Evaluating the Perceived Utility of an Artificial Intelligence-Powered Clinical Decision Support System for Depression Treatment Using a Simulation Centre

Author:

Tanguay-Sela Myriam,Benrimoh David,Popescu Christina,Perez Tamara,Rollins Colleen,Snook Emily,Lundrigan Eryn,Armstrong Caitrin,Perlman Kelly,Fratila Robert,Mehltretter Joseph,Israel Sonia,Champagne Monique,Williams Jérôme,Simard Jade,Parikh Sagar V.,Karp Jordan F.,Heller Katherine,Linnaranta Outi,Cardona Liliana Gomez,Turecki Gustavo,Margolese Howard

Abstract

AbstractAifred is a clinical decision support system (CDSS) that uses artificial intelligence to assist physicians in selecting treatments for major depressive disorder (MDD) by providing probabilities of remission for different treatment options based on patient characteristics. We evaluated the utility of the CDSS as perceived by physicians participating in simulated clinical interactions. Twenty psychiatry and family medicine staff and residents completed a study in which each physician had three 10-minute clinical interactions with standardized patients portraying mild, moderate, and severe episodes of MDD. During these scenarios, physicians were given access to the CDSS, which they could use in their treatment decisions. The perceived utility of the CDSS was assessed through self-report questionnaires, scenario observations, and interviews. 60% of physicians perceived the CDSS to be a useful tool in their treatment-selection process, with family physicians perceiving the greatest utility. Moreover, 50% of physicians would use the tool for all patients with depression, with an additional 35% noting they would reserve the tool for more severe or treatment-resistant patients. Furthermore, clinicians found the tool to be useful in discussing treatment options with patients. The efficacy of this CDSS and its potential to improve treatment outcomes must be further evaluated in clinical trials.

Publisher

Cold Spring Harbor Laboratory

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