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A hybrid multiple-criteria decision portfolio with the resource constraints model of a smart healthcare management system for public medical centers

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  • Yang, Chih-Hao
  • Hsu, Wei
  • Wu, Yong-Lin

Abstract

A Smart Healthcare Management System (SHMS) is an intelligent technology integration practice for public medical centers. During the implementation of the SHMS, information on strategy and decision-making problems play an important role in smart hospital development, which directly affects the effective workflow of the hospital operation and the service quality of patient care. Existing literature has explored the main factors for evaluation the SHMS, but a qualitative and quantitative analysis is rarely mentioned. To address the research gap, this study proposes a hybrid exploratory three-phased Multi-criteria Decision-making (MCDM) model that combines the Decision-Making Trial and Evaluation Laboratory Model (DEMATEL) approach, the Analytic Network Process (ANP), and Zero-One Goal Programming (ZOGP) for evaluating SHMS portfolios in a resource-limited environment. The results indicate that the Financial Subsidy Policy is the most important determinant for SHMS development, while the Medical Data Informational System (MDIS) and Medical Device and Drug Management System (MDMS) are the optimal SHMS portfolios that satisfy the goal of strategy weights and limited resources. The proposed hybrid decision model can improve the reliability of SHMS portfolios.

Suggested Citation

  • Yang, Chih-Hao & Hsu, Wei & Wu, Yong-Lin, 2022. "A hybrid multiple-criteria decision portfolio with the resource constraints model of a smart healthcare management system for public medical centers," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    • Handle: RePEc:eee:soceps:v:80:y:2022:i:c:s0038012121000653
    DOI: 10.1016/j.seps.2021.101073
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    1. Zhao, Meng & Wang, Yajun & Zhang, Xueyi & Xu, Chang, 2023. "Online doctor-patient dynamic stable matching model based on regret theory under incomplete information," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).

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