0.8839

0.8584

Carroll, OH

Stark, OH

1350 Casper, WY

0.7798

0.8405

0.8724

Natrona, WY

1360 Cedar Rapids, IA

0.8652

0.9390

0.8736

Linn, IA

1400 Champaign-Urbana, IL

0.9478

1.0588

0.9198

Champaign, IL

1440 Charleston-North Charleston, SC

0.7764

0.7695

0.9038

Berkeley, SC

Charleston, SC

Dorchester, SC

1480 Charleston, WV

0.9525

0.9975

0.9240

Kanawha, WV

Putnam, WV

1520 Charlotte-Gastonia-Rock Hill, NC-SC

1.0230

0.9661

0.9407

Cabarrus, NC

Gaston, NC

Lincoln, NC

Mecklenburg, NC

Rowan, NC

Stanly, NC

Union, NC

York, SC

1540 Charlottesville, VA

0.9619

0.9943

1.0789

Albemarle, VA

Charlottesville City, VA

Fluvanna, VA

Greene, VA

1560 Chattanooga, TN-GA

0.9186

0.8876

0.9833

Catoosa, GA

Dade, GA

Walker, GA

Hamilton, TN

Marion, TN

1580 Cheyenne, WY

1.0743

0.9800

0.8308

Laramie, WY

1600 Chicago, IL

0.9358

0.9860

1.1146

Cook, IL

De Kalb, IL

Du Page, IL

Grundy, IL

Kane, IL

Kendall, IL

Lake, IL

McHenry, IL

Will, IL

1620 Chico-Paradise, CA

0.9238

0.9565

0.9918

Butte, CA

1640  Cincinnati, OH-KY-IN

0.9579

0.9615

0.9415

Dearborn, IN

Ohio, IN

Boone, KY

Campbell, KY

Gallatin, KY

Grant, KY

Kenton, KY

Pendleton, KY

Brown, OH

Clermont, OH

Hamilton, OH

Warren, OH

1660 Clarksville-Hopkinsville, TN-KY

0.7928

0.7668

0.8204

Christian, KY

Montgomery, TN

1680 Cleveland-Lorain-Elyria, OH

1.0330

1.0271

0.9597

Ashtabula, OH

Geauga, OH

Cuyahoga, OH

Lake, OH

Lorain, OH

Medina, OH

1720 Colorado Springs, CO

0.8972

0.9387

0.9697

El Paso, CO

1740 Columbia, MO

0.9174

0.8050

0.8961

Boone, MO

1760 Columbia, SC

0.9423

0.9195

0.9554

Lexington, SC

Richland, SC

1800 Columbus, GA-AL

0.7897

0.8062

0.8568

Russell, AL

Chattanoochee, GA

Harris, GA

Muscogee, GA

1840 Columbus, OH

1.0294

1.0288

0.9619

Delaware, OH

Fairfield, OH

Franklin, OH

Licking, OH

Madison, OH

Pickaway, OH

1880 Corpus Christi, TX

0.8333

0.8573

0.8726

Nueces, TX

San Patricio, TX

1890 Corvallis, OR

0.7759

0.8492

1.1326

Benton, OR

1900 Cumberland, MD-WV

0.8879

0.9957

0.8369

Allegany, MD

Mineral, WV

1920 Dallas, TX

0.8943

0.9558

0.9913

Collin, TX

Dallas, TX

Denton, TX

Ellis, TX

Henderson, TX

Hunt, TX

Kaufman, TX

Rockwall, TX

1950 Danville, VA

0.7390

0.7589

0.8589

Danville City, VA

Pittsylvania, VA

1960 Davenport-Moline-Rock Island, IA-IL

0.8633

0.8694

0.8898

Scott, IA

Henry, IL

Rock Island, IL

2000 Dayton-Springfield, OH

0.9102

0.9455

0.9442

Clark, OH

Greene, OH

Miami, OH

Montgomery, OH

2020 Daytona Beach, FL

0.8922

0.9231

0.9200

Flagler, FL

Volusia, FL

2030 Decatur, AL

0.9186

0.8669

0.8534

Lawrence, AL

Morgan, AL

2040 Decatur, IL

0.8804

0.8322

0.8125

Macon, IL

2080 Denver, CO

1.0833

1.0643

1.0181

Adams, CO

Arapahoe, CO

Denver, CO

Douglas, CO

Jefferson, CO

2120 Des Moines, IA

0.9003

0.9712

0.9118

Dallas, IA

Polk, IA

Warren, IA

2160 Detroit, MI

0.9798

0.9957

1.0510

Lapeer, MI

Macomb, MI

Monroe, MI

Oakland, MI

St. Clair, MI

Wayne, MI

2180 Dothan, AL

0.7485

0.8621

0.7943

Dale, AL

Houston, AL

2190 Dover, DE

1.1346

1.0334

1.0078

Kent, DE

2200 Dubuque, IA

0.9533

1.0244

0.8746

Dubuque, IA

2240 Duluth-Superior, MN-WI

0.9492

1.0842

1.0032

St. Louis, MN

Douglas, WI

2281 Dutchess County, NY

1.0745

1.1267

1.0249

Dutchess, NY

2290 Eau Claire, WI

0.9402

0.9868

0.8790

Chippewa, WI

Eau Claire, WI

2320 El Paso, TX

0.7912

0.8687

0.9346

El Paso, TX

2330 Elkhart-Goshen, IN

1.0718

0.9752

0.9145

Elkhart, IN

2335 Elmira, NY

1.0063

1.0535

0.8546

Chemung, NY

2340 Enid, OK

0.7874

0.7879

0.8610

Garfield, OK

2360 Erie, PA

1.0605

1.0583

0.8985

Erie, PA

2400 Eugene-Springfield, OR

0.8713

0.8417

1.0965

Lane, OR

2440 Evansville-Henderson, IN-KY

0.9297

0.9342

0.8173

Posey, IN

Vanderburgh, IN

Warrick, IN

Henderson, KY

2520 Fargo-Moorhead, ND-MN

0.9621

1.0643

0.8749

Clay, MN

Cass, ND

2560 Fayetteville, NC

0.8495

0.8584

0.8655

Cumberland, NC

2580 Fayetteville-Springdale-Rogers, AR

0.8193

0.8512

0.7910

Benton, AR

Washington, AR

2620 Flagstaff, AZ-UT

1.2591

1.0997

1.0686

Coconino, AZ

Kane, UT

2640 Flint, MI

0.9788

0.9726

1.1205

Genesee, MI

2650 Florence, AL

0.9251

0.9031

0.7616

Colbert, AL

Lauderdale, AL

2655 Florence, SC

0.7684

0.7799

0.8777

Florence, SC

2670 Fort Collins-Loveland, CO

0.9010

0.9680

1.0647

Larimer, CO

2680 Ft. Lauderdale, FL

0.9681

0.9625

1.0121

Broward, FL

2700 Fort Myers-Cape Coral, FL

0.9444

0.8951

0.9247

Lee, FL

2710 Fort Pierce-Port St. Lucie, FL

1.0172

0.9880

0.9538

Martin, FL

St. Lucie, FL

2720 Fort Smith, AR-OK

0.7268

0.7499

0.8052

Crawford, AR

Sebastian, AR

Sequoyah, OK

2750 Fort Walton Beach, FL

0.9440

0.9582

0.9607

Okaloosa, FL

2760 Fort Wayne, IN .

0.9082

0.9763

0.8665

Adams, IN

Allen, IN

De Kalb, IN

Huntington, IN

Wells, IN

Whitley, IN

2800 Forth Worth-Arlington, TX

0.8821

0.9047

0.9527

Hood, TX

Johnson, TX

Parker, TX

Tarrant, TX

2840 Fresno, CA

0.8738

0.9823

1.0104

Fresno, CA

Madera, CA

2880 Gadsden, AL

0.9108

0.6287

0.8423

Etowah, AL

2900 Gainesville, FL

0.9325

1.0300

1.0074

Alachua, FL

2920 Galveston-Texas City, TX

0.7678

0.6821

0.9918

Galveston, TX

2960 Gary, IN

0.9827

0.9807

0.9454

Lake, IN

Porter, IN

2975 Glens Falls, NY

0.9560

0.9772

0.8361

Warren, NY

Washington, NY

2980 Goldsboro, NC

0.9370

0.8740

0.8423

Wayne, NC

2985 Grand Forks, ND-MN

0.8816

0.9022

0.8816

Polk, MN

Grand Forks, ND

2995 Grand Junction, CO

0.9539

0.9156

0.9109

Mesa, CO.

