Congressional Budget Office

Background Paper

the congress of the united states

The Impact of Medicare’s 

Payment Rates on the 

Volume of Services Provided by 

Skilled Nursing Facilities

July 2007
Pub. No. 2761
The Congress of the United States O Congressional Budget Office

CBO

The Impact of Medicare’s 

Payment Rates on the Volume of Services 

Provided by Skilled Nursing Facilities

July 2007
Note

Unless otherwise indicated, all payment rates reflect payments per resident per day received by 

a skilled nursing facility from Medicare and from patients.
Preface

Rising costs in Medicare, Medicaid, and other federal health-related programs represent the 

central long-term fiscal challenge facing the nation. The Congressional Budget Office (CBO) 

is therefore increasingly focusing on analyzing the causes of those rising costs and potential 

policy responses.

Medicare’s spending under the fee-for-service portion of the program depends on the rates 

that Medicare pays to medical providers and the volume of services that medical providers 

supply to beneficiaries. The Congress has periodically limited growth in Medicare’s payments 

to providers to reduce spending. The effect on Medicare’s spending of changes in Medicare’s 

payment rates depends on whether and to what extent the volume of services adjusts in 

response. 

In this background paper, CBO examines changes in the volume of services provided by 

skilled nursing facilities (SNFs) in response to changes in Medicare’s payment rates for SNFs. 

As with other CBO background papers, it is designed to make the agency’s analyses more 

transparent by explaining CBO’s methods and assumptions. In keeping with CBO’s mandate 

to provide objective, nonpartisan analysis, this paper makes no recommendations.

Chapin White and Robert Nguyen of CBO’s Health and Human Resources Division prepared the paper under the supervision of James Baumgardner and Bruce Vavrichek. The 

report benefited from comments by Thomas B. Bradley, Arlene Holen, and Donald B. Marron, all of CBO. A number of outside reviewers also provided useful comments, including 

Melinda Beeuwkes Buntin of the RAND Corporation and Carol Carter and Jeffrey Stensland 

of the Medicare Payment Advisory Commission. (The assistance of external reviewers implies 

no responsibility for the final product, which rests solely with CBO.)

Christine Bogusz edited the paper, and Leah Mazade proofread it. Maureen Costantino prepared the paper for publication. Lenny Skutnik printed copies of the paper, Linda Schimmel 

handled the print distribution, and Simone Thomas prepared the electronic versions for 

CBO’s Web site (www.cbo.gov).

Peter R. Orszag

Director

July 2007

v

Contents

Summary and Introduction 1

Background Information 2

The Volume Response: A Theoretical Framework 2

Previous Empirical Research 4

Medicare’s Payment Rates for Skilled Nursing Facilities 4

Methods for Measuring the Volume Response Among

Skilled Nursing Facilities 6

Empirical Specification for Both Analyses 7

Specific Methods for the Geographic-Level Analysis 8

Data Sources for the Geographic-Level Analysis 9

Specific Methods for the Provider-Level Analysis 9

Data Sources for the Provider-Level Analysis 11

Results of the Analyses 11

Descriptive Statistics 11

Key Results for the Geographic-Level Analysis 11

Key Results for the Provider-Level Analysis 12

Discussion of the Results 14

Appendix: Detailed Regression Results 17
vi

Tables

1. Medicare’s Payment Rates for SNFs and the Volume of 

SNF Services Provided 6

2. Year-to-Year Changes in Total SNF Days from the 

Exit and Entry of SNFs,

1999 to 2003 10

3. Estimated Volume Responses Among SNFs to 

Changes of 1 Percent in Medicare’s Payment Rates 14

A-1. Detailed Regression Results from CBO’s

Geographic-Level Analysis 18

A-2. Detailed Regression Results from CBO’s 

Provider-Level Analysis 20

Figures

1. Changes in Medicare’s Payment Rates, 1997 to 2001, 

Based on CBO’s Geographic-Level Analysis 12

2. Year-to-Year Changes in Medicare’s Payment Rates,

1999 to 2003, Based on CBO’s Provider-Level

Analysis 13
The Impact of Medicare’s 

Payment Rates on the Volume of Services 

Provided by Skilled Nursing Facilities

Summary and Introduction

The central long-term fiscal challenge facing the nation 

involves rising costs in Medicare, Medicaid, and other 

federal health-related programs. The Congressional Budget Office (CBO) is therefore expanding its work in 

examining the rising costs within the nation’s federal 

health programs as well as possible policy responses.

Medicare’s benefit package includes coverage for shortterm posthospitalization care in skilled nursing facilities 

(SNFs). Medicare beneficiaries can qualify to receive 

Medicare-covered SNF care if they previously had an 

inpatient hospital stay of at least three days and if they 

require skilled nursing services. SNFs’ covered services 

include rehabilitation and medical services such as intravenous drug therapy.

Medicare spent $19.5 billion on SNF care in 2006, 

which is about 6.6 percent of total Medicare spending in 

the fee-for-service sector.1

 The system Medicare uses to 

determine SNF payment rates has undergone several 

major revisions in the past decade, the most significant of 

which was the introduction of a prospective payment system (PPS) in 1998. Under that system, Medicare pays a 

daily rate for SNF care that is calculated by combining a 

national base rate, a local wage index adjustor, and a casemix adjustor. In the years since the PPS was implemented, payment rates have been changed repeatedly, 

with the impact of those changes varying substantially 

across SNFs.

This Congressional Budget Office background paper 

measures how the volume of Medicare-covered SNF services adjusts in response to changes in Medicare’s SNF 

payment rates (the so-called volume response). The payment rate equals the payment received by a medical provider in exchange for providing a single unit of medical 

service; that rate comprises payments both from Medicare 

and from the patient. Although Medicare’s payment rates 

for SNFs have been changed repeatedly over the past 

decade, beneficiaries’ coinsurance for SNF care and other 

factors that affect the demand for that care have remained 

relatively stable. The volume response measured in 

this paper, therefore, reflects mainly a supply-driven 

phenomenon.

This paper includes two separate analyses. The two analyses take similar approaches, but they measure changes in 

payment rates and volume using different units of analysis over different periods. The use of two separate analyses 

provides a robustness check and offers some evidence on 

the sensitivity of the key findings to the analytical 

approach taken. In the geographic-level analysis, changes 

from 1997 to 2001 in SNF volume and payment rates are 

measured for 3,436 different hospital service areas, or 

HSAs. (HSAs are geographic areas corresponding to local 

health care markets.) The years 1997 and 2001 were chosen for the geographic analysis because they fall on either 

side of the implementation of the SNF prospective payment system. In the provider-level analysis, year-to-year 

changes in SNF volume and payment rates are measured 

for each SNF from 1999 through 2003. During those 

years, there were several legislative changes to Medicare’s 

SNF payment rates under the PPS.

Although most SNFs operate as units within freestanding 

nursing facilities, a significant share of SNFs are hospital 

based. Freestanding and hospital-based SNFs differ in 

several important ways. At the median, Medicare-covered 

1. Congressional Budget Office, “Fact Sheet for CBO’s March 2007 

Baseline: Medicare (Components of Benefits Payments),” p. 2.
2

SNF days made up 11 percent of total patient days in 

freestanding facilities in 2005 (the remaining patients in 

freestanding SNFs are non-Medicare patients or longterm care residents).2

 On average, hospital-based SNFs 

tend to largely serve Medicare beneficiaries. To account 

for that and other differences, this analysis measures 

volume responses among freestanding and hospital-based 

SNFs separately.

The geographic-level and provider-level analyses together 

provide evidence that the volume of Medicare-covered 

SNF days varies positively with Medicare’s SNF payment 

rates. For example, a change of 1 percent in Medicare’s 

payment rate for SNFs is estimated to result in a modest 

change of 0.13 percent in volume (based on the 

geographic-level analysis) or 0.23 percent (based on the 

provider-level analysis), with volume changing in the 

same direction as payment rates. In both the geographiclevel and provider-level analyses, that same direction of 

volume response is found among hospital-based and freestanding SNFs. 

