Two-Stage Data Envelopment Analysis in Healthcare: Concerns, Controversies, and Future Directions

Mehtap Çakmak Barsbay

Chapter 6 in Handbook on Data Envelopment Analysis in Business, Finance, and Sustainability:Recent Trends and Developments, 2024, pp 193-219 from World Scientific Publishing Co. Pte. Ltd.

Abstract: Data envelopment analysis (DEA) is the most widely used non-parametric method in healthcare operation management to measure technical, productive, and allocative efficiency. As healthcare is characterized by complex production processes, we need some other subsequent techniques. Thus, integrated with DEA models, additional estimation procedures have been applied to evaluate efficiency. Although the literature on DEA is prevalent, there exists a lack of evidence in the studies using two-stage DEA in healthcare efficiency analysis. This chapter aims to review publications about two-stage DEA, which is a specific variation of conventional DEA, and to explore how two-stage DEA procedures are prevalent in healthcare. Investigating the state of the art of two-stage DEA models can add value for researchers who plan to conduct research using DEA. This chapter offers a rapid review and bibliometric analysis to explore publications regarding the relevant topic. The number of publications reached a peak in 2021. Review articles focused on various healthcare specialties. Seventeen articles were related to hospitals and healthcare centers, and tobit regression remained the primary choice of analysis for the dependent variable in 11 articles. It was widely used across various units, such as health regions, health systems, and patient-level treatment. Some concerns and controversies were addressed to improve validation and prove practical usefulness.

Keywords: Data Envelopment Analysis; Business; Finance; Banking; Accounting; Sustainability; Efficiency; Performance; Productivity; Total Factor Productivity; Frontier Analysis (search for similar items in EconPapers)
JEL-codes: C44 C5 (search for similar items in EconPapers)
Date: 2024
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