3000 Grand Rapids-Muskegon-Holland, MI

0.9715

0.9978

1.0248

Allegan, MI

Kent, MI

Muskegon, MI

Ottawa, MI

3040 Great Falls, MT

0.9712

1.0019

0.9065

Cascade, MT

3060 Greeley, CO

0.9253

0.8880

0.9814

Weld, CO

3080 Green Bay, WI

0.9441

1.0262

0.9225

Brown, WI

3120 Greensboro-Winston-Salem-High Point, NC

1.0166

0.9782

0.9131

Alamance, NC

Davidson, NC

Davie, NC

Forsyth, NC

Guilford, NC

Randolph, NC

Stokes, NC

Yadkin, NC

3150 Greenville, NC

0.8844

0.9400

0.9384

Pitt, NC

3160 Greenville-Spartanburg-Anderson, SC

0.8362

0.9622

0.9003

Anderson, SC

Cherokee, SC

Greenville, SC

Pickens, SC

Spartanburg, SC

3180 Hagerstown, MD

0.9318

0.9153

0.9409

Washington, MD

3200 Hamilton-Middletown, OH

0.9739

0.9532

0.9061

Butler, OH

3240 Harrisburg-Lebanon-Carlisle, PA

1.1052

1.0753

0.9386

Cumberland, PA

Dauphin, PA

Lebanon, PA

Perry, PA

3283 Hartford, CT

1.2733

1.1675

1.1373

Hartford, CT

Litchfield, CT

Middlesex, CT

Tolland, CT

3285 Hattiesburg, MS

0.8421

0.7540

0.7490

Forrest, MS

Lamar, MS

3290 Hickory-Morganton-Lenoir, NC

0.9086

0.9027

0.9008

Alexander, NC

Burke, NC

Caldwell, NC

Catawba, NC

3320 Honolulu, HI

1.2242

1.2838

1.1863

Honolulu, HI

3350 Houma, LA

0.6694

0..6749

0.8086

Lafourche, LA

Terrebonne, LA

3360 Houston, TX

0.8506

0.8634

0.9732

Chambers, TX

Fort Bend, TX

Harris, TX

Liberty, TX

Montgomery, TX

Waller, TX

3400 Huntington-Ashland, WV-KY-OH

0.7948

0.8957

0.9876

Boyd, KY

Carter, KY

Greenup, KY

Lawrence, OH

Cabell, WV

Wayne, WV

3440 Huntsville, AL

0.9774

0.7569

0.8932

Limestone, AL

Madison, AL

3480 Indianapolis, IN

0.9932

1.0128

0.9787

Boone, IN

Hamilton, IN

Hancock, IN

Hendricks, IN

Johnson, IN

Madison, IN

Marion, IN

Morgan, IN

Shelby, IN

3500 Iowa City, IA

0.9092

0.8611

0.9657

Johnson, IA

3520 Jackson, MI

0.9393

1.0367

0.9134

Jackson, MI

3560 Jackson, MS

0.8731

0.9642

0.8812

Hinds, MS

Madison, MS

Rankin, MS

3580 Jackson, TN

0.9437

0.8032

0.8796

Chester, TN

Madison, TN

3600 Jacksonville, FL

0.9566

0.9309

0.9208

Clay, FL

Duval, FL

Nassau, FL

St. Johns, FL

3605 Jacksonville, NC

0.6554

0.8257

0.7777

Onslow, NC

3610 Jamestown, NY

0.9276

0.8990

0.7818

Chautaqua, NY

3620 Janesville-Beloit, WI

0.8899

0.9652

0.9585

Rock, WI

3640 Jersey City, NJ

1.2879

0.8535

1.1502

Hudson, NJ

3660 Johnson City-Kingsport-Bristol, TN-VA

0.8853

0.8303

0.8272

Carter, TN

Hawkins, TN

Sullivan, TN

Unicoi, TN

Washington, TN

Bristol City, VA

Scott, VA

Washington, VA

3680 Johnstown, PA

0.9877

0.9914

0.8846

Cambria, PA

Somerset, PA

3700 Jonesboro, AR

0.6568

0.8322

0.7832

Craighead, AR

3710 Joplin, MO

0.8112

0.8128

0.8148

Jasper, MO

Newton, MO

3720 Kalamazoo-Battle Creek, MI

0.9773

0.9982

1.0453

Calhoun, MI

Kalamazoo, MI

Van Buren, MI

3740 Kankakee, IL

0.8635

0.8886

0.9902

Kankakee, IL

3760 Kansas City, KS-MO

0.9439

0.9726

0.9527

Johnson, KS

Leavenworth, KS

Miami, KS

Wyandotte, KS

Cass, MO

Clay, MO

Clinton, MO

Jackson, MO

Lafayette, MO

Platte, MO

Ray, MO

3800 Kenosha, WI

1.1006

1.0354

0.9611

Kenosha, WI

3810 Killeen-Temple, TX

0.7996

0.8280

1.0119

Bell, TX

Coryell, TX

3840 Knoxville, TN

0.9046

0.8712

0.8340

Anderson, TN

Blount, TN

Knox, TN

Loudon, TN

Sevier, TN

Union, TN

3850 Kokomo, IN

1.0415

0.8785

0.9518

Howard, IN

Tipton, IN

3870 La Crosse, WI-MN

0.9343

0.9838

0.9211

Houston, MN

La Crosse, WI

3880 Lafayette, LA

0.7373

0.7000

0.8490

Acadia, LA

Lafayette, LA

St. Landry, LA

St. Martin, LA

3920 Lafayette, IN

1.0308

0.9298

0.8834

Clinton, IN

Tippecanoe, IN

3960 Lake Charles, LA

0.7437

0.7102

0.7399

Calcasieu, LA

3980 Lakeland-Winter Haven, FL

1.0545

1.0235

0.9239

Polk, FL

4000 Lancaster, PA

1.0528

1.0114

0.9259

Lancaster, PA

4040 Lansing-East Lansing, MI

0.9933

1.0271

0.9934

Clinton, MI

Eaton, MI

Ingham, MI

4080 Laredo, TX

0.7832

0.8348

0.8168

Webb, TX

4100 Las Cruces, NM

0.6816

0.7263

0.8658

Dona Ana, NM

4120 Las Vegas, NV-AZ

1.0189

1.0278

1.0796

Mohave, AZ

Clark, NV

Nye, NV

4150 Lawrence, KS

0.9625

0.9352

0.8190

Douglas, KS

4200 Lawton, OK

0.6546

0.7951

0.8996

Comanche, OK

4243 Lewiston-Auburn, ME

0.8717

0.9202

0.9036

Androscoggin, ME

4280 Lexington, KY

0.9208

0.7549

0.8866

Bourbon, KY

Clark, KY

Fayette, KY

Jessamine, KY

Madison, KY

Scott, KY

Woodford, KY

4320 Lima, OH

0.8609

0.9397

0.9320

Allen, OH

Auglaize, OH

4360 Lincoln, NE

1.0497

1.0192

0.9626

Lancaster, NE

4400 Little Rock-North Little Rock, AR

0.9213

0.9210

0.8906

Faulkner, AR

Lonoke, AR

Pulaski, AR

Saline, AR

4420 Longview-Marshall, TX

0.7978

0.9291

0.8922

Gregg, TX

Harrison, TX

Upshur, TX

4480 Los Angeles-Long Beach, CA

1.0083

1.0129

1.1996

Los Angeles, CA

4520 Louisville, KY-IN

0.9433

0.9206

0.9350

Clark, IN

Floyd, IN

Harrison, IN

Scott, IN

Bullitt, KY

Jefferson, KY

Oldham, KY

4600 Lubbock, TX

0.7676

0.7802

0.8838

Lubbock, TX

4640 Lynchburg, VA

0.8673

0.8209

0.8867

Amherst, VA

Bedford City, VA

Bedford, VA

Campbell, VA

Lynchburg City, VA

4680 Macon, GA

0.8420

0.7877

0.8974

Bibb, GA

Houston, GA

Jones, GA

Peach, GA

Twiggs, GA

4720 Madison, WI

0.9982

1.0705

1.0271

Dane, WI

4800 Mansfield, OH

0.8294

0.9051

0.8690

Crawford, OH

Richland, OH

4840 Mayaguez, PR

0.0000

0.0000

0.4589

Anasco, PR

Cabo Rojo, PR

Hormigueros, PR

Mayaguez, PR

Sabana Grande, PR

San German, PR

4880 McAllen-Edinburg-Mission, TX

0.8136

0.7935

0.8566

Hidalgo, TX

4890 Medford-Ashland, OR

0.9732

0.9528

1.0344

Jackson, OR

4900 Melbourne-Titusville-Palm Bay, FL

1.0452

1.0178

0.9688

Brevard, Fl

4920 Memphis, TN-AR-MS

0.9554

0.9919

0.8723

Crittenden, AR

De Soto, MS

Fayette, TN

Shelby, TN

Tipton, TN

4940 Merced, CA

0.7959

0.9022

0.9646

Merced, CA

5000 Miami, FL

0.9359

0.9577

1.0059

Dade, FL

5015 Middlesex-Somerset-Hunterdon, NJ

1.1283

1.2052

1.1075

Hunterdon, NJ

Middlesex, NJ

Somerset, NJ

5080 Milwaukee-Waukesha, WI

1.0373

1.0397

0.9767

Milwaukee, WI

Ozaukee, WI

Washington, WI

Waukesha, WI

5120 Minneapolis-St Paul, MN-WI

1.2186

1.2375

1.1017

Anoka, MN

Carver, MN

Chisago, MN

Dakota, MN

Hennepin, MN

Isanti, MN

Ramsey, MN

Scott, MN

Sherburne, MN

Washington, MN

Wright, MN

Pierce, WI

St. Croix, WI

5140 Missoula, MT

0.9197

0.8724

0.9274

Missoula, MT

5160 Mobile, AL

0.8273

0.9284

0.8163

Baldwin, AL

Mobile, AL

5170 Modesto, CA

0.8732

0.9675

1.0396

Stanislaus, CA

5190 Monmouth-Ocean, NJ

1.1251

1.0979

1.1278

Monmouth, NJ

Ocean, NJ

5200 Monroe, LA

0.7793

0.8161

0.8396

Ouachita, LA

5240 Montgomery, AL

0.7738

0.8229

0.7653

Autauga, AL

Elmore, AL

Montgomery, AL

5280 Muncie, IN

0.9597

0.9550

1.0969

Delaware, IN

5330 Myrtle Beach, SC

0.9077

0.7922

0.8440

Horry, SC

5345 Naples, FL

0.9628

1.0437

0.9661

Collier, FL

5360 Nashville, TN

0.9408

0.9345

0.9490

Cheatham, TN

Davidson, TN

Dickson, TN

Robertson, TN

Rutherford, TN

Sumner, TN

Williamson, TN

Wilson, TN

5380 Nassau-Suffolk, NY

1.5592

1.5034

1.3932

Nassau, NY

Suffolk, NY

5483 New Haven-Bridgeport-Stamford-Waterbury-Danbury, CT

1.2799

1.3446

1.2297

Fairfield, CT

New Haven, CT

5523 New London-Norwich, CT

1.2035

1.2438

1.2063

New London, CT

5560 New Orleans, LA

0.8077

0.8436

0.9295

Jefferson, LA

Orleans, LA

Plaquemines, LA

St. Bernard, LA

St. Charles, LA

St. James, LA

St. John The Baptist, LA

St. Tammany, LA

5600 New York, NY

1.5638

1.4983

1.4651

Bronx, NY

Kings, NY

New York, NY

Putnam, NY

Queens, NY

Richmond, NY

Rockland, NY

Westchester, NY

5640 Newark, NJ

1.2344

1.1704

1.1837

Essex, NJ

Morris, NJ

Sussex, NJ

Union, NJ

Warren, NJ

5660 Newburgh, NY-PA

1.2791

1.2347

1.0847

Orange, NY

Pike, PA

5720 Norfolk-Virginia Beach-Newport News, VA-NC

0.8084

0.7828

0.8412

Currituck, NC

Chesapeake City, VA

Gloucester, VA

Hampton City, VA

Isle of Wight, VA

James City, VA

Mathews, VA

Newport News City, VA

Norfolk City, VA