The geographic-level analysis suggests that SNFs increase 

the volume of services they provide in response to an 

increase in payment rates and likewise decrease volume in 

response to a decrease in payment rates, with the magnitude of those responses being roughly similar. The 

provider-level analysis also suggests a modest and statistically significant increase in the volume of SNF services in 

response to payment increases (in that analysis, the 

response to payment decreases was not statistically significant). Overall, those findings imply that the impact on 

Medicare’s spending of a change in Medicare’s SNF payment rates will be magnified to some extent by the volume response, meaning that an increase in payment rates 

will lead to a somewhat larger percentage increase in 

Medicare’s spending on skilled nursing facilities.

Background Information

Volume response refers to a change in the volume of medical services in response to a change in the payment rate 

that medical providers receive. The measurement of volume response is relevant to CBO’s estimates of the 

impact on Medicare’s spending of proposed changes in 

Medicare’s payment rates. For example, a proposed 

increase of 1 percent in Medicare’s payment rates for 

SNFs could increase Medicare’s spending on that care by 

more than 1 percent if volume increased as a result of the 

change in payment rates, or by less than 1 percent if volume decreased.3 To date, there has been little research on 

changes in Medicare’s payment rates for skilled nursing 

facilities and how they affect Medicare’s spending.

In theory, providers will respond in certain ways to 

changes in payment rates. This section of the paper 

examines providers’ responses and reviews the relevant 

empirical research. It also looks at Medicare’s payment 

system for SNFs and the payment changes that underlie 

the analyses in this paper.

The Volume Response: A Theoretical Framework

In general, a change in the volume of medical services 

provided in response to a given change in the payment 

rate may stem from supply-side factors, demand-side 

factors, or both. An example of a demand-side volume 

response would be a coinsurance arrangement in which 

beneficiaries’ out-of-pocket payment equals a fixed share 

of the payment rate. Changes in the payment rate would 

lead directly to changes in the out-of-pocket payment, 

which would affect beneficiaries’ demand for services. In 

the case of Medicare’s SNF services, however, the out-ofpocket payment does not vary with the payment rate. 

For the first 20 days of a SNF stay, Medicare beneficiaries 

face no cost sharing for SNF care. Beginning on the 21st 

day of a SNF stay, Medicare beneficiaries pay a daily 

coinsurance amount. In recent years, that amount has 

increased roughly in line with general inflation, rising 

from $95 in 1997 to $119 in 2007. The out-of-pocket 

payment for Medicare’s SNF services does not vary across 

types of services, across the facilities themselves, or across 

regions, and it has remained stable over time. That fact 

implies that changes in SNF volume in response to 

changes in Medicare’s payment rate mainly reflect 

changes in the supply or availability of SNF care (which 

depends on factors such as input prices and licensing 

requirements) rather than changes in the demand for 

2. Medicare Payment Advisory Commission, Report to Congress: 

Medicare Payment Policy (March 2007), p. 171.

3. In cases in which a decrease in the payment rate has been found to 

lead to an increase in volume, the volume response has been 

referred to in the literature as a “volume offset.” That term is used 

because some of the savings to Medicare from the decrease in payment rates would be offset by the increase in volume.
3

SNF care (which depends on factors such as beneficiaries’ 

coinsurance, health status, and income).

Most previous research on the volume response of health 

care providers has focused on physicians. The behavior of 

physicians has been analyzed as a labor-supply decision, 

with a trade-off between working longer hours and earning more income or having more leisure time and earning 

less income.4

 An increase in fees paid to physicians will, 

according to the standard theoretical model, have two 

supply-side effects, which work in opposite directions. 

First, physicians will substitute work for leisure time 

because working has become more financially rewarding; 

second, physicians will decrease their supply of labor 

(work hours) because their potential income has 

increased and they can afford to “buy” more leisure time 

(“potential income” equals the amount a physician could 

earn if he or she only worked and spent no time on leisure activities). 

In the case of Medicare’s payments to physicians, changes 

in physicians’ fees also have a demand-side effect because 

of Medicare’s cost-sharing arrangements. Medicare beneficiaries’ cost sharing for physicians’ services is set equal to 

a percentage of the physicians’ fees. (Different approaches 

are used to determine beneficiaries’ cost sharing for SNF 

care and for other nonphysician services.) A change in 

physicians’ fees results in a proportional change in the 

coinsurance amount, which affects the demand for physicians’ services. The net effect of an increase in physicians’ 

fees on the volume of services provided could be either 

positive or negative, depending on the relative magnitudes of the two supply-side effects (the substitution 

effect that increases work hours and the income effect 

that decreases work hours) and the demand-side coinsurance effect.5

Researchers have also proposed theories regarding volume 

responses in institutional settings, such as hospitals, nursing facilities, and laboratories. In those settings, volume 

responses have been characterized as firms’ choosing their 

level of output in response to the payment rate, prices for 

medical inputs (primarily wages paid to their workers), 

and factors that affect demand. The key difference 

between firms’ and physicians’ choice of output level is 

that physicians have a demand for leisure time, whereas 

firms do not. Because of that difference, in the standard 

theoretical model of the behavior of an institutional provider, output would generally be assumed to rise in 

response to an increase in the payment rate and to fall in 

response to a decrease in the payment rate.6

One assumption underlying the analyses in this paper is 

that medical providers have some influence over the volume of medical services consumed. If that were not the 

case—if, for example, the consumption of medical services was determined solely by patients’ preferences or by 

some objective assessment of medical “need”—then 

changes in payment rates would not be expected to affect 

the volume of services consumed. In fact, the availability 

of medical services has been shown to exert a strong influence over the volume of medical services consumed, in 

particular the volume of so-called supply-sensitive services.7 In the specific case of post-acute care, the level of 

availability of different types of services has been shown 

to be a strong predictor of whether patients use postacute care and what type of that care they use.8

Changes in Medicare’s payment rates for SNF care could 

lead to supply-driven changes in the volume of SNF services provided. For example, in response to changes in 

Medicare’s payment rates, SNFs could alter the availability of the care they provide through changes in the num4. See, for example, Thomas G. McGuire and Mark V. Pauly, “Physician Response to Fee Changes with Multiple Payers,” Journal of 

Health Economics, vol. 10, no. 4 (1991), pp. 385–410.

5. Congressional Budget Office, Factors Underlying the Growth in 

Medicare’s Spending for Physicians’ Services (June 2007).

6. For a theoretical analysis of hospitals’ responses to payment 

changes and a summary of early evidence on the effects of Medicare’s PPS for hospitals, see Dominic Hodgkin and Thomas G. 

McGuire, “Payment Levels and Hospital Response to Prospective 

Payment,” Journal of Health Economics, vol. 13, no. 1 (March 

1994), pp. 1–29. A volume offset could occur in the hospital setting if a hospital, facing a reduction in the payment rate, increased 

its output to maintain its total revenues. That type of behavior 

might be expected if the hospital had large fixed costs and was 

concerned primarily with its own survival rather than maximizing 

its profits.

7. John E. Wennberg, Elliott S. Fisher, and Jonathan S. Skinner, 

“Geography and the Debate over Medicare Reform,” Health 

Affairs, Web exclusive (February 13, 2002), pp. W96–W114.

8. Melinda Beeuwkes Buntin and others, How Much Is Post-Acute 

Care Use Affected by Its Availability? Working Paper No. 10424 

(Cambridge, Mass.: National Bureau of Economic Research, 

2004), available at http://papers.nber.org/papers/w10424.pdf.
4

ber of patients they treat, changes in their target mix of 

patients, or changes in their marketing practices (or all 

three). It is beyond the scope of this analysis to determine 

the exact mechanisms by which SNF volume could adjust 

in response to changes in payment rates, however. 

Previous Empirical Research

Most of the recent empirical research on the volume 

response of health care providers has focused on the effect 

of fees paid to physicians on the volume of services provided by physicians.9 The results of those studies are 

mixed: Some studies find that an increase in physicians’ 

fees is associated with a decrease in the volume of services 

provided;10 other studies find the opposite.11

Although hospitals account for a large share of total 

Medicare spending, there has been little empirical work 

done on volume responses in that setting. One recent 

paper found that increases in Medicare’s payment rates 

for hospitals were associated with upcoding (toward 

diagnosis-related groups whose prices have been raised) 

rather than increases in the volume of admissions.12 A 

separate study, which focused on the home health care 

setting, linked lower payment rates with a lower volume 

of home health care services.13

The lack of agreement in the empirical literature on physicians’ volume response almost certainly stems, at least in 

part, from differences in research methods and data 

sources. That lack of agreement may also reflect the fact 

that the direction of the physicians’ volume response is 

theoretically ambiguous and may, in reality, vary over 

time and across types of services. That theoretical ambiguity does not apply to services provided by institutions 

such as hospitals or nursing facilities. Perhaps as a consequence, the little research that has been done on those 

types of facilities points consistently toward volume varying positively with payment rates.

