Medicare Hospital Subsidies: Money in Search of a Purpose

Medicare Hospital Subsidies AEI EVALUATIVE STUDIES Marvin H. Kosters Series Editor RETHINKING WIC: AN EVALUATION OF TH...

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Medicare Hospital Subsidies

AEI EVALUATIVE STUDIES Marvin H. Kosters Series Editor RETHINKING WIC: AN EVALUATION OF THE WOMEN, INFANTS, AND CHILDREN PROGRAM Douglas J. Besharov and Peter Germanis MEDICARE HOSPITAL SUBSIDIES: MONEY IN SEARCH OF A PURPOSE Sean Nicholson THE U.S. ORGAN PROCUREMENT SYSTEM: A PRESCRIPTION FOR REFORM David L. Kaserman and A. H. Barnett

Medicare Hospital Subsidies Money in Search of a Purpose Sean Nicholson

The AEI Press Publisher for the American Enterprise Institute WA S H I N G T O N , D . C . 2002

Available in the United States from the AEI Press, c/o Publisher Resources Inc., 1224 Heil Quaker Blvd., P.O. Box 7001, La Vergne, TN 37086-7001. To order, call 1-800-937-5557. Distributed outside the United States by arrangement with Eurospan, 3 Henrietta Street, London WC2E 8LU, England. ISBN 0-8447-4174-4 1 3 5 7 9 10 8 6 4 2

© 2002 by the American Enterprise Institute for Public Policy Research, Washington, D.C. All rights reserved. No part of this publication may be used or reproduced in any manner whatsoever without permission in writing from AEI except in the case of brief quotations embodied in news articles, critical articles, or reviews. The AEI Press Publisher for the American Enterprise Institute 1150 17th Street, N.W. Washington, D.C. 20036 Printed in the United States of America

Contents

FOREWORD, Christopher DeMuth

vii

ACKNOWLEDGMENTS

ix

1 INTRODUCTION

1

2 GRADUATE MEDICAL EDUCATION POLICY

7

3 DISPROPORTIONATE SHARE HOSPITAL PAYMENTS

25

4 THE EFFECT OF THE MEDICARE GME AND DSH SUBSIDIES

36

5 CONCLUSION

49

STATISTICAL APPENDIX

53

NOTES

69

REFERENCES

72

ABOUT THE AUTHOR

75

v

Foreword

The AEI Evaluative Studies series consists of detailed empirical analyses of government programs and policies in action. Each study documents the history, purposes, operations, and political underpinnings of the program in question; analyzes its costs, consequences, and efficacy in achieving its goals; and presents proposals for reform. The studies are prepared by leading academic students of individual policy fields and are reviewed by scholars, agency officials, and program proponents and critics before publication. The growth of public policy research in recent decades has been accompanied by a burgeoning of research and writing on proposed policies and those in the initial stages of implementation. Careful evaluation of the large base of existing programs and policies—many of them politically entrenched and no longer at the forefront of policy debate—has suffered from relative neglect. Within the government, program evaluation is typically limited to scrutiny of annual spending levels and of the number and composition of constituents who are served. Insufficient attention is devoted to fundamental questions: whether a program’s social or economic goals are being accomplished, whether the goals are worthy and important, and whether they might be better achieved through alternative approaches. The AEI series, directed by Marvin Kosters, aims to redress that imbalance. By examining government programs in action, it aims to direct more academic, political, and public attention to whether we are getting our money’s worth from well-established vii

VIII

FOREWORD

programs and whether current “policy reform” agendas are indeed focused on issues with the greatest potential for improved public welfare. CHRISTOPHER DEMUTH PRESIDENT AMERICAN ENTERPRISE INSTITUTE FOR PUBLIC POLICY RESEARCH

Acknowledgments

I would like to thank Mark Pauly, Barbara Wolfe, Jonathan Gruber, Robert Helms, Marvin Kosters, and two anonymous reviewers for their helpful comments, and David Song for his assistance in analyzing the data. Financial support was provided by the National Institute of Mental Health through training grant 5 T32 MH 18029-11.

ix

1 Introduction

In 1998 the Medicare program allocated $5.9 billion in graduate medical education (GME) payments to teaching hospitals and $4.5 billion in Medicare disproportionate share hospital (DSH) payments to hospitals that treat a substantial number of lowincome patients. These supplemental payments to hospitals are in addition to the standard reimbursement payments that all hospitals receive for providing inpatient services to Medicare beneficiaries. The standard reimbursement amounts, known as diagnostic related group or DRG payments, are set equal to the average cost of treating a Medicare patient with a particular health condition. DRG payments to all hospitals totaled $87.4 billion in 1998. Since DRG payments are intended to cover the cost of treating Medicare patients, the supplemental payments under the GME and DSH programs can be viewed as subsidies to hospitals. Supplemental reimbursements to hospitals in the form of GME and DSH payments have grown rapidly over the last decade. They now equal 12 percent of standard Medicare payments for inpatient hospital care under the DRG system, up from 8.6 percent in 1988. Since these payments are growing rapidly and are an important source of funds for many U.S. hospitals, the original rationale for these subsidies and their effects on hospital behavior are worth reviewing. Medicare’s Prospective Payment System is administered using DRG pricing formulas. Its two principal goals are (1) to ensure that Medicare beneficiaries have access to high-quality inpatient hospital care, and (2) to encourage hospitals to provide these services efficiently. To foster these objectives, DRG payments are set, as we have noted, at the average cost of treating 1

2

MEDICARE HOSPITAL SUBSIDIES

a Medicare patient. Some hospitals, however, such as teaching hospitals or hospitals with a high proportion of poor patients, have higher-than-average costs, and thus the government finds it appropriate to pay these hospitals more by giving them GME and DSH payments that take into account their systematic differences from average costs. The supplemental payments that teaching hospitals receive (GME payments) come in two kinds: direct medical education (DME) payments and indirect medical education (IME) payments. DME payments—instituted when Medicare was enacted in 1965—were justified on the grounds that some (costly) educational activities enhance the quality of hospital care; so hospitals should be compensated for the components of medical education that contribute to better patient care. IME payments were instituted in 1983 to compensate for the higher operating costs that teaching hospitals have—even after the additional costs of medical education are taken into account—because some legislators feared that if teaching hospitals didn’t receive the same degree of subsidization as nonteaching hospitals, Medicare beneficiaries might have less access to the presumed higher-quality care offered by teaching hospitals. The original justification for the Medicare DSH program was that poor Medicare patients were relatively costly to treat. Thus, if hospitals were to receive the same price for treating a poor patient as a nonpoor patient, poor Medicare beneficiaries might be denied access to hospital care. The GME and DSH policies reimburse hospitals to cover costs they are presumed to incur that exceed the payment they would receive under standard Medicare payment formulas. Reimbursement of these higher costs is intended to ensure that the payments hospitals receive are commensurate with the costs of the services they provide to Medicare beneficiaries. For several reasons, the existence and magnitude of GME and DSH payments are controversial. First, increased expenditures on these supplemental programs may lead to lower payments for nonteaching hospitals and hospitals that only treat an average number of poor patients. Congress sets the percentage increase in the standard DRG payments several years in advance,

INTRODUCTION

3

but until recently there had been no cap on GME and DSH supplemental payments. If the latter grow rapidly, Congress may respond by setting a lower rate of increase on DRG payments than they otherwise would. Second, the payments are more generous than can be justified by quantitative analysis. The payment formulas for both programs were based on empirical analysis of hospital costs. Congress set an IME payment that was double the size implied by the original (1983) regression analysis, and a similar analysis using more recent data resulted in a cost differential only half the original. Similarly, when more data were used to reestimate the relevant figure for Medicare DSH payments, empirical support for such payments vanished entirely. Despite these studies, DSH payments have became more generous instead of being cut back. The third reason the subsidies are controversial is that they are poorly designed. The IME and DSH payment formulas were open-ended from their inception until the Balanced Budget Act of 1997; total program expenditures were determined by the actions of hospitals as a group instead of policymakers. Open-ended policies are not in themselves problematic if expenditures increase only when hospitals change their behavior to achieve well-defined policy objectives. The IME and DSH policies, however, encouraged hospital behavior that was not consistent with Medicare’s aims or other social goals. The GME policy, for example, provides hospitals with financial incentives to hire residents, close beds, and admit more Medicare patients. Subsidizing the training of residents is an odd policy because the United States has no shortage of physicians. The Medicare DSH policy provides hospitals with incentives to admit more Medicaid and Medicare patients, but fewer uninsured patients. Discouraging hospitals from admitting uninsured persons is another odd policy, given that 14 percent of the U.S. population is uninsured and uninsured persons receive much less medical care than the insured. If hospitals respond to the financial incentives of these two policies, government expenditures will increase without any guarantee the money will further a declared policy objective. Although the empirical justification for the GME and DSH

4


policies has weakened and they contain perverse incentives, it is politically difficult to eliminate or revise the policies because they have become such an important source of revenue for hospitals, especially large teaching hospitals and public hospitals. The 5,100 short-term acute care U.S. hospitals are categorized in table 1* according to whether they received both GME and DSH payments in 1995, payments from one program only, or no supplemental payments. Although 2,364 hospitals received either GME or DSH payments, a mere 714 teaching hospitals, most of them located in urban areas, received almost three-quarters of the supplemental payments. Hospitals receiving both GME and DSH payments had average supplemental payments of $11 million each. The median hospital in this group received 5.6 percent of its revenue from GME and DSH payments and would probably have lost money if these programs were eliminated because the hospital’s overall profit margin was only 4.5 percent of revenue. Five percent of the hospitals in this category received at least 13 percent of their revenue from the GME and DSH programs. Supplemental payments are less important for the 423 teaching hospitals that only receive GME payments and for the 1,227 nonteaching hospitals that receive DSH payments only. The median hospital in these two categories received about 1.5 percent of its revenue from supplemental payments in 1995, although some hospitals in these two categories relied much more heavily on GME and DSH funds. Hospital profit margins for Medicare patients and all patients in 1992 and 1995 are presented in table 2 by type of hospital. The hospital categories are not mutually exclusive. For example, major teaching hospitals are listed as a separate category and also included in either the “DSH and teaching” category or the “teaching only” category. Major teaching hospitals and hospitals that received GME and DSH payments had the highest profit margins on Medicare patients in 1992 and 1995, largely because of the substantial supplemental payments. Yet despite the high Medicare profit margins they were earning, hospitals in these two * All tables and figures may be found in the Statistical Appendix beginning on page 53.

INTRODUCTION

5

categories were the least profitable hospitals overall, across all payer groups—further evidence that major urban teaching hospitals rely heavily on Medicare subsidies, and Medicare patients in general, to offset their losses on other payers, namely, Medicaid, private health plans, and self-paying/uninsured persons. Moreover, the major teaching hospitals and other teaching hospitals that received DSH payments became more dependent on Medicare between 1992 and 1995. This study reviews the rationales, legislative history, and financial incentives of the GME policy in chapter 2 and the DSH policy in chapter 3. In chapter 4 I examine whether teaching hospitals have responded to these price changes by hiring more residents and fewer nurses, and by closing beds. I examine nurse staffing because hospitals might have responded to the policy by replacing nurses with the now less expensive residents. There is evidence that teaching hospitals did respond to the price distortions created by the GME policy. I estimate that between 1984 and 1991 the policy increased the number of residents employed by U.S. hospitals by 6 percent, reduced the number of beds by 3 percent, and had no measurable effect on the use of registered nurses. This response, combined with the open-ended structure of the policy, allowed GME expenditures to increase substantially. The expansion of residency training will eventually lead to a larger physician workforce. The GME and DSH policies also increased the price that eligible hospitals received for treating Medicare and Medicaid patients, and lowered the price they received for treating uninsured patients. In chapter 4 I examine whether hospitals responded to these price changes by admitting a different mix of patients. The Medicare DSH policy appears to have had a small but measurable effect on the types of patients that hospitals treat. I estimate that the Medicare DSH policy increased the number of Medicaid admissions by about 3 percent and reduced charity care by less than 1 percent. Although the latter effect is small, it is ironic that a policy that was intended to promote access to hospital care for poor patients may actually worsen access for uninsured poor patients. The evidence on the effect of the GME and DSH policies on Medicare admissions is less clear.

6


Several studies have evaluated whether graduate medical education and DSH payments are appropriately sized, in the sense that the payments are commensurate with the extra costs associated with being a teaching hospital and treating poor patients (see Anderson and Lave 1986, Thorpe 1988, Rogowski and Newhouse 1992, Dalton and Norton 2000 for analysis of GME payments; U.S. Congressional Budget Office 1990, Kominski and Long 1997 for analysis of DSH). Yet despite the magnitude of the subsidies, there has been no systematic study in the economics or health services literature on the financial incentives of the GME and Medicare DSH programs, and the effect of these incentives on hospital behavior. Some proposed alternative structures for the GME and Medicare DSH policies are presented in chapter 5. The Balanced Budget Act of 1997 improved the design of the GME program but essentially left the DSH program intact. The GME policy is no longer open-ended, and the perverse incentives have been eliminated, but there still is no requirement that teaching hospitals document the activities or services they provide with the GME funds. In that sense, the policy still constitutes throwing money around.