Poquoson City, VA

Portsmouth City, VA

Suffolk City, VA

Virginia Beach City, VA

Williamsburg City, VA

York, VA

5775 Oakland, CA

1.0815

1.0616

1.4983

Alameda, CA

Contra Costa, CA

5790 Ocala, FL

0.9967

0.7345

0.9243

Marion, FL

5800 Odessa-Midland, TX

0.7857

0.8858

0.9205

Ector, TX

Midland, TX

5880 Oklahoma City, OK

0.7911

0.7955

0.8822

Canadian, OK

Cleveland, OK

Logan, OK

McClain, OK

Oklahoma, OK

Pottawatomie, OK

5910 Olympia, WA

0.9888

0.9548

1.0677

Thurston, WA

5920 Omaha, NE-IA

1.0212

1.0731

0.9572

Pottawattamie, IA

Cass, NE

Douglas, NE

Sarpy, NE

Washington, NE

5945 Orange County, CA

1.0747

1.0649

1.1467

Orange, CA

5960 Orlando, FL

0.9445

0.9566

0.9610

Lake, FL

Orange, FL

Osceola, FL

Seminole, FL

5990 Owensboro, KY

1.0374

0.8987

0.8159

Daviess, KY

6015 Panama City, FL

0.9224

0.9344

0.9010

Bay, FL

6020 Parkersburg-Marietta, WV-OH

0.9779

0.9064

0.8274

Washington, OH

Wood, WV

6080 Pensacola, FL

0.7929

0.8519

0.8176

Escambia, FL

Santa Rosa, FL

6120 Peoria-Pekin, IL

0.8375

0.9017

0.8645

Peoria, IL

Tazewell, IL

Woodford, IL

6160 Philadelphia, PA-NJ

1.1553

1.1460

1.0937

Burlington, NJ

Camden, NJ

Gloucester, NJ

Salem, NJ

Bucks, PA

Chester, PA

Delaware, PA

Montgomery, PA

Philadelphia, PA

6200 Phoenix-Mesa, AZ

1.0176

1.0219

0.9669

Maricopa, AZ

Pinal, AZ

6240 Pine Bluff, AR

0.6727

0.7983

0.7791

Jefferson, AR

6280 Pittsburgh, PA

1.0937

1.0574

0.9741

Allegheny, PA

Beaver, PA

Butler, PA

Fayette, PA

Washington, PA

Westmoreland, PA

6323 Pittsfield, MA

1.1357

1.0739

1.0288

Berkshire, MA

6340 Pocatello, ID

0.7864

0.7717

0.9076

Bannock, ID

6360 Ponce, PR

0.7238

0.6854

0.5006

Guayanilla, PR

Juana Diaz, PR

Penuelas, PR

Ponce, PR

Villalba, PR

Yauco, PR

6403 Portland, ME

1.0594

1.0378

0.9748

Cumberland, ME

Sagadahoc, ME

York, ME

6440 Portland-Vancouver, OR-WA

1.0495

1.0048

1.0910

Clackamas, OR

Columbia, OR

Multnomah, OR

Washington, OR

Yamhill, OR

Clark, WA

6483 Providence-Warwick-Pawtucket, RI

1.0486

1.0120

1.0864

Bristol, RI

Kent, RI

Newport, RI

Providence, RI

Washington, RI

6520 Provo-Orem, UT

0.7640

0.9453

1.0029

Utah, UT

6560 Pueblo, CO

0.8689

0.9305

0.8815

Pueblo, CO

6580 Punta Gorda, FL

0.9549

0.9761

0.9613

Charlotte, FL

6600 Racine, WI

1.1701

1.1432

0.9246

Racine, WI

6640 Raleigh-Durham-Chapel Hill, NC

1.0767

1.0122

0.9646

Chatham, NC

Durham, NC

Franklin, NC

Johnston, NC

Orange, NC

Wake, NC

6660 Rapid City, SD

0.7728

0.9584

0.8865

Pennington, SD

6680 Reading, PA

1.0531

1.1283

0.9152

Berks, PA

6690 Redding, CA

1.1269

1.0330

1.1664

Shasta, CA

6720 Reno, NV

1.0926

1.2112

1.0550

Washoe, NV

6740 Richland-Kennewick-Pasco, WA

1.0241

1.0334

1.1460

Benton, WA

Franklin, WA

6760 Richmond-Petersburg, VA

0.7927

0.8517

0.9617

Charles City County, VA

Chesterfield, VA

Colonial Heights City, VA

Dinwiddie, VA

Goochland, VA

Hanover, VA

Henrico, VA

Hopewell City, VA

New Kent, VA

Petersburg City, VA

Powhatan, VA

Prince George, VA

Richmond City, VA

6780 Riverside-San Bernardino, CA

1.0127

1.0086

1.1239

Riverside, CA

San Bernardino, CA

6800 Roanoke, VA

0.7443

0.8052

0.8750

Botetourt, VA

Roanoke, VA

Roanoke City, VA

Salem City, VA

6820 Rochester, MN

1.1764

1.1235

1.1315

Olmsted, MN

6840 Rochester, NY

1.0708

1.0488

0.9182

Genesee, NY

Livingston, NY

Monroe, NY

Ontario, NY

Orleans, NY

Wayne, NY

6880 Rockford, IL

0.8844

0.9617

0.8819

Boone, IL

Ogle, IL

Winnebago, IL

6895 Rocky Mount, NC

0.9221

0.8247

0.8849

Edgecombe, NC

Nash, NC

6920 Sacramento, CA

1.0230

1.0580

1.1950

El Dorado, CA

Placer, CA

Sacramento, CA

A6960 Saginaw-Bay City-Midland, MI

0.8510

0.9002

0.9575

Bay, MI

Midland, MI

Saginaw, MI

6980 St. Cloud, MN

0.8480

0.9556

1.0016

Benton, MN

Stearns, MN

7000 St. Joseph, MO

1.1074

1.0774

0.9071

Andrews, MO

Buchanan, MO

7040 St. Louis, MO-IL

0.8900

0.9056

0.9049

Clinton, IL

Jersey, IL

Madison, IL

Monroe, IL

St. Clair, IL

Franklin, MO

Jefferson, MO

Lincoln, MO

St. Charles, MO

St. Louis, MO

St. Louis City, MO

Warren, MO

Sullivan City, MO

7080 Salem, OR

0.9308

0.8379

1.0189

Marion, OR

Polk, OR

7120 Salinas, CA

1.0856

1.1224

1.4502

Monterey, CA

7160 Salt Lake City-Ogden, UT

0.9984

0.9405

0.9807

Davis, UT

Salt Lake, UT

Weber, UT

7200 San Angelo, TX

0.8222

0.7841

0.8083

Tom Green, TX

7240 San Antonio, TX

0.8252

0.8159

0.8580

Bexar, TX

Comal, TX

Guadalupe, TX

Wilson, TX

7320 San Diego, CA

1.0177

1.0038

1.1784

San Diego, CA

7360 San Francisco, CA

1.1958

1.1930

1.4156

Marin, CA

San Francisco, CA

San Mateo, CA

7400 San Jose, CA

1.0787

1.1736

1.3652

Santa Clara, CA

7440 San Juan-Bayamon, PR

0.5454

0.5070

0.4690

Aguas Buenas, PR

Barceloneta, PR

Bayamon, PR

Canovanas, PR

Carolina, PR

Catano, PR

Ceiba, PR

Comerio, PR

Corozal, PR

Dorado, PR

Fajardo, PR

Florida, PR

Guaynabo, PR

Humacao, PR

Juncos, PR

Los Piedras, PR

Loiza, PR

Luguillo, PR

Manati, PR

Morovis, PR

Naguabo, PR

Naranjito, PR

Rio Grande, PR

San Juan, PR

Toa Alta, PR

Toa Baja, PR

Trujillo Alto, PR

Vega Alta, PR

Vega Baja, PR

Yabucoa, PR

7460 San Luis Obispo-Atascadero-Paso Robles, CA

1.0873

0.9472

1.0673

San Luis Obispo, CA

7480 Santa Barbara-Santa Maria-Lompoc, CA

0.9547

1.0338

1.0597

Santa Barbara, CA

7485 Santa Cruz-Watsonville, CA

1.1349

0.9398

1.4040

Santa Cruz, CA

7490 Santa Fe, NM

0.8636

1.3115

1.0537

Los Alamos, NM

Santa Fe, NM

7500 Santa Rosa, CA

1.0368

1.1709

1.2646

Sonoma, CA

7510 Sarasota-Bradenton, FL

1.0006

1.0294

0.9809

Manatee, FL

Sarasota, FL

7520 Savannah, GA

0.8804

0.7861

0.9697

Bryan, GA

Chatham, GA

Effingham, GA

7560 Scranton-Wilkes-Barre-Hazleton, PA

1.0313

1.0346

0.8421

Columbia, PA

Lackawanna, PA

Luzerne, PA

Wyoming, PA

7600 Seattle-Bellevue-Everett, WA

1.1078

1.0440

1.0996

Island, WA

King, WA

Snohomish, WA

7610 Sharon, PA

1.0333

0.9605

0.7928

Mercer, PA

7620 Sheboygan, WI

1.1775

1.2892

0.8379

Sheboygan, WI

7640 Sherman-Denison, TX

0.8663

0.8372

0.8694

Grayson, TX

7680 Shreveport-Bossier City, LA

0.7241

0.6735

0.8750

Bossier, LA

Caddo, LA

Webster, LA

7720  Sioux City, IA-NE

0.9021

0.9063

0.8473

Woodbury, IA

Dakota, NE

7760 Sioux Falls, SD

0.8511

0.9286

0.8790

Lincoln, SD

Minnehaha, SD

7800 South Bend, IN

1.0075

1.0621

1.0000

St. Joseph, IN

7840 Spokane, WA

0.9486

0.9854

1.0513

Spokane, WA

7880 Springfield, IL

0.8276

0.9314

0.8685

Menard, IL

Sangamon, IL

7920 Springfield, MO

0.9289

0.9309

0.8488

Christian, MO

Greene, MO

Webster, MO

8003 Springfield, MA

1.2171

1.1537

1.0637

Hampden, MA

Hampshire, MA

8050 State College, PA

1.0164

0.9558

0.9038

Centre, PA

8080 Steubenville-Weirton, OH-WV

0.9182

0.9057

0.8548

Jefferson, OH

Brooke, WV

Hancock, WV

8120 Stockton-Lodi, CA

0.9860

1.0313

1.0629

San Joaquin, CA

8140 Sumter, SC

0.7762

0.8687

0.8271

Sumter, SC

8160 Syracuse, NY

1.0121

1.0499

0.9549

Cayuga, NY

Madison, NY

Onondaga, NY

Oswego, NY

8200 Tacoma, WA

0.9407

0.9441

1.1564

Pierce, WA

8240 Tallahassee, FL

0.9658

0.9761

0.8545

Gadsden, FL

Leon, FL

8280 Tampa-St. Petersburg-Clearwater, FL

1.0177

1.0025

0.8982

Hernando, FL

Hillsborough, FL

Pasco, FL

Pinellas, FL

8320 Terre Haute, IN

0.8222

0.8286

0.8304

Clay, IN

Vermillion, IN

Vigo, IN

8360 Texarkana, AR-Texarkana, TX

0.8290

0.8049

0.8363

Miller, AR

Bowie, TX

8400 Toledo, OH

0.9963

0.9904

0.9832

Fulton, OH

Lucas, OH

Wood, OH

8440 Topeka, KS

0.7969

0.8241

0.9117

Shawnee, KS

8480 Trenton, NJ

1.1897

1.1835

1.0137

Mercer, NJ

8520 Tucson, AZ

0.9488

0.9534

0.8794

Pima, AZ

8560 Tulsa, OK

0.8445

0.8104

0.8454

Creek, OK

Osage, OK

Rogers, OK

Tulsa, OK

Wagoner, OK

8600 Tuscaloosa, AL

0.8490

0.8208

0.8064

Tuscaloosa, AL

8640 Tyler, TX

0.8607

0.8562

0.9404

Smith, TX

8680 Utica-Rome, NY

0.9634

0.9279

0.8560

Herkimer, NY

Oneida, NY