Medicare’s Payment Rates for 

Skilled Nursing Facilities

From the 1980s through the mid-1990s, Medicare’s outlays for SNFs increased rapidly. Between 1983 and 1997, 

annual growth in those outlays averaged 26 percent.14

Since 1997, Medicare’s system for paying for skilled nursing care has undergone a series of major revisions, with 

substantial impacts on the payment rates SNFs receive. 

Prior to those revisions, SNFs were paid by Medicare on a 

cost-reimbursement basis, meaning that SNFs were reimbursed for the actual costs they reported, subject to certain limits. Those limits were applied to routine costs, 

such as nursing and housekeeping, but not to ancillary 

9. Several decades ago, prior to the rise of managed care and 

government-run administered pricing systems, physicians had a 

great deal of discretion over the fees they charged and the payment 

rates they received. In that context, an appropriate model of physicians’ volume responses would treat both the volume of 

physicians’ services and payment rates as jointly determined 

outcomes of interest (see, for example, Martin S. Feldstein, “The 

Rising Price of Physicians’ Services,” Review of Economics and Statistics, vol. 52, no. 2, May 1970, pp. 121–133; and Mark V. Pauly 

and Mark A. Satterthwaite, “The Pricing of Primary Care Physicians Services: A Test of the Role of Consumer Information,” Bell 

Journal of Economics, vol. 12, no. 2, Autumn 1981, pp. 488–506). 

More-recent research on physicians’ volume responses, reflecting 

the institutional changes that have occurred, generally assumes 

that payment rates are not chosen by the physician or patients and 

that physicians and patients respond to externally driven changes 

in payment rates.

10. Sandra Christensen, “Volume Responses to Exogenous Changes 

in Medicare’s Payment Policies,” Health Services Research, vol. 27, 

no. 1 (April 1992), pp. 65–79; Xuan Nguyen Nguyen and Frederick William Derrick, “Physician Behavioral Response to a Medicare Price Reduction,” Health Services Research, vol. 32, no. 3 

(August 1997), pp. 283–298; and Winnie C. Yip, “Physician 

Response to Medicare Fee Reductions: Changes in the Volume of 

Coronary Artery Bypass Graft (CABG) Surgeries in the Medicare 

and Private Sectors,” Journal of Health Economics, vol. 17, no. 6 

(December 1998), pp. 675–699.

11. Jon Gruber and others, “Physician Fees and Procedure Intensity: 

The Case of Cesarean Delivery,” Journal of Health Economics,

vol. 18, no. 4 (August 1999), pp. 473–490; Jean M. Mitchell and 

others, “Spillover Effects of Medicare Fee Reductions: Evidence 

from Ophthalmology,” International Journal of Health Care 

Finance and Economics, vol. 2, no. 3 (2002), pp. 171–188; and 

Jean M. Mitchell and others, “Physicians’ Responses to Medicare 

Fee Schedule Reductions,” Medical Care, vol. 38, no. 10 (2000), 

pp. 1029–1039.

12. Leemore S. Dafny, “How Do Hospitals Respond to Price 

Changes?” American Economic Review, vol. 95, no. 5 (December 

2005), pp. 1525–1547.

13. Robin McKnight, Home Care Reimbursement, Long-Term Care 

Utilization, and Health Outcomes, Working Paper No. 10414 

(Cambridge, Mass.: National Bureau of Economic Research, 

2004), available at http://papers.nber.org/papers/w10414.pdf.

14. Centers for Medicare and Medicaid Services, “2006 Medicare and 

Medicaid Statistical Supplement,” available at www.cms.hhs.gov/

MedicareMedicaidStatSupp/. 
5

services, such as physical and occupational therapy. As a 

result, Medicare’s reimbursements to SNFs for ancillary 

services grew more rapidly than its reimbursements for 

routine costs.

In part to rein in Medicare’s spending, lawmakers enacted 

the Balanced Budget Act of 1997, which replaced the 

cost-reimbursement system for SNFs with a prospective 

payment system. Under that system, SNFs are paid a 

fixed rate per resident per day.15 The daily payment rate 

is set separately for different categories of residents and 

equals a national base rate multiplied by a local wage 

adjustor and a case-mix adjustor. The base rate is updated 

annually on the basis of changes in the SNF market basket (an index of input prices for SNFs calculated by the 

Centers for Medicare and Medicaid Services, or CMS). 

The local wage adjustor used by CMS in setting payment 

rates reflects differences across geographic regions in local 

hospital wages.16 The case-mix adjustor is assigned separately to each SNF resident and reflects the estimated 

resource costs of caring for that resident.17 To assign casemix adjustors, CMS groups residents into resource utilization groups (RUGs) on the basis of a detailed assessment of each resident that is filled out by SNF staff.

After the initial implementation of the PPS, several large 

nursing facility chains reported large financial losses and 

filed for bankruptcy. In part, those bankruptcies 

prompted the Congress to pass an additional set of legislative changes that temporarily increased Medicare’s SNF 

payment rates.18 Both the Balanced Budget Refinement 

Act of 1999 (BBRA-1999) and the Benefits Improvement 

and Protection Act of 2000 (BIPA-2000) increased SNF 

payment rates across the board and also provided targeted 

increases for certain case-mix categories. For example, 

BBRA-1999 temporarily increased by 20 percent payment rates for 15 of the 44 RUGs. The expiration of 

those temporary increases in 2002 resulted in a decline 

in average payment rates between 2002 and 2003 (see 

Table 1). 

The shift in Medicare’s payment method for SNFs from 

cost reimbursement to prospective payment resulted in 

only fairly modest changes in the national average payment rates. The mean inflation-adjusted Medicare payment rate dropped from $357 in 1997 (pre-PPS) to $317 

in 1999 (immediately post-PPS) and then rose again to 

$343 in 2001 (see Table 1). The impact on individual 

SNFs was much more varied; many experienced substantial increases in payment rates, but many others experienced sizable decreases.

In general, the introduction of the PPS compressed payment rates. That compression in the distribution of 

payment rates reflects the switch from a system in which 

payment rates depended on each SNF’s costs to a system 

in which a uniform national formula was used (albeit 

with geographic-level and patient-level adjustors). SNFs 

that in the pre-PPS period had higher costs per patientday (and, therefore, higher payment rates) generally faced 

declines in payment rates, whereas SNFs that had lower 

costs (and, therefore, lower payment rates) generally faced 

increases in payment rates.

Before the PPS was implemented, hospital-based SNFs 

received much higher payment rates, on average, than 

15. Each SNF began the transition to the new payment system beginning with its first cost-reporting period on or after July 1, 1998. 

During the three-year transition period, part of the payment rate 

that each SNF received was based on the facility’s specific historical unit cost. By fiscal year 2002, all SNFs were paid the PPS federal rate.

16. CBO includes in the regression analyses a measure of the change 

over time in local hospital wages (measured by aggregating salaries 

and hours for all hospitals in each county or HSA). That measure 

differs from the wage adjustor used by CMS in setting payment 

rates. CBO calculated changes over time in the wages paid by hospitals during the periods corresponding to the changes in SNF 

volume. The local wage adjustor calculated by CMS was not used 

because, by the time it could have been applied in setting payment 

rates, it would have been based on data that were several years out 

of date.

17. Julie Stone, Medicare’s Skilled Nursing Facility Payment, CRS 

Report for Congress RL33921 (March 14, 2007), available at 

www.congress.gov/erp/rl/pdf/RL33921.pdf. At different times 

during a single stay, SNF residents may be assigned to different 

case-mix categories if their resident assessments change over the 

course of their stay.

18. For a discussion of the bankruptcies and the adequacy of Medicare’s payment rates for SNFs, see the statement of Laura A. Dummit, Associate Director, Health Financing and Public Health 

Issues, Health, Education, and Human Services Division, General 

Accounting Office (now the Government Accountability Office), 

before the Senate Special Committee on Aging, Nursing Homes: 

Aggregate Medicare Payments Are Adequate Despite Bankruptcies, 

GAO/T-HEHS-00-192 (September 5, 2000), available at 

www.gao.gov/archive/2000/he00192t.pdf.
6

Table 1.

