Exploring decision-makers' challenges and strategies when selecting multiple systematic reviews: insights for AI decision support tools in healthcare.

Autor:	Lunny C; Knowledge Translation Program, Li Ka Shing Knowledge Institute, UBC, Toronto, Ontario, Canada carole.lunny@ubc.ca.; Evidence Synthesis, Precisionheor LLC, Vancouver, British Columbia, Canada., Whitelaw S; Faculty of Medicine and Health Sciences, McGill University, Montreal, Québec, Canada., Reid EK; Department of Pharmacy, Nova Scotia Health Authority, Halifax, Nova Scotia, Canada., Chi Y; Yealth Network, Beijing Health Technology Co., Ltd, Beijing, China., Ferri N; Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy., Zhang JHJ; Anesthesiology, Pharmacology & Therapeutics, The University of British Columbia, Vancouver, British Columbia, Canada., Pieper D; Institute for Health Services and Health System Research, Faculty of Health Sciences Brandenburg, Brandenburg Medical School Theodor Fontane, Neuruppin, Brandenburg, Germany., Kanji S; Department of Pharmacy, Ottawa Hospital, Ottawa, Ontario, Canada.; Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada., Veroniki AA; Li Ka Shing Knowledge Institute of St Michael's Hospital, Knowledge Translation Program, St Michael's Hospital, Toronto, Ontario, Canada.; Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, Ontario, Canada., Shea B; University of Ottawa, Ottawa, Ontario, Canada., Dourka J; Knowledge Translation Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Ontario, Canada., Ardern C; Department of Family Practice, The University of British Columbia-Vancouver Campus, Vancouver, British Columbia, Canada., Pham B; Knowledge Translation Program, Li Ka Shing Knowledge Institute, University of Toronto, Toronto, Ontario, Canada., Bagheri E; Department of Electrical and Computer Engineering, Toronto Metropolitan University, Toronto, Ontario, Canada., Tricco AC; Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, Ontario, Canada.; Knowledge Translation Program, St Michael's Hospital, Toronto, Ontario, Canada.
Jazyk:	angličtina
Zdroj:	BMJ open [BMJ Open] 2024 Jul 05; Vol. 14 (7), pp. e084124. Date of Electronic Publication: 2024 Jul 05.
DOI:	10.1136/bmjopen-2024-084124
Abstrakt:	Background: Systematic reviews (SRs) are being published at an accelerated rate. Decision-makers may struggle with comparing and choosing between multiple SRs on the same topic. We aimed to understand how healthcare decision-makers (eg, practitioners, policymakers, researchers) use SRs to inform decision-making and to explore the potential role of a proposed artificial intelligence (AI) tool to assist in critical appraisal and choosing among SRs. Methods: We developed a survey with 21 open and closed questions. We followed a knowledge translation plan to disseminate the survey through social media and professional networks. Results: Our survey response rate was lower than expected (7.9% of distributed emails). Of the 684 respondents, 58.2% identified as researchers, 37.1% as practitioners, 19.2% as students and 13.5% as policymakers. Respondents frequently sought out SRs (97.1%) as a source of evidence to inform decision-making. They frequently (97.9%) found more than one SR on a given topic of interest to them. Just over half (50.8%) struggled to choose the most trustworthy SR among multiple. These difficulties related to lack of time (55.2%), or difficulties comparing due to varying methodological quality of SRs (54.2%), differences in results and conclusions (49.7%) or variation in the included studies (44.6%). Respondents compared SRs based on the relevance to their question of interest, methodological quality, and recency of the SR search. Most respondents (87.0%) were interested in an AI tool to help appraise and compare SRs. Conclusions: Given the identified barriers of using SR evidence, an AI tool to facilitate comparison of the relevance of SRs, the search and methodological quality, could help users efficiently choose among SRs and make healthcare decisions. Competing Interests: Competing interests: None declared. (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
Databáze:	MEDLINE
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