8720 Vallejo-Fairfield-Napa, CA

1.1949

1.1287

1.2847

Napa, CA

Solano, CA

8735 Ventura, CA

1.0838

1.0338

1.1030

Ventura, CA

8750 Victoria, TX

0.7002

0.7270

0.8154

Victoria, TX

8760 Vineland-Millville-Bridgeton, NJ

1.1806

1.1019

1.0501

Cumberland, NJ

8780 Visalia-Tulare-Porterville, CA

0.9010

0.9027

0.9551

Tulare, CA

8800 Waco, TX

0.8453

0.8291

0.8314

McLennan, TX

8840 Washington, DC-MD-VA-WV

1.0430

1.0368

1.0755

District of Columbia, DC

Calvert, MD

Charles, MD

Frederick, MD

Montgomery, MD

Prince Georges, MD

Alexandria City, VA

Arlington, VA

Clarke, VA

Culpepper, VA

Fairfax, VA

Fairfax City, VA

Falls Church City, VA

Fauquier, VA

Fredericksburg City, VA

King George, VA

Loudoun, VA

Manassas City, VA

Manassas Park City, VA

Prince William, VA

Spotsylvania, VA

Stafford, VA

Warren, VA

Berkeley, WV

Jefferson, WV

8920 Waterloo-Cedar Falls, IA

0.8201

0.8820

0.8404

Black Hawk, IA

8940 Wausau, WI

1.1470

1.2648

0.9418

Marathon, WI

8960 West Palm Beach-Boca Raton, FL

1.0131

0.9912

0.9682

Palm Beach, FL

9000 Wheeling, OH-WV

0.9131

0.9078

0.7733

Belmont, OH

Marshall, WV

Ohio, WV

9040 Wichita, KS

0.9211

0.9050

0.9544

Butler, KS

Harvey, KS

Sedgwick, KS

9080 Wichita Falls, TX

0.7375

0.7385

0.7668

Archer, TX

Wichita, TX

9140 Williamsport, PA

0.9543

1.0264

0.8392

Lycoming, PA

9160 Wilmington-Newark, DE-MD

1.0931

1.0284

1.1191

New Castle, DE

Cecil, MD

9200 Wilmington, NC

0.9507

0.8675

0.9402

New Hanover, NC

Brunswick, NC

9260 Yakima, WA

0.9038

0.8770

0.9907

Yakima, WA

9270 Yolo, CA

1.0452

1.0260

1.0199

Yolo, CA

9280 York, PA

1.0718

1.0923

0.9264

York, PA

9320 Youngstown-Warren, OH

0.8731

0.8594

0.9543

Columbiana, OH

Mahoning, OH

Trumbull, OH

9340 Yuba City, CA

1.0615

1.0246

1.0706

Sutter, CA

Yuba, CA

9360 Yuma, AZ

0.9209

0.9020

0.9529

Yuma, AZ

Table 8.—Wage Index for Rural Areas

Rural area

Wage index

SNF98

SNF99

HOSP

Col. A

Col. B

Col. C

Col. D

Alabama

0.7724

0.8020

0.7489

Alaska

1.4132

1.3582

1.2392

Arizona

1.0111

0.9175

0.8317

Arkansas

0.6972

0.7278

0.7445

California

0.9685

0.9712

0.9861

Colorado

0.8710

0.9147

0.8968

Connecticut

1.2870

1.0540

1.1715

Delaware

1.0854

0.9338

0.9074

Florida

0.8331

0.8921

0.8919

Georgia

0.7850

0.7985

0.8329

Guam

0.0000

0.0000

0.9611

Hawaii

1.1915

1.2995

1.1059

Idaho

0.8892

0.8320

0.8678

Illinois

0.8296

0.8274

0.8160

Indiana

0.8875

0.9008

0.8602

Iowa

0.7706

0.7834

0.8030

Kansas

0.7562

0.7941

0.7605

Kentucky

0.8237

0.7905

0.7931

Louisiana

0.6699

0.7014

0.7681

Maine

0.8766

0.8908

0.8766

Maryland

0.9015

0.8780

0.8651

Massachusetts

1.1740

1.2039

1.1204

Michigan

0.9505

0.9655

0.8987

Minnesota

1.1396

1.0221

0.8881

Mississippi

0.7412

0.7885

0.7491

Missouri

0.7904

0.7898

0.7698

Montana

0.8996

0.8606

0.8688

Nebraska

0.7977

0.8182

0.8109

Nevada

0.8621

0.9222

0.9232

New Hampshire

1.1065

1.1171

0.9845

New Jersey

1

New Mexico

0.6834

0.8052

0.8497

New York

1.0081

0.9981

0.8499

North Carolina

0.9255

0.9028

0.8445

North Dakota

0.7649

0.7779

0.7716

Ohio

0.8895

0.8948

0.8670

Oklahoma

0.7481

0.7275

0.7491

Oregon

0.8616

0.8455

1.0132

Pennsylvania

0.9870

0.9443

0.8578

Puerto Rico

0.3897

0.3866

0.4264

Rhode Island

1

South Carolina

0.7941

0.8367

0.8370

South Dakota

0.7946

0.8373

0.7570

Tennessee

0.8656

0.8415

0.7838

Texas

0.7512

0.7528

0.7502

Utah

0.9492

0.8196

0.9037

Vermont

0.9914

1.0299

0.9274

Virginia

0.8157

0.8601

0.8189

Virgin Islands

0.0000

0.0000

0.6306

Washington

0.9539

0.9475

1.0434

West Virginia

0.8260

0.8668

0.8231

Wisconsin

0.9516

0.9893

0.8880

Wyoming

0.9081

0.8314

0.8817

1

All counties within the State are classified urban.

We have drawn the following conclusions from these tables and our analysis of the wage data:

A comparison of the wage index based on hospital data with one based on SNF-specific wage data has created many significant variances, not only between the SNF wage index and the hospital wage index, but also between the two SNF wage indexes illustrated in Tables 7 and 8. While we would expect some changes from year to year, and between a wage index based on SNF data and one based on hospital data, we believe that the large quantity of significant variations raises questions as to the reliability of the SNF-specific wage data.

The following illustrates the impact of using the various wage indexes contained in Tables 7 and 8:

• When comparing the FY 1998 SNF-specific wage index to the hospital wage index, we found the number of areas that:

Increased more than 20%—15 (the highest was 44.59%)

Increased between 10-20%—53

Increased between 5-10%—49

Increased between 0-5%—64

Decreased between 0-5%—69

Decreased between 5-10%—56

Decreased between 10-20%—51

Decreased greater than 20%—12 (the largest was 37.55%)

• When comparing the FY 1999 SNF-specific wage index to the hospital wage index, we found the number of areas that:

Increased more than 20%—12 (the largest was 53.86%)

Increased between 10-20%—47

Increased between 5-10%—67

Increased between 0-5%—70

Decreased between 0-5%—56

Decreased between 5-10%—60

Decreased between 10-20%—44

Decreased greater than 20%—13 (the largest was 33.06%)

• When comparing the FY 1998 SNF-specific wage index to the FY 1999 SNF-specific wage index, we found the number of areas that:

Increased more than 20%—9 (the largest was 51.86%)

Increased between 10-20%—25

Increased between 5-10%—52

Increased between 0-5%—102

Decreased between 0-5%—110

Decreased between 5-10%—44

Decreased between 10-20%—22

Decreased greater than 20%—5 (the largest was 33.73%)

The FY 1998 and FY 1999 SNF wage index had 6 areas with no values.

For FY 1998, from a total of 13,587 freestanding providers, we eliminated 2,674 providers because they had a zero value for wages or hours. For hospital-based SNFs, of the 2,185 providers, we eliminated 160 providers for the same reason. For FY 1999, of the 12,491 freestanding providers, we eliminated 2,461 providers because they had a zero value for wages or hours. For hospital-based SNFs, of the 2,034 providers, we eliminated 132 providers for the same reason. In addition, for FY 1998, we eliminated 231 providers that had average hourly wages either below $5.00, or above the 99th percentile ($24.15). For FY 1999, we eliminated 206 providers with average hourly wages either below $5.00, or above the 99th percentile ($24.79).

There are far fewer significant changes between MSAs in the annual hospital wage index. The latest comparison of the year-to-year differences in the hospital wage index (pre-classified, pre-floor) shows only 7 areas with increases of 10 percent or more and 4 with decreases greater than 10 percent. A comparison of the FY 1998 and 1999 SNF-specific wage indexes shows 34 areas that experienced an increase of 10 percent or more and 27 areas with decreases of 10 percent or more.

We believe that any changes to the wage index adjustment under the SNF PPS should support greater precision in Medicare payments; however, as a result of the variations in the SNF-specific wage data and the large number of SNFs that are unable to provide adequate wage and hourly data, we are concerned about the reliability of the data used in establishing a SNF wage index at this time.

We continue to believe that a wage index based on hospital wage data is the best and most appropriate to use in adjusting payments to SNFs, since both hospitals and SNFs compete in the same labor markets. We invite public comment on the SNF-specific wage data; however, for the reasons discussed above we currently plan to use the updated hospital wage data when we publish the final rule. In addition, in accordance with section 315(b) of BIPA 2000, since we currently do not have reliable SNF-specific wage data, we are not proposing at this time to develop or incorporate any type of geographic reclassification system for SNFs.