2 Graduate Medical Education Policy

In 1997 there were about 1,100 hospitals in the United States that trained residents and were therefore classified as teaching hospitals. These institutions provide a substantial amount of patient care to insured and uninsured patients and have a strong influence on both the number of U.S. physicians and the specialties in which they practice. In 1997, teaching hospitals treated 44 percent of all inpatients, were responsible for an estimated 64 percent of that year’s $17.5 billion of uncompensated hospital care, and provided a training ground for approximately 64,000 medical students and 100,000 residents (ProPAC 1997, Mann et al. 1997). The Structure and Rationale of the Direct Medical Education (DME) Program Teaching hospitals receive two supplemental payments, or subsidies, from Medicare: direct medical education (DME) payments and indirect medical education (IME) payments. The DME subsidy reimburses a hospital for Medicare’s share of the direct costs of training residents. Direct costs include resident salaries, faculty salaries, and the administrative costs associated with running a residency program. Congress’s original rationale for covering medical education costs was to ensure that Medicare beneficiaries would be able to be treated at the highest quality hospitals: Many hospitals engage in substantial education activities, including the training of medical students, internship and residency programs, the training of nurses, and the training of various paramedical personnel. Educational activities enhance the quality of care in an institution and it is intended, until the community undertakes to bear such education 7

8

MEDICARE HOSPITAL SUBSIDIES costs in some other way, that a part of the net cost of such activities (including stipends of trainees as well as compensation of teachers and other costs) should be considered as an element in the cost of patient care, to be borne to an appropriate extent by the hospital insurance program. [Committee on Ways and Means 1965]

Perhaps not surprisingly, few communities have developed explicit measures to finance medical education in the thirty-five years since the passage of this bill, although private health insurance companies might argue that the higher price they pay to teaching hospitals does serve this function implicitly. When the Medicare program was instituted, teaching hospitals were allowed to “pass through” the direct costs of medical education. Since 1985, a hospital’s direct medical education payments are calculated by multiplying three terms: the proportion of patient days that are accounted for by Medicare patients, the hospital’s average direct cost of training a resident in 1984, updated to current dollars to account for inflation, and the number of residents the hospital employs in the current year:1 Medicare patient days DME = __________________ payments total patient days × cost of a × number of resident residents

(1)

The DME policy makes it less expensive for a hospital to hire a resident because the government pays its share of the costs associated with training a resident, where “share” is defined as Medicare’s proportion of inpatient days. Among teaching hospitals in 1995, Medicare patient days accounted for an average of 43 percent of total patient days, and the direct cost of training a resident was $62,000, measured in 1995 dollars. Therefore, the federal government paid teaching hospitals an average of $26,600 for each resident hired (0.43 X $62,000). Hospitals with a relatively high proportion of Medicare patients and with relatively high training costs in 1984 receive more substantial payments. For example, 10 percent of teaching hospitals received DME payments in 1995 in excess of $53,000 per resident, while

GRADUATE MEDICAL EDUCATION POLICY

9

an equal number received DME payments of less than $5,800 per resident. As the number of residents employed at U.S. hospitals increased over the last two decades, direct medical education expenditures grew in real terms from $1.5 billion in 1988 to $2.2 billion in 1998 (see table 3). The DME program has grown more slowly than the IME and Medicare DSH programs, in part because residents who are beyond their initial training period are only counted as one-half of a full-time resident in DME payment calculations. For example, a resident who has completed a three-year internal medicine residency program and then enters a cardiology residency program is considered to be beyond her initial training period. DME payments are justified on economic grounds. According to the theory of human capital, residents acquire general rather than specific human capital because residency training increases physicians’ earnings whether they remain affiliated with the hospital that trains them or seek employment elsewhere (Becker 1964). Therefore, residents should implicitly pay for the direct costs of medical education by accepting a wage that is equal to the difference between the value to the teaching hospital of the patient care the resident produces and the cost of training the resident, which is incurred by the hospital. Consider a simple example. Assume that a resident provides $60,000 worth of medical care, receives an annual salary of $30,000 from the teaching hospital, and the hospital spends an average of $30,000 per resident for faculty and the residency program director. According to the theory of human capital, the resident’s wage is the value of patient care he provides minus the training costs incurred by the hospital. The sum of the resident’s wage and the administrative cost of training the resident are equal to the value of the patient services that health insurers, including Medicare, should pay for. If Medicare included the residents’ wages in a hospital’s cost base when determining the DRG price, then Medicare would be correctly reimbursing teaching hospitals for the amount of care they provide to Medicare beneficiaries. But direct medical education costs, which consist of residents’ wages and costs such as the

10


residency program directors’ salaries, are “carved out” of total hospital costs when calculating the DRG price. Therefore, the separate DME payments that teaching hospitals receive are not redundant, but represent payment for patient care services received by Medicare beneficiaries. Although the magnitude of DME payments is justified on economic grounds, the DME program is still flawed for two reasons. First, DME payments distort incentives by reducing the cost to a hospital of hiring residents, thereby encouraging hospitals to hire more than the efficient number of residents. Second, because medical education costs are excluded when calculating the DRG prices that all hospitals receive, DRG prices are lower than they would be if these costs were included. This means that nonteaching hospitals are essentially funding the DME program by receiving lower payments than they would if the program did not exist. The Structure and Rationale of the Indirect Medical Education (IME) Program In 1982 Congress tried to promote efficiency and reduce the growth rate of Medicare expenditures by mandating that the Health Care Financing Administration (HCFA) create a prospective payment system. In order to set the payment rates for the Prospective Payment System, HCFA researchers analyzed the relationship between the average operating cost per Medicare admission for each U.S. hospital in 1981 and several hospital and market characteristics: the number of staffed beds, a hospital’s Medicare case-mix index, a local hospital wage index, indicator variables for hospitals located in mid-sized and large Metropolitan Statistical Areas, and the logarithm of one plus the resident-tobed ratio, which is HCFA’s measure of teaching intensity (Pettengill and Vertrees 1982). The case-mix index measures how costly it is, on average, to treat a patient with a particular diagnosis, relative to a benchmark diagnosis. 2 The results of this regression analysis by HCFA are presented in table 4 (Thorpe 1988). In December 1982, HCFA recommended that under PPS a hospital’s Medicare payments for each diagnostic related group (DRG) should be adjusted for the first three variables in table 4: the severity of a patient’s illness, wages


11

in a hospital’s market, and the intensity of teaching at the hospital (Anderson and Lave 1986). Based on the teaching intensity regression coefficient of 0.579, HCFA recommended that a hospital’s DRG payments should increase by 5.8 percent for every 0.10 increase in its resident-to-bed ratio. For example, HCFA proposed paying a teaching hospital that had 40 residents and 400 beds 5.8 percent more than a nonteaching hospital for treating the same type of patient. If this teaching hospital received Medicare DRG payments of $100 million, it would also receive supplemental payments of $5.8 million. The rationale for HCFA’s recommendation is ambiguous because it depends on what the teaching intensity variable in the regression analysis is actually measuring. One interpretation is that teaching hospitals have higher costs than nonteaching hospitals due to the indirect expenses associated with training residents. Indirect expenses exist because residents order more diagnostic services than practicing physicians (for instance, a full set of lab tests rather than one particular test), nurses and other support staff at teaching hospitals are less productive because they spend time teaching residents, and teaching hospitals install expensive medical equipment in part to educate residents. Under this interpretation, the supplemental payments are used to finance a prospective physician’s education rather than to secure medical services for Medicare beneficiaries. A second interpretation of HCFA’s recommendation is that teaching hospitals provide a higher quality product than nonteaching hospitals by using more resources (residents as well as other inputs such as lab tests) and more expensive resources (for example, MRI scans instead of CT scans). Under this interpretation, the resident-to-bed ratio is correlated with high costs but is not the cause of the high costs. Medicare is justified in paying teaching hospitals a higher price than nonteaching hospitals because its beneficiaries are receiving a better product, and the resident-to-bed ratio is a convenient mechanism of differentiating the price according to the quality rendered. It appears from the Ways and Means quotation cited earlier that one of the assumptions in the original legislation to fund Medicare was that teaching hospitals provide a higher quality product.

12


A third interpretation is that the teaching intensity variable in the regression was positive because the case-mix index was an imperfect measure of the severity of a patient’s medical condition, and therefore an imperfect measure of patients’ needs. Patients at teaching hospitals, particularly teaching hospitals with a substantial number of residents, might be more acutely ill than patients at nonteaching hospitals, even after their diagnosis is considered. According to this view, if the case-mix system were sophisticated enough to measure a patient’s needs perfectly, the regression coefficient on the teaching intensity variable would be zero. With an imperfect case-mix system, higher payments to teaching hospitals would be justified not because of indirect costs associated with training residents, but because the patients at teaching hospitals are sicker and receive a relatively large amount of medical resources. Rather than creating a more sophisticated case-mix adjustment mechanism, perhaps with more diagnostic groups to capture subtler differences in patients’ needs, it was more expedient to supplement teaching hospitals’ DRG payments. Under this interpretation, supplemental payments act as a “case-mix Bandaid” by compensating teaching hospitals for the extra resources they require to treat Medicare beneficiaries. A fourth interpretation is that the teaching intensity variable in the regression analysis captures the incremental costs associated with a wide array of extra activities and services that teaching hospitals provide, particularly teaching hospitals with a substantial number of residents. For example, teaching hospitals conduct a great deal of medical research and provide a disproportionate share of charity care for poor people (Mann et al. 1997). These activities are costly, and teaching hospitals may not be fully reimbursed for their costs. Medical research and charity care can be interpreted as public goods. Under this interpretation, the government would be justified in providing teaching hospitals with supplemental payments in order to encourage them to provide a sufficient amount of public goods. Although teaching hospitals would have discretion to use the extra funds for any activity, they would be expected to spend the incremental funds by providing public goods. Under HCFA’s proposed payment system, teaching hospitals


13

were projected to receive 7 percent less Medicare revenue, on average, under the new PPS system compared to the existing Medicare system (Lave 1985). This revenue shortfall was due, in part, to HCFA’s decision to omit the number of hospital beds as a means of adjusting DRG payments, even though the regression analysis indicated that larger hospitals had relatively high costs (table 4). Moreover, the three city-size variables in the regression were collapsed into a single urban/rural adjustment in the proposed PPS system. Because teaching hospitals are large and tend to be located in populous areas, these omissions would affect teaching hospitals more adversely than other hospitals. Congress decided, therefore, to double HCFA’s recommended adjustment for teaching hospitals from 5.8 percent to 11.6 percent. The original indirect medical education formula became _______ × 1.16 × DRG payments IME payments = residents beds

(

)

(2)

Under this IME policy, a hospital’s Medicare payment would increase by 11.6 percent for every 0.10 increase in its resident-tobed ratio. In order to keep total budgeted Medicare expenditures constant when the IME coefficient was doubled, the basic DRG price that all hospitals (teaching and nonteaching) receive was reduced. This means that nonteaching hospitals are essentially funding one-half of the IME teaching hospital subsidy. The Senate committee explained its decision this way: “This [IME] adjustment is provided in light of doubts . . . about the ability of the DRG case classification system to account fully for factors such as severity of illness of patients requiring the specialized services and the treatment programs provided by teaching institutions and the additional costs associated with the teaching of residents. . . . [T]he adjustment for indirect medical education costs is only a proxy to account for a number of factors which may legitimately increase the costs in teaching hospitals” (Anderson and Lave 1986). Congress apparently embraced all four of the rationales described above to justify the IME policy. Can all four of the rationales be justified by economic theory? According to the theory of human capital, the higher costs of teaching hospitals should not

14


stem from the costs of medical education. Since residents acquire general human capital, residents should implicitly pay for training costs (direct and indirect) by accepting a wage that is equal to the difference between the value to the teaching hospital of the patient care the resident produces and the cost of training the resident incurred by the hospital. Consider a simple example that is similar to the one presented above when the DME program was discussed: A nonteaching hospital hires two nurses and pays them $30,000 each to provide care to Medicare beneficiaries. Assume that residents provide twice as much hospital care as registered nurses, but residents order $30,000 more in lab tests per year, costs which are borne by the teaching hospital that employs them. A teaching hospital hires one resident to provide the same amount of patient care as the nonteaching hospital and pays the resident $30,000. The resident is willing to accept this salary because his total compensation, including the cost of the training he receives in the form of lab tests, is equal to the value of the patient care he produces. The total patient care costs of the two hospitals should be identical; so a hospital’s resident-to-bed ratio should not be correlated with costs. Therefore, IME payments cannot be justified on the grounds that teaching hospitals incur indirect costs associated with training residents, and such payments are redundant. If the IME payments are justified by training costs, then hospitals are being reimbursed for training costs twice: once by residents and a second time by the government. There is evidence that residents do, in fact, implicitly pay for the costs of medical education. In 1991, for example, residents received an average salary of $27,000. The value of a resident to a teaching hospital should be approximately equal to the value of a young physician on a medical school’s faculty. Although both faculty and residents teach medical students and treat patients, faculty are generally more productive than residents and also perform nonpatient care activities, such as research. Residents, on the other hand, generally work longer and less desirable hours. In 1991, full-time medical school faculty members who had fewer than four years of experience received an average salary of $95,000 (Practice Patterns of Young Physicians survey). The


15

$68,000 difference between the average salary of a young faculty member and a resident is very close to empirical estimates of the annual cost of training a resident (Duffy, Rusedski, and Cavanaugh 2000). If residents are making these implicit payments, the indirect costs of medical education cannot explain why the HCFA analysis finds a positive relationship between a hospital’s Medicare costs and the number of residents it employs. Teaching hospitals might have higher costs than nonteaching hospitals because they treat sicker patients, provide a more expensive higher quality product, and provide more charity care, but not because residents are relatively inefficient. It is unfortunate that the policy was given a name—“indirect medical education” adjustment—that is the least compelling of the four justifications for the supplemental payments. A more appropriate name for the policy would be “case-mix adjustment,” “quality adjustment,” or “public goods promotion adjustment.” IME payments can still be justified on the grounds that the standard DRG system does not correctly measure the illness severity of patients admitted to teaching hospitals. Recent analysis by the Medicare Payment Advisory Commission (MedPAC) provides some evidence, however, that this justification for IME payments is not warranted. The current reimbursement system adjusts the Medicare price for 500 different patient diagnoses. Using 1997 hospital data, MedPAC simulated the effect on Medicare payments of using the all-patient refined diagnosis related group reimbursement system (APR-DRG), which has 1,420 unique diagnostic categories. The APR-DRG system should be able to measure more accurately than the current DRG system how sick a hospital’s patients are, and therefore how costly it is likely to be to treat a set of patients. If the resident-to-bed ratio is a means of increasing Medicare payments for teaching hospitals because they treat sicker patients within each of the 500 DRGs, then a more accurate system of classifying patients should transfer money from nonteaching to teaching hospitals. But according to MedPAC’s simulations, teaching hospitals would receive only 0.2 percent more from Medicare under the APR-DRG system than they do today (MedPAC 2000a).