Medicare’s Payment Rates for SNFs and the Volume of SNF Services Provided

Source: Congressional Budget Office analysis of Medicare administrative data.

Notes: SNF = skilled nursing facility.

Payment rates are inflated to the fourth quarter of 2003 using the national SNF market basket index. For the geographic-level analysis, 

payment rates and the volume of SNF services are calculated at the level of the hospital service area, and statistics are weighted by the 

number of fee-for-service beneficiaries in each area in 1997. For the provider-level analysis, payment rates and the volume of SNF 

services are calculated at the level of the SNF, and statistics are weighted by the average payments each SNF receives for Medicarecovered services. The number of SNFs included in the provider-level analysis is about 14,000 in each year.

freestanding SNFs did. With the implementation of the 

PPS, therefore, they tended to face decreases in payment 

rates. Conversely, most freestanding SNFs faced increases 

in payment rates. Among both hospital-based and freestanding SNFs, however, there was a great deal of variation from one SNF to the next in the impact of the new 

system on payment rates.19 The variation across SNFs 

both in the initial impact of the prospective payment system and in the impact of the changes from BBRA-1999 

and BIPA-2000 provides a valuable opportunity for 

research into how SNFs respond to changes in payment 

rates.

Methods for Measuring the Volume 

Response Among Skilled Nursing 

Facilities

This paper uses two approaches to measure the effect 

on volume of changes in Medicare’s SNF payment rates. 

The first is a geographic-level analysis, and the second is 

a provider-level analysis. Although those two empirical 

approaches are broadly similar, they use different data 

sets, units of analysis, and time periods. In both analyses, 

the percentage change in the volume of Medicare-covered 

SNF services is explained by the percentage change in the 

real (inflation-adjusted) payment rate and other control 

variables. Each approach identifies a component of the 

change in SNF payment rates that is directly attributable 

to changes in Medicare’s payment formula and is not 

attributable to other factors (such as changes in the 

demographics of the SNF patient population or changes 

in the types of services provided by SNFs). 

Both analyses focus exclusively on the services provided 

to Medicare beneficiaries who are enrolled in the traditional fee-for-service program. Medicare beneficiaries 

enrolled in private managed care plans (termed Medicare 

Advantage) are excluded because data on SNF volume 

All SNFs 357 343 317 316 343 348 315

Freestanding SNFs 332 341 308 311 341 350 317

Hospital-Based SNFs 463 350 356 344 350 338 303

All SNFs 1.36 1.35 2,786 2,933 3,275 3,649 3,964

Freestanding SNFs 1.11 1.18 2,659 2,846 3,215 3,636 3,983

Hospital-Based SNFs 0.25 0.17 3,550 3,506 3,700 3,741 3,806

Average Medicare Payment Rate (2003 dollars) 

Volume of SNF Services Provided (Days per beneficiary for geographic-level analysis 

and days per facility for provider-level analysis)

Geographic-Level Analysis Provider-Level Analysis

1997 2001 1999 2000 2001 2002 2003

19. The average SNF payment rate (in 2003 dollars and keeping the 

case mix constant) declined by 4.7 percent during the 1997–2001 

period but by only 2.1 percent during the 1999–2003 period. 

One measure of variation—the range in payment rate changes 

between the 75th and 25th percentiles—was 44.6 percent in the 

former period and 20.4 percent during the latter period. (Those 

data underlie Figures 1 and 2.)
7

and payment rates are not available for those beneficiaries. CBO chose to use resident-days, rather than spending or admissions, as the measure of the volume of SNF 

services because resident-days are used as Medicare’s basis 

of payment for SNFs as well as Medicare beneficiaries’ 

coinsurance payments for SNFs.

Empirical Specification for Both Analyses

The following general empirical specification is used in 

all the regression analyses in this paper:

where indexes either the geographic area or the SNF, 

 equals the arc percentage change in the volume of 

Medicare-covered SNF days, equals the arc percentage change in case-mix-constant real SNF payment rates, 

 includes a set of control variables, and is an error 

term. The change in SNF volume, , is defined using 

an arc percentage change formula:

where the subscript denotes the base year and 

denotes a later year.20

The change in the SNF payment rate, , is also 

defined using an arc percentage change:

where the subscript denotes a case-mix group (that is, a 

group of SNF residents with similar clinical characteristics and resource needs), where and denote a 

national index of input prices for SNFs, and where 

denotes the payment rate for unit (either a geographic 

area or a SNF) for case-mix group in time .21

Defining the arc percentage change in SNF payment 

rates in that way holds the case mix constant using the 

base-year distribution and adjusts for inflation in prices 

of inputs. CBO’s method for calculating the change in 

payment rates is referred to as a Laspeyres-type index 

because payment rates in the base year and the later year 

are both multiplied by the case-mix distribution in the 

base year. The change in the payment rate, , is attributable solely to real changes in payment rates within each 

case-mix group, rather than changes in the distribution of 

patients across case-mix groups.

In the regression analyses, the dependent variable, , 

measures the arc percentage change in SNF volume. 

Because the dependent variable captures a change over 

time, the coefficient vector, , captures differential time 

trends that vary with the control variables included in . 

The control variables in include state indicator variables, an indicator for rural location, and an indicator for 

large urban location, as well as percentage changes in 

local real income per capita and local hospital wages.22

The coefficients on the state indicator variables capture 

the impact of state-specific trends that might affect SNF 

utilization, such as changes in Medicaid’s payment rates

20. Arc percentage changes are used rather than simple percentage 

changes or natural logarithm-based changes 

 for two reasons: First, the arc percentage change 

is defined (that is, nonmissing) even when volume is zero in either 

the base year or the later year; and, second, the arc percentage 

change is naturally bounded by the range [-2, 2], which reduces 

the need to screen for extreme values.

ΔQi βΔPi Xi = + +γ εi

i

ΔQi

ΔPi

Xi εi

ΔQi

ΔQi

Qi t , 2 – Qi t , 1

Qi t , 1 + Qi t , 2 ( ) ⁄ 2 = ---------------------------------------

t1 t2

Qi t , 2 Qi t , 1 ( ) – Qi t , 1 ( ) ⁄

ln Qi t , 2 Qi t , 1 ( ) ( ) ⁄

ΔPi

ΔPi

Pict , , 2Qict , , 1

c

It2 Pict , , 1Qict , , 1

c

⁄ – It1 ⁄

Pict , , 2Qict , , 1

c

It2 ⁄ Pict , , 1Qict , , 1 It1 ⁄

c

 +   ⁄ 2

= --------------------------------------------------------------------------------------------------------

21. All payment rates are inflated to the fourth quarter of 2003 using 

the national SNF market basket index.

22. Income per capita is inflated using the consumer price index for 

all urban consumers. The percentage change in hospital wages is 

used as a proxy for local changes in SNFs’ input prices. The 

provider-level analysis includes additional controls that are not 

in the geographic-level analysis: an indicator variable for whether 

the SNF is hospital based, an indicator variable for nonprofit 

ownership, an indicator variable for for-profit ownership (the 

government-owned reference category is omitted), and an indicator variable for whether the SNF is a member of a large national 

chain (independence from a large chain is the reference category).

c

It1 It2

Pict , ,

i

c t

ΔPi

ΔQi

γ

Xi

Xi
8

or changes in other health sectors, such as home health 

care.23

The coefficient of interest, , captures the volume 

response, and it may be interpreted as follows. If, for 

example, equals 0.2, then an increase of (arc) 1 percent 

in the payment rate (that is, equals 0.01) is associated with an increase of (arc) 0.2 percent in SNF volume 

(that is, the estimated increases by 1 percent multiplied by 0.2).

In addition to estimating an overall SNF volume 

response, the analyses also estimate separate volume 

responses for hospital based and freestanding SNFs. In 

the geographic-level analysis, SNFs are first split into two 

groups, hospital based and freestanding, and then the 

changes in SNF volume and payment rates are calculated 

separately for those groups of SNFs, and separate regression models are run. In the provider-level analysis, 

separate regressions are run for hospital-based and freestanding SNFs. That approach allows the coefficient on 

the payment rate, , and the vector of coefficients on the 

control variables, , to vary for hospital-based versus freestanding SNFs.

