Accounting for heterogeneity in the measurement of hospital performance

ABSTRACT

As the Corona pandemic of 2020 has shown, disposing of sufficient hospital capacity is of great importance. Ideally, this capacity should be provided by efficient units, calling for measurement of their performance. However, the standard cost frontier model yields biased efficiency scores because it ignores (often unobserved) heterogeneity between hospitals. In this paper, efficiency scores are derived from a cost function with both random intercept and random slope parameters which overcomes the problem of unobserved heterogeneity in stochastic frontier analysis. Based on an unbalanced panel covering the years 2004 to 2007 and comprising at least 100 Swiss hospitals per year, Bayesian inference points to significant heterogeneity suggesting rejection of the standard cost frontier model. When unobserved heterogeneity is fully accounted for, average estimated inefficiency decreases to 5%, below the 14% (21%, respectively) value reported for a number of European and Middle-Eastern countries (Hollingsworth, 2008; Alawi et al. 2019). Moreover, hospitals rated below 85% efficiency according to the standard model gain up to 12% points. They can provide much needed capacity that otherwise would be discarded on the grounds that they are not sufficiently efficient providers.

KEYWORDS:

• Hospital efficiency
• unobserved heterogeneity
• Bayesian inference
• Switzerland
• Stochastic frontier analysis

JEL CLASSIFICATION:

• C11
• C33
• D24
• I18

Acknowledgment

The authors wish to thank an anonymous referee for several helpful suggestions.

Disclosure statement

No potential conflict of interest was reported by the authors.

Ethical

No ethical concerns to report; data are aggregated to the level of an entire hospital so do not relate to individual patients