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It appears, then, that the only viable economic justification for the IME adjustment is that the correlation between the teaching intensity and higher costs might be attributable to costs associated with other beneficial activities provided by teaching hospitals, such as medical research, charity care, and higher quality of care. It is difficult, however, to distinguish this situation from the alternative explanation that teaching hospitals have higher costs because those hospitals are relatively inefficient. But whatever the reason for the higher costs of teaching hospitals, when Congress doubled the regression coefficient used to calculate IME payments, the lawmakers implied that they see the IME policy, at least in part, as an income support program that provides teaching hospitals with extra funds and allows discretion in spending the funds. The government has instituted other income support policies; for example, nonprofit hospitals are exempt from federal income tax and state sales tax and therefore have the potential to earn a higher income than for-profit hospitals. The government expects nonprofit hospitals will use these extra funds to provide beneficial public goods, such as medical research and charity care. Similarly, higher payments to teaching hospitals provide them with the potential to earn higher profits than nonteaching hospitals. Financial Incentives Created by the DME and IME Policies If there is legitimate economic justification for IME payments—a debatable proposition—the next logical question is whether the IME payment formula is the best method of directing supplemental funds to the appropriate hospitals. I argue that the IME subsidy is poorly designed, even if one accepts the premise that Medicare should pay teaching hospitals more than nonteaching hospitals either to promote the supply of public goods or to improve a flawed system of measuring hospitals’ case mixes. The IME policy distorts prices and therefore encourages hospitals to produce medical care in an inefficient way, and the IME policy is open-ended with no way to predict or control governmental expenditures, because the amount of supplemental IME funds that a hospital receives depends on the resident-to-bed ratio that a teaching hospital chooses. The DME program, which has a


17

stronger economic rationale than the IME program, suffers from the same two design flaws: It encourages hospitals to hire more residents than they would in the absence of the policy, and it is open-ended. The open-ended nature of the two subsidies would not be so problematic if expenditures increased only when hospitals came closer to fulfilling a desired policy objective. Unfortunately, the IME policy distorts prices and creates financial incentives for teaching hospitals to hire more residents, close beds (to increase the resident-to-bed ratio), and admit more Medicare patients to increase the revenue base on which the IME payments are calculated. The DME policy likewise creates financial incentives for hospitals to hire residents. But although admitting more Medicare patients promotes access to teaching hospitals, hiring more residents and closing beds are not policy goals. People who believe physicians can induce demand for their services would argue that hiring more residents will actually reduce social welfare. The IME subsidy does not provide any financial incentives for hospitals to increase either medical research or charity care, the two public goods that presumably motivated Congress to double HCFA’s recommended IME payment level. The price distortions created by the DME and IME policies are substantial, as reported in the first column of table 5. In 1995, the median teaching hospital received DRG payments that were 6.8 percent higher than nonteaching hospitals due to the IME policy, which translates into $360 extra per admission on average. Five percent of U.S. teaching hospitals—those with high resident-to-bed ratios—received a price subsidy of at least 42 percent per admission ($2,250) relative to nonteaching hospitals. In 1995, the median teaching hospital received $67,000 from Medicare for each additional resident it hired due to the DME and IME policies, and $4,000 for each bed it closed due to the IME policy. As before, the financial incentives vary substantially across hospitals. Five percent of the teaching hospitals received payments in excess of $121,000 per resident hired and $29,000 per bed closed. The resident payments are very large and, according to the human capital theory, the government payments are redundant because residents are already implicitly paying hospitals

18


for medical education costs. As we will see, the financial incentives to hire residents, close beds, and admit Medicare patients were even stronger in the early years of the program before the payments were made less generous. By reducing the cost of hiring a resident, the DME subsidy increases hospital demand for residents. By linking supplemental payments to the resident-to-bed ratio, the IME likewise increases hospital demand for residents. The increased demand for residents could increase the residents’ salary, the financial returns to medical education, and eventually the number of physicians practicing in the United States. One could economically justify the design of the IME and DME programs by arguing that without the subsidy, teaching hospitals would hire too few residents, or residents of insufficient quality, and the United States would have a sub-optimal number of physicians. This argument might have been plausible in 1965, when the Medicare program was launched and the federal government was subsidizing the development of new medical schools. The government was trying to expand the supply of physicians in order to ensure Medicare beneficiaries would have sufficient access to medical care. Because of the government’s success, the number of physicians per capita grew from 1.53 per thousand in 1970 to 2.56 per thousand in 1997, a 67 percent increase. Today the prevailing sentiment among policymakers is that the country has, or will soon have, a surplus of physicians (Council on Graduate Medical Education 1994). When the mean physician income is almost $200,000 and there are three applicants for each medical school position, no compelling case exists for the government to provide financial incentives encouraging more students to become physicians. The government does not subsidize the education and training of most professions, and it is not clear why it should make an exception for physicians. If one looks only at the descriptive data, it appears that teaching hospitals have responded strongly to the financial incentives created by the DME and IME policies. Between 1983 and 1996, the number of residents training at U.S. hospitals increased by 35 percent, and the number of beds at teaching hospitals decreased by 15 percent. As a result, the resident-to-bed ratio


19

increased by 60 percent, as displayed in figure 1, and indirect medical education payments nearly doubled in real terms from $2.5 billion in 1988, when the Prospective Payment System was fully operational, to $4.8 billion in 1996 (table 3). Since then IME expenditures have decreased by about $1 billion, largely due to reductions in the generosity of the payments instituted by the Balanced Budget Act of 1997. The descriptive data do not make clear, however, whether the GME subsidies were the catalyst behind these changes in the number of residents and beds. The institution of the PPS in 1983 created incentives for hospitals to reduce the length of stay for Medicare patients and close idle beds. Furthermore, a 57 percent increase between 1981 and 1993 in the number of medical school graduates entering the resident market has helped keep residents’ wages low, relative to other hospital labor inputs. The resident’s wage rose 1 percent in real terms during this period, versus a 23 percent increase in the registered nurse wage. The increase in residents could be the result of hospitals’ substituting less expensive residents for more expensive nurses, rather than the institution of the GME policies. Chapter 4 contains a formal analysis of whether the subsidies caused a change in the number of residents, beds, and Medicare admissions. But regardless of whether the GME subsidies caused the increase in the resident-to-bed ratio, the open-ended structure of the subsidies caused expenditures to rise automatically rather than by the conscious choice of legislatures. The GME subsidies have a second design flaw that, fortunately, has not caused as many problems as it could have. A hospital’s GME payments are based on the number of residents it employs. Under certain circumstances, teaching hospitals may receive very little of the DME and IME payments; the money could be collected by residents in the form of higher salaries. Figure 2 depicts the labor market for residents across all teaching hospitals. Hospital demand for residents (D0) slopes downward, which means that as the residents’ salary falls, hospitals substitute residents for other types of labor. Two different supply curves are depicted. The supply curve S1 shows a situation where the number of people who want to become residents is not very responsive to the residents’ salary. This could occur, for example, if the

20


number of qualified residents is restricted to graduates of accredited U.S. medical schools. The supply curve S2 depicts a situation where the supply of residents responds dramatically to changes in salary, perhaps because graduates of international medical schools are allowed to apply for residency positions in the United States. Residents would receive a salary W0 in the absence of the subsidies. The DME and GME subsidies increase the value of a resident to a hospital. Consider the institution of IME payments in 1983. The demand curve for residents would shift up by about $69,000 per resident—the marginal IME payment a hospital received by hiring a resident—to D1.3 If the supply of residents were essentially fixed (S1), hospitals would bid up the residents’ wage by close to the $69,000 subsidy, residents would receive most of the supplemental payments targeted for teaching hospitals, and the policy goals would not be achieved. If the supply of residents is responsive to the salary (S2), the institution of the IME subsidy would cause the number of residents to increase substantially, the wage would remain fairly constant, hospitals would receive most of the supplemental payments, and the policy goals could be achieved. Fortunately for teaching hospitals, the supply of residents is fairly responsive to the salary. Figure 3 depicts the number of U.S. medical school graduates, international medical school graduates, and other individuals who entered the National Resident Matching Program (“the Match”) between 1980 and 1996. Most first-year residency positions are filled in the Match; so the number of Match applicants should accurately reflect the supply of residents. Each year about 14,300 U.S. medical school graduates enter the Match. The number of graduates from foreign medical schools entering the Match, on the other hand, varies considerably over time; between 1980 and 1984, for example, the number entering the Match increased five-fold, from 1,100 to 5,900. The average resident’s salary, measured in 1996 dollars, is reported at the bottom of figure 3. Notice that the IME subsidy, implemented in 1983, does not appear to have had a strong effect on the residents’ wage. If the number of graduates from international medical schools had not increased as dramatically as it did between 1980 and 1984, the residents’ wage might have increased substantially


21

and teaching hospitals would have only received a fraction of the GME payments. The government probably helped create an elastic supply by relaxing immigration rules in the early 1980s, thereby allowing more foreign-schooled medical students to train at U.S. hospitals. Recent Legislative Revisions to the IME and DME Programs The graduate medical education payment formulas have been revised several times since 1983. In 1985 HCFA instituted the Medicare disproportionate share (DSH) program, described in chapter 3. When the disproportionate share adjustment was added to the regression analysis that is reported in table 4, the coefficient on the teaching intensity variable (the resident-to-bed ratio) decreased from 0.5795 to 0.405. The IME formula was modified to reflect this lower regression coefficient, although as before the 0.405 coefficient was still doubled to prevent teaching hospitals from losing too much money under the new DRG payment system. The IME formula was also revised at this time to be consistent with the econometric specification of the regression equation.4 Beginning in 1986, a teaching hospital’s DRG payments were increased by the following percentage: 2[(1 + resident:bed ratio).405 - 1]. The 2 in the formula expresses Congress’s desire to double the regression coefficient. Medicare DSH payments were modified again in 1988 and the IME formula was revised to be slightly less generous: 1.89[(1 + resident:bed ratio).405 -1]. The DME formula was modified slightly in 1993 to encourage hospitals to offer more primary care residency positions and fewer nonprimary care positions.5 Recall that DME payments depend on a hospital’s direct cost of training residents in 1984, updated to the current year using the consumer price index. Between 1993 and 1995, HCFA did not update the per resident cost figure for inflation when determining DME payments for nonprimary care residents, while DME payments for primary care residents were updated as usual for inflation. This decision did not greatly affect financial incentives. A teaching hospital’s DME payments are now about 6 percent higher for primary care than nonprimary care residents (MedPAC 1999a).

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The Prospective Payment Assessment Commission, the organization that advises Congress about Medicare and Medicaid reimbursement issues and is now called the Medicare Payment Advisory Commission, has repeatedly recommended that IME payments be made less generous (ProPAC 1997). The rationale for this recommendation is that several analysts have used more recent hospital cost data to reestimate HCFA’s original regression analysis. The coefficient on the resident-to-bed ratio in each of these studies has been substantially smaller than the original coefficient of 0.5795 and the revised coefficient of 0.405 (Thorpe 1988, Sheingold 1990, Dalton and Norton 2000). The most common explanation for this decline is that the method of coding patients to the correct DRG has improved over time so that the teaching intensity variable is no longer picking up as much of the unmeasured patient severity. Another hypothesis is that teaching hospitals have reduced their costs relative to nonteaching hospitals since 1983 because the DRG payment system put teaching hospitals under a great deal of pressure, given their relatively high costs. Some substantial changes to the DME and IME programs were instituted with the passage of the Balanced Budget Act of 1997. HCFA now uses a three-year rolling average to determine the number of residents who qualify for DME and IME payments at each hospital. Furthermore, the number of residents that a hospital employed in 1996 establishes the maximum number of residents for which a hospital can receive DME payments. Likewise, a hospital’s resident-to-bed ratio for 1996 establishes the maximum value for calculating its IME payments. The Balanced Budget Act also reduced the generosity of IME payments by about 29 percent when it was fully implemented in 2001. The “multiplier” in the IME formula will be reduced over time from 1.89 to 1.35. As a result, IME and DME payments fell by $1 billion between 1997 and 1998 (table 3). The second column of table 5 reports the median incremental payment per Medicare admission as well as the payments at the fifth and ninety-fifth percentiles. Hospitals that are currently at or above their 1996 resident-to-bed ratio would not receive any extra payments for adding residents or closing beds.


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How should the IME subsidy be designed so that it does not (1) distort prices, (2) encourage hospitals to change their behavior in ways that do not advance a policy objective, and (3) allow program expenditures to be determined by hospital behavior rather than an explicit government decision? One alternative would be to increase all teaching hospitals’ DRG payments by the same fixed percentage. Under this structure, the only way for teaching hospitals to increase their supplemental payments would be to admit more Medicare patients, which arguably would improve access for Medicare beneficiaries. There would be incentives, however, for all nonteaching hospitals to hire one resident in order to receive the higher payment. Moreover, all teaching hospitals would receive the same price subsidy, even though the regression analysis indicated that costs increased with teaching intensity. A better alternative would be to continue to use the residentto-bed ratio to direct more money to larger teaching hospitals, but fix each hospital’s subsidy at a level based on its resident-to-bed ratio in a baseline year, say 1982. A teaching hospital that added residents and closed beds after 1982 would still receive the same percentage mark-up in its DRG payments. A hospital’s IME payments would increase only when its Medicare admissions increased. This closed-ended structure would direct more money to major teaching hospitals without distorting the price of a resident and the price of a bed. If the government subsequently wants to make the payments more or less generous, it could apply the resident-to-bed ratio present at each hospital in 1982 to a new formula. This is essentially the arrangement instituted by the Balanced Budget Act of 1997, fourteen years after the introduction of the IME subsidy. The DME program could be improved by including residents’ wages when calculating the standard DRG reimbursements, rather than carving out these costs beforehand, and then eliminating the separate DME payments. Total Medicare program expenditures would decrease slightly because DME payments currently cover residents’ wages and other direct medical education costs such as residency program directors’ salaries. Nonteaching hospitals would no longer be financing the DME

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payments, and teaching hospitals would no longer have incentives to hire more than the efficient amount of residents (the amount of residents that minimize the cost of hospital care). Under this revised payment system, teaching hospitals would be compensated for the care that their residents provide to Medicare beneficiaries, just as their nurses and other labor and nonlabor inputs are compensated. The Balanced Budget Act of 1997 required the Medicare Payment Advisory Commission to examine whether any changes should be made to Medicare’s graduate medical education policy. A 1999 MedPAC report recommended replacing DME and IME payments with a single enhanced patient care (EPC) adjustment for teaching hospitals, because “the services provided by residents and other trainees are just one part of the enhanced patient care furnished in teaching hospitals” (MedPAC 1999a). Rather than referring to the supplemental payments as payments for medical education, the EPC would acknowledge that teaching hospitals are providing a superior and more costly product to Medicare beneficiaries than nonteaching hospitals. Measuring quality in health care is difficult; so it is hard to prove or disprove MedPAC’s assertion of enhanced care at teaching hospitals. Rather than carving out direct medical education costs, MedPAC recommends including them when calculating the average cost per Medicare discharge because they represent patient care services. This recommendation is sensible. The EPC would be established by analyzing the relationship between teaching intensity and this more complete measure of patient care costs, much as the IME adjustment was set originally. MedPAC simulated the impact of the EPC policy adjustment under three alternative scenarios. The effect of the EPC on Medicare payments to major teaching hospitals is projected to range from a decrease of 5 percent to an increase of 1.1 percent in the three different scenarios (MedPAC 2000b).

