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Pierre Azoulay pa2009@columbia Columbia University Graduate School of Business

Medical Research and Health Care Financing: Academic Medical Centers Following the 1997 Medicare Cuts. Abigail Tay at436@columbia.edu Columbia University Department of Economics. Pierre Azoulay pa2009@columbia.edu Columbia University Graduate School of Business

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Pierre Azoulay pa2009@columbia Columbia University Graduate School of Business

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  1. Medical Research and Health Care Financing: Academic Medical Centers Following the 1997 Medicare Cuts Abigail Tay at436@columbia.edu Columbia UniversityDepartment of Economics Pierre Azoulay pa2009@columbia.edu Columbia UniversityGraduate School of Business Wharton School, University of Pennsylvania Leonard Davis Institute of Health EconomicsFebruary 6th, 2004

  2. Research Agenda • Academic Medical Centers (AMCs) play a crucial role in the American system of biomedical innovation • Research within AMCs comes from 4 sources: • Public sources — mostly NIH, about 65% • Foundations — ignored in this paper, about 10% • Industry — mostly clinical trials, about 15% • “Institutional Funds” — X-subsidies from patient-care activities, about 10% • Cross-subsidies have been a traditional source of seed-research funds, especially for physician-scientists • What have been the effects of changes in health care financing on the level and composition of research in AMCs?

  3. or or ? ? + + - - Two views of X-subsidies • Old Boys’ Network • Substitute with other sources of funding • Essential Lubricant • Complement other sources of funding + Financial Slack X-Subsidies Research

  4. Evolution of Extramural NIH Funds, by Degree of Investigator, 1970-2002

  5. Research Strategy • Pure time series analysis will be contaminated by secular trends such as the massive expansion of the NIH budget during the 1990s • Cross-sectional comparisons across disease areas or research institutions will suffer from omitted variable bias (scientific opportunities, etc.) • We focus on the impact of a discrete shock to hospital finances:Cuts in the Medicare Indirect Medical Education (IME) subsidy following the Balanced Budget Act of 1997 • Compare grant awards, before and after 1997, between hospitals that faced a potential large decrease in the level of Medicare reimbursements with those that faced merely a modest decrease

  6. Preview of Results • Elasticity of NIH grant awards with respect to health care reimbursements: About .15 • Endowments cushion the effect of the reform • Only very weak evidence that effect is driven by substitution of residents by full-time faculty • Results consistent with the view that hospital X-subsidies complement external sources of funding • Effect shows up “too soon” • One would have expected a 1-2 year lag • Suggests that the reform was anticipated • No response of industry-funded research activity • But more affected hospitals see a rebalancing of their research portfolio towardsclinical trials away from NIH-funded research • Important differences in the magnitude of the response across types of investigators • MDs & MD/PhDs are more affected than PhDs • Human-subjects research is more affected than lab-based research • Young investigators are more affected than experienced faculty members(the result is not consistent across measures of experience) • No difference between competing and noncompeting grants; only noncompeting funds appear to be affected (very counterintuitive)

  7. A Primer on the Medicare PPS System • Since 1984, Medicare reimburses inpatient care prospectively, based on the following formula: $ Reimbursed = Std. Amount × DRG weight × (1+ Teaching Adjustment + Medicaid Adjustment) %IME %DSH %IME = a× [(1+ #Residents/#Beds).405– 1] a<1997= 1.89 a1998= 1.72 a>1999= 1.60

  8. Data • NIH Consolidated Grant Applicant File • Clinical trial grant data from FastTrack Systems, Inc. • American Hospital Association Survey • AAMC Faculty Roster • HCFA/CMS Cost Reports and IMPACT Files • Area Resource File • HMO penetration variable

  9. Data Issues: JHU and Affiliated Hospitals 1 2 3 4 5

  10. Descriptive Statistics:163 Hospitals/“Hospital Aggregates”

  11. Distribution of Average Yearly NIH Awards,1994-2001

  12. Distribution of Average Yearly Industry Awards, 1994-2001

  13. Evolution of Industry Expenditures on Clinical Trials by Type of Site, 1991-2000

  14. “Parameterizing” the Reform • Regressing research outputs on actual Medicare reimbursements is problematic, because hospitals can change behavior in response to the reform • We create a measure of “Counterfactual” Medicare Payments • Before the Act, Counterfactual = Actual • After the Act, CMP corresponds to the payments that would have accrued to the hospital based on the new formula if the underlying determinants of reimbursement levels (patient mix, #residents, #beds, #Medicare discharges) had remained at their average pre-reform level • The CMP variable is defined entirely as of the before period: nothing that the hospital does after the passage of the act (e.g., close beds, DRG “upcoding”...) will affect it

  15. Mean Counterfactual Medicare Payments(Balanced PPS Sample, 1994 Real $ ×106)

  16. Impact of BBA Reform [1]

  17. Impact of BBA Reform [2]

  18. Impact of BBA Reform [3]

  19. Regression Analyses b2 < 0 or > 0 ? • Regression weighted by average grant amounts in the pre-period (unweighted residuals exhibit extreme form of heteroskedasticity) • Standard errors clustered by medical schools • Equations estimated jointly by SUR to account for contemporaneous correlations of the residuals

  20. Scatterplot of Unweighted Residuals Against Chosen Weights

  21. Table 3: “After” Dummy Summarizes the Passage of the Reform

  22. Table 4: Robustness Checks

  23. Table 5: Year-specific Slopes for the Impact of the Reform

  24. Are X-subsidies Driving the Effect? [1] Note: Endowment Measure is the sum of investment income and contributions, bequests and gifts during the 4 years before the reform.

  25. Are X-subsidies Driving the Effect? [2] Dep. Variable: Log of number of FTE Residents

  26. Concluding Thoughts • Our results do not suggest that cutting the IME subsidy was a bad idea; rather, we highlight unintended consequences of the reform • Health economists have examined how insurance type, for profit/not-for-profit care, etc. influence current health outcomes • Meta-analysis of this literature: health care financing does not seem to explain much once selection issues are dealt with adequately • Our results suggest that financing may affect future health outcomes through its effect on the pace of medical progress • Congress, NIH, academics often focus on the efficiency of the horizontal allocation of public research funds across diseases (Lichtenberg, 2001) • But the imbalances along the vertical chain of biomedical innovation may ultimately be of greater importance

  27. Youngsters vs. Old-timers:Contradictory Results

  28. Competing vs. Noncompeting Funds:Counterintuitive Results

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