Hospital productivity: The role of efficiency drivers

Abstract

Summary 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.

Performance measurement of Brazilian federal university hospitals: an overview of the public health care services through principal component analysis

“…It is worth mentioning that the development of research in the hospital environment depends on the structure and technological resources belonging to a determined unit (Ali et al ., 2019). Thus, the production of knowledge and training of highly qualified residents becomes a complex activity for most units in the five groups analyzed.…”

“…The connection between the analyzed inputs and outputs can help in understanding the performance framework of hospital units. Thus, organizations that present a reduced number of service contracts and, above all, days of hospitalization of patients have greater availability for investments in complementary areas, such as student production and technical-scientific research (Ali et al ., 2019; Upadhyai et al ., 2020). In other words, the less overloaded the units are, there will be a greater propensity in the generation and dissemination of knowledge by areas of specialty (Upadhyai et al ., 2020).…”

“…In the case of the selected set of efficient units considered in this analysis, hospitals 4, 9 and 22 showed good results, mainly due to the reduced number of days of hospitalization, as well as a reasonably acceptable number of residents in training. Even so, these are data that reveal growth potential in all areas of specialty, in order to unblock the service flow of the units and level the standard of services offered (Ali et al ., 2019). This fact can be seen in the other units of this set, which is the case of hospitals 5, 17, 19, 24 and 31.…”

Ranking of Factors Affecting Productivity in Ahvaz Hospitals Using Analytic Network Process (ANP) Technique

“…In addition, organizational productivity is a determining factor for salaries, prices, and other production factors (3). Productivity ratios are used for controlling production processes and comparing the performance of institutions (4).…”