D. Updates to the Federal Rates

In accordance with section 1888(e)(4)(E) of the Act and section 311 of BIPA 2000, the proposed payment rates listed here reflect an update equal to the SNF market basket minus 0.5 percentage point, which equals 2.4 percent. For each succeeding FY, we will publish the rates in the

Federal Register

before August 1 of the year preceding the affected Federal FY.

E. Relationship of RUG-III Classification System to Existing Skilled Nursing Facility Level-of-Care Criteria

As discussed in § 413.345, we include in each update of the Federal payment rates in the

Federal Register

the designation of those specific RUGs under the classification system that represent the required SNF level of care, as provided in § 409.30. This designation reflects an administrative presumption that beneficiaries who are correctly assigned to one of the upper 26 RUG-III groups in the initial 5-day, Medicare-required assessment are automatically classified as meeting the SNF level of care definition up to that point.

Those beneficiaries assigned to any of the lower 18 groups are not automatically classified as either meeting or not meeting the definition, but instead receive an individual level of care determination using the existing administrative criteria. This presumption recognizes the strong likelihood that beneficiaries assigned to one of the upper 26 groups during the immediate post-hospital period require a covered level of care, which would be significantly less likely for those beneficiaries assigned to one of the lower 18 groups.

We propose to continue the existing designation of the upper 26 RUG-III groups for purposes of this administrative presumption, consisting of the following RUG-III classifications: all groups within the Ultra High Rehabilitation category; all groups within the Very High Rehabilitation category; all groups within the High Rehabilitation category; all groups within the Medium Rehabilitation category; all groups within the Low Rehabilitation category; all groups within the Extensive Services category; all groups within the Special Care category; and, all groups within the Clinically Complex category.

F. Three-Year Transition Period

As noted previously, the rates that we now propose are for the fourth year of the SNF PPS. As a result, the PPS is no longer operating under the initial three-year transition period from facility-specific to Federal rates and, therefore, now equals 100 percent of the adjusted Federal per diem rate.

G. Example of Computation of Adjusted PPS Rates and SNF Payment

Using the XYZ SNF described in Table 9A, the following shows the adjustments made to the Federal per diem rate to compute the provider's actual per diem PPS payment. XYZ's 12-month cost reporting period begins October 1, 2001. Table 9B displays the 44 RUG-III categories and their respective add-ons, as provided in BBRA 1999 and BIPA 2000.

Table 9.A.—SNF XYZ From Above Is Located in State College, PA With a Wage Index of 0.9038

RUG group

Labor

portion

Wage

index

Adjusted

labor

Nonlabor

portion

Adjusted

rate

Percent

adjustment

Medicare

days

Payment

RVC

$257.54

0.9038

$232.76

$84.14

$316.90

$350.81

50

$17,541

SSC

171.76

0.9038

155.24

56.12

211.36

3

262.09

25

6,552

IA2

113.56

0.9038

102.64

37.10

139.74

4

145.33

25

3,633

Total

100

27,726

1

From Table 5.

2

Reflects a 10.7 percent adjustment (the 4 percent adjustment from section 101(d) of BBRA 1999 and the 6.7 percent adjustment from section 314 of BIPA 2000).

3

Reflects a 24 percent adjustment (the 4 percent and 20 percent adjustments from sections 101(a) and (d) of BBRA 1999).

4

Reflects the 4 percent adjustment from section 101(d) of BBRA 1999.

Table 9.B.—BBRA 1999 & BIPA 2000 Add-Ons, by RUG-III Category

RUG-III

category

4%

1

10.7%

2

24%

3

RUC

X

RUB

X

RUA

X

RVC

X

RVB

X

RVA

X

RHC

X

RHB

X

RHA

X

RMC

X

RMB

X

RMA

X

RLB

X

RLA

X

SE3

X

SE2

X

SE1

X

SSC

X

SSB

X

SSA

X

CC2

X

CC1

X

CB2

X

CB1

X

CA2

X

CA1

X

IB2

X

IB1

X

IA2

X

IA1

X

BB2

X

BB1

X

BA2

X

BA1

X

PE2

X

PE1

X

PD2

X

PD1

X

PC2

X

PC1

X

PB2

X

PB1

X

PA2

X

PA1

X

1

From BBRA 1999.

2

Includes the 4% increase from BBRA 1999 and the 6.7% increase from BIPA 2000.

3

Includes the 4% and 20% increases from BBRA 1999.

For rates addressed in this proposed rule, we are using wage index values that are based on hospital wage data from cost reporting periods beginning in FY 1996, the same wage data as used to compute the FY 2001 wage index values for the SNF PPS. We will incorporate updated wage data in the final rule for the FY 2002 SNF PPS update. XYZ's total PPS payment will equal $27,726.

III. The Skilled Nursing Facility Market Basket Index

A. Background

Section 1888(e)(5)(A) of the Act requires the Secretary to establish a market basket index that reflects changes over time in the prices of an appropriate mix of goods and services included in the SNF PPS. Effective for cost reporting periods beginning on or after July 1, 1998, we revised and rebased our 1977 routine costs input price index and adopted a total expenses SNF input price index using data from 1992 as the base year.

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

The 1992-based SNF market basket represents routine costs, costs of ancillary services and capital-related costs. The percentage change in the market basket reflects the average change in the price of a fixed set of goods and services purchased by SNFs to furnish all services. For further background information, see the May 12, 1998

Federal Register

(63 FR 26289).

For purposes of SNF PPS, the SNF market basket is a fixed-weight (Laspeyres type) price index. (A Laspeyres type index compares the cost of purchasing a specified group of commodities at current prices to the cost of purchasing that same group in a selected base period.) The SNF market basket is constructed in three steps. First, a base period is selected and total base period expenditure shares are estimated for mutually exclusive and exhaustive spending categories. Total costs for routine services, ancillary services, and capital are used. These proportions are called “cost” or “expenditure weights”. The second step is to match each expenditure category to a price/wage variable, called a price proxy. These price proxy variables are drawn from publicly available statistical series published on a consistent schedule, preferably at least quarterly. In the final step, the price level for each spending category is multiplied by the expenditure weight for that category. The sum of these products (that is, weights multiplied by proxy index levels) for all cost categories yields the composite index level in the market basket for a given quarter or year. Repeating the third step for other quarters and years produces a time series of market basket index levels, from which rates of growth can be calculated.

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

As discussed in the May 12, 1998

Federal Register

(63 FR 26252), to implement section 1888(e)(5)(A) of the Act, we have revised and rebased the market basket so the cost weights and price proxies reflected the mix of goods and services that SNFs purchase for all costs (routine, ancillary, and capital-related) encompassed by SNF PPS in fiscal year 1992.

B. Rebasing and Revising the Skilled Nursing Facility Market Basket

The terms “rebasing” and “revising”, while often used interchangeably, actually denote different activities. Rebasing means shifting the base year for the structure of costs of the input

price index (for example, for this proposed rule, we would shift the base year cost structure from fiscal year 1992 to fiscal year 1997). Revising means changing data sources, cost categories, and/or price proxies used in the input price index.

We are proposing to rebase and revise the SNF market basket to reflect 1997 total cost data (routine, ancillary, and capital-related). Fiscal year 1997 was selected as the new base year because 1997 is the most recent year for which relatively complete data are available. These data include settled 1997 Medicare Cost Reports as well as 1997 data from two U.S. Department of Commerce surveys: the Bureau of the Census' Business Expenditures Survey, and the Bureau of Economic Analysis' Annual Input-Output tables. Preliminary analysis of 1998 data from Medicare Cost Reports showed little change in cost shares from those in the 1997 Medicare Cost Reports.

In developing the proposed market basket, we reviewed SNF expenditure data from Medicare Cost Reports for FY 1997 for each freestanding SNF that had Medicare expenses. FY 1997 Cost Reports are those with cost reporting periods beginning after September 30, 1996 and before October 1, 1997. We maintained our policy of using data from freestanding SNFs because they reflect the actual cost structure faced by the SNF itself. By contrast, expense data for a hospital-based SNF is influenced by the allocation of overhead over the entire institution.

Data on SNF expenditures for six major expense categories (wages and salaries, employee benefits, contract labor, pharmaceuticals, capital-related, and a residual “all other”) were edited and tabulated. Using these data, we then determined the proportion of total costs that each category represented. The six major categories for the revised and rebased cost categories and weights derived from SNF Medicare Cost Reports are summarized in Table 10.A.

Table 10.A.—1992 and Proposed 1997 Skilled Nursing Facility Major Cost Categories and Weights From Medicare Cost Reports

Cost categories

1992-based skilled nursing facility weights

(percent)

Proposed 1997-based skilled nursing facility weights

(percent)

Wages and Salaries

47.805

46.889

Employee Benefits

10.023

9.631

Contract Labor

12.852

6.478

Pharmaceuticals

2.531

3.006

Capital-related Costs

9.778

9.877

All Other Costs

17.012

24.119

Total Costs

100.000

100.000

We fully discuss the methodology for developing these weights in the Appendix. The main methodological difference between the 1992-based SNF market basket and the proposed 1997-based market basket is in the calculation of the contract labor weight. For the 1992-based market basket, we estimated this share using non-salary costs for therapy cost centers. For the proposed 1997-based index, we used the contract labor amounts for a subset of edited reports from Worksheet S-3 in the Medicare Cost Reports. We believe this new methodology provides a more accurate reflection of the share of total costs that are attributable to contract labor. The data from this worksheet were not available in the 1992 Medicare Cost Reports.

Relative weights within the six major categories were derived using relative cost shares from the Bureau of the Census' 1997 Business Expenditures Survey (BES), 1997 Medicare Cost Reports, and the Bureau of Economic Analysis' (BEA) 1997 Annual Input-Output tables. They were used to disaggregate and allocate costs within the six major categories determined from the 1997 SNF Medicare Cost Reports. The BEA Input-Output database is benchmarked at 5-year intervals and updated annually between benchmarks. We are using the annual update for 1997. The BES is updated every five years.

The capital-related portion of the proposed rebased and revised SNF PPS market basket employs the same overall methodology used to develop the capital-related portion of the 1992-based SNF market basket, described in the May 12, 1998

Federal Register

(63 FR 26289). It is also the same methodology used for the inpatient hospital PPS capital input price index described in the

Federal Register

May 31, 1996 (61 FR 27466) and August 30, 1996 (61 FR 46196). The strength of this methodology is that it reflects the vintage nature of capital, which represents the acquisition and use of capital over time.

