Multifactor efficiency in data envelopment analysis with an application to urban hospitals.
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.
Division of Health Management and Policy, College of Medicine, University of Iowa, Iowa City 52242-1008, USA. liam-oneill@uiowa.edu
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D003659:Decision Making, Organizational; D017598:Efficiency, Organizational / Q000706:statistics & numerical data*; D006784:Hospitals, Teaching / Q000458:organization & administration* / Q000706:statistics & numerical data; D006786:Hospitals, Urban / Q000458:organization & administration* / Q000706:statistics & numerical data; D015233:Models, Statistical; D014481:United States