3 Disproportionate Share Hospital Payments

The 1983 Social Security Amendments that created the Prospective Payment System directed the Secretary of the Department of Health and Human Services to examine whether Medicare payments should be adjusted “to take into account the special needs of regional and national referral centers [including those hospitals of 500 or more beds located in rural areas], and of public or other hospitals that serve a significantly disproportionate number of patients who have low income or are entitled to [Medicare] benefits” (ProPAC 1985, Technical Appendix). The concern was that hospitals that treat a substantial number of poor patients, including poor patients insured by Medicare, Medicaid, and poor patients without health insurance, might have higher operating costs. The source of these higher costs was not well understood at the time. Higher costs could occur either because poor patients are sicker and require more medical resources, or because hospitals that treat a substantial number of poor patients require extra administrative services (e.g., discharge planning, social services, security). If the Medicare price was not adjusted to account for these higher costs, hospitals that treat a lot of poor Medicare beneficiaries might lose a substantial amount of money, and the quality of care they provide to Medicare (and other) patients might worsen. These hospitals might also restrict access for Medicare (and other) patients who could not fully cover the cost of their care. The Health Care Financing Administration determined that no special adjustments were required in either 1984 or 1985 for 25

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hospitals treating a disproportionate share of Medicaid and poor Medicare patients, based on analysis of hospital costs from 1980. The quantity of low-income patients and Medicare patients did not substantially affect a hospital’s cost per Medicare patient once the following hospital characteristics were accounted for: geographic location (urban/rural), patients’ case-mix index, number of beds, teaching intensity (resident-to-bed ratio), market wages, ownership, proportion of patients by income category, proportion of patients by payer type, and proportion of nonwhite patients (ProPAC 1985, Technical Appendixes). HCFA realized that this regression analysis was preliminary because hospital case mix was poorly measured in 1980 and few hospitals collected data on their patients’ income. In 1985 the Congressional Budget Office (CBO) reexamined the relationship between the volume of poor patients and hospital costs using data from 1981. The CBO developed a “DSH index” to serve as a proxy for the quantity of low-income patients treated by a hospital. The index, referred to here as θ, is the sum of two ratios that measure the volume of care provided to low-income insured patients: Medicaid patient days SSI/Medicare patient days θ = __________________ + _____________________ total patient days Medicare patient days

(3)

The first ratio is the proportion of patient days accounted for by Medicaid patients; the second ratio is the proportion of Medicare patient days accounted for by beneficiaries who also receive Supplemental Security Income (SSI) benefits.6 Note that this index can exceed one because the denominator of the second ratio is a subset of total patients. The index provides a disproportionate weight to the quantity of care provided to poor Medicare patients. Although each of the two ratios is equally important in determining θ, patients receiving SSI account for only 4 percent of total hospital patient days, while Medicaid patients account for 14 percent of total patient days (MedPAC 1998). Medicare patients as a whole account for about 40 percent of total hospital days. The CBO ran a separate regression analysis for three categories of hospitals: urban hospitals with fewer than 100 beds, urban hospitals with 100 or more beds, and rural hospitals. All

DISPROPORTIONATE SHARE HOSPITAL PAYMENTS

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three analyses found a positive relationship between the DSH index and hospital costs, but only above a certain threshold of the DSH index. Among hospitals with relatively low Medicaid and Medicare/SSI days (θ), there was no correlation with the cost per Medicare patient. The Medicare Disproportionate Share Hospital payment adjustment was instituted by the Consolidated Omnibus Budget Reconciliation Act of 1985, and payments began in May 1986.7 The initial eligibility criteria and payment amounts were based on the CBO analysis. In 1989 the three hospital categories were replaced by eight categories, the eligibility thresholds were lowered, and the payment formulas were altered to be more generous. Under the DSH program that has been in place since 1989, a hospital is eligible for DSH payments if its DSH index, θ, exceeds a threshold that differs across the eight categories, as described in table 6 and depicted in figure 4. The eligibility rules favor urban hospitals. For example, urban hospitals with 100 or more staffed beds are eligible if θ exceeds 0.15, whereas similarly sized rural hospitals are eligible only if θ exceeds 0.30. Payments to eligible urban hospitals are also higher than to rural hospitals. For example, a 300-bed rural hospital with a DSH index of 0.30 receives DSH payments equal to 4 percent of its DRG revenue. A 300-bed urban hospital with a DSH index of 0.30, on the other hand, receives DSH payments equal to 14 percent of its Medicare DRG revenue: 5.88 + 82.5(0.30 - 0.202) = 14 (see table 6). For some hospitals, DSH payments are capped. A 300-bed rural hospital can never receive DSH payments greater than 4 percent of its DRG revenue.8 For other hospitals the DSH policy is open-ended like the IME policy. Urban hospitals with over 100 beds, for example, receive higher payments as the DSH index increases. If the 300-bed urban hospital described above admitted more Medicaid and Medicare/SSI patients so that its DSH index increased to 0.40, it would receive DSH payments equal to 22.2 percent of its DRG revenue. When Congress instituted the Medicare DSH program in 1985 it mandated that the CBO reexamine the relationship between a hospital’s costs and its volume of low-income patients and recommend revisions to the eligibility criteria and payment

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formulas. Using data from 1987, the CBO reported in 1990 that costs were no longer higher at hospitals that had a large share of low-income patients, which meant the original premise for creating the DSH program no longer appeared to be true (U.S. Congressional Budget Office 1990). The only statistical relationship identified was that hospitals with a DSH index above 0.55 had costs that were 5.2 percent higher, on average, than hospitals with low values of the DSH index. This newly estimated cost difference was one-fifth the size of the previous estimate: Under the existing DSH rules, large urban hospitals with a DSH index of 0.55 were receiving DSH payments equal to 28.2 percent of their DRG revenue. The new study led to only minor revisions of the DSH rules. Meanwhile, Congress had relaxed the eligibility rules and revised the formulas in 1988 and 1989, causing Medicare DSH expenditures to increase rapidly as more hospitals became eligible and the payments became more generous. The Medicaid program itself expanded from 22 million beneficiaries in 1985 to 36 million in 1996, and since one of the ratios in the DSH index is the ratio of Medicaid patient days to total hospital days, this expansion and the open-ended nature of the DSH formula also caused Medicare DSH payments to increase. The end result: DSH expenditures increased four-fold between 1988 and 1996, rising from $1.2 billion to $4.6 billion in real terms (table 3). Although the 1990 CBO study did not prompt a revision in the payment rules, it did mark a turning point in how the Medicare DSH program was justified. DSH payments were originally viewed as a way to ensure that hospitals treating poor Medicare patients received a payment that accurately reflected the relatively high cost of treating those patients. Since low-income patients were assumed to be relatively costly to treat, if hospitals treated a substantial amount of low-income patients but did not receive a higher price from Medicare, the low-income patients might be denied access to care. After 1990, DSH payments were justified on the grounds that they provided general financial support for inner-city hospitals that would otherwise lose a substantial amount of money. For example, the CBO projected that the 77 hospitals with a DSH index above 0.55 would earn an 18.3 percent profit on Medicare patients in 1991, would lose money on its


29

other patients, and would break even overall (CBO 1990). The hospitals that received the largest DSH payments would lose an average of $16 million each if the DSH program were eliminated. So rather than paying for the higher costs of treating low-income patients, the DSH funds could be used to support any hospital activity. Kominski and Long (1997) analyzed 1988 data at the patient rather than the hospital level. They confirmed the previous CBO finding that low-income Medicare patients are not, in fact, relatively costly to treat. But the large urban hospitals receiving DSH payments still relied heavily on Medicare to offset losses, or marginal gains, from all other payers. In 1995 the median urban teaching hospital had a Medicare profit margin of 13.7 percent but an overall profit margin of only 3.9 percent (table 2). The poor financial performance of DSH-eligible hospitals was probably the reason the Medicare DSH program was largely spared by the Balanced Budget Act of 1997. While this act reduced IME payments by 28 percent when fully implemented, Medicare DSH payments were reduced by only 5 percent. Policymakers increasingly view the Medicare DSH program as a way to ensure that hospitals with a high share of low-income patients will be financially solvent, and therefore able to treat both Medicare beneficiaries and the low-income population (Medicare Payment Advisory Commission 1998). The evolution of the Medicare DSH program from one that was targeted to treatment of low-income Medicare patients to one that provides general support for hospital activities raises several policy questions. The premise of Medicare’s Prospective Payment System is that hospital payments should only be adjusted for legitimate sources of cost variation between hospitals. Such a system encourages hospitals to provide services efficiently. The Medicare DSH program is now an exception to this rule. Hospitals with a large volume of low-income patients receive higher Medicare prices even though there is no evidence of a positive correlation between the volume of low-income patients and the cost of treating Medicare patients. By continuing Medicare DSH payments when the empirical evidence for the payments disappeared, Medicare is defining a

30


broader role for itself than merely securing services for its beneficiaries at the lowest possible price. Why do hospitals that treat a substantial number of lowincome insured persons (Medicaid and Medicare/SSI) earn a relatively small profit if their patient care costs are similar? The most likely answer is that the average collected revenue per patient at these hospitals is low because they provide a substantial amount of uncompensated care. In 1994 the cost of uncompensated care provided by U.S. hospitals was an estimated $16.8 billion (Mann et al. 1997). Major public teaching hospitals, which receive a considerable amount of Medicare DSH money, provided 26.5 percent of the total amount of uncompensated care, nearly three times their share as measured by total hospital costs. This raises two questions: (1) should the government bail out hospitals that would otherwise lose money due to the provision of a disproportionate amount of charity care, and (2) is the Medicare DSH program the most effective and efficient way for the government to accomplish this task? I will not address the first issue at length. Public hospitals are required to accept patients regardless of their ability to pay; it seems logical that the government is responsible for supporting these facilities so that they can fulfill their mandated obligation. Private nonprofit hospitals receive favorable treatment from the government even before Medicare DSH payments are considered. These hospitals are exempt from income, sales, and property taxes, and are allowed to issue tax-exempt bonds with relatively low interest rates. In return these hospitals are expected to provide benefits to the community, presumably including charity care to low-income persons. There is some evidence that nonprofit hospitals in the aggregate do not provide as many community benefits as they should, compared to for-profit hospitals that do not receive tax exemptions (Nicholson et al. 2000). Regardless of whether the government should bail out hospitals that provide disproportionate quantities of charity care, the Medicare DSH program is clearly not the optimal method of promoting charity care: The DSH payment formula rewards hospitals that treat poor patients who have health insurance but penalizes hospitals for treating patients who do not have health insurance.


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These perverse incentives are discussed below. The program also directs money only to hospitals that provide some minimum threshold of care to low-income insured persons, rather than subsidizing charity care wherever it is delivered. If the government wishes to promote charity care, it is not clear why institutions that provide a substantial amount receive some money and all other hospitals below this threshold receive nothing. The Medicare Payment Advisory Commission has recommended a more equitable system where 50 or 60 percent of U.S. hospitals would receive DSH funds, rather than the current 38 percent (Medicare Payment Advisory Commission 1999b). Another alternative would be to use the $4.6 billion currently allocated to the Medicare DSH program to pay all hospitals 25 cents on the dollar for all verified uncompensated care that they provide.9 Subsidizing the desired activity rather than the institution where this activity occurs targets the money more directly and reduces the hospitals’ discretion in how the funds are used. There are other methods of promoting hospital care for the poor. Rather than promoting the supply of hospital care to poor persons, the government could use the money instead to promote the demand for hospital care among poor persons. One alternative would be to eliminate the Medicare DSH program and use the $4.5 billion dollars to subsidize the purchase of health insurance by low-income persons. When these otherwise uninsured persons were admitted to a hospital, the hospital would be paid by the person’s insurance company rather than implicitly by the government. The Medicare DSH program is not sufficiently large to completely finance tax credits for the uninsured. The $4.5 billion in DSH expenditures would translate into about $100 for each of the 44 million uninsured persons, about one-tenth the estimated amount needed to pay for the medical services or health insurance of the uninsured. Financial Incentives Created by the Medicare DSH Program Ninety percent of Medicare DSH payments are made to urban hospitals with 100 or more beds; so in this section I concentrate on how the policy may affect the behavior of large urban hospitals. Hospitals eligible for Medicare DSH payments receive supplemental

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funding whether or not they alter their mix of patients. The Medicare DSH policy, however, provides financial incentives for hospitals to alter their mix of patients because the DSH formula changes the prices that eligible hospitals receive for all patient types—Medicare, Medicaid, privately insured, and uninsured patients. The magnitude of the price changes experienced by large urban hospitals is presented in table 7, separately by type of patient. The DSH policy increases the price of a Medicaid admission by an average of $980, or 26 percent. This sizable increase occurs because admitting an incremental Medicaid patient increases the first ratio in equation (3), which increases the DSH index, and therefore increases Medicare DSH payments. Although the payment the hospital receives from the state Medicaid program has not changed, the DSH policy increases the “effective price” of a Medicaid patient because incremental Medicare DSH payments are triggered by the incremental Medicaid admission. The Medicare DSH policy increases the price of a non-SSI Medicare patient by an average of $640, or 12 percent, among large urban hospitals, and increases the price of a Medicare SSI patient by an average of $1,600 (30 percent). Although Medicare patients do not appear in either numerator of equation (3), admitting more Medicare patients increases a hospital’s DRG revenue, and DRG revenue determines the base from which the Medicare DSH payments are calculated. The financial incentives to admit more Medicaid and Medicare patients, and particularly poor Medicare patients, are consistent with the policy goal of ensuring that low-income persons have access to hospital care. The structure of the DSH payment formula does, however, create some perverse incentives. By admitting an uninsured patient or a privately insured patient, a hospital’s total patient days increase (the denominator of the second term in equation (1), the DSH index decreases, and DSH payments decrease. This occurs because the DSH index, a proxy for the number of low-income patients treated by a hospital, is based on the volume of insured poor patients. A hospital receives no “credit” for admitting an uninsured patient because his treatment days do not appear in either numerator of equation (3). Admitting


