Inclusion of Clinicians in the Development and Evaluation of Clinical Artificial Intelligence Tools: A Systematic Literature Review

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dc.contributor.authorJesso, Stephanie Tulken
dc.contributor.authorKelliher, Aislingen
dc.contributor.authorSanghavi, Harshen
dc.contributor.authorMartin, Thomasen
dc.contributor.authorParker, Sarah H.en
dc.date.accessioned2023-04-18T17:54:52Zen
dc.date.available2023-04-18T17:54:52Zen
dc.date.issued2022-04-07en
dc.description.abstractThe application of machine learning (ML) and artificial intelligence (AI) in healthcare domains has received much attention in recent years, yet significant questions remain about how these new tools integrate into frontline user workflow, and how their design will impact implementation. Lack of acceptance among clinicians is a major barrier to the translation of healthcare innovations into clinical practice. In this systematic review, we examine when and how clinicians are consulted about their needs and desires for clinical AI tools. Forty-five articles met criteria for inclusion, of which 24 were considered design studies. The design studies used a variety of methods to solicit and gather user feedback, with interviews, surveys, and user evaluations. Our findings show that tool designers consult clinicians at various but inconsistent points during the design process, and most typically at later stages in the design cycle (82%, 19/24 design studies). We also observed a smaller amount of studies adopting a human-centered approach and where clinician input was solicited throughout the design process (22%, 5/24). A third (15/45) of all studies reported on clinician trust in clinical AI algorithms and tools. The surveyed articles did not universally report validation against the “gold standard” of clinical expertise or provide detailed descriptions of the algorithms or computational methods used in their work. To realize the full potential of AI tools within healthcare settings, our review suggests there are opportunities to more thoroughly integrate frontline users’ needs and feedback in the design process.en
dc.description.versionPublished versionen
dc.format.extent13 pagesen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationTulk Jesso S, Kelliher A, Sanghavi H, Martin T and Henrickson Parker S (2022) Inclusion of Clinicians in the Development and Evaluation of Clinical Artificial Intelligence Tools: A Systematic Literature Review. Front. Psychol. 13:830345. doi: 10.3389/fpsyg.2022.830345en
dc.identifier.doihttps://doi.org/10.3389/fpsyg.2022.830345en
dc.identifier.urihttp://hdl.handle.net/10919/114550en
dc.identifier.volume13en
dc.language.isoenen
dc.publisherFrontiersen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectartificial intelligence (AI)en
dc.subjectclinical AIen
dc.subjectmachine learningen
dc.subjectclinicianen
dc.subjecthuman-centered designen
dc.subjectevaluationen
dc.subjecthealthcareen
dc.titleInclusion of Clinicians in the Development and Evaluation of Clinical Artificial Intelligence Tools: A Systematic Literature Reviewen
dc.title.serialFrontiers in Psychologyen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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