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Hospital Efficiency Measurement: Simple Ratios vs Frontier Methods

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journal contribution
posted on 07.06.2017, 04:02 by Mortimer, Duncan, Peacock, Stuart
Objectives: To provide a critical appraisal of the methods, results and policy value of two frontier methods for hospital efficiency measurement: data envelopment analysis (DEA) and stochastic frontier analysis (SFA). To compare the policy value of DEA- and SFA-based measures against more commonly used indicators of hospital performance. Methods: Comparative analysis of DEA and SFA in estimating the relative efficiency of public hospitals in Victoria. Possible sources of measured inefficiency are investigated via the Battese and Coelli (1995) effects model in the case of SFA-based efficiency scores and via second-stage regressions in the case of DEA-based efficiency measures. The content and consistency of DEA- and SFA-based targets and measures are then compared against simple cost/output ratios. Results: Moderate correspondence between DEA- and SFA-based efficiency scores with measured inefficiency at least partially attributable to between-hospital differences in casemix, stay-mix, quality of care, teaching/research activity and location. More or less the same set of hospital characteristics turned out to be important in explaining between-hospital variation in both DEA- and SFA-based measures of hospital efficiency. In short, results provided some reassurance that DEA and SFA are measuring closely related constructs, along similar dimensions. Perhaps surprisingly, there is at least as much common ground between simple cost/output ratios and SFA-based measures of hospital efficiency, as there is between DEA- and SFA-based alternatives. Conclusions: Frontier-based measures of hospital performance are broadly consistent with simpler, more commonly available performance measures. However, consistency and precision are not the only considerations in selecting policy-ready performance measures and deliberations as to the policy-value of frontier- and ratio-based options should take account of both precision and content.


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Centre for Health Program Evaluation

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