Evaluating the perceived utility of an artificial intelligence-powered clinical decision support system for depression treatment using a simulation center. (February 2022) - 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; et al.
Highlights: The treatment of major depression still relies on trial and error for treatment selection. Novel artificial intelligence models may assist with treatment selection. These models must be tested to ensure clinicians and patients find them useful and acceptable. Here we describe a mixed methods simulation center study of an AI tool and its perceived utility. The tool seems to integrate well into practice and may help enrich clinician-patient interactions. Abstract: Aifred 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 physicians who were either staff or residents in psychiatry or family medicine completed a study in which they 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 that 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.