A Feasibility Study of an AI-Powered Clinical Decision Aid for Personalized Depression Treatment Selection

Depression Clinical Trial

Official title: A Feasibility Study of a Hybrid-Classic/Deep-Learning Enabled Clinical Decision Aid for Personalized and Individualized Pharmacological Depression Treatment Selection

Status Completed

Clinical Trial Summary

The Clinical Decision Aid (CDA) is a predictive model that takes as input individual patient characteristics, called 'features', which are inputted by the physician or by patient self-report, and outputs a list of possible treatments, with each treatment associated with a predicted efficacy (likelihood to achieve response and likelihood to achieve remission, each expressed as a percentage). The treatments, which may include any approved treatment for depression, will be presented to the physician who will then make a treatment choice.

Clinical Trial Description

Hypothesis 1. There will not be a significant difference in measured non-initial intake appointment lengths between the baseline period and the appointment length measured at two and four months after introduction of the study software and CDA. Hypothesis 2. Physicians will not subjectively report that using the CDA and study software increased the length of their appointments. Hypothesis 3. At least 66% of patients and 66% of physicians will rate the trustworthiness of the CDA as a 4 or 5 on a 5 point Likert scale (with higher ratings indicating greater trust). Hypothesis 4. At least 66% of patients and 66% of physicians will rate the overall usability of the CDA as a 4 or 5 on a 5 point Likert scale (with higher ratings indicating greater usability). Hypothesis 5. At least 70% of physicians and 65% of patients will still be using the application regularly by the end of the study. For physicians, regularly will be defined as the application being used in every study-related visit. For patients regularly will be defined as completing at least one PHQ-9 and GAD-7 questionnaire on the application per week. Exploratory hypothesis: Based on our machine learning results to date, we expect between 40-50% of patients starting a new treatment for depression and whose treatment follows the highest probability treatment output by the CDA to remit within 14 weeks. This is exploratory, and the study is not necessarily powered to demonstrate this. ;

Related Conditions & MeSH terms

• Depression
• Depressive Disorder

• NCT number: NCT04061642
• Study type: Interventional
• Source: Aifred Health Inc.
• Status: Completed
• Phase: N/A
• Start date: December 16, 2019
• Completion date: December 31, 2020