Our work resulted in 21 separate categories for the proposed rebased and revised SNF market basket. The 1992-based total cost SNF market basket also had 21 separate cost categories. Detailed descriptions of each cost category and respective price proxy in the proposed 1997-based SNF market basket are provided in the Appendix to this proposed rule.

As in the 1992-based SNF market basket, the proposed 1997-based SNF market basket does not include a separate cost category for professional liability insurance. Our analysis of the BEA 1997 Annual Input-Output survey indicated that the general category for insurance carriers (which includes professional liability insurance as a subset) was, at just 0.2 percent, a small share of the total costs in 1997. It has been our policy in the past not to provide detailed breakouts of cost categories unless they represent a significant portion of the providers' costs. We also reviewed data available on professional liability insurance from Worksheet S-2 of the SNF Medicare Cost Reports, but found that nearly all SNFs did not report data for malpractice premiums, paid losses, or self-insurance in 1997.

Professional liability insurance is included with other insurance paid to carriers in the all other labor-intensive services cost category. We are soliciting comments on possible data sources for professional liability insurance costs for SNFs. Recent indications are that professional liability insurance costs for SNFs are rising quickly. We are looking both for information that would be

available for a cost weight as well as for a time-series of professional liability premiums for a constant level of coverage, similar to the data we currently collect for hospitals and physicians from a small sample of insurance carriers.

After the 21 cost weights for the proposed revised and rebased SNF market basket were developed, we selected the most appropriate wage and price proxies currently available to monitor the rate of change for each expenditure category. With three exceptions (all for the capital-related expenses cost category), the wage and price proxies are based on Bureau of Labor Statistics (BLS) data and are grouped into one of the following BLS categories:

•

Employment Cost Indexes

. Employment Cost Indexes (ECIs) measure the rate of change in employment wage rates and employer costs for employee benefits per hour worked. These indexes are fixed-weight indexes and strictly measure the change in wage rates and employee benefits per hour. They are not affected by shifts in occupation or industry mix. ECIs are superior to Average Hourly Earnings (AHEs) as price proxies for input price indexes for two reasons: (1) They measure pure price change, and (2) they are available by both occupational group and by industry.

•

Producer Price Indexes

. Producer Price Indexes (PPIs) measure price changes for goods sold in other than retail markets. PPIs were used when the purchases of goods or services were made at the wholesale level.

•

Consumer Price Indexes

. Consumer Price Indexes (CPIs) measure change in the prices of final goods and services bought by consumers. CPIs were only used when the purchases were similar to those of retail consumers rather than purchases at the wholesale level, or if no appropriate PPI was available.

The contract labor weight of 6.478 was reallocated to (1) wages and salaries, and (2) employee benefits, so that the same price proxies that we propose to use for direct labor costs are applied to contract costs. While we understand that the level of unit labor costs for contract labor can differ from the unit labor costs of a SNF employee, we feel that the rate at which these labor costs change should be similar. That is, unit contract labor costs should not grow any more or less rapidly than SNF employee labor costs. The rebased and revised cost categories, weights, and price proxies for the proposed 1997-based SNF market basket are listed in Table 10.B.

Table 10.B.—Proposed 1997-Based SNF Market Basket Cost Categories, Weights, and Price Proxies

Cost category

1997-based skilled nursing facility market basket weight

Price proxy

Operating Expenses

90.123

Compensation

62.998

Wages and Salaries

52.263

ECI for Wages and Salaries for Private Nursing Homes.

Employee benefits

10.734

ECI for Benefits for Private Nursing Homes.

Nonmedical professional fees

2.634

ECI for Compensation for Private Professional, Technical and Specialty workers.

Utilities

2.368

Electricity

1.420

PPI for Commercial Electric Power.

Fuels, nonhighway

0.426

PPI for Commercial Natural Gas.

Water and sewerage

0.522

CPI-U for Water and Sewarge.

Other Expenses

22.123

Other Products

13.522

Pharmaceuticals

3.006

PPI for Prescription Drugs.

Food

4.136

Food, wholesale purchase

3.198

PPI for Processed Foods.

Food, retail purchase

0.937

CPI-U for Food Away From Home.

Chemicals

0.891

PPI for Industrial Chemicals.

Rubber and plastics

1.611

PPI for Rubber and Plastic Products.

Paper products

1.289

PPI for Converted Paper and Paperboard.

Miscellaneous products

2.589

PPI for Finished Goods less Food and Energy.

Other Services

8.602

Telephone Services

0.448

CPI-U for Telephone Services.

Labor-intensive Services

4.094

ECI for Compensation for Private Service Occupations.

Non labor-intensive services

4.059

CPI-U for All Items.

Capital-related Expenses

9.877

Total Depreciation

5.266

Building & Fixed Equipment

3.609

Boeckh Institutional Construction Index (vintage-weighted over 23 years).

Movable Equipment

1.657

PPI for Machinery & Equipment (vintage-weighted over 10 years).

Total Interest

3.852

Government & Nonprofit SNFs

1.890

Average Yield Municipal Bonds (Bond Buyer Index-20 bonds) (vintage-weighted over 22 years).

For-Profit SNFs

1.962

Average Yield Moody's AAA Bonds (vintage-weighted over 22 years).

Other Capital-related Expenses

0.760

CPI-U for Residential Rent.

0Total

* 100.000

* Total may not equal 100 due to rounding

In the proposed 1997-based SNF market basket, the labor-related share for FY 1997 is 73.588 percent, while the non-labor-related share is 26.412 percent. The labor-related share reflects the proportion of the average SNF's costs that vary with local area wages. This share includes wages and salaries, employee benefits, professional fees, labor-intensive services, and a 39.1 percent share of capital-related expenses, as shown in Table 10.C. By comparison, the labor-related share of the 1992-based SNF market basket was 75.888 percent. The labor-related share of the market basket is the sum of the weights for those cost categories that are influenced by the local labor market. The labor-related share is calculated from the base year, which for the proposed SNF market basket is FY 1997.

The labor-related share for capital-related expenses was estimated using a statistical analysis of individual SNF Medicare Cost Reports for 1997, similar to the analysis done on the 1992 SNF Medicare Cost Reports and explained in the May 12, 1998

Federal Register

(63 FR 26289). The statistical analysis was necessary because the proportion of capital-related expenses related to local area wage costs cannot be directly determined from the SNF capital-related portion of the market basket. We used regression analysis with total costs per day in SNFs as the dependent variable and relevant explanatory variables for size, complexity, efficiency, age of capital, and local wage variation. To account for these factors, we used number of beds, case-mix indexes, occupancy rate, ownership, age of assets, length of stay, FTEs per bed, and wage index values based on the hospital wage index (wages and employee benefits) as independent variables. Our regression analysis indicated that the coefficient on the area wage index was 73.588, which represents the proportion of total costs that vary with local labor markets, holding constant other factors. From the operating portion of the market basket, we can specifically identify cost categories that reflect local labor markets and include them in the labor-related share. These cost categories equal 69.727, and reflect approximately 77 percent of operating costs. Thus, the labor-related share for capital-related costs is 3.861 (73.588 minus 69.727), and reflects approximately 39 percent of capital-related costs.

Capital-related expenses are determined in some proportion by local area labor costs (such as construction worker wages and building materials costs) that are reflected in the price of the capital asset. However, many other inputs that determine capital costs are not related to local area wage costs, such as equipment prices and interest rates. Thus, it is appropriate that capital-related expenses would vary less with local wages than would operating expenses for SNFs. Therefore, we are proposing to use this analysis in determining the labor-related share for SNF PPS.

All price proxies for the proposed revised and rebased SNF market basket are listed in Table 10.B and summarized in the Appendix to this proposed rule. A comparison of the yearly historical percent changes from FY 1995 through FY 2000 for the current 1992-based market basket and the proposed 1997-based market basket is shown in Table 10.D.

Table 10.C.—1992 and Proposed 1997-Based Labor-Related Share

Cost category

1992-based skilled nursing facility market basket weight

Proposed 1997-based skilled nursing facility market basket weight

Wages and Salaries

54.262

52.263

Employee Benefits

12.797

10.734

Nonmedical Professional Fees

1.916

2.634

Labor-intensive Services

3.686

4.094

Capital-related

3.227

3.861

Total

75.888

73.588

Table 10.D.—Comparison of the 1992-Based Skilled Nursing Facility Market Basket and the Proposed 1997-Based Skilled Nursing Facility Market Basket, Percent Changes, 1995-2000

Fiscal years beginning October 1

1992-based skilled nursing facitlity market basket

Proposed 1997-based skilled nursing facility market basket

Historical:

October 1994, FY 1995

2.9

3.0

October 1995, FY 1996

2.7

2.7

October 1996, FY 1997

2.4

2.4

October 1997, FY 1998

2.8

2.8

October 1998, FY 1999

3.1

3.0

October 1999, FY 2000

4.1

4.0

Historical average 1995-2000:

3.0

3.0

Released by HCFA, OACT, National Health Statistics Group.

The historical average rate of growth for 1995 through 2000 for the proposed SNF 1997-based market basket is similar to that of the 1992-based market basket. The proposed 1997-based SNF market basket provides a more current measure of the annual price increases for total care than the 1992-based SNF market basket because the cost weights reflect the structure of costs for the most recent year for which there are relatively complete data. The forecasted rates of

growth for FY 2002 for the proposed 1997-based and current 1992-based SNF market basket are shown in Table 10.E.

Table 10.E.—Comparison of Forecasted Change for the 1992-Based Skilled Nursing Facility Market Basket, and the Proposed 1997-Based Skilled Nursing Facility Market Basket Percent Change for FY 2002

Fiscal Year beginning October 1

1992-based skilled nursing facility market basket

1997-based skilled nursing facility market basket

October 2001, FY 2002

3.0

2.9

Source: Standard & Poor's DRI HCC, 1st QTR, 2001; @ USMARCRO/MODTREND@CISSIM/TRENDLONG0201.

Released by HCFA, OACT, National Health Statistics Group.

IV. Update Framework

A. The Need for an Update Framework

Medicare payments to SNFs are based on a predetermined national payment amount per day. Annual updates to these payments are required by section 1888(e) of the Act. These updates are usually based on the increase in the SNF market basket. For FY 2002, the update is set at market basket minus 0.5 percent. Our goal is to develop a method for analyzing and comparing expected trends in the underlying cost per day to use in establishing these updates.

The SNF market basket, or input price index, developed by HCFA's Office of the Actuary (OACT) is just one component in the SNF cost per day amount. It captures only the pure price change of inputs (labor, materials, and capital) used by the SNF to produce a constant quantity and quality of care. Other factors also contribute to the change in costs per day, which include changes in case-mix, intensity, and productivity.

