Benrimoh David, Tanguay-Sela Myriam, Perlman Kelly, Israel Sonia, Mehltretter Joseph, Armstrong Caitrin, Fratila Robert, Parikh Sagar V, Karp Jordan F, Heller Katherine, Vahia Ipsit V, Blumberger Daniel M, Karama Sherif, Vigod Simone N, Myhr Gail, Martins Ruben, Rollins Colleen, Popescu Christina, Lundrigan Eryn, Snook Emily, Wakid Marina, Williams Jérôme, Soufi Ghassen, Perez Tamara, Tunteng Jingla-Fri, Rosenfeld Katherine, Miresco Marc, Turecki Gustavo, Gomez Cardona Liliana, Linnaranta Outi, Margolese Howard C
Department of Psychiatry, McGill University, Canada; Aifred Heath Inc., Montreal, Canada; and Faculty of Medicine, McGill University, Canada.
Montreal Neurological Institute, McGill University, Canada; and Aifred Health Inc., Montreal, Canada.
BJPsych Open. 2021 Jan 6;7(1):e22. doi: 10.1192/bjo.2020.127.
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.
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.
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.
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.
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.
最近，人工智能驱动的设备已被提出作为改善精神卫生保健的潜在有力工具。一个重要的问题是这些设备如何影响医患互动。
Aifred是一种用于治疗重度抑郁症的人工智能驱动的临床决策支持系统（CDSS）。在此，我们探讨使用模拟中心环境来评估Aifred的可用性，特别是其对医患互动的影响。
招募了20名精神科和家庭医学主治医师及住院医师，在临床互动模拟中心与标准化患者完成一项2.5小时的研究。每位医生可以选择在三个10分钟的临床场景中使用CDSS来指导他们的治疗选择，这些场景中有标准化患者分别表现出轻度、中度和重度重度抑郁发作。通过自我报告问卷、场景观察、访谈和标准化患者反馈收集可行性和可接受性数据。
所有20名参与者均完成了研究。初步结果表明，该工具为临床医生所接受，并且在临床会诊期间使用是可行的。临床医生表示愿意在实际临床实践中使用该工具，对系统预测辅助治疗选择有高度信任，并报告该工具有助于增加患者对治疗的理解和信任。模拟环境有助于评估该工具对医患互动的影响。
模拟中心能够在临床研究之前直接观察临床医生对该工具地使用情况及其对医患互动的影响。因此，它可能为新技术工具的早期测试提供一个有用且重要的环境。目前的结果将为进一步的工具开发和临床医生培训材料提供参考。