CBO used additional models to estimate separate volume 

responses for SNFs that received real increases and 

real decreases in payment rates. Two separate variables 

are used to capture the changes in payment rates: 

, which equals if the SNF or the geographic area faced an increase in the payment rate and 

equals zero, otherwise; and , which equals 

 if the SNF or the geographic area faced a decrease in 

the payment rate and zero, otherwise. The volume 

responses for increases and decreases in payment rates are 

calculated separately for hospital-based versus freestanding SNFs, which produces four separate volume response 

coefficients (increases to hospital-based SNFs, decreases 

to hospital-based SNFs, and so on).24

Specific Methods for the Geographic-Level Analysis

As a first step in the geographic-level analysis, CBO 

grouped Medicare fee-for-service beneficiaries into hospital service areas on the basis of their zip code of residence. 

HSAs, which were developed by the Center for the Evaluative Clinical Sciences at Dartmouth Medical School, 

represent local health care markets and are defined on the 

basis of observed patterns of health care utilization.25 The 

analytical data set includes one observation for each HSA. 

There are 3,436 HSAs, and each has an average of around 

10,000 Medicare fee-for-service beneficiaries.26

The volume of SNF services, which is measured at the 

HSA level in 1997 and 2001, equals the mean Medicarecovered SNF days per beneficiary per year. The volume of 

SNF services is defined on the basis of a beneficiary’s residence; SNF days are attributed to the beneficiary’s HSA 

regardless of the location of the SNF used. SNF volume is

23. Several major changes to Medicare policy were implemented 

around the same time as the new prospective payment system for 

SNFs. Those changes include clarification of the eligibility standards for Medicare’s home health benefit and transitions to prospective payment for the following types of providers: home 

health agencies, hospital outpatient departments, inpatient rehabilitation facilities, long-term care hospitals, and psychiatric facilities. The impact of the changes in the home health care sector was 

particularly striking, with Medicare’s spending on home health 

care falling by more than half from 1997 to 1999 and then 

rebounding sharply beginning in 2001. The changes occurring in 

sectors outside SNFs may have affected trends in SNF utilization 

if SNFs have the potential to serve as substitutes for those other 

sectors. The state indicator variables are included in the analyses 

to help control for the changes that were occurring in other 

sectors.

β

β

ΔPi

ΔQi

β

γ

ΔPi increase ΔPi 24. In the geographic-level analysis, areas with large concentrations 

of hospital-based SNFs are highly correlated with areas facing a 

payment rate decrease. Estimating responses to increases and 

decreases separately for hospital-based versus freestanding SNFs 

helps avoid confusing the effect of having a large concentration of 

hospital-based SNFs with the effect of facing a decrease in payment rates. In the provider-level analysis, however, because 

hospital-based SNFs are more likely than freestanding SNFs to 

experience decreases in payment rates, controlling for hospitalbased and freestanding SNFs can be done directly by including 

the hospital-based/freestanding fixed effects and their interactions 

with the price variable on the right-hand side of the regression 

equation.

25. Dartmouth Medical School, Center for the Evaluative Clinical 

Sciences, The Dartmouth Atlas of Health Care (Hanover, N.H.: 

American Hospital Publishing, 1996).

26. In 2002, 90 percent of HSAs had a Medicare fee-for-service population of between 700 and 37,000.

ΔPi decrease

ΔPi
9

adjusted for beneficiaries’ age and sex.27 The year 1997 

was chosen as the initial year because it was just before 

the prospective payment system was implemented; 2001 

was chosen as the end year because the system had been 

phased in by then, and SNFs had had an opportunity to 

respond to the new payment rates.

For a given HSA, the arc percentage change in the payment rate is calculated on the basis of the payment rates 

for SNFs serving beneficiaries living in that HSA. To calculate that change in payment rates, case-mix-constant 

payment rates are first calculated for each SNF in 1997 

and 2001, and then HSA-level payment rates are calculated as weighted means of the SNF-level payment rates. 

The first step is to calculate the mean SNF payment rate 

for each SNF in 1997. The second step is to simulate the 

mean payment rate for each SNF in 2001, assuming that 

each SNF’s case mix is held constant.28 Then HSA-level 

mean SNF payment rates are calculated for 1997 and 

2001 from SNF-level payment rates using the following 

weight: the fraction of SNF days provided by each facility 

in 1997 to beneficiaries living in a given HSA. The HSAlevel change in payment rates equals the arc percentage 

difference between the 1997 HSA-level mean payment 

rate and the simulated case-mix-constant 2001 payment 

rate. That arc percentage change is attributable solely to 

the implementation of the prospective payment system 

and does not reflect changes in SNFs’ case mix or SNFs 

entering or exiting the market. For the geographic-level 

analysis, each HSA is weighted by the number of Medicare fee-for-service beneficiaries living in that HSA in 

1997.

Data Sources for the Geographic-Level Analysis

Data on Medicare beneficiaries’ zip code of residence, utilization of SNF services, and payments to SNFs are all 

taken from Medicare administrative records that include 

100 percent of fee-for-service beneficiaries and SNF days. 

Beneficiaries’ zip code of residence and fee-for-service 

enrollment are taken from the “Denominator” file, SNF 

utilization (Medicare-covered days and payments) is 

taken from the “MEDPAR” file, and SNF characteristics 

are taken from the “Provider of Services” file. Countylevel characteristics (urbanization and income) are taken 

from the 2004 Area Resource File (ARF).29 The “crosswalk” from zip code to HSA is provided by the Dartmouth Atlas of Health Care.30 Hospital wages are calculated from Medicare’s hospital cost reports.

Specific Methods for the Provider-Level Analysis

The provider-level analysis measures the SNF volume 

response using data at the provider level from 1999 (the 

first full year after implementation of Medicare’s new 

payment system) through 2003 (one year after the full 

transition to the PPS in 2002). The analysis reflects the 

payment add-ons by BBRA-1999 and BIPA-2000, which

27. To adjust SNF volume for beneficiaries’ demographics, the volume of SNF services (SNF days per beneficiary) is first measured 

for the year 1998 for different demographic cells. Those demographic cells are defined by combinations of age group (under 65, 

65 to 74, 75 to 84, and 85 and up) and sex. The 1998 SNF volume by demographic cell is then multiplied by the number of 

beneficiaries in each HSA in each demographic cell in each year—

that calculation yields a predicted SNF volume for each HSA for 

each year. The adjusted SNF volume for a given HSA is then calculated by multiplying the actual SNF volume in the HSA by the 

inverse of the ratio of predicted SNF volume in that HSA to the 

national mean SNF volume for that year.

28. Simulated 2001 payment rates are used instead of observed 2001 

payment rates, for several reasons. A mean payment rate could be 

calculated for each SNF for 2001, but the differences between the 

observed 1997 payment rates and the observed 2001 payment 

rates reflect not just legislative changes to Medicare’s payment formula (which is the focus of the analysis) but also changes in SNFs’ 

patient populations and in the services SNFs provide. In addition, 

some SNFs exited the market between 1997 and 2001; for those 

facilities, the mean 2001 payment rate cannot be calculated. A 

detailed explanation of the process of simulating 2001 payment 

rates for each SNF is available in Chapin White, “Medicare’s New 

Prospective Payment System for Skilled Nursing Facilities: Effects 

on Staffing and Quality of Care,” Inquiry, vol. 43, no. 1 (Winter 

2005/2006), pp. 351–366.

29. The county-level data from the ARF are aggregated to generate 

HSA-level measures by taking the weighted means of the countylevel measures (using as the weight the fraction of Medicare feefor-service beneficiaries living in a given HSA who also live in a 

given county).

30. Dartmouth Medical School, Center for the Evaluative Clinical 

Sciences, Zip Code to HSA to HRR Crosswalk File (accessed 

May 15, 2003).
10

Table 2.

Year-to-Year Changes in Total SNF Days from the Exit and Entry of SNFs, 

1999 to 2003

Source: Congressional Budget Office analysis of Medicare administrative data.

Notes: SNF = skilled nursing facility.

A SNF is defined as an “entrant” if it provided Medicare-covered SNF services in a given year but not in the prior year, and it is defined 

as an “exiter” if it provided Medicare-covered SNF services in a given year but not in the next year.