Under the inpatient hospital PPS, HCFA and MedPAC use an update framework to account for these other factors and to make annual recommendations to the Congress concerning the magnitude of the update. We are currently examining these factors and exploring ways that they could be incorporated into an update framework for the SNF PPS. We are also examining some additional conceptual and data issues that must be considered when the framework is constructed and applied.

We are not proposing to apply an update framework in a recommendation to the Congress at this time. We are actively pursing development efforts aimed at producing an analytical framework which, by informing policy makers concerning the magnitude of annual updates, would support the continued appropriateness and relevance of the payment rates for services provided to beneficiaries in SNFs. To this end, we are requesting comments concerning the conceptual approach we have outlined in this proposed rule, including the utility and feasibility of this approach for SNFs. We are specifically interested in comments concerning whether certain factors should be accounted for in the framework, and suggestions concerning potential data sources and analysis to support the model. As with the existing methodology, the features of a SNF-specific update framework would need to be based on a sound policy and methodology.

B. Factors Inherent in SNF Payments per Day

In order to understand the factors that determine SNF costs per day, it is first necessary to understand the factors that determine SNF payments per day. Payments per day under SNF PPS are based on the cost and an implicit normal profit margin to the SNF in providing an efficient level of care. We have developed a methodology to identify a mutually exclusive and exhaustive set of factors included in SNF payments per day. The discussion here details a set of equations to identify these factors.

In its simplest form, the average payment per day to a SNF can be separated into a cost term and a profit term as shown in equation (1):

EP10MY01.000

This equation can be made multiplicative by converting profit per day into a profit rate as shown in equation (2):

EP10MY01.001

An output price term can be introduced into the equation by multiplying and dividing through by input prices and productivity. As shown in equation (3), the term inside the brackets represents the output price, since an output price reflects the input price and profit margin adjusted for productivity:

EP10MY01.002

The cost per day term can be further separated by accounting for real case-mix. Under SNF PPS, Resource Utilization Groups (RUGs) are used to classify patients. Based on accurate RUG classification data, average real case-mix per day can be incorporated, as shown in equation (4):

EP10MY01.003

The term “real” is imperative here because only true case-mix should be measured, not case-mix caused by improper coding behavior. By rearranging the terms in equation (4), a set of mutually exclusive and exhaustive factors such as those shown in equation (5) can be identified:

EP10MY01.004

The term of the equation in brackets can be analyzed in two steps. First, excluding the productivity term from the equation results in case-mix adjusted real cost per day, which is input intensity per day. Second, multiplying input intensity by productivity results in case-mix adjusted real payment per day, or output intensity per day. The rationale behind this step is explained in detail in the next section.

The result of this exercise is that SNF payment per day can be determined from the following factors:

EP10MY01.005

Thus, it holds that the change in SNF payment per day is a function of the change in these factors. In order to determine an annual update that most accurately reflects the underlying cost to the SNF of efficiently providing care, the four factors related to cost must be accounted for when an update framework is developed. A brief discussion of each factor, including specific conceptual and data issues, is provided in the next section.

C. Defining Each Factor Inherent in SNF Costs per Day

Each cost factor from equation (6) above is discussed here in detail. Because this is a basic conceptual discussion, it is likely that more detailed issues may be relevant that are not explored here.

1. Input Prices

Input prices are the pure prices of inputs used by the SNF in providing services. When we refer to inputs we are referring to costs, which have both a price and a quantity component. The price is an input price, and the quantity component reflects real inputs, or real costs. Similarly, when we refer to outputs, we are referring to payments, which also have both a price and a quantity component. The price component is the transaction output price, and the quantity component is the real output, or real payment. The real inputs include labor, capital, and materials, such as drugs. By definition, an input price reflects prices that SNFs encounter in purchasing these inputs, whereas an output price reflects the prices that buyers encounter in purchasing SNF services. We currently can measure input prices using the SNF market basket.

2. Productivity

Productivity measures the efficiency of the SNF in producing outputs. It is the amount of real outputs, or real payments, that can be produced from a given amount of real inputs, or real costs. For SNFs, these inputs are in the form of both labor and capital; thus, they represent multi-factor productivity, as not just labor productivity is reflected. The following set of equations shows how multi-factor productivity can be measured in terms of available data, such as payments, costs, and input prices:

EP10MY01.006

Rearranging the terms, this multi-factor productivity equation was used as the basis for incorporating an output price term in equation (3) above. This equation is the basis for understanding the relationship between input prices, output prices, profit margins, and productivity.

Equation (6) shows that productivity is divided through the equation, offsetting other factors. The theory behind this offset is that if an efficient SNF in a competitive market can produce more output with the same amount of inputs, the full increase in input costs does not have to be passed on by the provider to maintain a normal profit margin.

3. Real Case-Mix per Day

Real case-mix per day is the average overall mix of care provided by the SNF, as measured using the RUG classification system. Over time, a measure of real case-mix will change as care is given in more or less complex RUGs. Changes in the level of care within a RUG classification group would not be reflected in a case-mix measure based on RUGs, but instead should be captured in the intensity factor of equation (6).

The important distinction here is the difference between real and nominal case-mix. SNFs submit claims using the RUG classification system. The case-mix reflected by the claims is considered “nominal”. However, the reported classification can reflect the true level of care provided or improper coding behavior. An example of improper coding behavior would be the upcoding, or case-mix “creep,” that took place when the hospital PPS was implemented. Any change in case-mix that is not associated with the actual level of care or a true change in the level of care provided must be excluded in order to determine real case-mix. Section 1888(e)(4)(F) of the Act provides us with the statutory authority to make adjustments to the unadjusted Federal per diem rates for changes caused by case-mix creep.

4. Case-Mix-Constant Real Output Intensity per Day

Intensity is the true underlying nature of the product or service and can take the form of output and/or input intensity. In the case of SNFs, output intensity per day is associated with real payment per day, while input intensity per day is associated with real cost per day. For example, input intensity would be associated with a therapist's hours when providing treatment, whereas output intensity would be associated with the amount of treatments a therapist provides. The underlying nature of SNF services is determined by such factors as technological capabilities, increased utilization of inputs (such as labor or drugs), site of care, and practice patterns. Because these factors can be difficult to measure, intensity per day is usually calculated as a residual after the other factors from equation (6) have been accounted for.

Accounting for output intensity associated with an efficient SNF can be more accurately analyzed using a SNF's costs rather than its payments. This analysis would also provide an alternative to developing or using a transaction output price index, which has been difficult for the Bureau of Labor Statistics (BLS) to measure for SNFs. The following series of equations shows how to use the definition of an output price as defined earlier to convert the equation for output intensity per day to reflect costs instead of payments, as used in equation (6):

EP10MY01.007

The last equation is identical to the term in brackets in equation (5), case-mix-constant real input intensity per day multiplied by productivity. Thus, output intensity per day can be defined in such a way that cost data from the SNF are utilized. This equation can be broken down even further to account for different types of input intensity per day. We discuss this matter more fully in the next section.

D. Applying the Factors That Affect SNF Costs per Day in an Update Framework

As discussed earlier, payments per day under SNF PPS must be updated each year. Currently, the updates are specified by legislation as the percent change in the SNF market basket for FY 2001, the percent change in the SNF market basket minus 0.5 percentage points for FY 2002 and FY 2003, and the percent change in the SNF market basket thereafter. However, it is important to understand the underlying trends in SNF costs per day for an efficient provider, especially should the change in these costs deviate from the legislated updates. The development of an update framework with a sound conceptual basis will provide this capability.

Earlier, factors inherent in SNF costs per day were identified. Changes in these factors determine the change in SNF costs per day. Fitting these factors into a framework would allow us to recommend updates each year that appropriately reflect changes in underlying costs for efficient SNFs. Accounting for each of these factors from equation (6) under SNF PPS is discussed below:

• Change in case-mix constant real output intensity per day would be accounted for in the update framework, reflecting the factors that affect not only case-mix constant real input intensity per day, but also productivity, which is determined separately. Factors that can cause changes in case-mix constant real input intensity per day include, but are not limited to, changes in site of service, changes in within-RUG case-mix, changes in practice patterns, changes in the use of inputs, and changes in technology available.

• As discussed earlier, changes in nominal case-mix are automatically included in the payment to the SNF. However, the law gives us the authority to make adjustments for case-mix change due to improper coding behavior. Therefore, the update framework should include an adjustment to convert changes in nominal case-mix per day to changes in real case-mix per day.

• Change in multi-factor productivity would be accounted for in the update framework. The availability of historical data on input prices, payments, and costs are useful in the analysis of this factor. MedPAC sets this factor as a target under hospital PPS.

• Changes in input prices for labor, material, and capital would be accounted for in the update framework. Our Office of the Actuary currently has an input price index, or market basket, for SNF services. This is the market basket referred to in the legislated updates. In an update framework, a

forecast error adjustment has typically been included, to reflect that the updates are set prospectively and some degree of forecast error is inevitable. In the case of the inpatient hospital PPS, this adjustment is made on a two-year lag and only if the error exceeds a defined threshold (0.25 percentage points).

E. Current HCFA Inpatient Hospital PPS and Illustrative SNF PPS Payment Update Frameworks

Table 11 shows the payment update framework for the current inpatient hospital PPS and an illustrative update framework for the SNF PPS. Some of the factors in the inpatient hospital PPS framework are computed using the Medicare Cost Report data, while others are determined based on policy considerations. The details of calculating each factor for the inpatient hospital PPS framework can be found in the August 1, 2000

Federal Register

(65 FR 47054) final rule that set forth updates to the payment rates used under the inpatient PPS. This design for a SNF update framework is for illustrative purposes only, as much more work needs to be done to determine the appropriate level of detail for each factor and the manner in which the factors would be developed through policy. The numbers provided for the hospital update are only intended to serve as examples of prior updates recommended for the hospital PPS.

MedPAC supports the use of this type of framework for updating payments and applies a similar framework when it proposes updates to hospital payments in its annual recommendation to Congress. The appropriateness of this framework for updating inpatient hospital payments was discussed in the Health Care Financing Review, Winter 1992, in an article entitled, “Are PPS Payments Adequate? Issues for Updating and Assessing Rates.” A similar framework would be useful for analyzing updates to SNF payments.

Table 11.—Current HCFA Hospital PPS and Illustrative SNF PPS Payment Update Frameworks

HCFA hospital PPS update

FY 2001 calculated hospital update

percent change

Illustrative SNF PPS update

Percent Change in:

HCFA PPS Hospital Market Basket

3.4

HCFA SNF Market Basket.

Forecast Error

0.0

Forecast Error.

