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.
O'Neill
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Division of Health Management and Policy, College of Medicine, University of Iowa, Iowa City 52242-1008, USA. liam-oneill@uiowa.edu
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