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Bayesian Inference for Hospital Quality in a Selection Model

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  • John Geweke
  • Gautam Gowrisankaran
  • Robert J. Town

Abstract

This paper develops new econometric methods to infer hospital quality in a model with discrete dependent variables and non-random selection. Mortality rates in patient discharge records are widely used to infer hospital quality. However, hospital admission is not random and some hospitals may attract patients with greater unobserved severity of illness than others. In this situation the assumption of random admission leads to spurious inference about hospital quality. This study controls for hospital selection using a model in which distance between the patient's residence and alternative hospitals are key exogenous variables. Bayesian inference in this model is feasible using a Markov chain Monte Carlo posterior simulator, and attaches posterior probabilities to quality comparisons between individual hospitals and groups of hospitals. The study uses data on 74,848 Medicare patients admitted to 114 hospitals in Los Angeles County from 1989 through 1992 with a diagnosis of pneumonia. It finds the smallest and largest hospitals to be of high quality and public hospitals to be of low quality. There is strong evidence of dependence between the unobserved severity of illness and the assignment of patients to hospitals. Consequently a conventional probit model leads to inferences about quality markedly different than those in this study's selection model.

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Bibliographic Info

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 8497.

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Date of creation: Oct 2001
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Publication status: published as Geweke, John, Gautam Gowrisankaran and Roert J. Town. "Bayesian Inference For Hospital Quality In A Selection Model," Econometrica, 2003, v71(4,Jul), 1215-1238.
Handle: RePEc:nbr:nberwo:8497

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  1. Cutler, D.M., 1992. "The Incidence of Adverse Medical Outcome Under Prospective Payment," Harvard Institute of Economic Research Working Papers 1603, Harvard - Institute of Economic Research.
  2. McClellan, Mark & Noguchi, Haruko, 1998. "Technological Change in Heart-Disease Treatment: Does High Tech Mean Low Value?," American Economic Review, American Economic Association, vol. 88(2), pages 90-96, May.
  3. John Geweke & Gautam Gowrisankaran & Robert J. Town, 2003. "Bayesian Inference for Hospital Quality in a Selection Model," Econometrica, Econometric Society, vol. 71(4), pages 1215-1238, 07.
  4. Daniel P. Kessler & Mark B. McClellan, 2000. "Is Hospital Competition Socially Wasteful?," The Quarterly Journal of Economics, MIT Press, vol. 115(2), pages 577-615, May.
  5. Mark B. McClellan & Douglas O. Staiger, 2000. "Comparing Hospital Quality at For-Profit and Not- for-Profit Hospitals," NBER Chapters, in: The Changing Hospital Industry: Comparing For-Profit and Not-for-Profit Institutions, pages 93-112 National Bureau of Economic Research, Inc.
  6. Burns, Lawton R. & Wholey, Douglas R., 1992. "The impact of physician characteristics in conditional choice models for hospital care," Journal of Health Economics, Elsevier, vol. 11(1), pages 43-62, May.
  7. Chib, Siddhartha & Greenberg, Edward, 1996. "Markov Chain Monte Carlo Simulation Methods in Econometrics," Econometric Theory, Cambridge University Press, vol. 12(03), pages 409-431, August.
  8. Sloan, Frank A., 2000. "Not-for-profit ownership and hospital behavior," Handbook of Health Economics, in: A. J. Culyer & J. P. Newhouse (ed.), Handbook of Health Economics, edition 1, volume 1, chapter 21, pages 1141-1174 Elsevier.
  9. Mark McClellan & Douglas Staiger, 1999. "The Quality of Health Care Providers," NBER Working Papers 7327, National Bureau of Economic Research, Inc.
  10. Gowrisankaran, Gautam & Town, Robert J., 1999. "Estimating the quality of care in hospitals using instrumental variables," Journal of Health Economics, Elsevier, vol. 18(6), pages 747-767, December.
  11. repec:cup:etheor:v:12:y:1996:i:3:p:409-31 is not listed on IDEAS
  12. Geweke, John F. & Keane, Michael P. & Runkle, David E., 1997. "Statistical inference in the multinomial multiperiod probit model," Journal of Econometrics, Elsevier, vol. 80(1), pages 125-165, September.
  13. Keane, Michael P, 1992. "A Note on Identification in the Multinomial Probit Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(2), pages 193-200, April.
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