Evaluating hospital performance with plant capacity utilization and machine learning

Malin Song, Wenzhuo Zhou, Arvind Upadhyay and Zhiyang Shen

Journal of Business Research, 2023, vol. 159, issue C

Abstract: This study extends the measurement of plant capacity utilization by incorporating undesirable outputs. We select indicators through feature selection in machine learning and also introduce an undesirable output for assessment in these models. By defining and applying four plant capacity concepts, we analyze plant capacity utilization in health institutions in 31 provinces in China over the last 11 years (2009 to 2019). This paper has two main contributions. First, we propose a refined by-production hospital technology by introducing the mortality rate into the performance evaluation of public hospitals. Second, we expand the measures of plant capacity utilization with undesirable outputs. The preliminary results show that after the introduction of the death rate, the long-run output-oriented plant capacity utilization of medical institutions is significantly impacted. Furthermore, we find a high level of long-run input-oriented plant capacity utilization tends to increase mortality.

Keywords: Plant capacity utilization; Undesirable output; Machine learning; Health care (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:159:y:2023:i:c:s0148296323000450

DOI: 10.1016/j.jbusres.2023.113687

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