Exploring decision-makers' challenges and strategies when selecting multiple systematic reviews: insights for AI decision support tools in healthcare.
cross-sectional studies
decision making
implementation science
natural language processing
quality in health care
systematic review
Journal
BMJ open
ISSN: 2044-6055
Titre abrégé: BMJ Open
Pays: England
ID NLM: 101552874
Informations de publication
Date de publication:
05 Jul 2024
05 Jul 2024
Historique:
medline:
6
7
2024
pubmed:
6
7
2024
entrez:
5
7
2024
Statut:
epublish
Résumé
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. 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. 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. 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.
Sections du résumé
BACKGROUND
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
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
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
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.
Identifiants
pubmed: 38969371
pii: bmjopen-2024-084124
doi: 10.1136/bmjopen-2024-084124
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e084124Informations de copyright
© 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.
Déclaration de conflit d'intérêts
Competing interests: None declared.