33

a patient with private health insurance has the same effect of reducing DSH payments. Ironically, the structure of the DSH payment formula may increase the supply of hospital care to Medicaid beneficiaries and poor Medicare beneficiaries—the low-income insured population— but reduce the supply of hospital care to the (low-income) uninsured, the group that arguably faces the greatest barriers to medical care. This scenario is most likely to occur if hospitals respond strongly to price changes. It is possible, however, that hospitals are not very sensitive to price changes but instead respond more strongly to changes in their overall profit level. That is, if hospitals use a large percentage of their DSH payments to provide additional care for the poor, the perverse price incentives could be overwhelmed by the “income effect.” This possibility will be tested below. Although the Medicare DSH policy only causes a slight reduction in the effective price of an uninsured patient ($171 per uninsured admission, on average), the implication is that large urban hospitals eligible for DSH payments will actually pay on the margin to admit an incremental uninsured patient; the effective price falls from zero to negative $171. But the effect on the amount of care provided to the uninsured could still be substantial if one considers the opportunity cost of providing charity care. For most hospitals Medicaid is the least generous payer. When a hospital admits an uninsured patient, that person may crowd out a Medicaid admission. Therefore, the opportunity cost of providing charity care can be interpreted as the payment foregone by not admitting a Medicaid patient. As reported in table 7, the DSH policy increases the Medicaid price by $982 on average and decreases the price of admitting an uninsured patient by $171; so the policy increases the opportunity cost of providing charity care for urban hospitals with 100 or more beds by an average of $1,153 ($982 + $171). If hospitals respond to price changes by altering their pattern of admission, then the DSH policy might restrict access for uninsured patients and promote access for Medicaid patients. The perverse incentives inherent in the Medicare DSH formula exist because in 1985 HCFA did not have data on the proportion

34


of a hospital’s patients that were low income and the amount of uncompensated care each hospital provided. Although the government understood that the DSH index had limitations, it nevertheless viewed the formula as the best practical measure: “As with the Medicaid measure alone, hospitals with many indigent, uninsured patients, but few Medicaid patients might not receive an adequate adjustment (using the index based on Medicaid and Medicare/SSI patient days only)” (ProPAC 1986, Technical Appendixes). Policymakers apparently understood that using the Medicaid and Medicare/SSI proxy might result in inequitable DSH payments. There is no indication, however, that policy makers were aware of the perverse price incentives created by the DSH index—that hospitals would be penalized for increasing the quantity of charity care. The Balanced Budget Act of 1997 required HCFA to assess the DSH payment formula.10 The Medicare Payment Advisory Commission recommends replacing the existing DSH index with a more inclusive measure of care provided to the poor: “The measure should reflect Medicare patients eligible for SSI, patients sponsored by Medicaid or other state and local indigent care programs, and uninsured and under insured patients as represented by uncompensated care. Uncompensated care for this purpose would include both charity care and bad debts” (MedPAC 1998). The nine current formulas would be replaced by a single formula and the nonlinear “notches” that can be seen in figure 4 would be eliminated. MedPAC also recommends setting the eligibility threshold much lower than it currently is so that 60 percent of all hospitals would be eligible for DSH payments rather than 38 percent, as is currently the case. MedPAC’s proposal corrects most of the problems with the structure of the DSH program. The more inclusive measure of care provided to the poor would direct more DSH funds to hospitals that provide a substantial amount of uncompensated care but have a relatively low volume of Medicaid and Medicare/SSI patients. Previous analysis by ProPAC revealed that hospitals with the largest volume of uncompensated care often do not have the largest volume of Medicaid patients (MedPAC 1999a). The proposed index would also eliminate the perverse incentive that currently


35

exists of penalizing hospitals that increase the number of uninsured patients they treat. Under the recommended formula, admitting more uninsured patients would increase rather than decrease DSH payments. MedPAC’s proposed changes would have a relatively small effect on the amount of Medicare payments received by teaching hospitals. Using data from 1997, MedPAC projects that major public teaching hospitals would experience a 1.2 percent increase and major private teaching hospitals a 0.7 percent decrease in Medicare payments if the new low-income measure were instituted such that 60 percent of all hospitals would be eligible for DSH payments (MedPAC 2000b). Nonteaching public hospitals would be the biggest beneficiaries of the new payment formula.

4 The Effect of the Medicare GME and DSH Subsidies

The Medicare GME and DSH subsidies allocate supplemental funds to teaching hospitals and hospitals that provide a substantial amount of care to low-income patients. These subsidies also alter the prices that hospitals receive for admitting certain types of patients and using certain resources in the provision of patient care. Some of these price changes, such as the increase in the Medicare price caused by both subsidies and the increase in the Medicaid price caused by the DSH policy, encourage hospitals to change behavior (admitting more Medicare and Medicaid beneficiaries) in a way that is consistent with policy objectives (maintaining access to care). Other price changes, such as subsidizing residents, taxing beds, and decreasing the price of an uninsured patient, encourage hospitals to change behavior in a manner that is either unrelated to policy objectives (increasing the resident-tobed ratio) or antithetical to policy objectives (reducing the amount of charity care provided). In this chapter I examine whether, and to what extent, the transfer of supplemental funds and the financial incentives inherent in the GME and DSH policies caused hospitals to change their behavior. First, I calculate the price changes caused by the policies for each hospital in the sample. For example, I calculate how the GME policy changes the cost of a resident at each teaching hospital in the United States. Second, I separately measure the change in each hospital’s input (the number of residents, the number of staffed beds per admission, and the number of registered nurses per admission) and output (the number of Medicare and 36

THE EFFECT OF THE MEDICARE GME AND DSH SUBSIDIES

37

Medicaid admissions) from the first year the policy was in place until a future year. The future year is chosen to allow hospitals sufficient time to respond to the price changes. Third, I separately regress the change in the hospital input or output on the corresponding price change and other control variables to see whether the direction and magnitude of the price change is related to the direction and magnitude of the hospitals’ responses. The effects of the GME and Medicare DSH policies are analyzed separately, given the different data requirements and implementation dates. (For a more extensive presentation of the empirical results, see Nicholson and Song 2001 and Nicholson 1998). The Effect of Medicare’s Graduate Medical Education Policy Two data sources are used in the GME analysis. The Prospective Payment System (PPS) Minimum Data Sets contain information on the number of residents employed by each U.S. hospital, as well as information on each hospital’s IME and DSH payments. Data from 1984 and 1991 have been combined to create a panel data set of 3,928 general, acute care hospitals. I supplement these data with information on the number of beds, registered nurses, and Medicare admissions from the six American Hospital Association (AHA) annual surveys for 1984–1989. The entire sample is used to analyze the effect of IME payments on beds, registered nurses, and Medicare admissions. A sub-sample of 933 teaching hospitals is used to analyze how the IME subsidy affected the number of residents hired.11 The direct medical education (DME) subsidy was formally instituted in 1985, but it did not change financial incentives because teaching hospitals had been able to “pass through” the direct costs of training residents since the 1970s. I focus therefore on the IME policy, announced in 1983 as part of PPS and in effect for the 1984 fiscal year. As illustrated in figure 5, teaching hospitals can be placed into three groups according to when, or if, the IME policy affected their prices. In 1983 four states received permission from HCFA to use their all-payer reimbursement systems rather than participating in PPS.12 Teaching hospitals located in these four “waiver” states—New York, Massachusetts, New Jersey, and

38


Maryland—were not eligible for IME payments in 1984 and 1985; so they did not have a financial incentive to hire residents and close beds. At teaching hospitals in the 46 states that were eligible for IME payments, residents were subsidized and became less expensive, and beds were taxed and became more expensive. I calculate the incremental IME payment associated with adding a resident, closing a bed, and admitting a Medicare patient for each teaching hospital in 1984.13 In table 8, hospitals are ranked according to magnitude of the marginal IME payments, and payment amounts for the fifth percentile, median, and ninety-fifth percentile hospitals are reported. The median IME payment among teaching hospitals in the 46 nonwaiver states in 1984 was $69,200 per resident and $4,200 per bed closed, and the median mark-up in the DRG price due to the IME policy was 7.8 percentage points. The range between the fifth and ninetyfifth percentile hospitals indicates that there was considerable variation in the magnitude of the marginal payments between teaching hospitals. In 1986 the IME formula was revised to be less generous and HCFA revoked the waiver for New York and Massachusetts. The latter decision included New York and Massachusetts hospitals in the Prospective Payment System and allowed teaching hospitals in these states to receive IME payments for the first time. Information on the payment per resident, bed, and Medicare admission for 1986 are presented in table 8, separately for hospitals in the original 46 nonwaiver states, New York and Massachusetts, and New Jersey and Maryland. The effect of the IME policy on hospital staffing and use of beds is measured by regressing the change in a hospital’s inputs between 1984 and 1989 (∆Y), or between 1984 and 1991 in the case of residents, on the magnitude of the price change caused by the policy (∆P), a set of state indicators (S), and indicator variables for hospital characteristics (X), such as type of ownership (for-profit, private nonprofit, or public): ∆Yi = β1S + β2Xi + β3∆Pi + εI

(4)

Three separate regressions are performed, but I will refer to the


39

resident regression to describe the method. Y is the change in the number of residents employed by a hospital between 1984 and 1991. The term ∆P refers to the hospital-specific initial (1983–1984) change in the marginal IME payment per input caused by the institution of the IME policy. Since residents were not subsidized prior to 1983, ∆P is the extra money a hospital received in 1984 for each resident it hired. For New York and Massachusetts hospitals, ∆P measures the change in marginal IME payments in 1986 rather than in 1984 as with hospitals in the original 46 nonwaiver states. ∆P is zero for all New Jersey and Maryland hospitals because they were excluded from the PPS system during 1984 to 1991. The coefficient β3 measures how responsive the number of residents is to a change in the price of a resident. β3 is expected to be positive; an increase in the IME payment per resident lowers the cost of a resident and should increase a hospital’s demand for residents. State indicator variables are included to control for state-specific policies or market changes that might have affected hospitals’ use of residents, beds, and registered nurses. The regression equation for beds is similar to the resident regression described above. The dependent variable is the change between 1984 and 1989 in the number of beds per admission at each hospital. The main variable of interest is ∆P, the change in the incremental payment per bed caused by the institution of the IME policy. When input prices change, hospitals can substitute between different types of inputs. Therefore, I also examine whether hospitals responded to the subsidy on residents by hiring more or fewer registered nurses. Nurses account for about one-quarter of hospital costs. When residents become less expensive, hospitals might hire fewer nurses and have residents perform tasks that nurses used to do or, conversely, hospitals might hire more nurses to help supervise and teach the residents. In the registered nurse regression, ∆Y measures the change in the number of registered nurses per admission between 1984 and 1989, and ∆P measures the change in the payment per resident. I examine the change in hospital staffing and use of beds over a long period (five or seven years) because it will take hospitals time to change how they treat patients. For example, a hospital

40


that wants to hire more residents would likely do so by hiring more first-year residents rather than by trying to attract experienced residents from other programs. Residency programs range in length from three to eight years; so examining the change in residents over a two- or three-year period would probably understate the magnitude of hospitals’ response to the new policies. Equation (4) is modified in order to estimate the effect of the IME and Medicare DSH policies on treatment of Medicare beneficiaries. The IME policy was only one part of the Prospective Payment System that fundamentally changed how hospitals were paid for treating Medicare patients. A Medicare “bite” variable is added to equation (4) to control for how profitable Medicare patients were at each hospital under the new PPS system: ∆Yi = β1S + β2Xi + β3∆Pi + β4Bitei + εi

(5)

The Medicare bite variable is the sum of the DRG and supplemental IME payments a hospital actually received in the first year of PPS (fiscal year 1984), divided by the hospital’s total Medicare costs in that year, multiplied by 100. Prior to PPS, hospitals received Medicare payments based on their actual cost of treating Medicare patients. Hospitals with a bite value less than 100 are estimated to be losing money on Medicare patients under PPS based on their average costs. One would expect hospitals with a high value of the Medicare bite variable to try to admit more Medicare patients once the DRG system was instituted, all else being equal, while hospitals with a low value would be under pressure to reduce costs and alter their service offerings to attract patients with higher profit margins. The mean value for the Medicare bite variable in 1984 was 108.7, implying that hospitals made a modest profit on Medicare patients in the initial year of the program. The effect of the IME policy on a hospital’s Medicare price is included in the Medicare bite variable. In order to identify the effect of the IME and DSH policies on Medicare admissions separately from the effect of the entire PPS system, I analyze how hospitals responded to the revision of the IME policy and introduction of the Medicare DSH policy in May 1986, controlling for


41

the impact of the PPS system. Therefore, ∆P in equation (5) refers to the change in a hospital’s DRG mark-up in 1986 caused by the revision of the IME policy and the introduction of the DSH policy. The effect of the DSH policy on each hospital’s Medicare price is determined according to the relevant formula from table 6. All teaching hospitals in the 46 nonwaiver states experienced a reduction in their DRG mark-up in 1986 because of the revision in the IME policy, with the largest reductions occurring at hospitals with high resident-to-bed ratios. All hospitals, teaching and nonteaching, that became eligible for DSH payments experienced an increase in their Medicare price, all else being equal. The net change in the percentage mark-up to hospitals’ DRG price in 1986 is reported in the last column of table 8. Although the median teaching hospital in the 46 states experienced little change in its DRG price, many hospitals experienced a decrease greater than 10 percent. Since the price that New York and Massachusetts hospitals were receiving for treating Medicare patients from the all-payer reimbursement systems in 1985 was not observed, hospitals in these states are excluded from the analysis of Medicare admissions. Results of the resident, registered nurse, and bed regressions are reported in table 9. The positive coefficient on the change in the subsidy per resident indicates that hospitals did respond to the IME subsidy of residents by hiring more residents. A $1,000 increase in the IME payment per resident, and therefore a $1,000 decrease in the cost of a resident, is associated with a 0.12 percent increase in the number of residents.14 The coefficient on the change in the per resident subsidy is insignificant in the registered nurse regression, which implies that hospitals did not substitute residents for nurses when residents became less expensive. Teaching hospitals also appear to have responded to the tax on beds by closing beds. A $1,000 increase in the tax is associated with a reduction of 0.16 in the number of beds per 1,000 admissions. One way to interpret the magnitude of the above coefficients is to estimate the aggregate effect of the IME policy on teaching hospitals’ use of residents and beds. The average increase in the IME payment per resident in 1983 (when the payment was zero

