ABSTRACT
IntroductionMulti-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. We aimed to provide valuable insights on the use of MCDA in health care through examining the research focus of existing studies, major fields, major applications, most productive authors and countries, and most common journals in the domain using a scientometric and bibliometric analysis.MethodsPublications related to MCDA in health care were identified by searching the Web of Science Core Collection on 14 July 2021. Three bibliometric software programs (VOSviewer, Bibliometrix, and CiteSpace) were used to conduct the analysis.ResultsA total of 410 publications were identified from 196 academic journals (average yearly growth rate of 32% from 1999 to 2021), with 23,637 co-cited references by 871 institutions from 70 countries or regions. The USA was the most productive country (n=80), while the Universiti Pendidikan Sultan Idris (n=16), Université de Montréal (n= 13), and Syreon Research Institute (n=12) were the most productive institutions. The biggest nodes in every cluster of author networks were Aos Alaa Zaidan, Mireille Goetghebeur, and Zoltan Kalo. The top journals in terms of number of articles (n=17) and citations (n=1,673) were Value in Health and the Journal of Medical Systems, respectively. The research hotspots mainly included the analytic hierarchy process (AHP), decision-making, health technology assessment, and healthcare waste management. In the recent literature there was more emphasis on coronavirus disease 2019 (COVID-19) and fuzzy Technique for Order Preference by Similarities to Ideal Solution (TOPSIS). Big data, telemedicine, TOPSIS, and the fuzzy AHP, which are well-developed and important themes, may be the trends in future research.ConclusionsThis study provides a holistic picture of the MCDA-related literature published in health care. MCDA has a broad application in different topic areas and would be helpful for practitioners, researchers, and decision makers working in health care when faced with complex decisions. It can be argued that the door is still open for improving the role of MCDA in health care, both in its technologies and its application.
ABSTRACT
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).
Subject(s)
COVID-19 , Bibliometrics , Decision Support Techniques , Delivery of Health Care , Humans , Technology Assessment, Biomedical , United StatesABSTRACT
Introduction: Until now, there is no clinically approved specific medicine to treat COVID-19. Prior systematic reviews (SRs) have shown that traditional Chinese medicine (TCM) reduces the number of patients with severe disease and time to fever clearance, promotes clinical effectiveness, and improves chest images and the negativity rate of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleic acid test. Few SRs arrived at a definitive conclusion, and more randomized controlled trials (RCTs) were published. We conducted this study to summarize the latest evidence of TCM in COVID-19. Methods: Eight online databases were searched from December 2019 to July 2020, updated to March 2021. Only RCTs evaluating the clinical efficacy and safety of TCM in the treatment of COVID-19 were included. Primary outcomes were clinical cure and the negativity of the SARS-CoV-2 nucleic acid test. Secondary outcomes included clinical deterioration, ARDS, mechanical ventilation, death, time to fever clearance, duration of hospitalization, and chest imaging improvement. Safety outcomes included adverse events and serious adverse events during treatment. Two reviewers selected the included articles, assessed the risk of bias, and extracted data independently and in duplicate. Results: A total of 25 RCTs involving 2222 participants were selected in the systematic review, and seven RCTs were included in the meta-analysis. The results showed that TCM plus routine treatment was significantly better than routine treatment alone in clinical cure (risk ratio [RR] = 1.20, 95% confidence interval (CI) [1.04, 1.38], P = 0.01) and chest image improvement (RR = 1.22, 95% CI [1.07, 1.39], P = 0.01) and could reduce clinical deterioration (RR = 0.39, 95% CI [0.18, 0.86], P = 0.02), ARDS (RR = 0.28, 95% CI [0.11, 0.69], P = 0.01), mechanical ventilation (RR = 0.30, 95% CI [0.12, 0.77], P = 0.01), or death rate (RR = 0.28, 95% CI [0.09, 0.84], P = 0.02). No significant difference between TCM and routine treatment in the negativity of SARS-CoV-2 nucleic acid test (RR = 1.08, 95% CI [0.94, 1.23], P = 0.29) was observed. Finally, there was no overall significant difference in the incidence of adverse events between the two groups. The summary of evidence showed moderate confidence of a benefit of 11.8% in clinical cure and 14.0% in chest image improvement and a reduction of 5.9% in clinical deterioration, 25.4% in ARDS, 18.3% in mechanical ventilation, and 4.5% in death with TCM plus routine treatment compared to routine treatment alone in patients with COVID-19. A low confidence of a benefit of 5.4% in the negativity of SARS-CoV-2 nucleic acid test was also observed. Conclusions: Synethized evidence of 21 outcomes in 8 RCTs showed moderate certainty that TCM treatment plus routine treatment may promote a clinical cure and chest image improvement compared to routine treatment alone while reducing clinical deterioration, development of ARDS, use of mechanical ventilation, and death in patients with COVID-19. TCM treatment plus routine treatment may not promote the negativity of the SARS-CoV-2 nucleic acid test compared to routine treatment alone. TCM treatment was found to be safe for patients with COVID-19.