Using nonparametric conditional approach to integrate quality into efficiency analysis: Empirical evidence from cardiology departments

In the past decades, hospitals have been facing pressure to increase the efficiency of resource allocation. One way to achieve higher levels of technical efficiency is to treat more patients with the same amount of personnel, which could potentially lead to a trade-off between improving efficiency and maintaining good patient service. The aim of this study is to demonstrate how the nonparametric conditional approach can be used to integrate quality into the analysis of efficiency. The conditional approach allows investigating the mechanism through which quality enters the production process. Generally, an external variable may enter the production process by affecting either the attainable frontier or the distribution of inefficiencies inside the production set. To account for the heterogeneity of hospital services, we focus on a hospital department as the unit of analysis. We use data from 178 departments of interventional cardiology and consider three different measures of quality: patient satisfaction, risk-adjusted mortality, and patient radiation exposure. Our empirical assessment shows that the impact of quality on the production process differs according to the utilized quality measure. Patient satisfaction does not affect the attainable frontier but does have an inverted U-shaped effect on the distribution of inefficiencies; risk-adjusted mortality negatively impacts the attainable frontier at high values of mortality but does not impact the distribution of inefficiencies; and patient radiation exposure is not associated with the production process. Our results refute the existence of a clear trade-off between efficiency and quality. The conditional approach can be applied to deal with the complexity of the underlying relationships between efficiency and quality.