Incorporating artificial intelligence in medical diagnosis: A case for an invisible and (un)disruptive approach

Matt Sibbald*, Laura Zwaan, Yusuf Yilmaz, Sarrah Lal

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

10 Citations (Scopus)

Abstract

As big data becomes more publicly accessible, artificial intelligence (AI) is increasingly available and applicable to problems around clinical decision-making. Yet the adoption of AI technology in healthcare lags well behind other industries. The gap between what technology could do, and what technology is actually being used for is rapidly widening. While many solutions are proposed to address this gap, clinician resistance to the adoption of AI remains high. To aid with change, we propose facilitating clinician decisions through technology by seamlessly weaving what we call ‘invisible AI’ into existing clinician workflows, rather than sequencing new steps into clinical processes. We explore evidence from the change management and human factors literature to conceptualize a new approach to AI implementation in health organizations. We discuss challenges and provide recommendations for organizations to employ this strategy.
Original languageEnglish
Pages (from-to)3-8
Number of pages6
JournalJournal of Evaluation in Clinical Practice
Volume30
Issue number1
Early online date27 Jun 2022
DOIs
Publication statusPublished - Feb 2024

Bibliographical note

ACKNOWLEDGEMENT
This paper was written for and presented as a panel discussion at ‘ReThink Clinical Reasoning Conference’. The authors thank Amy Keuhl and Sandra Monteiro for bringing together the team and fostering the development of the central idea behind this paper.

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