AUTHOR=Dai Zeqi , Xu Simin , Wu Xue , Hu Ruixue , Li Huimin , He Haoqiang , Hu Jing , Liao Xing 

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

JOURNAL=Frontiers in Public Health

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2022.895552

DOI=10.3389/fpubh.2022.895552

ISSN=2296-2565

ABSTRACT=Objective: Multi-criteria 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 of 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 Web of Science Core Collection (WoSCC) database on July 14th 2021. Three bibliometric software (VOSviewer, R-bibliometrix, and CiteSpace) were used to conduct the analysis including years, countries, institutes, authors, journals, co-cited references, and keywords. 
Results: A total of 410 publications were identified with 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 Sates 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 number of articles (n= 17) and citations (n= 1673) were Value in Health and Journal of Medical Systems, respectively. The extant literature has focused on four aspects, including 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 are well-developed and important themes, may be the trends in future research. 
Conclusion: This study uncovers a holistic picture on the performance of MCDA related literatures published in healthcare. MCDA has a broad application on different topics and would be helpful or 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).