42


for all hospitals) was $47,200. Based on the regression coefficient from table 9, I estimate that the institution of the IME policy led to a 5.5 percent increase in the number of residents between 1984 and 1991.15 The number of residents employed by teaching hospitals in the sample increased by 12.6 percent between 1984 and 1991; so the IME policy explains 43 percent of the total increase during this period. The regression analysis implies that the IME subsidy was not the only reason why teaching hospitals employed more residents in the late 1980s, but it was a big part of the increase. The impact of the IME policy on beds is not as large as on residents. The mean tax per bed in the sample is $6,700, or 9 percent of the estimated marginal cost of a bed; so the IME policy is estimated to have caused a 3.0 percent reduction in the number of beds per admission at teaching hospitals between 1984 and 1989. Overall there was a 15 percent reduction in beds at teaching hospitals during this time period. By linking IME payments to the resident-to-bed ratio, a variable chosen by hospitals and not policy makers, the government ceded control over IME expenditure amounts to teaching hospitals and market forces. The evidence that teaching hospitals responded to changes in the price of residents and beds indicates that the design of the IME policy did encourage teaching hospitals to increase the resident-to-bed ratio and thereby receive larger payments from Medicare. If Medicare’s total hospital expenditures were essentially capped, then this increase in IME payments was implicitly funded by nonteaching hospitals, which were receiving smaller DRG payment increases than they would have if the IME policy was designed so that expenditures were fixed. IME expenditures increased by $3 billion in real terms between 1987 and 1997. If the government wanted this to occur, it should have legislated this increase rather than allowing the decisions of teaching hospitals and an open-ended IME policy to dictate the increase. Results of the Medicare analysis are presented in table 10. The IME and DSH policies are Medicare price subsidies. One rationale for these supplemental payments is to ensure that Medicare beneficiaries have access to teaching hospitals and hospitals that treat a substantial number of poor people by paying


43

these hospitals relatively high prices. The expectation is that hospitals that receive relatively large increases in their price per Medicare admission will admit more Medicare patients, either by recruiting physicians with a heavy mix of Medicare patients, or by offering services that appeal to the elderly. All teaching hospitals experienced a reduction in their effective DRG price due to the revision of the IME policy in 1986, while hospitals (teaching and nonteaching) eligible for DSH payments experienced an increase in their DRG price of 2.5 to 15 percentage points. The sample for the Medicare regressions includes teaching and nonteaching hospitals. The coefficient on the change in the Medicare price in 1986 is positive but insignificant in the first column where the IME and DSH price changes are combined into a single variable. The ratio of Medicare to total admissions decreased by 1.2 and 1.5 percentage points between 1984 and 1989 among for-profit and teaching hospitals, respectively, relative to private nonprofit hospitals. In the second column of table 10 the Medicare price change variable is separated into its two components. The coefficient on the IME price change is positive and significant while the coefficient on the DSH price change is insignificant. A 1 percent increase in a hospital’s DRG price due to the IME policy is associated with an increase of 0.098 in the ratio of Medicare to total admissions. In this specification hospitals do appear to admit more Medicare patients when the government raises the payment rate. This is good news for proponents of the IME and DSH policies, and implies generally that the government needs to consider the implications of a change in the DRG price on beneficiaries’ access to care.16 The IME policy was revised by the Balanced Budget Act of 1997. The regression results presented above can be used to predict how the policy change will affect hospital behavior. The IME payment for each resident hired, bed closed, and Medicare patient admitted will be reduced by 28 percent for all teaching hospitals once the changes are fully implemented in fiscal year 2002. The change in the marginal payment per resident is substantial. Teaching hospitals will receive an average of $13,400 less for each resident hired, $2,800 less for each bed closed, and 3.8 percent

44


less for each Medicare patient admitted. Based on the regression analysis, the number of residents employed by teaching hospitals is predicted to fall by only 1.6 percent, the number of beds per admission is predicted to increase by less than 1 percent, and Medicare admissions are predicted to decrease by 1.3 percent. As predicted, teaching hospitals have not responded to the Balanced Budget Act by substantially scaling back residency training. In fact, the number of first-year residency positions offered in the Match increased by 0.2 percent between 1996 and 2000 and the number of first-year residency positions filled in the Match increased by 2.1 percent during this period. Effect of the Medicare DSH Policy For an eligible hospital, the Medicare DSH policy increases the price it receives for treating Medicaid and Medicare patients and decreases the price it receives for treating uninsured and privately insured patients. Large urban hospitals that admit a substantial number of Medicare patients experience the largest prices changes; smaller rural hospitals experience the smallest price changes. In this analysis I focus on the effect of the Medicare DSH policy on hospital care to poor patients: Medicaid beneficiaries and the uninsured.17 Two data sets are used to examine the effectiveness of the DSH policy: the Prospective Payment System Minimum Data Set and the Nationwide Inpatient Sample (NIS). Data from the 1986 and 1993 Minimum Data Sets were combined to create a panel data set containing 4,573 general acute care hospitals.18 The first observation for each hospital occurs in the year the DSH policy was instituted; the second observation is sufficiently far in the future to allow hospitals to respond to the price changes. The Minimum Data Set contains the information required to calculate for each hospital the effect of the DSH policy on the prices it receives for each type of patient. Unfortunately, in the Minimum Data Sets hospital admissions are reported for only three patient types: Medicaid, Medicare, and all other; charity care admissions are grouped with private insurance admissions. The NIS Release 1 data set does separate charity care and privately insured admissions. Created by the Agency for Health


45

Care Policy and Research, the NIS contains patient-level data for a 20 percent sample of U.S. community hospitals for each year between 1988 and 1992. Six different patient types are identified: Medicaid, Medicare, private health insurance, self-pay, no charge, and other. For this analysis I interpret both self-pay and no charge patients as being uninsured, and therefore representing charity care. The NIS sample for this paper consists of 289 hospitals, located in seven states, that were surveyed in 1988 and 1992 and reported information on their patients’ payment source.19 The price changes caused by the institution of the Medicare DSH policy are calculated in the Minimum Data Set and linked to each hospital in the NIS sample. The principal advantage of the NIS data set is that it allows me to examine how the DSH policy affects hospital care to uninsured persons. The two disadvantages of using the NIS data are the smaller number of observations relative to the Minimum Data Set and the timing of the survey. The first observation for each hospital in the NIS data set occurs in 1988, the second full year of the DSH policy. If hospitals responded quickly to the price changes, my estimate of the effect of the DSH policy will be biased downward. I estimate the effect of the Medicare DSH policy by separately regressing the change in a hospital’s Medicaid and uninsured patients (∆Q) on the change in the price (∆P) of admitting those patients caused by the implementation of the DSH policy: ∆Qi = β∆Pi + α∆Xi + εi,

(6)

where X includes hospital and market characteristics that affect the demand for and supply of care to low-income persons. Hospitals receive little if any payment for treating uninsured patients. If hospitals strictly maximized profit, they would admit as few uninsured patients as possible. But if hospitals receive utility from providing charity care, they will admit uninsured patients until the marginal utility of an incremental charity care patient is equal to the marginal utility of the profit generated by the lowestpaying insured patient, which is usually a Medicaid patient. The price a hospital receives for treating a Medicaid patient can be

46


interpreted, therefore, as the opportunity cost of admitting a charity care patient. In the regression analysis, the ∆P term is the change in the price of admitting a Medicaid patient due to the institution of the DSH policy minus the change in the price of admitting an uninsured patient. The coefficient β is hypothesized to be positive in the Medicaid regression and negative in the charity care regression. If the government increases the price of a Medicaid patient, hospitals will admit more Medicaid patients. If Medicaid patients crowd out uninsured patients, the hospital will also admit fewer uninsured patients. Hospitals will also admit more Medicaid patients and fewer uninsured patients if the government reduces the price of admitting an uninsured patient. The price change ∆P is interacted with two indicator variables for whether the hospital is for-profit and whether it is a sole community hospital in order to allow price responsiveness to vary by ownership type and geographic location of the hospital.20 The three hospital ownership types are public, private nonprofit, and private for-profit. The regressions also include statelevel market variables (X) that affect the demand for hospital care among the uninsured and Medicaid populations. These variables include the change in the number of Medicaid beneficiaries, the change in the proportion of Medicaid beneficiaries enrolled in a Medicaid HMO, the change in the number of nonelderly uninsured persons, and the change in the number of people with a household income below the poverty line. Equation (6) is estimated with ordinary least squares. Between 1988 and 1992, most states raised the price they paid hospitals for treating Medicaid patients, in part to avoid potential lawsuits stemming from the Boren Amendment.21 For example, New Jersey, Colorado, Washington, and Massachusetts—states included in the NIS data set—increased their average hospital payment per Medicaid admission by over 35 percent in real terms during this four-year period.22 I include the change in the state’s average price per Medicaid admission into the ∆P term in equation (6). State-initiated changes in the Medicaid price per admission are assumed to affect all hospitals


47

within the state equally, whereas the Medicare DSH policy affects eligible hospitals only. Coefficient estimates for the Medicaid regression are reported in the second column of table 11. The coefficient estimate on the change in the Medicaid price is positive, as expected. A $1,000 increase in the effective price of a Medicaid admission (or a $1,000 reduction in the price of an uninsured admission) is associated with an increase of 60 Medicaid admissions. This implies a price elasticity of 0.35 for private nonprofit hospitals. As expected, sole community hospitals that are isolated geographically are less responsive to price changes than hospitals that operate in more populous markets. The coefficient on the change in the number of Medicaid beneficiaries is positive as expected. Hospitals in states that expanded Medicaid eligibility increased their Medicaid admissions relative to similar hospitals in other states. As hypothesized, growth in Medicaid HMO enrollment is associated with a reduction in the number of Medicaid admissions. The estimated effect of Medicaid HMOs is small; a one percentage point increase in the state’s Medicaid beneficiaries who are enrolled in an HMO is associated with a reduction of 5.4 Medicaid admissions, or 0.65 percent of total Medicaid admissions for the average hospital in the sample. Coefficient estimates from the charity care regression are reported in the first column of table 11. The coefficient on the change in the opportunity cost of providing charity care is negative as expected. A $1,000 increase in the opportunity cost (either an increase in the price of admitting a Medicaid patient or a decrease in the price of admitting a charity care patient) is associated with a decrease of 14.4 charity care admissions. The estimated price elasticity of 0.10 is small. The sample size in the charity care regression consists of only 289 hospitals. Although the coefficient on the change in the opportunity cost is significant, the above result should still be interpreted cautiously. The Medicare DSH program appears to be effective, therefore, at promoting hospital care for Medicaid beneficiaries but has a slightly negative effect on hospital care for the uninsured. A hospital that experienced a relatively large increase in the Medicaid price increased its Medicaid admissions between 1986 and 1993

48


relative to other hospitals and reduced its charity care admissions. The effect of the Medicare DSH policy on hospital care for the poor is simulated by applying the regression coefficients to the actual price changes caused by the Medicare DSH policy at each hospital in the sample. The Medicare DSH policy is predicted to increase the number of Medicaid admissions by 2.8 percent and reduce the number of charity care admissions by 0.70 percent. If the DSH-eligible hospitals in this sample are representative of the 1,900 hospitals that receive DSH payments, the policy is predicted to lead to 164,000 incremental Medicaid admissions per year and 23,000 fewer charity care admissions per year than would otherwise occur.

5 Conclusion

There are two fundamental problems with the Medicare graduate medical education program and the disproportionate share hospital program. First, the IME and DSH programs are not well supported by economic theory. Second, until the Balanced Budget Act of 1997, the programs were not well designed; the programs distorted prices and created perverse incentives for hospitals to change their behavior in ways unrelated or antithetical to policy objectives. The open-ended structure of the payment formulas allowed expenditures on these two supplemental programs to grow from 8.6 to 12 percent of Medicare hospital spending without any guarantee that the incremental payments were being used to fulfill policy objectives. Medicare provides teaching hospitals with supplemental IME payments for one or all of the following four reasons: to reimburse hospitals for the indirect costs of medical education, to adjust the price that teaching hospitals receive from Medicare to reflect the needs of relatively sick patients, to pay teaching hospitals a higher price for providing a higher quality product, and to provide teaching hospitals with supplemental funds to ensure adequate provision of public goods such as charity care and medical research. The first rationale has little economic justification because residents should already be paying teaching hospitals for the indirect costs of medical education. Although the other rationales can be justified economically, the program is not well designed to meet these objectives. Rather than providing a fixed price subsidy to teaching hospitals or transferring a fixed amount of money to hospitals for the provision of public goods, the IME formula distorts prices and provides financial 49

50


incentives for hospitals to hire residents, close beds, and admit more Medicare patients. Medicare provides teaching hospitals with supplemental DME payments because the government believes that residents improve the quality of hospital care. Nurses and lab technicians also improve the quality of hospital care, which is why nurses’ and lab technicians’ wages are included in a hospital’s cost when the government determines the appropriate DRG price (a price that equals the average cost of treating a Medicare patient). Residents’ wages should be treated in the same way, incorporated into the single price that a hospital receives for treating a Medicare patient, rather than being singled out so that hospitals have incentives to hire more residents than they would if the hospital’s sole purpose was to deliver high-quality hospital care at the lowest possible cost. The original rationale of the Medicare DSH policy was to ensure that poor Medicare beneficiaries would have adequate access to hospital care. Over time the evidence that poor Medicare beneficiaries were relatively costly to treat was refuted. The program is now justified mainly on the grounds that providing supplemental payments to urban teaching hospitals helps keep the safety net intact. Unfortunately, because DSH payments are based on the proportion of a hospital’s patient days accounted for by low-income insured individuals, the program encourages hospitals to admit Medicaid and Medicare patients but actually discourages them from admitting uninsured patients. The only way the program will promote hospital care for uninsured poor persons is if the income effect of the program is stronger than the perverse price effect. That is, the program could increase charity care if hospitals use a substantial amount of the supplemental Medicare DSH payments to provide more charity care, even though hospitals are now penalized on the margin for providing charity care. My empirical analysis indicates that the IME policy did cause teaching hospitals to hire residents and close beds. The policy accounted for an estimated 43 percent of the increase in residents between 1984 and 1991. HCFA’s use of the resident-to-bed ratio to disburse IME payments combined with the formula’s open-ended structure allowed the collective action of 1,200

