Evaluation of an Artificial Intelligence and Online Psychotherapy Initiative to Improve Access and Efficiency in an Ambulatory Psychiatric Setting: Évaluation d'une initiative de psychothérapie en ligne basée sur l'intelligence artificielle visant à améliorer l'accès et l'efficacité en milieu psychiatrique ambulatoire.

Journal: Canadian journal of psychiatry. Revue canadienne de psychiatrie
Published Date: Aug 1, 2025

Abstract

ObjectivesThis study aimed to implement an artificial intelligence-assisted psychiatric triage program, assessing its impact on efficiency and resource optimization.MethodsThis project recruited patients on the waitlist for psychiatric evaluation at an outpatient hospital. Participants ( = 101) completed a digital triage module that used natural language processing and machine learning to recommend a care intensity level and a disorder-specific digital psychotherapy program. A psychiatrist also assessed the same information, and the decisions for care intensity and psychotherapy programs were compared with the artificial intelligence recommendations.ResultsThe overall wait time to receive care decreased by 71.43% due to this initiative. Additionally, participants received psychological care within three weeks after completing the triage module. In 71.29% of the cases, the artificial intelligence-assisted triage program and the psychiatrist suggested the same treatment intensity and psychotherapy program. Additionally, 63.29% of participants allocated to lower-intensity treatment plans by the AI-assisted triage program did not require psychiatric consultation later.ConclusionsUsing artificial intelligence to expedite psychiatric triaging is a promising solution to address long wait times for mental health care. With future accuracy refinements, this could be a valuable tool to implement in hospital settings to assist care teams and improve mental health care. This could result in increased care capacity and improved workflow and decision-making.

Authors

  • Callum Stephenson
    Department of Psychiatry, Faculty of Health Sciences, Queen's University, Kingston, ON, Canada.
  • Jazmin Eadie
    Department of Psychiatry, Faculty of Health Sciences, Queen's University, Kingston, ON, Canada.
  • Christina Holmes
    Department of Psychiatry, Queen's University, Kingston, ON, Canada.
  • Kimia Asadpour
    Department of Psychiatry, Queen's University, Kingston, ON, Canada.
  • Gilmar Gutierrez
    Department of Psychiatry, Faculty of Health Sciences, Queen's University, Kingston, ON, Canada.
  • Anchan Kumar
    Department of Psychiatry, Faculty of Health Sciences, Queen's University, Kingston, ON, Canada.
  • Jasleen Jagayat
    Department of Psychiatry, Faculty of Health Sciences, Queen's University, Kingston, ON, Canada.
  • Charmy Patel
    Department of Psychiatry, Faculty of Health Sciences, Queen's University, Kingston, ON, Canada.
  • Saad Sajid
    Department of Psychiatry, Queen's University, Kingston, ON, Canada.
  • Oleksandr Knyahnytskyi
    Centre for Neuroscience Studies, Queen's University, Kingston, ON, Canada.
  • Megan Yang
    Department of Psychiatry, Faculty of Health Sciences, Queen's University, Kingston, ON, Canada.
  • Taras Reshetukha
    Department of Psychiatry, Queen's University, Kingston, ON, Canada.
  • Christina Moi
    Department of Psychiatry, Queen's University, Kingston, ON, Canada.
  • Tricia Barrett
    Kingston Health Sciences Centre, Kingston, ON, Canada.
  • Amirhossein Shirazi
    OPTT Inc., Toronto, ON, Canada.
  • Vedat Verter
    Smith School of Business, Queen's University, Kingston, ON, Canada.
  • Claudio N Soares
    Department of Psychiatry, Queen's University School of Medicine, Kingston, ON, Canada.
  • Mohsen Omrani
    Department of Psychiatry, Faculty of Health Sciences, Queen's University, Kingston, ON, Canada.
  • Nazanin Alavi
    Department of Psychiatry, Faculty of Health Sciences, Queen's University, Kingston, ON, Canada.

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