Artificial Intelligence Search Tools for Evidence Synthesis: Comparative Analysis and Implementation Recommendations

To inform implementation recommendations for novel or emerging technologies, Research Information Services at Canada's Drug Agency conducted a multimodal research project involving a literature review, a retrospective comparative analysis, and a focus group on 3 Artificial Intelligence (AI) or automation tools for information retrieval (AI search tools): Lens.org, SpiderCite, and Microsoft Copilot. For the comparative analysis, the customary information retrieval practices used at Canada's Drug Agency served as our reference standard for comparison, and we used the eligible studies of 7 completed projects to measure tool performance. For searches conducted with our usual practice approaches and with each of the 3 tools, we calculated sensitivity/recall, number needed to read (NNR), time to search and screen, unique contributions, and the likely impact of the unique contributions on the projects' findings. Our investigation confirmed that AI search tools have inconsistent and variable performance for the range of information retrieval tasks performed at Canada's Drug Agency. Implementation recommendations from this study informed a "fit for purpose" approach where Information Specialists leverage AI search tools for specific tasks or project types.

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Publication Details

Journal
Cochrane Evidence Synthesis and Methods
Published
2025-09-01
DOI
https://doi.org/10.1002/cesm.70045
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial Intelligence Search Tools for Evidence Synthesis: Comparative Analysis and Implementation Recommendations

Hannah Loshak, Danielle MacDougall, Robin Featherstone, Sharon Bailey et al.
Cochrane Evidence Synthesis and Methods
Artificial Intelligence in Healthcare and Education
article

Artificial Intelligence Search Tools for Evidence Synthesis: Comparative Analysis and Implementation Recommendations

Hannah Loshak, Danielle MacDougall, Robin Featherstone, Sharon Bailey, Caitlyn Ford, Robyn Butcher, David Kaunelis, Melissa Walter, Eric Morenz
article en

Abstract

To inform implementation recommendations for novel or emerging technologies, Research Information Services at Canada's Drug Agency conducted a multimodal research project involving a literature review, a retrospective comparative analysis, and a focus group on 3 Artificial Intelligence (AI) or automation tools for information retrieval (AI search tools): Lens.org, SpiderCite, and Microsoft Copilot. For the comparative analysis, the customary information retrieval practices used at Canada's Drug Agency served as our reference standard for comparison, and we used the eligible studies of 7 completed projects to measure tool performance. For searches conducted with our usual practice approaches and with each of the 3 tools, we calculated sensitivity/recall, number needed to read (NNR), time to search and screen, unique contributions, and the likely impact of the unique contributions on the projects' findings. Our investigation confirmed that AI search tools have inconsistent and variable performance for the range of information retrieval tasks performed at Canada's Drug Agency. Implementation recommendations from this study informed a "fit for purpose" approach where Information Specialists leverage AI search tools for specific tasks or project types.

Cochrane Evidence Synthesis and MethodsVol. 3(5)
Canadian Agency for Drugs and Technologies in Health (CA), Public Health Agency of Canada (CA)
Openalex Percentile: Top 82%
Artificial Intelligence in Healthcare and Education
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Artificial Intelligence Search Tools for Evidence Synthesis: Comparative Analysis and Implementation Recommendations — Hannah Loshak, Danielle MacDougall, et al. · Cochrane Evidence Synthesis and Methods (2025) | TGRS Research Map | TGRS