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A Clinical Feasibility Study of an Artificial Intelligence-Powered Clinical Decision Support System
medRxiv - Psychiatry and Clinical Psychology Pub Date : 2021-07-07 , DOI: 10.1101/2021.07.03.21259812
Christina Popescu , Grace Golden , David Benrimoh , Myriam Tanguay-Sela , Dominique Slowey , Eryn Lundrigan , Jérôme Williams , Bennet Desormeau , Divyesh Kardani , Tamara Perez , Colleen Rollins , Sonia Israel , Kelly Perlman , Caitrin Armstrong , Jacob Baxter , Kate Whitmore , Marie-Jeanne Fradette , Kaelan Felcarek-Hope , Ghassen Soufi , Robert Fratila , Joseph Mehltretter , Karl Looper , Warren Steiner , Soham Rej , Jordan F. Karp , Katherine Heller , Sagar V. Parikh , Rebecca McGuire-Snieckus , Manuela Ferrari , Howard Margolese , Gustavo Turecki

Objective: We examine the feasibility of an Artificial Intelligence (AI)-powered clinical decision support system (CDSS), which combines the operationalized 2016 Canadian Network for Mood and Anxiety Treatments guidelines with a neural-network based individualized treatment remission prediction. Methods: Due to COVID-19, the study was adapted to be completed entirely at a distance. Seven physicians recruited outpatients diagnosed with major depressive disorder (MDD) as per DSM-V criteria. Patients completed a minimum of one visit without the CDSS (baseline) and two subsequent visits where the CDSS was used by the physician (visit 1 and 2). The primary outcome of interest was change in session length after CDSS introduction, as a proxy for feasibility. Feasibility and acceptability data were collected through self-report questionnaires and semi-structured interviews. Results: Seventeen patients enrolled in the study; 14 completed. There was no significant difference between appointment length between visits (introduction of the tool did not increase session length). 92.31% of patients and 71.43% of physicians felt that the tool was easy to use. 61.54% of the patients and 71.43% of the physicians rated that they trusted the CDSS. 46.15% of patients felt that the patient-clinician relationship significantly or somewhat improved, while the other 53.85% felt that it did not change. Conclusions: Our results confirm the primary hypothesis that the integration of the tool does not increase appointment length. Findings suggest the CDSS is easy to use and may have some positive effects on the patient-physician relationship. The CDSS is feasible and ready for effectiveness studies.

中文翻译:

人工智能驱动的临床决策支持系统的临床可行性研究

目标:我们研究了人工智能 (AI) 驱动的临床决策支持系统 (CDSS) 的可行性,该系统结合了 2016 年加拿大情绪和焦虑治疗网络指南与基于神经网络的个性化治疗缓解预测。方法:由于 COVID-19,该研究被调整为完全在远处完成。七名医生根据 DSM-V 标准招募了诊断为重度抑郁症 (MDD) 的门诊患者。患者至少完成了一次没有 CDSS 的就诊(基线)和两次随后的医生使用 CDSS 的就诊(就诊 1 和 2)。感兴趣的主要结果是引入 CDSS 后会话长度的变化,作为可行性的代理。通过自我报告问卷和半结构化访谈收集可行性和可接受性数据。结果: 17 名患者参加了研究;14 完成。访问之间的预约长度没有显着差异(该工具的引入没有增加会话长度)。92.31% 的患者和 71.43% 的医生认为该工具易于使用。61.54% 的患者和 71.43% 的医生认为他们信任 CDSS。46.15%的患者认为医患关系显着或有所改善,而另外53.85%的患者认为没有改变。结论:我们的结果证实了该工具的集成不会增加约会时间的主要假设。结果表明 CDSS 易于使用,并且可能对医患关系产生一些积极影响。CDSS 是可行的,可以进行有效性研究。
更新日期:2021-07-08
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