Productivity

−0.5 to −0.4

Productivity.

Output Intensity

0.0 to −0.6

Output Intensity:

Science and Technology

Science and Technology

Practice Patterns

Real within-DRG Change

Real within-RUG Change.

Site of Service

Utilization of Inputs.

Site of Service.

Case-mix Adjustment Factors:

Case-mix Adjustment Factors:

Projected Case-mix

−0.5

Nominal across-RUG Case-mix.

Real across-DRG Change

0.5

Real across-RUG Change.

Total Cost per Admission

−0.5 to −1.0

Total per Diem Cost.

Other Policy Factors:

Other Policy Factors:

Reclassification and Recalibration

0.0

None.

Total Calculated Update

2.4 to 2.9

Total Calculated Update.

Table data derived from the August 1, 2000

Federal Register

, Medicare Program; Changes to the Hospital Inpatient Prospective Payment System and Fiscal Year 2001 Rates; Final Rule.

F. Additional Conceptual and Data Issues

Three conceptual issues specific to the SNF PPS are the relevance of a site-of-service substitution adjustment, the necessity of an adjustment for RUG reclassification, and the handling of one-time factors.

Under the inpatient hospital PPS, a site-of-service substitution factor (captured as part of intensity) was necessary because of the incentive to shift care from hospital inpatient to such other settings as hospital outpatient, SNFs, or home health agencies (HHAs). For SNF PPS, it must be determined whether incentives to shift care to these other settings will continue or whether the SNF PPS will reduce these incentives and/or create alternative incentives to shift care out of SNFs. It is not clear without additional research in this area whether changes in behavior created by the different Medicare payment systems should be reflected in a SNF update framework.

A reclassification and recalibration adjustment under the inpatient hospital PPS is necessary to account for additional changes in the case-mix factor resulting from reclassifying and recalibrating the DRG classification software. This factor is applied to the current fiscal year update, but reflects the effect of revisions in the fiscal year two years prior. MedPAC does not account for this adjustment in its update framework. Whether a RUG reclassification adjustment would be necessary in the update framework would depend on the data availability and the likelihood of revisions to RUG classifications on a periodic basis.

There is also a question about how to handle one-time factors, such as the increased costs of converting computer systems to Year 2000 (Y2K) compliance. An update framework is the appropriate mechanism to account for these items, but because of uncertainty surrounding their impact on costs, determining an appropriate adjustment amount may be difficult. MedPAC has discussed this issue in prior sessions, but was unable to agree on the exact methodology for these types of factors.

The purpose of this conceptual discussion is not to determine how the identified factors of the update framework would be measured. We do recognize, however, that it would be important to use the Medicare Cost Report (MCR) and other relevant data from SNFs to analyze the factors that would account for growth in costs per day. As was the case for the inpatient hospital PPS, we will be required to make optimal use of the MCR data as we proceed in the development of an update framework methodology.

The lack of historical case-mix data is another important issue. These data are

currently being collected under contract but will not be available for most historical years. This factor may prove difficult to account for in a historical analysis. In addition, there is no information currently available to make the distinction between real and nominal case-mix change. There are also concerns about the BLS output price measures for SNFs, especially during the first years of publication in 1996 and 1997. Output prices are relevant for measuring productivity in a historical context. Most of these concerns were also encountered and addressed in the inpatient hospital PPS update framework.

The discussion here provides the conceptual basis for developing an update framework for SNF PPS that reflects changes in the underlying costs of efficiently providing SNF services. It is important to note that the framework does not handle distribution issues such as geographic wage variations.

Due to some variations in technical methodologies for measuring the factors of an update framework, and because of some of the data concerns mentioned earlier, implementing an update framework for SNF PPS would involve making significant policy decisions on issues similar to those for the inpatient hospital PPS update framework. We invite comments on the type of data sources to use, what other factors (if any) we should consider in an update framework, and any additional comments concerning the issues discussed in this proposed rule.

V. Consolidated Billing

The consolidated billing requirement established by section 4432(b) of BBA 1997 places the Medicare billing responsibility with the SNF for virtually all of the services that the SNF's residents receive, except for a small number of services that the law specifically identifies as being excluded from this provision. For services that are subject to this provision, the original legislation made no distinction as to whether the services were furnished during the course of a covered Part A SNF stay.

We have implemented consolidated billing only for services that are furnished during the course of a covered Part A SNF stay. We have not implemented consolidated billing for those services furnished to SNF residents who are not in a covered Part A stay (for example, residents who have exhausted their available days of coverage under the Part A SNF benefit, or who do not meet that benefit's post-hospital or level of care requirements). As explained in the final rule of July 30, 1999 (64 FR 41671), implementing the Part B aspect of the provision would entail making significant systems modifications, which have been delayed by systems constraints that arose in connection with achieving Y2K compliance.

In addition, recently enacted provisions in BIPA 2000 have also affected this aspect of consolidated billing. For services furnished on or after January 1, 2001, section 313(a) of BIPA 2000 amends section 1862(a)(18) of the Act by eliminating consolidated billing for most services furnished to SNF residents during noncovered stays. This amendment limits the application of consolidated billing to those services that are furnished during the course of a covered Part A stay, with one exception: for SNF residents in noncovered stays, the only services for which the SNF retains the Medicare billing responsibility are physical, occupational, and speech-language therapy. (The related requirements for fee schedule payment and appropriate HCFA Common Procedure Coding System (HCPCS) coding for Part B SNF services have not been repealed, and remain the law.) We propose to revise the regulations at § 411.15(p) to reflect this change.

We regard the provision of therapy services as an inherent and integral function of this type of facility, and we believe that the statutory requirement for SNFs to retain the Part B billing responsibility for these particular services reflects a number of policy considerations. First, these are services for which the SNF already has the billing responsibility under the separate Part B therapy cap provision enacted by section 4541 of BBA 1997. In addition, unlike some types of services (such as ambulance and laboratory) with which SNFs historically have had only limited billing experience, most SNFs are familiar with the procedures involved in furnishing and billing for therapy and other skilled rehabilitation services. In fact, section 1819(a)(1) of the Act describes such a facility in terms of being primarily engaged in furnishing skilled nursing or rehabilitation services to its residents. The SNF level of care definition in section 1814(a)(2)(B) of the Act defines a beneficiary's access to SNF coverage under Part A as involving the need for and receipt of “skilled nursing care * * * or other skilled rehabilitation services * * *”.

Finally, since the inception of the Medicare program, section 1861(h)(3) of the Act has provided for coverage of physical, occupational, and speech-language therapy services under the Part A extended care benefit when furnished either directly by the facility, or by others under arrangements with the facility. Thus, physical, occupational, and speech-language therapy are unique among SNF services because the law has always explicitly provided for Part A coverage of them when furnished under an arrangement with an outside supplier in which the SNF performs the Medicare billing for the services.

Section 313 of BIPA 2000 also contains a number of technical and conforming changes to reflect the amendment of section 1862(a)(18) of the Act, as discussed above. Section 313(b)(1) amends section 1842(b)(6)(E) of the Act (which provides that only the SNF can receive Part B payments for services furnished to those of its residents in noncovered stays), by limiting payment to SNFs to only those situations in which the SNF elects to furnish such Part B services—either directly with its own resources, or under an arrangement with an outside supplier in which the SNF assumes the billing responsibility. We are revising the regulations at § 410.150 to reflect this change. This section of the legislation also removes the existing language in section 1842(b)(6)(E) of the Act that refers to services furnished to a resident of “* * * a part of a facility that includes a skilled nursing facility (as determined under regulations)”. As explained in the May 12, 1998, SNF PPS interim final rule (63 FR 26297), BBA 1997 originally introduced this language in order to apply the consolidated billing requirement not only to the portion of a nursing home that is actually certified as a Medicare SNF, but also to any noncertified remainder:

This avoids creating a perverse incentive for SNFs to set aside a nonparticipating section in which they could otherwise circumvent the Consolidated Billing requirement for those residents who are not in a covered Part A stay.

However, since the consolidated billing requirement has now been limited to those residents in Part A covered stays, and physical, occupational, and speech-language therapy in noncovered stays, the language that extended its applicability to the noncertified portion of a nursing home is no longer relevant. This is reflected in our proposed change to the regulation at § 411.15.

Section 313(b)(2) of BIPA 2000 amends section 1842(t) of the Act by deleting a similar reference to the noncertified portion of a nursing home. Section 1842(t) of the Act requires that Part B claims for physician services furnished to SNF residents (which are excluded from consolidated billing)

must include the SNF Medicare provider number. Section 313(b)(2) of BIPA 2000 also expands this requirement to apply to Part B claims for all types of services furnished to SNF residents. For a SNF resident in a covered Part A stay, this expanded requirement would apply to claims for any type of service that is excluded from consolidated billing (and, thus, is separately billable to Part B by an outside source). For residents in a noncovered stay, it would encompass claims for all Part B services that the resident receives. We are proposing to revise the regulations at § 424.32 to reflect this change.

Section 313(b)(3) of BIPA 2000 amends the existing language in section 1866(a)(1)(H)(i)(I) of the Act by requiring compliance with section 1862(a)(18), as amended, under the terms of a SNF's Medicare provider agreement. We are proposing to revise the regulations at § 489.20 to reflect this change. Finally, section 313(d) of BIPA 2000 directs the Office of Inspector General to monitor payments for services furnished to SNF residents during noncovered stays, in order to help prevent duplicate payment or the excessive provision of services.

VI. Application of the SNF PPS to SNF Services Furnished by Swing-Bed Hospitals

A. Current System for Payment of Swing-bed Facility Services Under Part A of the Medicare Program

Section 1883 of the Act permits certain small, rural hospitals to enter into a swing-bed agreement, under which the hospital can use its beds to provide either acute or SNF care, as needed. Currently, Part A pays for SNF services furnished in Medicare swing-bed hospitals on a cost-related basis, with both calculated rate and retrospective, reasonable cost-based components. Under Medicare payment principles set forth in section 1883(a)(2)(B) of the Act and regulations at § 413.114, swing-bed facilities receive payment for two major categories of costs: routine and ancillary.

Routine costs are the costs of those services included by the provider in a daily service charge. Routine service costs include regular room, dietary, and nursing services, minor medical supplies, medical social services, psychiatric social services, and the use of certain facilities and equipment for which a separate charge is not made. Ancillary costs are costs for specialized services, such as therapy, drugs, and laboratory services, that are directly identifiable to individual patients. Capital-related costs, such as the cost of land, building, equipment, and the interest incurred in financing the acquisition of such items, are not reimbursed separately. Instead, they are incorporated

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