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Measuring technical efficiency in health care organizations

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Abstract

The rising cost of health care has created great interest in developing methods to increase the efficiency of health care organizations. Despite this interest most analyses of prospective payment and other programs designed to control expenditures have examined costs and not efficiency. This article examines a new technique—data envelopment analysis (DEA)—that facilitates the conduct of efficiency studies. The utility of DEA is analyzed by comparing this technique with other methods used to measure efficiency, by discussing the application of DEA in the health care industry and by assessing the validity of results from DEA studies. The article concludes with an assessment of the strengths and weaknesses of DEA and suggestions for refining this technique.

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References

  1. Rosko, M.D., A comparison of hospital performance under the partial-payer Medicare PPS and state all-payer rate-setting systems.Inquiry 26(1):48–61, 1989.

    Google Scholar 

  2. Rosko, M.D., and Broyles, R.,The Economics of Health Care: A Reference Handbook, Greenwood Press, New York, 1988.

    Google Scholar 

  3. Charnes, A., Cooper, W.W., and Rhodes, E., Evaluating program and managerial efficiency: An application of data envelopment analysis to program follow through.Management Science 27(6):668–697, 1978.

    Google Scholar 

  4. Sexton, T., Leiken, A., Nolan, A.,et al., Evaluating managerial efficiency of Veterans Administration Medical Centers using data envelopment analysis.Med. Care 27(12):1175–1188, 1989.

    Google Scholar 

  5. Fare, R., and Lovell, C.A., Measuring the technical efficiency of production.J. Roy. Stat. Soc. 19(1):150–62, 1978.

    Google Scholar 

  6. Banker, R.D., Charnes, A., and Cooper, W.W., Some models for estimating technical and scale inefficiencies in data envelopment analysis.Manag. Sci. 32(1):30–44, 1984.

    Google Scholar 

  7. Banker, R.D., Conrad, R.R., and Strauss, R.P., A comparative application of DEA and translog methods: An illustrative study of hospital production.Manag. Sci. 31(1):30–44, 1986.

    Google Scholar 

  8. Bitran, G.R., and Valor-Sabatier, J., Some mathematical programming based measures of efficiency in health care institutions.Advan. Math. Program. Finan. Plann. 1:61–84, 1987.

    Google Scholar 

  9. Bowlin, W.R., Charnes, A., Cooper, W.W., and Sherman, H.D., Data envelopment analysis and regression approaches to efficiency estimation and evaluation.Ann. Operat. Res. 2:113–138, 1985.

    Google Scholar 

  10. Chilingerian, J.A., Investigating non-medical factors associated with the technical efficiency of physicians in the provision of hospital services: a pilot study.Best Paper Proceedings 1989: 49th Annual Meeting of Academy of Management, Washington, D.C.:85–89, 1989.

  11. Chilingerian, J.A., and Sherman, H.D., Managing physician efficiency and effectiveness in providing hospital services.Health Serv. Manag. Res. 3(1):3–15, 1990.

    Google Scholar 

  12. Grosskopf, S., and Valdmanis, V., Measuring hospital performance: A nonparametric approach.J. Health Econ. 6(2):89–107, 1987.

    Google Scholar 

  13. Hogan, A.J., Chesney, J., Wroblewski, R., and Fleming, S., The impact of the Medicare prospective payment system on hospital efficiency: A data envelopment analysis. Paper presented to the American Economic Association Annual Meeting, Chicago, 1987.

  14. Huang, Y.L., and McLaughlin, C.P., Relative efficiency in rural primary health care: An application of data envelopment analysis.Health Serv. Res. 24(2):143–158, 1989.

    Google Scholar 

  15. Morey, R.C., Capettini, R., and Dittman, D.A., Pareto rate setting strategies: An application to Medicaid Drug Reimbursement.Policy Sci. 18(2):169–200, 1985.

    Google Scholar 

  16. Nunamaker, T.R., Measuring routine nursing service efficiency: A comparison of cost per patient day and data envelopment analysis models.Health Serv. Res. 18(2):183–205, 1983.

    Google Scholar 

  17. Nyman, J.A., and Bricker, D.L., Profit incentives and technical efficiency in the production of nursing home care.Rev. Econ. Stat. 71(4):586–594, 1989.

    Google Scholar 

  18. Nynam, J.A., Bricker, D.L., and Link, D., Technical efficiency in nursing homes.Med. Care 28(6):541–551, 1990.

    Google Scholar 

  19. Sherman, H.D., Hospital efficiency measurement and evaluation.Med. Care 22(10):922–935, 1984.

    Google Scholar 

  20. Valdmanis, B.G., Ownership and technical efficiency of hospitals.Med. Care 28(6):552–561, 1990.

    Google Scholar 

  21. Wilson, G.W., and Jadlow, J.M., Competition, profit incentives, and technical efficiency in the provision of nuclear medicine services.Bell J. of Econ. 13(2):472–482, 1982.

    Google Scholar 

  22. Conrad, R.F., and Strauss, R.P., A Multiple-Output Multiple-Input Model of the hospital industry in North Carolina.Appl. Econ. 15(3):341–352, 1983.

    Google Scholar 

  23. Arrow, K.J., Uncertainty and the welfare economics of medical care.Am. Econ. Rev. 53(4):941–973, 1963.

    Google Scholar 

  24. Rosko, M.D., DRGs and severity of illness measures: An analysis of patient classification systems.J. Med. Syst. 12(4):257–274, 1988.

    Google Scholar 

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Rosko, M.D. Measuring technical efficiency in health care organizations. J Med Syst 14, 307–322 (1990). https://doi.org/10.1007/BF00993937

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  • DOI: https://doi.org/10.1007/BF00993937

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