Total SNF days are the number of Medicare-covered SNF days provided by all SNFs in a given year.

produced substantial price variations across SNFs (most 

of those add-ons ended in 2003).31

Volume is measured by the number of Medicare-covered 

SNF days provided by a given facility in a given year. The 

data set used for the provider-level analysis includes one 

observation for each combination of SNF and year-pair. 

For example, for a given SNF, there is one observation for 

1999–2000 (changes in volume and payment rates are 

measured from 1999 to 2000), another observation for 

2000–2001, and so forth. The changes in payment rates 

are calculated using a Laspeyres-type index, in which the 

mix of patients in the base year is used to generate an 

average payment rate in both the base year and the next 

year.

For SNFs that entered or exited the system during that 

five-year span, the arc percentage changes are calculated 

differently. A SNF is defined as an “entrant” if it provided 

Medicare-covered SNF services in a given year but not in 

the prior year, and it is defined as an “exiter” if it provided 

Medicare-covered SNF services in a given year but not in 

the next year. For exiters, the arc percentage changes in 

payment rate and volume are calculated using the standard formulas. For entrants, although it is possible to calculate the arc percentage change in volume using the 

standard formula, there is no information available on the 

distribution of patients across case-mix groups in the base 

year. Therefore, for entrants, the arc percentage change in 

payment rates in the year-pair in which they enter is calculated using a Paasche-type index, which incorporates 

the case-mix distribution in the later year.

The data show that the impact on total SNF days from 

the exit and entry of SNFs during the 1999–2003 period 

was not substantial (the net change was never larger than 

1 percent; see Table 2). The net loss of days resulting 

from the exit of SNFs, however, increased throughout the 

period, rising from 0.3 percent of total days during the 

1999–2000 period to 0.8 percent during the 2002–2003 

period.

41 43 48 53

43 48 53 57 ___ ___ ___ ___

Change in total SNF days (Millions) 1.9 4.7 5.1 4.5

Days lost from exit of SNFs (Thousands) 435 386 388 444

Days gained from entry of SNFs (Thousands) 316 299 14 4 ____ ___ ____ ____

Net change in total SNF days (Thousands) -119 -87 -374 -440

-0.3 -0.2 -0.7 -0.8

Total SNF Days (Millions)

In originating year

1999–2000 2000–2001 2001–2002 2002–2003

In ending year

Net Change as a Percentage of 

Total SNF Days in Ending Year

31. The real average payment per day declined by 9.5 percent in 2003 

(see Table 1). That drop would have been even larger had RUG 

refinement been implemented in 2003. (The 20 percent increase 

to 15 RUG groups and the 6.7 percent increase to 14 rehabilitation RUG groups initiated by BBRA-1999 and BIPA-2000 still 

remained in 2003 because RUG refinement was not implemented 

that year.)
11

To examine whether SNFs responded differently to payment decreases than to payment increases, CBO created 

separate variables for increases and decreases in payment 

rates using the same approach as in the geographic-level 

analysis. In the provider-level analysis, each provider is 

weighted by payments it receives from Medicare-covered 

services.32

Data Sources for the Provider-Level Analysis

The primary data source for the provider-level analysis is 

a set of Medicare administrative records that summarize 

claims for each combination of SNF, case-mix group, and 

year. Payment rates are computed for each case-mix 

group within each facility for each year. Each facility’s 

characteristics are taken from the “Provider of Services” 

file and Medicare’s SNF cost reports. County-level characteristics (urbanization and income) are taken from the 

2004 Area Resource File, and hospital wages are computed from Medicare’s hospital cost reports.

Results of the Analyses

The results of the geographic- and provider-level analyses 

indicate that the volume of SNF services varies positively 

with the SNF payment rate and that those responses 

occur among both freestanding and hospital-based SNFs. 

In both analyses, increases in payment rates are found to 

result in modest increases in volume. In the geographiclevel analysis, decreases in payment rates are found to 

result in decreases in volume, whereas in the providerlevel analysis, decreases in payment rates are found not to 

affect volume significantly.

Descriptive Statistics

CBO’s analysis of Medicare administrative data provides 

descriptive statistics on the volume of SNF services and 

changes in SNF payment rates (all payment rates are 

expressed in 2003 dollars). 

The geographic-level analysis shows that the mean Medicare payment per SNF day declined by 4 percent between 

1997 and 2001, falling from $357 to $343, while the volume of SNF services was nearly unchanged at 1.36 days 

per beneficiary in 1997 and 1.35 days in 2001 (see the 

left panel of Table 1). In 1997, prior to the implementation of the prospective payment system, mean payment 

rates were much higher for hospital-based SNFs than for 

freestanding SNFs, $463 versus $332. By 2001, after the 

payment system had been fully implemented, that gap 

had almost entirely disappeared, reflecting a sharp drop 

in mean payment rates for hospital-based SNFs and a 

slight increase in mean payment rates for freestanding 

SNFs. The volume of hospital-based SNF services 

declined fairly sharply from 1997 to 2001, from 

0.25 days per beneficiary to 0.17 days, while the volume 

of freestanding SNF services increased slightly, from 

1.11 days to 1.18 days. It is notable that both payment 

rates and volume declined among hospital-based SNFs 

but increased among freestanding SNFs. That fact provides some preliminary evidence that SNF volume varies 

positively with the payment rate.

The provider-level analysis shows that in 2003, the mean 

SNF payment rate was almost identical to the mean payment rate in 1999 ($315 versus $317), but payment rates 

fluctuated sharply in the intervening years (see the right 

panel of Table 1). Changes legislated by BBRA-1999 and 

BIPA-2000 raised SNF payment rates in 2001 and 2002, 

but those rates dropped sharply in 2003. Mean SNF days 

for each facility increased substantially from 1999 to 

2003, particularly among freestanding SNFs.

CBO’s analysis also shows the distribution of the changes 

in Medicare’s payment rates. In the geographic-level analysis, there is a great deal of variation in the distribution of 

changes in payment rates across areas—at the 90th percentile, the SNF payment rate increased by 23.2 percent, 

whereas at the 10th percentile, the SNF payment rate 

decreased by 33.0 percent (see Figure 1). In the providerlevel analysis, the distribution of changes in payment 

rates is narrower, but there is still a substantial amount of 

variation across SNFs and from year-pair to year-pair (see 

Figure 2).

Key Results for the Geographic-Level Analysis

The key regression results for the geographic-level analysis indicate that increases in SNF payment rates are 

32. Several edits are performed on the provider-level data to limit the 

influence of observations with extreme values. First, an editing 

screen is used to identify and remove observations with unusual 

changes in volume or payment rate. Second, observations that are 

found to be very highly influential in the basic model are removed 

from all provider-level analyses. Those edits are based on information in David A. Belsley and others, Regression Diagnostics: Identifying Influential Data and Sources of Collinearity (New York: 

Wiley-Interscience, 1980).
12

Figure 1.

Changes in Medicare’s Payment Rates, 1997 to 2001, Based on CBO’s 

Geographic-Level Analysis

(Arc percentage change)

Source: Congressional Budget Office analysis of Medicare administrative data.

Notes: SNF = skilled nursing facility.

This figure presents statistics on the distribution of the arc percentage changes in Medicare’s case-mix-constant payment rates for 

SNFs. All payment rates are inflated to the fourth quarter of 2003 using the national SNF market basket index. Changes in payment 

rates are calculated at the level of the hospital service area, and statistics are weighted by the number of fee-for-service beneficiaries 

in each area in 1997.

associated with a statistically significant increase in SNF 

volume and that decreases in payment rates are associated 

with decreases in volume (see the left panel of Table 3). 

Among all SNFs, a change of 1 percent in the SNF payment rate is associated with a change in SNF volume 

of 0.13 percent. Compared with the volume-response 

coefficient for freestanding SNFs, the coefficient for 

hospital-based SNFs is found to be larger (0.26), which 

implies that hospital-based SNFs are more responsive 

than freestanding SNFs to changes in payment rates. 

Among hospital-based SNFs, both those facing increases 

in payment rates and those facing decreases in payment 

rates exhibited similar responses, with volume in both 

cases changing in the same direction as the change in the 

payment rate.33 Among freestanding SNFs, the coefficients on increases and decreases in payment rates are not 

individually statistically significant, but they are jointly 

statistically significant, and both point estimates are similar to the overall volume response.

