A comprehensive and systematic review of multi-criteria decision-making methods and applications in healthcare

多准则决策分析 医疗保健 层次分析法 斯科普斯 管理科学 持续性 计算机科学 知识管理 风险分析(工程) 运筹学 业务 工程类 梅德林 政治学 法学 生态学 生物
作者
Santonab Chakraborty,Santonab Chakraborty,Rakesh D. Raut,T. M. Rofin,Shankar Chakraborty,Shankar Chakraborty
出处
期刊:Healthcare analytics [Elsevier]
卷期号:4: 100232-100232 被引量:91
标识
DOI:10.1016/j.health.2023.100232
摘要

Healthcare decision-making has often been viewed as a complex multi-dimensional problem due to medical, technological, social, ethical, economic, and environmental factors along with multiple and conflicting objectives and the participation of different stakeholders. Several multi-criteria decision-making (MCDM) techniques have been successfully deployed to resolve this issue, providing transparent, consistent, accurate, and timely solutions. This paper reviews 140 journal articles published during 2013-2022 (available in the Scopus database) on MCDM applications in healthcare decision-making. Those articles are subsequently categorized into 11 application areas, i.e., (a) supply chain management, (b) medical device and material selection, (c) disease identification and treatment, (d) healthcare information system, (e) logistics, (f) operations management in healthcare, (g) healthcare quality evaluation, (h) risk management, (i) waste management, (J) COVID-19, and (k) miscellaneous. Their contents are also critically analyzed concerning year-wise, journal-wise, institution-wise, and country-wise publications, authors’ nationality, MCDM techniques employed, other mathematical tools considered for criteria weight measurement and uncertainty modeling, and relation with other keywords. The analysis identifies Waste Management as the most explored area; Computers and Industrial Engineering, Journal of Cleaner Production, and Sustainability as the most popular journals; Shiraz University of Medical Sciences, Iran, as the most contributing university; and India as the most productive country in respect of several authors and co-authors; and analytic hierarchy process as the most popular MCDM tool. It would help healthcare professionals understand how other researchers have efficiently explored the benefits of various MCDM tools in solving healthcare-related decision-making problems.
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