Skip to main content
SpringerLink
Log in

Measuring Hospital Efficiency with Data Envelopment Analysis: Nonsubstitutable vs. Substitutable Inputs and Outputs

  • Original Paper
  • Published:
Journal of Medical Systems Aims and scope Submit manuscript

Abstract

There is a conflict between Data Envelopment Analysis (DEA) theory’s requirement that inputs (outputs) be substitutable, and the ubiquitous use of nonsubstitutable inputs and outputs in DEA applications to hospitals. This paper develops efficiency indicators valid for nonsubstitutable variables. Then, using a sample of 87 community hospitals, it compares the new measures’ efficiency estimates with those of conventional DEA measures. DEA substantially overestimated the hospitals’ efficiency on the average, and reported many inefficient hospitals to be efficient. Further, it greatly overestimated the efficiency of some hospitals but only slightly overestimated the efficiency of others, thus making any comparisons among hospitals questionable. These results suggest that conventional DEA models should not be used to estimate the efficiency of hospitals unless there is empirical evidence that the inputs (outputs) are substitutable. If inputs (outputs) are not substitutes, efficiency indicators valid for nonsubstitutability should be employed, or, before applying DEA, the nonsubstitutable variables should be combined using an appropriate weighting scheme or statistical methodology.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Hollingsworth, B., The measurement of efficiency and productivity of health care delivery. Health Econ. 17(10):1107–1128, 2008.

    Article  Google Scholar 

  2. Chern, J. Y., and Wan, T. T. H., The impact of the prospective payment system on the technical efficiency of hospitals. J. Med. Syst. 24(3):159–172, 2000.

    Article  Google Scholar 

  3. Sahin, I., and Ozcan, Y. A., Public sector hospital efficiency for provincial markets in Turkey. J. Med. Syst. 24(6):307–320, 2000.

    Article  Google Scholar 

  4. Kirigia, J. M., Emrouznejad, A., and Sambo, L. G., Measurement of technical efficiency of public hospitals in Kenya: using data envelopment analysis. J. Med. Syst. 26(1):39–45, 2002.

    Article  Google Scholar 

  5. Wan, T. T. H., Lin, B. Y. -J., and Ma, A., Integration mechanisms and hospital efficiency in integrated health care delivery systems. J. Med. Syst. 26(2):127–143, 2002.

    Article  Google Scholar 

  6. Harrison, J. P., Coppola, M. N., and Wakefield, M., Efficiency of federal hospitals in the United States. J. Med. Syst. 28(5):411–422, 2004.

    Article  Google Scholar 

  7. Hajialiafzali, H., Moss, J., and Mahmood, M., Efficiency measurement for hospitals owned by the iranian social security organisation. J. Med. Syst. 31(3):166–172, 2007.

    Article  Google Scholar 

  8. Kirigia, J., Emrouznejad, A., Cassoma, B., Asbu, E., and Barry, S., A performance assessment method for hospitals: the case of municipal hospitals in Angola. J. Med. Syst. 32(6):509–519, 2008.

    Article  Google Scholar 

  9. Nayar, P., and Ozcan, Y., Data envelopment analysis comparison of hospital efficiency and quality. J. Med. Syst. 32(3):193–199, 2008.

    Article  Google Scholar 

  10. Lee, K. H., Yang, S. B., and Choi, M., The association between hospital ownership and technical efficiency in a managed care environment. J. Med. Syst. 33:307–315, 2009. doi:10.1007/s10916-008-9192-2.

    Article  Google Scholar 

  11. Hollingsworth, B., and Street, A., The market for efficiency analysis of health care organizations. Health Econ. 15:1055–1059, 2006.

    Article  Google Scholar 

  12. Beattie, B. R., and Taylor, C. R., The economics of production. Wiley, New York, 1985.

    Google Scholar 

  13. Farrell, M. J., The measurement of productive efficiency. J. R. Stat. Soc., A. 120(3):253–290, 1957.

    Article  Google Scholar 

  14. Charnes, A., Cooper, W. W., and Rhodes, E., Measuring the efficiency of decision making units. Eur. J. Oper. Res. 2(6):429–444, 1978.

    Article  MATH  MathSciNet  Google Scholar 

  15. Banker, R. D., Charnes, A., and Cooper, W. W., Some models for estimating technical and scale inefficiencies in data envelopment analysis. Manag. Sci. 30(9):1078–1092, 1984.

