Evaluating the perceived utility of an artificial intelligence-powered clinical decision support system for depression treatment using a simulation center

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

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

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.

Original languageEnglish (US)
Article number114336
JournalPsychiatry research
Volume308
DOIs
StatePublished - Feb 2022

Keywords

  • Artificial intelligence
  • Major depressive disorder
  • Outpatient treatment
  • Patient-Physician Relationship
  • Physician-patient relationship
  • Primary care
  • Simulation center

ASJC Scopus subject areas

  • Psychiatry and Mental health
  • Biological Psychiatry

Fingerprint

Dive into the research topics of 'Evaluating the perceived utility of an artificial intelligence-powered clinical decision support system for depression treatment using a simulation center'. Together they form a unique fingerprint.

Cite this