A robust analysis of hospital efficiency and factors affecting variability

The objectives of this paper are to use data envelopment analysis to measure hospital inefficiency in a way that accounts for patient outcomes and to study the association between organizational factors, such as hospital–physicians integration level and teaching status, and market competition with hospital inefficiency. We apply the robust data envelopment analysis approach to a sample of private (both not-for-profit and for-profit) hospitals operating in the United States. Our data envelopment analysis model includes mortality and readmission rates as bad outputs and admissions, surgeries, emergency room, and other visits as good outputs. Therefore, our measurement of hospital inefficiency accounts for quality. We then use a subsampling regression analysis to determine the predictors of hospital inefficiency. For-profit, fully integrated and teaching hospitals were more efficient than their counterparts. Also hospitals located in more competitive markets were more efficient than those located in less competitive markets. Incorporating quality in the measurement of hospital efficiency is key for producing valid efficiency scores. Hospitals in less competitive markets need to improve their efficiency levels. Moreover, high levels of hospital physician integration might be instrumental in ensuring that hospitals achieve their efficiency goals