Service quality and cost efficiency: Some empirical investigations in the U.S. healthcare industry

All service organizations must recognize critical factors that drive their service quality. In addition, understanding the association between cost and quality is a crucial issue as quality very often is affected when organizations respond to mounting competitive pressures to reduce costs. In a service context such as hospitals, the importance of such understandings becomes inescapable, because hospital services literally involve matters of life and death. This dissertation investigates critical drivers of quality performance and the relationship between quality performance and cost performance in the U.S. healthcare industry, using a cross-sectional data set featuring more than 2,000 hospitals.;Part 1 of this dissertation provides an empirical investigation of two quality drivers in healthcare settings by examining the relationships between patient volume, teaching mission, and process quality in U.S. hospitals. We develop a model that accurately assesses the impact of patient volume and teaching status on quality and propose that the impact of patient volume on process quality varies across hospitals with different teaching intensities. Our results suggest that, as hospital teaching intensity increases, greater patient volume is associated with decreased process quality.;In Part 2, we delve into the association between hospital costs and quality. We hypothesize that distinct quality dimensions (i.e., outcome quality vs. process quality) are associated with efficiency and costs in different ways. We propose a framework that links the quality of the outcome with explained costs (i.e., efficiently delivered costs) and the quality of the process with cost inefficiency. We empirically test our framework using Stochastic Frontier Analysis. Our key insight is that high quality care is more effective in bringing costs down than low quality care.;Finally, Part 3 compares the cost efficiency estimates obtained in Part 2 (using Stochastic Frontier Analysis) with those derived from a traditional technique for evaluating hospital efficiency, namely the Observed to Expected Costs ratio. Our analysis reveals a certain level of agreements between these two methods, but particular types of hospitals might benefit from the use of a specific technique and thus cautions against the use of one technique in isolation.