    Article  MATH  Google Scholar 

  16. Färe, R., Grosskopf, S., and Lovell, C. A. K., Production frontiers. Cambridge University Press, Cambridge, 1994.

    Google Scholar 

  17. Cooper, W. W., Seiford, L. M., Tone, K., and Zhu, J., Some models and measures for evaluating performances with DEA: past accomplishments and future prospects. J. Prod. Anal. 28(3):151, 2007.

    Article  Google Scholar 

  18. Fried, H. O., Lovell, C. A. K., and Schmidt, S. S., The measurement of productive efficiency and productivity growth. Oxford University Press, Oxford, 2008.

    Book  Google Scholar 

  19. Casu, B., and Thanassoulis, E., Evaluating cost efficiency in central administrative services in UK universities. Omega. 34(5):417–426, 2006.

    Article  Google Scholar 

  20. Banker, R. D., Chang, H., Janakiraman, S. N., and Konstans, C., A balanced scorecard analysis of performance metrics. Eur. J. Oper. Res. 154(2):423–436, 2004.

    Article  MATH  MathSciNet  Google Scholar 

  21. Holvad, T., Hougaard, J. L., Kronborg, D., and Kvist, H. K., Measuring inefficiency in the Norwegian bus industry using multi-directional efficiency analysis. Transportation. 31(3):349–369, 2004.

    Article  Google Scholar 

  22. Cooper, W. W., Seiford, L. M., and Tone, K., Data envelopment analysis: a comprehensive text with models, applications, references and DEA-Solver software. Springer, New York, 2007.

    MATH  Google Scholar 

  23. Bogetoft, P., and Hougaard, J. L., Efficiency evaluations based on potential (non-proportional) improvements. J. Prod. Anal. 12(3):233–247, 1999.

    Article  Google Scholar 

  24. Charnes, A., Cooper, W. W., Lewin, A. Y., and Seiford, L. M., Data envelopment analysis: theory, methodology and application. Kluwer Academic, Boston, 1994.

    Google Scholar 

  25. Gupta, S. R., Wojtynek, J. E., Walton, S. M., Botticelli, J. T., Shields, K. L., Quad, J. E., and Schumock, G. T., Pharmacy staffing and productivity. Am. J. Health. Syst. Pharm. 64(22):2323–2324, 2006.

    Article  Google Scholar 

  26. Sikka, V., Luke, R. D., and Ozcan, Y. A., The efficiency of hospital-based clusters: evaluating sustem performance using data envelopment analysis. Health Care Manage. Rev. 34(3):251–261, 2009.

    Google Scholar 

  27. Pedhazur, E. J., and Schmelkin, L. P., Measurement, design, and analysis: an integrated approach. Lawrence Erlbaum Associates, Hillsdale, 1991.

    Google Scholar 

  28. Wooldridge, J. M., Econometric analysis of cross section and panel data. MIT, Cambridge, 2002.

    MATH  Google Scholar 

  29. Greene, W. H., Econometric analysis, 6th edition. Prentice Hall, Upper Saddle River, 2008.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Managerial Studies, University of Illinois at Chicago, 601 South Morgan Street, Chicago, IL, 60607-7123, USA

    Darold T. Barnum

  2. Department of Information & Decision Sciences, University of Illinois at Chicago, Chicago, IL, USA

    Darold T. Barnum

  3. Department of Pharmacy Administration, University of Illinois at Chicago, Chicago, IL, USA

    Darold T. Barnum

  4. Center for Pharmacoeconomic Research, Department of Pharmacy Administration, University of Illinois at Chicago, Chicago, IL, USA

    Surrey M. Walton

  5. Department of Economics, University of Illinois at Chicago, Chicago, IL, USA

    Surrey M. Walton

  6. Sisters of St. Francis Health Services, Inc., Mishawaka, IN, USA

    Karen L. Shields

  7. Center for Pharmacoeconomic Research, Department of Pharmacy Practice, University of Illinois at Chicago, Chicago, IL, USA

    Glen T. Schumock

Authors
  1. Darold T. Barnum
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Surrey M. Walton
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Karen L. Shields
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Glen T. Schumock
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Darold T. Barnum.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Barnum, D.T., Walton, S.M., Shields, K.L. et al. Measuring Hospital Efficiency with Data Envelopment Analysis: Nonsubstitutable vs. Substitutable Inputs and Outputs. J Med Syst 35, 1393–1401 (2011). https://doi.org/10.1007/s10916-009-9416-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10916-009-9416-0

Keywords

Search

Navigation