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TEA-IS: : A hybrid DEA-TOPSIS approach for assessing performance and synergy in Chinese health care

Published: 01 August 2023 Publication History

Abstract

This paper presents an assessment of the Chinese healthcare system in 31 provinces for a 10-year period in light of relevant physical and human resource variables. First, a novel TEA-IS (Trigonometric Envelopment Analysis for Ideal Solutions) model is developed to assess healthcare efficiency at the province level. Machine learning methods are also employed to predict high-low performance and the synergistic Chinese healthcare province in terms of contextual variables. The results indicate that synergy has played a pivotal role in the Chinese healthcare systems, not only by triggering higher performance levels due to the progressive adoption of best practices over the course of time, but also by being closely related to different socioeconomic and demographic variables, such as the illiteracy rate. It is possible to claim that healthcare performance has remained stable in China over the past two decades, performance and synergy at the province level are still heterogeneous.

Highlights

we assess the performance and synergy in Chinese Health Care
a novel Trigonometric Envelopment Analysis for Ideal Solutions model is developed
Machine learning methods are employed to predict high-low performance
synergy has played a pivotal role in the Chinese healthcare systems

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Published In

cover image Decision Support Systems
Decision Support Systems  Volume 171, Issue C
Aug 2023
104 pages

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Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 August 2023

Author Tags

  1. Chinese provinces
  2. Health care
  3. Performance and synergy
  4. Hybrid DEA-TOPSIS
  5. TEA-IS

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