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Knowledge Mapping of Multicriteria Decision Analysis in Healthcare: A Bibliometric Analysis

OBJECTIVE: Multicriteria decision analysis (MCDA) is a useful tool in complex decision-making situations, and has been used in medical fields to evaluate treatment options and drug selection. This study aims to provide valuable insights into MCDA in healthcare through examining the research focus of...

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Detalles Bibliográficos
Autores principales: Dai, Zeqi, Xu, Simin, Wu, Xue, Hu, Ruixue, Li, Huimin, He, Haoqiang, Hu, Jing, Liao, Xing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9218106/
https://www.ncbi.nlm.nih.gov/pubmed/35757629
http://dx.doi.org/10.3389/fpubh.2022.895552
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author Dai, Zeqi
Xu, Simin
Wu, Xue
Hu, Ruixue
Li, Huimin
He, Haoqiang
Hu, Jing
Liao, Xing
author_facet Dai, Zeqi
Xu, Simin
Wu, Xue
Hu, Ruixue
Li, Huimin
He, Haoqiang
Hu, Jing
Liao, Xing
author_sort Dai, Zeqi
collection PubMed
description OBJECTIVE: Multicriteria decision analysis (MCDA) is a useful tool in complex decision-making situations, and has been used in medical fields to evaluate treatment options and drug selection. This study aims to provide valuable insights into MCDA in healthcare through examining the research focus of existing studies, major fields, major applications, most productive authors and countries, and most common journals in the domain. METHODS: A bibliometric analysis was conducted on the publication related to MCDA in healthcare from the Web of Science Core Collection (WoSCC) database on 14 July 2021. Three bibliometric software (VOSviewer, R-bibliometrix, and CiteSpace) were used to conduct the analysis including years, countries, institutes, authors, journals, co-citation references, and keywords. RESULTS: A total of 410 publications were identified with an average yearly growth rate of 32% (1999–2021), from 196 academic journals with 23,637 co-citation references by 871 institutions from 70 countries/regions. The United States was the most productive country (n = 80). Universiti Pendidikan Sultan Idris (n = 16), Université de Montréal (n = 13), and Syreon Research Institute (n = 12) were the top productive institutions. A A Zaidan, Mireille Goetghebeur and Zoltan Kalo were the biggest nodes in every cluster of authors' networks. The top journals in terms of the number of articles (n = 17) and citations (n = 1,673) were Value in Health and Journal of Medical Systems, respectively. The extant literature has focused on four aspects, including the analytic hierarchy process (AHP), decision-making, health technology assessment, and healthcare waste management. COVID-19 and fuzzy TOPSIS received careful attention from MCDA applications recently. MCDA in big data, telemedicine, TOPSIS, and fuzzy AHP is well-developed and an important theme, which may be the trend in future research. CONCLUSION: This study uncovers a holistic picture of the performance of MCDA-related literature published in healthcare. MCDA has a broad application on different topics and would be helpful for practitioners, researchers, and decision-makers working in healthcare to advance the wheel of medical complex decision-making. It can be argued that the door is still open for improving the role of MCDA in healthcare, whether in its methodology (e.g., fuzzy TOPSIS) or application (e.g., telemedicine).
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spelling pubmed-92181062022-06-24 Knowledge Mapping of Multicriteria Decision Analysis in Healthcare: A Bibliometric Analysis Dai, Zeqi Xu, Simin Wu, Xue Hu, Ruixue Li, Huimin He, Haoqiang Hu, Jing Liao, Xing Front Public Health Public Health OBJECTIVE: Multicriteria decision analysis (MCDA) is a useful tool in complex decision-making situations, and has been used in medical fields to evaluate treatment options and drug selection. This study aims to provide valuable insights into MCDA in healthcare through examining the research focus of existing studies, major fields, major applications, most productive authors and countries, and most common journals in the domain. METHODS: A bibliometric analysis was conducted on the publication related to MCDA in healthcare from the Web of Science Core Collection (WoSCC) database on 14 July 2021. Three bibliometric software (VOSviewer, R-bibliometrix, and CiteSpace) were used to conduct the analysis including years, countries, institutes, authors, journals, co-citation references, and keywords. RESULTS: A total of 410 publications were identified with an average yearly growth rate of 32% (1999–2021), from 196 academic journals with 23,637 co-citation references by 871 institutions from 70 countries/regions. The United States was the most productive country (n = 80). Universiti Pendidikan Sultan Idris (n = 16), Université de Montréal (n = 13), and Syreon Research Institute (n = 12) were the top productive institutions. A A Zaidan, Mireille Goetghebeur and Zoltan Kalo were the biggest nodes in every cluster of authors' networks. The top journals in terms of the number of articles (n = 17) and citations (n = 1,673) were Value in Health and Journal of Medical Systems, respectively. The extant literature has focused on four aspects, including the analytic hierarchy process (AHP), decision-making, health technology assessment, and healthcare waste management. COVID-19 and fuzzy TOPSIS received careful attention from MCDA applications recently. MCDA in big data, telemedicine, TOPSIS, and fuzzy AHP is well-developed and an important theme, which may be the trend in future research. CONCLUSION: This study uncovers a holistic picture of the performance of MCDA-related literature published in healthcare. MCDA has a broad application on different topics and would be helpful for practitioners, researchers, and decision-makers working in healthcare to advance the wheel of medical complex decision-making. It can be argued that the door is still open for improving the role of MCDA in healthcare, whether in its methodology (e.g., fuzzy TOPSIS) or application (e.g., telemedicine). Frontiers Media S.A. 2022-06-09 /pmc/articles/PMC9218106/ /pubmed/35757629 http://dx.doi.org/10.3389/fpubh.2022.895552 Text en Copyright © 2022 Dai, Xu, Wu, Hu, Li, He, Hu and Liao. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Public Health
Dai, Zeqi
Xu, Simin
Wu, Xue
Hu, Ruixue
Li, Huimin
He, Haoqiang
Hu, Jing
Liao, Xing
Knowledge Mapping of Multicriteria Decision Analysis in Healthcare: A Bibliometric Analysis
title Knowledge Mapping of Multicriteria Decision Analysis in Healthcare: A Bibliometric Analysis
title_full Knowledge Mapping of Multicriteria Decision Analysis in Healthcare: A Bibliometric Analysis
title_fullStr Knowledge Mapping of Multicriteria Decision Analysis in Healthcare: A Bibliometric Analysis
title_full_unstemmed Knowledge Mapping of Multicriteria Decision Analysis in Healthcare: A Bibliometric Analysis
title_short Knowledge Mapping of Multicriteria Decision Analysis in Healthcare: A Bibliometric Analysis
title_sort knowledge mapping of multicriteria decision analysis in healthcare: a bibliometric analysis
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9218106/
https://www.ncbi.nlm.nih.gov/pubmed/35757629
http://dx.doi.org/10.3389/fpubh.2022.895552
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