Key Results for the Provider-Level Analysis

The results of the provider-level analysis provide further 

evidence of the existence of a statistically significant volume response (see the right panel of Table 3). In the analysis including all SNFs, the coefficient on the change in 

the payment rate is 0.23, which implies that a change of 

1 percent in the SNF payment rate would lead to a 

change in volume of 0.23 percent in the same direction as 

the change in the payment rate. In the provider-level 

analysis, the volume response is found to be statistically 

significant only among freestanding SNFs. When 

increases and decreases in payment rates are analyzed separately, increases in payment rates are found to result in 

increases in volume among both freestanding and hospital-based SNFs, but decreases in payment rates are not 

associated with statistically significant changes in volume.

All SNFs Freestanding SNFs Hospital-Based SNFs

-70

-60

-50

-40

-30

-20

-10

0

10

20

30

90th Percentile

75th Percentile

Median

25th Percentile

10th Percentile

33. Among hospital-based SNFs, the magnitude of the volume 

response is larger among SNFs facing increases in payment rates 

than among those facing decreases (0.43 versus 0.20), but the difference is only weakly statistically significant (the p-value is less 

than 0.10).
13

Figure 2.

Year-to-Year Changes in Medicare’s Payment Rates, 1999 to 2003, Based on CBO’s 

Provider-Level Analysis

(Arc percentage change)

Source: Congressional Budget Office analysis of Medicare administrative data.

Notes: SNF = skilled nursing facility.

This figure presents statistics on the distribution of the arc percentage changes in Medicare’s case-mix-constant payment rates for 

SNFs. All payment rates are inflated to the fourth quarter of 2003 using the national SNF market basket index. Changes in payment 

rates are calculated at the level of the SNF, and statistics are weighted by the average payments each SNF receives for Medicarecovered services. The number of SNFs included in this analysis is about 14,000 in each year. 

1999–2000 2000–2001 2001–2002 2002–2003

-15

-10

-5

0

5

10

15

90th Percentile

75th Percentile

Median

25th Percentile

10th Percentile

All SNFs

1999–2000 2000–2001 2001–2002 2002–2003

-15

-10

-5

0

5

10

15

90th Percentile

75th Percentile

Median

25th Percentile

10th Percentile

Freestanding SNFs

1999–2000 2000–2001 2001–2002 2002–2003

-15

-10

-5

0

5

10

15

90th Percentile

75th Percentile

Median

25th Percentile

10th Percentile

Hospital-Based SNFs
14

Table 3.

Estimated Volume Responses Among 

SNFs to Changes of 1 Percent in 

Medicare’s Payment Rates

(Percent)

Source: Congressional Budget Office analysis of Medicare administrative data.

Notes: SNF = skilled nursing facility; ** = p-value < 0.05; 

*** = p-value < 0.01.

This table presents the key coefficients for a set of regression models. In each regression model, the dependent variable is the arc percentage change in the volume of 

Medicare-covered SNF services. In the geographic-level 

analysis, the volume of SNF services is measured by the 

number of Medicare-covered SNF days per beneficiary. In 

the provider-level analysis, the volume of SNF services is 

measured by the number of Medicare-covered SNF days 

provided by each facility. The statistics presented in this 

table are the coefficients on the arc percentage change in 

Medicare’s real payment rate for SNFs. A higher volumeresponse coefficient implies a more responsive SNF. For the 

geographic-level analysis, beneficiaries are grouped into 

hospital service areas on the basis of their zip code of 

residence, and regressions are weighted by the number of 

fee-for-service beneficiaries in each area in 1997. For the 

provider-level analysis, regressions are weighted by the 

average payments each SNF receives for Medicare-covered 

services. 

Discussion of the Results

Both the geographic-level analysis and the provider-level 

analysis indicate that the volume of Medicare-covered 

SNF services varies positively with the payment rate, that 

the magnitude of the response is fairly modest, and 

that the response occurs both among freestanding and 

hospital-based SNFs. Although the provider-level analysis 

suggests that SNF volume responds only to increases in 

payment rates, the geographic-level analysis suggests that 

SNFs respond, in a roughly symmetrical fashion, to both 

increases and decreases in payment rates. 

One possible explanation for that finding is that increases 

in volume in response to higher payment rates might 

occur over a relatively short time frame, whereas decreases 

in volume in response to lower payment rates might 

occur over a longer time frame. The geographic-level 

analysis is suited to detecting long-run responses to 

changes in payment rates (because it measures the fouryear response from 1997 to 2001), whereas the providerlevel analysis is better suited to detecting short-run 

responses (because it measures annual responses from 

1999 to 2003).

The difference between the overall volume response estimated in the geographic-level analysis (0.13) and the 

response estimated in the provider-level analysis (0.23) is 

not statistically significant, although it deserves some 

comment. The difference between those two estimates 

could reflect different time periods,34 different levels of 

measurement error in the two types of analyses, or a bias 

in one or both of the analyses.35

The difference in estimated volume responses could also 

reflect a certain type of volume spillover effect. Suppose 

that there are two SNFs in the same geographic area 

and that one SNF receives a payment increase and the 

other does not. Based on the provider-level analysis, the 

SNF that receives the increase in payment rate is predicted to increase its volume relative to the SNF that 

receives no change in payment rate. One possible spillover effect of one SNF taking steps to increase its volume 

0.13 *** 0.23 ***

Freestanding 0.08 ** 0.22 ***

Hospital-based 0.26 *** 0.08

Increase in payment rate 0.06 0.30 ***

Decrease in payment rate 0.10 0.10

Increase in payment rate 0.43 *** 0.39 ***

Decrease in payment rate 0.20 *** -0.06

All SNFs

Freestanding SNFs

Hospital-based SNFs

Analysis Analysis

Geographic-Level Provider-Level

34. By examining the 1997–2001 period, the geographic-level analysis largely estimated the response of SNFs to Medicare’s transition 

from a cost-based system to a prospective payment system. In contrast, the provider-level analysis, by focusing on the 1999–2003 

period, estimated the response of SNFs to Medicare’s payment 

changes under the PPS.

35. Measurement error in an independent variable will result in a bias 

toward zero in the estimated coefficient on that variable in a 

regression analysis. The discrepancy between the estimated volume responses could be explained by the greater degree of error in 

the measurement of changes in payment rates in the geographiclevel analysis versus the provider-level analysis.
15

could be to draw some volume away from other SNFs in 

the same area. The change in volume as measured in the 

geographic-level analysis would reflect the combination 

of both the main effect (an increase in volume at the SNF 

that received a payment increase) and the volume spillover effect (a decrease in volume at the SNF that received 

no change in payment rate). That type of spillover effect 

could explain the finding of a larger volume response in 

the provider-level analysis than in the geographic-level 

analysis.

The results of this research indicate that the volume of 

SNF services varies positively with changes in Medicare’s 

payment rate. However, the total effect on Medicare’s 

SNF spending of a change in Medicare’s payment rate 

would also include the impact on the “intensity” of services. Intensity, as it is generally defined, is a measure of 

the average complexity and costliness of medical services. 

In the SNF setting, changes in intensity would result 

from changes over time in the shares of residents assigned 

to different case-mix categories. (Each case-mix category 

is assigned a separate payment rate.) 

One potential topic for future research is the possible 

existence of spillover effects from changes in payment 

rates for SNFs on the volume of services provided in 

other types of health care facilities. Other topics of interest include volume responses in institutional settings 

besides SNFs, such as hospitals and home health agencies. Volume responses, particularly in the hospital setting, are directly relevant to projections of the impact on 

Medicare’s spending of changes in payment rates.

17

Appendix:

Detailed Regression Results

This appendix presents detailed regression results (see 

Tables A-1 and A-2) from the Congressional Budget 

Office’s geographic-level analysis and provider-level analysis of how the volume of Medicare-covered skilled nursing facility (SNF) services adjusts in response to changes 

in Medicare’s SNF payment rates. In both sets of analyses, 

the dependent variable is the arc percentage change in the 

volume of Medicare-covered SNF days, and the key independent variable is the case-mix-constant arc percentage 

change in Medicare’s real (inflation-adjusted) payment 

rate for SNFs. For the geographic-level analysis, the unit 

of the analysis is the hospital service area (N = 3,436), 

and changes in volume and payment rates are measured 

from 1997 to 2001. For the provider-level analysis, the 

unit of analysis is the SNF, and changes in volume and 

payment rates are measured for each year-pair from 1999 

through 2003 (1999–2000, 2000–2001, and so on).
18

Table A-1.