CONCLUSION

51

teaching hospitals to determine the magnitude of expenditures, rather than allowing legislators to determine spending amounts. The government is fortunate that hospitals did not respond aggressively to the financial incentives inherent in the Medicare DSH program. I have presented evidence that the Medicare DSH program encouraged hospitals to increase slightly (2.8 percent) the number of Medicaid admissions and decrease slightly (0.7 percent) the number of uninsured admissions. While the former outcome is positive, the latter is clearly not the intention of the program. There is a striking similarity in both the design and outcome of the GME and Medicare DSH programs. Although the Medicare DSH policy was not the most important cause of the increase in Medicaid admissions, HCFA’s use of Medicaid admissions to determine the magnitude of payments and the openended structure of the payment formula allowed Medicare DSH payments to increase substantially when the number of Medicaid beneficiaries increased by 64 percent between 1985 and 1996. The Balanced Budget Act of 1997 corrected most of the flaws of the GME program by establishing the number of residents employed at each hospital in 1996 as the maximum number that can be eligible for DME payments and by capping each hospital’s resident-to-bed ratio at its 1996 level for purposes of determining IME payments. These changes eliminated the financial incentive to hire additional residents and effectively capped the government’s total expenditures on these two programs. As my empirical analysis would predict, the number of residents employed at U.S. hospitals has changed very little since 1997, even though the Balanced Budget Act substantially increased the cost to a hospital of hiring a resident. The act only made minor changes to the Medicare DSH program, however. The Balanced Budget Act has eliminated the perverse incentives of the DME and IME programs and made the policy closedended. Some additional changes might further improve the programs. One option would be to eliminate DME payments entirely but include the residents’ wages in a hospital’s costs when determining the appropriate DRG price. This would treat residents just like other hospital employees, who presumably are hired by hospitals because they directly or indirectly improve the

52


quality of hospital care. If the government is concerned that the residents’ salary will decrease substantially with the cancellation of DME payments, they could simultaneously expand the student loan program to ensure that medical students have sufficient access to subsidized loans. There are three legitimate rationales for indirect medical education payments that are currently difficult to distinguish: (1) teaching hospitals treat relatively sick patients (controlling for the patient’s illness) and therefore merit a higher price from Medicare; (2) teaching hospitals provide a higher quality product and therefore deserve a higher price; or (3) teaching hospitals use the supplemental payments to provide additional public goods such as charity care and medical research that society values. The government could clarify the rationale for IME payments by expanding the number of DRGs to measure patient illness severity more precisely. The government might then require hospitals to measure and report the amount of public goods they provide so Congress could evaluate the efficacy of the program. Under this scenario HCFA would continue to allocate money to institutions that provided a substantial amount of public goods, but would require more accountability from hospitals than it does now regarding how these discretionary funds are used. The Balanced Budget Act of 1997 reduced Medicare DSH payments by 5 percent but did not revise the formula used to disburse the funds. Therefore, the policy is still open-ended and still penalizes hospitals for admitting uninsured patients. These flaws could be corrected by capping a hospital’s Medicare DSH payments at the current level, as was done for DME and IME payments, and revising the payment formula so hospitals are encouraged to admit low-income patients (insured and uninsured) rather than just insured low-income patients. The Medicare Payment Advisory Commission has proposed a formula that would eliminate the perverse incentives and described the data that would be necessary to implement the new formula (MedPAC 1998).

Statistical Appendix

Table 1 GME and DSH Payments by Type of Hospital, 1995 Type of Hospital GME GME DSH & DSH Only Only Neither Overall ________________________________________ Number of short–term, general hospitals

714

423

1,227

2,736

5,100

5,064 2,877

1,391 0

0 1,461

0 0

6,455 4,338

11.1

3.3

1.2

0

2.1

13.4% 7.7% 5.6% 1.4% 1.3% 0.1%

7.3% 1.5% 0.5%

0% 0% 4.3%

8.3% 0.0% 0.0%

4.5% 5.3%

5.4%

4.3%

4.7%

Total payments ($ millions) GME DSH Mean GME + DSH payment per hospital ($ millions) GME + DSH payments as a percentage of net revenue 95th percentile Median 5th percentile Median profit margin

Source: Health Care Financing Administration, Medicare Cost Reports, FY 1995.

53

54


Table 2 Median Hospital Profitability by Type of Hospital, 1992 and 1995 ($ millions) Medicare Inpatient Margina

Total Margin, All Payersb

1992 1995 ______________

1992 1995 _____________

Major teaching hospital

8.1

19.7

2.5

2.8

DSH and teaching

3.0

13.7

2.8

3.9

Teaching only

-5.6

3.8

3.9

5.1

DSH only

-1.6

8.4

4.5

5.2

No teaching or DSH

-6.4

2.7

3.1

4.2

Overall

-4.0

5.7

3.4

4.5

a. (PPS operating and capital payments - Medicare costs)/PPS operating and capital payments b. (Total revenues - total expenses)/total revenue Source: Prospective Payment Assessment Commission, 1997.


55

Table 3 Medicare GME and DSH Expenditures, 1988–1998 (billions of 1998 dollars) 1988 _____ 1992 _____

1994 _____

1996 _____

1997 _____

1998 _____

IME DME GME

$2.5 $4.1 $4.2 $4.8 $4.7 $3.7 $1.5 $1.7 $1.7 $2.3 $2.2 $2.2 ____________________________________________ $4.0 $5.8 $5.9 $7.1 $6.9 $5.9

DSH

$1.2

Medicare inpatient expendituresa

$2.4

$3.4

$60.9 $78.5 $77.4

$4.6

$4.6

$4.5

$85.3 $85.8 $87.4

Supplemental payments as a percentage of Medicare inpatient expenditures GME 6.6% 7.4% 7.6% 8.3% 8.0% 6.8% DSH 2.0% 3.1% 4.4% 5.4% 5.4% 5.1% ___________________________________________ Total 8.6% 10.5% 12.0% 13.7% 13.4% 11.9% a. Includes DME expenditures. Source: Health Care Financing Administration.

56


Table 4 Regression Analysis Justifying the Original IME Policy HCFA’s Cost Regression (dependent variable is the logarithm of Medicare operating costs) Included in PPS _______________ Constant

7.32

Clinical case-mix index

1.011

Average hospital wage

1.022

Teaching intensity: log(1 + resident/bed ratio)

0.579

Excluded from PPS __________________ Beds

0.119

Small city indicator

0.007

Mid-sized city indicator

0.026

Large city indicator

0.0099

Source: Thorpe 1988.


57

Table 5 Financial Incentives Associated with IME and DME Policies 1. Percentage Increase in Price of a Medicare Admission Fully-implemented Balanced 1995 Budget Act of 1997 __________________________________________ 95th percentile Median 5th percentile

42.8% 6.8 0.3

30.6% 4.9 0.2

2. Incremental Payment per Resident ($ thousands) Fully-implemented Balanced 1995 Budget Act of 1997 __________________________________________ 95th percentile Median 5th percentile

$121.7 67.0 10.7

$0 0 0

3. Incremental Payment Per Bed Closed ($ thousands) Fully-implemented Balanced 1995 Budget Act of 1997 __________________________________________ 95th percentile Median 5th percentile

$29.5 4.0 0.1

$0 0 0

Note: Hospitals that are currently at their 1996 ratio of residents to beds will have incremental payments of $0 under the Balanced Budget Act. Source: Medicare cost reports; author’s calculations.

58


Table 6 Medicare DSH Eligibility and Payment Rules, 1995 Medicaid patient days + ________________________ SSI/Medicare patient days θ = _____________________ total patient days Medicare patient days I. Urban Hospitals Eligibility Criteria _________________

Payment Rule ______________

Medicare DSH Payments Are Number Equal to the Following of Beds Eligible if . . . Percentage of DRG Revenue __________________________________________________________________ 0.202 2.50 + 65(θ - .150) if θ < 0.202

≥100

More than 30% of net inpatient revenues are derived from state and local government programs for indigent care

35%

II. Rural Hospitals Eligibility Criteria _________________

Payment Rule ______________

Medicare DSH Payments Are Number Equal to the Following of Beds Eligible if... Percentage of DRG Revenue __________________________________________________________________ < 100

θ ≥ .45

4%

100 - 499

θ ≥ .30

10% if hospital is a sole community provider 4 + 60(θ - .30) if hospital is a rural referral center 4% for all other 100-499 bed rural hospitals

θ ≥ .15

5.88 + 82.5(θ - .202) if θ > .202 2.50 + 65(θ - .150) if θ < .202

500+

Source: Health Care Financing Administration.


59

Table 7 Effect of the Medicare DSH Policy on the Effective Price per Hospital Admission by Type of Patient, 1993 Patient’s Source of Health Insurance ____________________________________ Uninsured, or Type of Hospital Medicaid Private Insurance Medicare __________________________________________________________________ Urban, 100+ beds and rural, 500+ beds

$982

-$171

$642

0

0

211

0 710 0

0 -184 0

423 596 169

Rural, 0-99 beds

0

0

169

Ineligible hospitals

0

0

0

Urban, 0-99 beds Rural, 100+ beds sole community provider rural referral center all other

Source: HCFA minimum data sets; author’s calculations.

$118.5 69.2 26.1

$107.8 66.6 21.4

$38.5 4.2 0.4

$0 0 0

$98.9 67.0 25.3

$0 0 0

$0

$0

$0

$37.4 9.8 0.4

0.0%

0% 0% 0%

54.3% 7.8% 0.8%

0.0%

36.4% 14.4% 1.1%

40.9% 7.8% 0.8%

Mark-up in DRG price 1984 1986a ________________

Source: PPS Minimum Data sets and author’s calculations. Data reported in 1993 dollars.

a. Includes the effect of the Medicare DSH program.

$0

Hospitals that have never been eligible for IME subsidy (NJ, MD)

95th percentile Median 5th percentile

$32.6 4.9 0.4

Marginal tax per bed ($000s) 1984 1986 _______________

Hospitals that became eligible for IME subsidy in 1986 (NY, MA)

95th percentile Median 5th percentile

Hospitals eligible for IME subsidy since 1984 (46 states)

Marginal IME subsidy per resident ($000s) 1984 1986 _______________

(ranked according to the magnitude of the price change caused by the revision)

Financial Incentives for Teaching Hospitals under the Original (1984) and Revised (1986) Graduate Medical Education Policies

Table 8

+ 36.4% + 14.4% + 1.1%

+ 3.1% - 2.1% - 20.0%

Change in Mark-up, 1986–1987 __________

60 STATISTICAL APPENDIX

- 0.129 (0.108) 0.081 (0.0542) -0.0496 (0.0922) 933 0.06

0.00116** (0.000492)

Change in log(residents) 1984–1991 _____________________

-0.369 (2.13) 0.0992 (0.959) 2.11 (3.37) 796 0.12

0.00831 (0.0136)

Change in RNs/1000 Admissions, 1984–1989 ______________________

-0.163** (0.0278) 0.837 (1.62) -1.40* (0.791) 1.34 (1.29) 813 0.14

Change in Beds/1000 Admissions, 1984–1989 ______________________

Source: Nicholson and Song 2001.

Note: All regressions include state indicator variables. RN regression also includes two indicator variables for the number of staffed beds, and the ratio of inpatient surgeries to admissions, a measure of the acuity of the patients’ illnesses. Standard errors are in parentheses. ** = significant at the 5 percent level. * = significant the 10 percent level.

Observations R2

Constant

Government-owned hospital

Change in subsidy per resident, 1983–1984 ($ thousands) Change in tax per bed, 1983–1984 ($ thousands) For-profit hospital

Dependent Variable _________

Coefficient Estimates for Residents, Registered Nurses, and Beds at Teaching Hospitals

Table 9

STATISTICAL APPENDIX 61

62


Table 10 Coefficient Estimates for the Medicare Admission Regression Change in Medicare admissions as a percentage of total admissions,1984–1989 All Hospitals ______________________________________ Combined Subsidy IME + DSH Separate Subsidies ___________ ___________________ Change in DRG mark-up in 1986 (percentage points) total

0.0589 (0.0507)

IME revision

0.0976** (0.0411) -0.162 (0.183)

introduction of DSH policy Medicare “bite” (percentage points)

0.789 (1.19)

0.834 (1.19)

For-profit hospital

-1.28** (0.577)

-1.24** (0.577)

Government-owned hospital

0.599 (0.375)

0.701 (0.376)

Teaching hospital

-1.52** (0.472)

-1.09** (0.447)

Constant

-0.115 (1.52)

0.126 (1.50)

Observations R2

3,928 0.05

3,928 0.05

Note: Regressions include state indicator variables and two indicator variables for number of staffed beds. Sample includes hospitals in the 46 original PPS states only; hospitals from Maryland, New Jersey, Massachusetts, and New York are excluded. Standard errors are in parentheses. ** = significantly different from zero at the 5 percent level. * = significantly different from zero at the 10 percent level. Source: Nicholson and Song 2001.


63

Table 11 Coefficient Estimates: Change in Hospital Admissions by Patients’ Source of Health Insurance Change in Charity Care Admissions, 1988–1992 ________________

Change in Medicaid Admissions, 1986–1993 ________________

n = 289

n = 4,573

-.0144* (.00608)

.0603* (.00622)

public hospital interaction

-.0376* (.0178)

-.00976 (.00879)

for-profit hospital interaction

.0692* (.0236)

-.0497* (.0106)

sole community hospital interaction

.000728 (.0241)

-.0618* (.0139)

Change in opportunity cost of providing charity care

Population change, state level (thousands) Medicaid beneficiaries

.421* (.0327)

nonelderly uninsured

.417 (.321)

people with income below poverty

-.561 (.370)

Change in percentage of a state’s Medicaid beneficiaries in an HMO Constant

R2

-2.99* (1.03)

1.7 (27.2)

44.1 (26.9)

.08

.06

Note: Standard errors in parentheses. * = significantly different from zero at the 5 percent level. Source: Nicholson 1998.

