Hospital productivity: The role of efficiency drivers.

Abstract

A major feature of health-care systems is substantial variation in hospital productivity. Hospital productivity varies widely across countries. The presence of such variation suggests potential areas for improvement, which can substantially lower health-care costs. This research aims to investigate factors that may explain variations in hospital productivity by constructing a longitudinal data (panel) on English NHS hospital trusts. It also seeks to explore possible interactions among the factors in a data-driven manner. We employ unbiased panel regression tree techniques from the machine-learning literature to explore the complex interactive structure of the data. We next use econometric panel regression to deal with individual hospital effects to identify some of the determinants of hospital productivity. The findings point to the significance of efficiency-enhancing mechanisms for hospital productivity, including measures to reduce the length of stay, increase day case (outpatient) surgery rate, and to minimize errors. Further, such measures are shaped by more fundamental factors such as the availability of human capital and management practices. Our results underscore the importance of within-hospital efficiency-enhancing mechanisms to cost-adjusted hospital productivity. Improving hospital operational processes will enhance productivity. At a deeper level, human capital and management practices are likely to be most critical.