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A chance-constrained network DEA approach for evaluating medical service and quality efficiency: a case study of Taiwan

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Listed:
  • Shiu-Wan Hung

    (National Central University)

  • Kai-Chu Yang

    (National Central University)

  • Wen-Min Lu

    (Chinese Culture University)

  • Minh-Hieu Le

    (Ho Chi Minh University of Banking)

Abstract

Healthcare efficiency is a critical concern for medical institutions, particularly in balancing service delivery and quality outcomes. This study aims to estimate the medical service efficiency (MSE) and medical quality efficiency (MQE) of 21 county-level and city-level medical institutions in Taiwan over the period from 2015 to 2019. We introduce a novel chance-constrained network Data Envelopment Analysis (DEA) model that integrates the advantages of the range directional measure (RDM), directional distance function (DDF), and enhanced Russell efficiency measure (ERM) to evaluate these efficiencies. Our findings reveal that non-metropolitan areas outperform metropolitan areas in MSE, while metropolitan areas excel in MQE. Furthermore, a truncated regression model is employed to identify the factors influencing MSE and MQE. The results indicate that the number of labor force and county or city attributes significantly negatively impact MSE, whereas these factors positively influence MQE. This study provides targeted optimization suggestions for medical institutions aiming to improve their operational and quality efficiencies.

Suggested Citation

  • Shiu-Wan Hung & Kai-Chu Yang & Wen-Min Lu & Minh-Hieu Le, 2025. "A chance-constrained network DEA approach for evaluating medical service and quality efficiency: a case study of Taiwan," Health Care Management Science, Springer, vol. 28(1), pages 99-118, March.
  • Handle: RePEc:kap:hcarem:v:28:y:2025:i:1:d:10.1007_s10729-025-09700-2
    DOI: 10.1007/s10729-025-09700-2
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