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Multifactor efficiency in Data Envelopment Analysis with an application to urban hospitals

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  • Liam O'Neill

Abstract

A perennial difficulty in measuring hospital efficiency, and one with important policy implications, is how to compare teaching versus non-teaching hospitals. This problem reflects a broader methodological concern in Data Envelopment Analysis (DEA), which is the comparison of specialist and non-specialist Decision-Making Units (DMUs). This paper presents a new performance measure in DEA, termed multifactor efficiency, which represents an average partial factor productivity index summed over all output–input ratios. We apply this technique to measure the performance of 27 large, urban hospitals, including 13 teaching hospitals. These results were reviewed and validated by a panel of health care experts, and multifactor efficiency was shown to offer several benefits that enhance and complement existing performance measures in DEA. Copyright Kluwer Academic Publishers 1998

Suggested Citation

  • Liam O'Neill, 1998. "Multifactor efficiency in Data Envelopment Analysis with an application to urban hospitals," Health Care Management Science, Springer, vol. 1(1), pages 19-27, September.
    • Handle: RePEc:kap:hcarem:v:1:y:1998:i:1:p:19-27
    DOI: 10.1023/A:1019030215768
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    Cited by:

    1. Giménez, Víctor & Prieto, William & Prior, Diego & Tortosa-Ausina, Emili, 2019. "Evaluation of efficiency in Colombian hospitals: An analysis for the post-reform period," Socio-Economic Planning Sciences, Elsevier, vol. 65(C), pages 20-35.
    2. Dino Rizzi & Vincenzo Rebba, 2006. "Measuring Hospital Efficiency through Data Envelopment Analysis when Policy-makers� Preferences Matter. An Application to a sample of Italian NHS hospitals," Working Papers 2006_13, Department of Economics, University of Venice "Ca' Foscari".
    3. O'Neill, Liam & Rauner, Marion & Heidenberger, Kurt & Kraus, Markus, 2008. "A cross-national comparison and taxonomy of DEA-based hospital efficiency studies," Socio-Economic Planning Sciences, Elsevier, vol. 42(3), pages 158-189, September.
    4. Rowena Jacobs, 2000. "Alternative methods to examine hospital efficiency: Data Envelopment Analysis and Stochastic Frontier Analysis," Working Papers 177chedp, Centre for Health Economics, University of York.
    5. Akkan, Can & Karadayi, Melis Almula & Ekinci, Yeliz & Ülengin, Füsun & Uray, Nimet & Karaosmanoğlu, Elif, 2020. "Efficiency analysis of emergency departments in metropolitan areas," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    6. Wagner, Janet M. & Shimshak, Daniel G. & Novak, Michael A., 2003. "Advances in physician profiling: the use of DEA," Socio-Economic Planning Sciences, Elsevier, vol. 37(2), pages 141-163, June.
    7. Nahra, Tammie A. & Mendez, David & Alexander, Jeffrey A., 2009. "Employing super-efficiency analysis as an alternative to DEA: An application in outpatient substance abuse treatment," European Journal of Operational Research, Elsevier, vol. 196(3), pages 1097-1106, August.

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