64


Figure 1 Resident-to-bed Ratio at U.S. Teaching Hospitals, 1983–1996

1.0 = 1983 1 .8

Resident: bed ratio (+60%)

1 .6 1 .4

Residents (+35%)

1 .2 1

Beds (-15%)

0 .8 0 .6 1983

1986

1989

1992

Source: Medicare cost reports, 1984–1996.

1994

1996


Figure 2 Supply and Demand of Residents

Resident’s wage S1

D1 D0 S2 w0

Quantity of residents

65

66


Figure 3 Students Applying to the Match, 1980–1996

Number of students 25,000

Total Othera International medical school graduates

20,000 15,000

10,000

U.S. medical school graduates

5,000

0 1980 '82 Average resident’s wage ($000s):b 30.8 30.8

'84

'86

'88

'90

'92

'94

'96

31.4

31.5

31.5

31.0

32.0

32.6

32.8

a. The “other” category includes licensed physicians practicing in the United States and U.S. citizens who received their medical training at international medical schools. b. In 1996 dollars. Source: Association of American Medical Colleges Data Book: Statistical Information Related to Medical Schools and Teaching Hospitals, 2000.

0

5

10

15

20

25%

0

.05

.15

.20

.25

.30

.35

Hospital’s low-income insured patient share

.10

.40

Rural, 100–499

Rural, < 100 beds

Urban, < 100 beds

.45

Rural referral center

Sole community provider

Urban > 100 beds; Rural > 500 beds

Source: Federal Register vol. 53, no. 190, Code of Federal Regulations, chapter 4, 10-1-96 edition.

DSH payments as a % of a hospital’s DRG revenue

Effect of Medicare DSH Policy on the Price Per Medicare Admission

Figure 4

STATISTICAL APPENDIX 67

IME policy instituted for all hospitals except those in waiver states (NY, MA, NJ, MD)

1983

1989/1991

MD and NJ teaching hospitals

NY and MA teaching hospitals

DSH instituted; NY and MA hospitals become eligible for IME for the first time; IME made less generous

1986

NY, MA, NJ, MD teaching hospitals

Teaching hospitals in 46 states

Source: Federal Register vol. 53, no. 190, Code of Federal Regulations, chapter 4, 10-1-96 edition.

Policy events

Ineligible

Generosity of IME subsidy

High

Policy Time Line for Medicare IME and Medicare DSH Policies

Figure 5

68 STATISTICAL APPENDIX

Notes

1. The DME payment formula does not take into consideration how much of a hospital’s outpatient care is provided to Medicare beneficiaries, even though outpatient services now generate over one-third of hospital revenue nationally. 2. Each of the 474 original diagnostic related groups had a unique case weight reflecting the average cost of treating Medicare patients with that diagnosis in all U.S. hospitals relative to a benchmark diagnosis. 3. The combined mean IME and DME payment per resident was $69,000 in 1995. In 1984 the mean IME and DME payment per resident would have been larger than that in real terms. 4. The original IME payment formula interpreted HCFA’s cost regression as a linear regression when in fact the dependent variable and the teaching intensity coefficient were both in logarithmic form. This misinterpretation caused teaching hospitals with very small and very large numbers of employed residents to be underpaid, and medium-sized teaching hospitals to be overpaid (Rogowski and Newhouse 1992). 5. Obstetrics/gynecology residency positions are classified as primary care. 6. SSI is a federal program that provides cash payments to lowincome elderly, disabled, and blind persons. To be eligible for SSI, a single person’s countable annual resources must not exceed $2,000; a married couple’s, $3,000. In 1993 about 1.5 million Medicare beneficiaries, or 4.3 percent of the total, received SSI payments (Committee on Ways and Means 1993). 7. Most states have instituted Medicaid DSH programs that are distinct from the Medicare DSH program. State Medicaid DSH program expenditures ($15 billion in 1996) are about three times as large as expenditures in the Medicare DSH program. 8. The Medicare DSH payments for a rural hospital that is defined by Medicare as a sole community hospital or a rural referral center are 69

70

NOTES

not fixed, but increase with the DSH index just as with large urban hospitals. 9. The 25 cent subsidy comes from the fact that Medicare DSH expenditures of $4.6 billion are about one-fourth as large as the total cost of uncompensated care provided by teaching hospitals. 10. The Balanced Budget Act of 1997 also reduced DSH payments by 5 percent for the year 2000. The Balanced Budget Reconciliation Act later changed this to a 4 percent reduction. 11. Pediatric hospitals are excluded because they treat very few Medicare patients; psychiatric hospitals are excluded because they are not subject to PPS rules. Hospitals that are not in an MSA are excluded because market characteristics are not available or are less accurate for these hospitals. Moreover, urban nonteaching hospitals are a better control group for teaching hospitals than are rural nonteaching hospitals because the latter face different market conditions. The teaching hospitals included in the sample account for two-thirds of the hospitals training residents in 1991 and for 80 percent of the residents trained in that year. There are 179 hospitals that employed residents in either 1986 or 1991, but not both years. These are small teaching hospitals; the median number of residents employed in 1991 by these hospitals is two. 12. Hospitals in an all-payer system receive a uniform price regardless of the patient’s source of insurance. This price may differ by type of hospital (e.g., urban/rural, teaching/nonteaching, upstate/downstate New York). 13. When calculating changes in the marginal subsidy payments, I assume that hospitals maintain their resident-to-bed ratio and Medicare admissions at the observed 1986 levels. 14. The estimated price elasticity of the demand for residents is -0.08. 15. The effect of the IME policy on the number of employed residents is derived by multiplying the mean change in the subsidy payment, $47.2, by 0.116, the regression coefficient on the change in the IME payment. 16. The coefficient on the price change due to the IME revision in column two of table 9 is 50 percent smaller when we examine the 1984–1988 time period. No other results in table 9 are sensitive to the length of the observation period. 17. The effect of the Medicare DSH policy on Medicare patients is incorporated into the analysis of the effect of the IME policy. 18. Psychiatric and rehabilitation hospitals are excluded; children’s hospitals are included.

NOTES

71

19. The number of NIS hospitals by state used in this analysis is as follows: Iowa (89), California (60), Illinois (48), Massachusetts (34), New Jersey (27), Washington (21), and Colorado (10). 20. To qualify as a sole community provider, a hospital must be at least 35 miles away from other like hospitals and no more than 25 percent of the local population must receive their hospital care outside of a 35-mile radius. 21. The Boren Amendment required that Medicaid reimbursement to hospitals and nursing homes be sufficiently high such that services are as available to Medicaid beneficiaries as to the general public. The Boren Amendment was repealed by the Balanced Budget Act of 1997. 22. Many states financed this increased spending by creating statespecific Medicaid DSH programs. Although Medicaid DSH payments are substantial ($15 billion in 1996), they are difficult to track. For example, a state may tax hospitals at the beginning of the year and then return the taxed payments along with some supplemental funds when a hospital treats Medicaid patients. The federal government pays a proportion of the gross payment to the hospital rather than the state’s net payment. States may use the incremental federal money to pay hospitals more for treating Medicaid patients or for any other purpose. For this analysis, only the net Medicaid DSH payments to hospitals, as determined by Ku and Coughlin (1995), are included in the state Medicaid price. The net payment is the difference between the gross amount a state pays the hospitals and the amount hospitals transfer to the state in the form of donations or provider taxes.

References

Anderson, Gerard F. and Judith R. Lave. 1986. “Financing Graduate Medical Education Using Multiple Regression to Set Payment Rates,” Inquiry 23: 191–99. Becker, Gary S. 1964. Human Capital: A Theoretical and Empirical Analysis, with Special Reference to Education. New York: National Bureau of Economic Research. Chan, Leighton, Thomas D. Koepsell, Richard Deyo, Peter C. Esselman, Jodie K. Haselkorn, Joseph K. Lowery, and Walter C. Stolov. 1997. “The Effect of Medicare’s Payment System for Rehabilitation Hospitals on Length of Stay, Charges, and Total Payments.” New England Journal of Medicine 337(14): 978–85. Coughlin, Teresa and David Liska. 1998. “Changing State and Federal Payment Policies for Medicaid Disproportionate Share Hospitals.” Health Affairs 17(3): 118–36. Council on Graduate Medical Education. 1994. Fourth Report to Congress and the Department of Health and Human Services Secretary. Washington, D.C. Dalton, Kathleen and Edward C. Norton. 2000. “Revisiting Rogowski and Newhouse on the Indirect Costs of Teaching: A Note on Functional Form and Retransformation in Medicare’s Payment Formulas.” Journal of Health Economics 19(6): 1027–46. Duffy, Sarah Q., Jane E. Rusedski, and Sean Cavanaugh. 2000. “Graduate Medical Education Costs in Nonacademic Health Center Teaching Hospitals: Evidence from Maryland.” Medical Care Research and Review 57(1): 3–28. Hodgkin, Dominic and Thomas G. McGuire. 1994. “Payment Levels and Hospital Response to Prospective Payment.” Journal of Health Economics 13: 1-29. Iglehart, John K. 1994. “Health Care Reform and Graduate Medical Education.” New England Journal of Medicine 330(16): 1167–71. 72

REFERENCES

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Kominski, Gerald F. and Stephen H. Long. 1997. “Medicare’s Disproportionate Share Adjustment and the Cost of Low-income Patients.” Journal of Health Economics 16(2): 177–90. Ku, Leighton and Teresa Coughlin. 1995. “Medicaid Disproportionate Share and Other Special Financing Programs.” Health Care Financing Review 16(3): 27–54. Lave, Judith. 1985. The Medicare Adjustment for the Indirect Costs of Medical Education: Historical Development and Current Status. Washington, D.C.: Association of American Medical Colleges. Lee, David W. and Kurt D. Gillis. 1994. “Physician Responses to Medicare Payment Reform: Update on Access to Care.” Inquiry, fall 1994, 346–53. Lee, Robert H. and Jack Hadley. 1985. “The Demand for Residents.” Journal of Health Economics 4:357–71. Mann, Joyce M., Glenn A. Melnick, Anil Bamezai, and Jack Zwanziger. 1997. “A Profile of Uncompensated Care, 1983–1995.” Health Affairs, July/August 1997, 223–32. Medicare Payment Advisory Commission (MedPAC). 1998. Report to the Congress: Medicare Payment Policy. Washington, D.C. ————. 1999a. Report to the Congress: Rethinking Medicare’s Payment Policies for Graduate Medical Education and Teaching Hospitals. Washington, D.C. ————. 1999b. Report to Congress: Medicare Payment Policy. Washington, D.C. ————. 2000a. Report to Congress: Selected Medicare Issues. Washington, D.C. ————. 2000b. Report to Congress: Medicare Payment Policy. Washington, D.C. Newhouse, Joseph P. 1989. “Do Unprofitable Patients Face Access Problems?” Health Care Financing Review 11(2): 33–42. Nicholson, Sean. 1998. “The Effect of Government Policy on Hospital Care for the Poor.” Manuscript. ————. 1999. “Physician Specialty Choice under Uncertainty.” Journal of Labor Economics, forthcoming. ————, Mark V. Pauly, Lawton R. Burns, Agnieshka Baumwritter, and David A. Asch. 2000. “Measuring Community Benefits Provided by For-profit and Nonprofit Hospitals.” Health Affairs 19(6): 168–77. ———— and David Song. 2001. “The Incentive Effects of the Medicare Indirect Medical Education Policy.” Journal of Health Economics 20(6): 909–33. Pettengill, J. and J. Vertrees. 1982. “Reliability and Validity in Hospital Case Mix Measurement.” Health Care Financing Review 4(2):101–127.

74

REFERENCES

Physician Payment Reform Commission. 1994. Annual Report to Congress. Washington, D.C. Plumb, Diane N. and Tim M. Henderson. 1995. Medicaid Funding of Graduate Medical Education: A Survey of the States. Washington, D.C.: Association of American Medical Colleges. Prospective Payment Assessment Commission (ProPAC). 1985. Technical Appendixes to the Report and Recommendations to the Secretary, U.S. Department of Health and Human Services. Washington, D.C.: U.S. Government Printing Office. ————. 1986. Technical Appendixes to the Report and Recommendations to the Secretary, U.S. Department of Health and Human Services. Washington, D.C.: U.S. Government Printing Office. ————. 1994. Analysis of Medicaid Disproportionate Share Payment Adjustments. Report C-94-01. Washington, D.C. ————. 1997. Report and Recommendations to Congress. Washington, D.C. Rogowski, Jeannete A. and Joseph P. Newhouse. 1992. “Estimating the Indirect Costs of Teaching.” Journal of Health Economics 11: 153–71. Sheingold, S. H. 1990. “Alternatives for Using Multivariate Regression to Adjust Prospective Payment Rates.” Health Care Financing Review 11(3): 31–41. Thorpe, Kenneth E. 1988. “The Use of Regression Analysis to Determine Hospital Payment: The Case of Medicare’s Teaching Adjustment.” Inquiry 25:219–31. U.S. Congress. House. Committee on Ways and Means. 1965. Report on H.R. 6675, to provide a hospital insurance program for the aged under the Social Security Act with a supplemental health benefits program and an expanded program of medical assistance, to increase benefits under the old age, survivors, and disability insurance system, to improve the federal-state public assistance program, and for other purposes, 89th Cong., 1st sess., H. Rept. 213. ————. 1993. Background Material and Data on Major Programs Within Jurisdiction of the Committee on Ways and Means. Washington, D.C.: Government Printing Office. U.S. Congressional Budget Office. 1990. Medicare’s Disproportionate Share Adjustment for Hospitals. Washington, D.C.: GPO. Zwanziger, Jack, Glenn A. Melnick, and Lisa Simonson. 1996. “Differentiation and Specialization in the California Hospital Industry 1983 to 1988.” Medical Care 34(4): 361–72. ———— and Glenn A. Melnick. 1988. “The Effects of Hospital Competition and the Medicare PPS Program on Hospital Cost Behavior in California.” Journal of Health Economics 7: 301–20.

About the Author

SEAN NICHOLSON is an assistant professor in the health care systems department of the University of Pennsylvania’s Wharton School of Business. He has worked as a management consultant to the hospital industry with APM and published widely on health economics.

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