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Using a simulation centre to evaluate preliminary acceptability and impact of an artificial intelligence-powered clinical decision support system for depression treatment on the physician-patient interaction

David Benrimoh, Myriam Tanguay-Sela, Kelly Perlman, Sonia Israel, Joseph Mehltretter, Caitrin Armstrong, Robert Fratila, Sagar V. Parikh, Jordan F. Karp, Katherine Heller, Ipsit V. Vahia, Daniel M. Blumberger, Sherif Karama, Simone N. Vigod, Gail Myhr, Ruben Martins, Colleen Rollins, Christina Popescu, Eryn Lundrigan, Emily Snook, Marina Wakid, Jerome Williams, Ghassen Soufi, Tamara Perez, Jingla-Fri Tunteng, Katherine Rosenfeld, Marc Miresco, Gustavo Turecki, Liliana Gomez Cardona, Outi Linnaranta, Howard C. Margolese

BJPsych open(2021)

Cited 21|Views47
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Abstract
Background Recently, artificial intelligence-powered devices have been put forward as potentially powerful tools for the improvement of mental healthcare. An important question is how these devices impact the physician-patient interaction. Aims Aifred is an artificial intelligence-powered clinical decision support system (CDSS) for the treatment of major depression. Here, we explore the use of a simulation centre environment in evaluating the usability of Aifred, particularly its impact on the physician-patient interaction. Method Twenty psychiatry and family medicine attending staff and residents were recruited to complete a 2.5-h study at a clinical interaction simulation centre with standardised patients. Each physician had the option of using the CDSS to inform their treatment choice in three 10-min clinical scenarios with standardised patients portraying mild, moderate and severe episodes of major depression. Feasibility and acceptability data were collected through self-report questionnaires, scenario observations, interviews and standardised patient feedback. Results All 20 participants completed the study. Initial results indicate that the tool was acceptable to clinicians and feasible for use during clinical encounters. Clinicians indicated a willingness to use the tool in real clinical practice, a significant degree of trust in the system's predictions to assist with treatment selection, and reported that the tool helped increase patient understanding of and trust in treatment. The simulation environment allowed for the evaluation of the tool's impact on the physician-patient interaction. Conclusions The simulation centre allowed for direct observations of clinician use and impact of the tool on the clinician-patient interaction before clinical studies. It may therefore offer a useful and important environment in the early testing of new technological tools. The present results will inform further tool development and clinician training materials.
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Key words
Primary care,out-patient treatment,depressive disorders,artificial intelligence,simulation centre
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