Detailed Regression Results from CBO’s Geographic-Level Analysis

Continued

SNF Days per

Beneficiary for First Second First Second

All SNFs Regression Regression Regression Regression

Medicare's Payment Rate

for SNFsa 0.130*** (0.029)

Medicare's payment rate

for freestanding SNFs 0.079** (0.036)

Medicare's payment rate

for freestanding SNFs 

x "increase" indicatorb 0.065 (0.052)

Arc percentage change in

Medicare's payment rate

for freestanding SNFs 

x "decrease" indicatorb 0.098 (0.062)

Arc percentage change in

Medicare's payment rate

for hospital-based SNFs 0.256*** (0.040)

Arc percentage change in 

Medicare's payment rate

for hospital-based SNFs 

x "increase" indicatorb 0.429*** (0.107)

Arc percentage change in

Medicare's payment rate

for hospital-based SNFs 

x "decrease" indicatorb 0.197*** (0.053)

0.020* (0.011) 0.015 (0.013) 0.015 (0.013) 0.080*** (0.027) 0.074*** (0.027)

-0.023** (0.009) -0.003 (0.011) -0.003 (0.011) -0.052** (0.024) -0.053** (0.024)

Arc Percentage Change from

1997 to 2001 in

Hospital Wagesd -0.032 (0.046) -0.038 (0.055) -0.038 (0.055) 0.028 (0.120) 0.035 (0.120)

Rural Indicatorc

Large Urban Indicatorc

Arc percentage change in

Arc percentage change in

SNF Days per Beneficiary for

Variable

Arc Percentage Change in 

Freestanding SNFs

SNF Days per Beneficiary for

Hospital-Based SNFs
19

Table A-1.

Continued

Source: Congressional Budget Office analysis of Medicare administrative data.

Notes: SNF = skilled nursing facility; * = p-value < 0.10; ** = p-value < 0.05; *** = p-value < 0.01;

CPI = the consumer price index for all urban consumers.

Standard errors are shown in parentheses. All regressions are weighted by the number of fee-for-service beneficiaries in each hospital 

service area (HSA) in 1997. State indicator variables are included in each regression (coefficient estimates are not shown).

a. All payment rates are inflated to the fourth quarter of 2003 using the national SNF market basket index.

b. For each HSA, an “increase” indicator and a “decrease” indicator are defined separately for freestanding and hospital-based SNFs 

depending on whether the arc percentage change in Medicare's input price-inflated payment rate for that type of SNF is positive or negative. The sign of the reported coefficients, however, reflects the effect of an increase in the payment rate.

c. The “small urban” reference category is omitted.

d. Hospital wages are measured by aggregating salaries and hours for all hospitals in each HSA. For HSAs that do not contain a hospital, hospital wages are measured by aggregating all hospitals in the hospital referral region in which the HSA is located. Hospital referral regions 

are aggregations of HSAs that represent regional health care markets.

e. County-level income per capita is measured using the 2004 Area Resource File. The county-level income measures are aggregated to the 

HSA level using as weights the fraction of all Medicare beneficiaries living in each HSA who lived in the county in 1997.

SNF Days per

Beneficiary for First Second First Second

All SNFs Regression Regression Regression Regression

Arc Percentage Change from

1997 to 2001 in Real

(CPI-inflated) Income

per Capitae -0.322*** (0.074) -0.371*** (0.089) -0.372*** (0.089) 0.015 (0.194) 0.005 (0.194)

Estimated Difference

Between Coefficients

on "Increases" and

"Decreases" -0.033 (0.088) 0.232* (0.133)

F-statistic on Exclusion of

Both "Increases" and

"Decreases" in

Payment Rates 4.99** 36.24***

3,435 3,424 3,424 3,396 3,396

R-squared 0.326 0.244 0.244 0.250 0.251

Variable

Freestanding SNFs Hospital-Based SNFs

SNF Days per Beneficiary for SNF Days per Beneficiary for

Number of Observations
20

Table A-2.

Detailed Regression Results from CBO’s Provider-Level Analysis

Continued

SNF Days per

Facility for First Second First Second

All SNFs Regression Regression Regression Regression

Arc Percentage Change in 

Medicare's Payment Ratea 0.227*** (0.030) 0.219*** (0.040) 0.079 (0.052)

Arc percentage change in

Medicare's payment rate 

x "increase" indicatorb 0.302*** (0.060) 0.392*** (0.132)

Arc percentage change in

Medicare's payment rate 

x "decrease" indicatorb 0.104 (0.073) -0.058 (0.074)

0 (0.004) -0.004 (0.004) -0.004 (0.004) 0.015 (0.009) 0.013 (0.009)

0.003 (0.003) 0.005* (0.003) 0.005* (0.003) -0.012 (0.008) -0.012 (0.008)

Arc Percentage Change from

1997 to 2001 in

Hospital Wagesd 0.021 (0.018) 0.031 (0.020) 0.031 (0.020) -0.035 (0.053) -0.033 (0.053)

Arc Percentage Change from

1997 to 2001 in Real

(CPI-inflated) Income

per Capitae -0.182*** (0.055) -0.105* (0.060) -0.105* (0.060) -0.568*** (0.149) -0.559*** (0.149)

-0.048*** (0.005) -0.044*** (0.006) -0.033*** (0.009) -0.037*** (0.010) -0.031*** (0.010)

-0.002 (0.007) -0.004 (0.009) 0.001 (0.009) 0.050*** (0.012) 0.046*** (0.012)

0.002 (0.005) 0.006 (0.006) 0.017** (0.008) 0 (0.010) 0.007 (0.011)

Hospital-Based Indicatorg -0.104*** (0.004)

Nonprofit Indicatorh -0.003 (0.006) 0.015* (0.008) 0.015* (0.008) -0.019** (0.010) -0.018* (0.010)

For-Profit Indicatorh -0.006 (0.006) 0.007 (0.008) 0.007 (0.008) -0.008 (0.013) -0.008 (0.013)

Large Urban Indicatorc

SNF Days per Facility for

Hospital-Based SNFs

SNF Days per Facility for

2000-2001f

2001-2002f

Year-Pair Indicator 

1999-2000f

Variable

Freestanding SNFs

Rural Indicatorc
21

Table A-2.

Continued

Source: Congressional Budget Office analysis of Medicare administrative data.

Notes: SNF = skilled nursing facility; * = p-value < 0.10; ** = p-value < 0.05; *** = p-value < 0.01;

CPI = the consumer price index for all urban consumers.

Standard errors are shown in parentheses. All regressions are weighted by each SNF’s average Medicare expenditures. State indicator 

variables and indicator variables for the top 10 national chains are included in each regression (coefficient estimates are not shown).

a. All payment rates are inflated to the fourth quarter of 2003 using the national SNF market basket index.

b. Each SNF is defined as receiving an “increase” or a “decrease” separately for each year-pair depending on whether the arc percentage 

change in Medicare's input price-inflated payment rate for that SNF is positive or negative. The sign of the reported coefficients, however, 

reflects the effect of an increase in the payment rate.

c. The “small urban” reference category is omitted.

d. Hospital wages are measured by aggregating salaries and hours for all hospitals in each county. For counties that do not contain a hospital, corresponding state average hospital wages are used.

e. County-level income per capita is measured using the 2004 Area Resource File.

f. The “2002–2003 year-pair” reference category is omitted.

g. The “freestanding” reference category is omitted.

h. The “government-owned” reference category is omitted.

SNF Days per

Facility for First Second First Second

All SNFs Regression Regression Regression Regression

Estimated Difference Between

Coefficient on "Increases"

and "Decreases" 0.198* (0.105) 0.451***(0.175)

F-statistic on Exclusion of

Changes in Payment 

Rates for "Increases"

and "Decreases" 24.16*** 7.27***

Number of Observations 52,265 46,016 46,016 6,249 6,249

R-squared 0.050 0.036 0.036 0.049 0.050

SNF Days per Facility for SNF Days per Facility for

Freestanding SNFs Hospital-Based SNFs

Variable


INSIDE MAIL

CONGRESS OF THE UNITED STATES

CONGRESSIONAL BUDGET OFFICE

WASHINGTON, DC 20515