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Estimating Hospital Inefficiency: Does Case Mix Matter?

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Abstract

A two-stage approach is used in a stochastic frontier analysis of the factors affecting hospital efficiency. In the first stage, a translog cost-function is used to estimate inefficiency scores. In the second stage, inefficiency scores are regressed against independent variables to test hypotheses that come from X-inefficiency Theory. The study was based on 1989 data for 195 Pennsylvania acute care hospitals. This data base was chosen because of the availability of patient-level severity of illness data, a measure of output that is not available from most data sources. The stochastic frontier analysis models estimated mean inefficiency scores that ranged from 0.075 to 0.180. The addition of the DRG case mix index (CMI) reduced estimated inefficiency by more than 50%. The incremental effect of a severity of illness variable to an equation with CMI was very small. The second-stage results suggest inefficiency and are inversely associated with regulatory pressures and industry concentration.

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Authors and Affiliations

  1. Graduate Program in Health and Medical Services Administration, Widener University, Chester, Pennsylvania, 19013

    Michael D. Rosko

  2. Heller School for Advanced Studies in Social Welfare Policy, Brandeis University, Waltham, Massachusetts, 02154

    Jon A. Chilingerian

Authors
  1. Michael D. Rosko
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  2. Jon A. Chilingerian
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Rosko, M.D., Chilingerian, J.A. Estimating Hospital Inefficiency: Does Case Mix Matter?. Journal of Medical Systems 23, 57–71 (1999). https://doi.org/10.1023/A:1020823612156

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