Artificial Intelligence in Depression - Medication Enhancement

Study Overview
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Brief Summary
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This study will determine the safety and potential effectiveness of a digital health platform aimed at improving treatment outcomes for patients with depression by assisting physicians with clinical decision making about depression treatment.

Official Title
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Artificial Intelligence in Depression - Medication Enhancement: A Randomized, Patient and Rater Blinded, Active-Controlled Trial of a Hybrid-Classic/Machine-Learning Enabled Clinical Decision Aid for Personalized and Individualized Pharmacological Depression Treatment Selection

Conditions
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Depression

Intervention / Treatment
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* Device: Clinical Decision Support System


Participation Criteria
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Eligibility Criteria
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Patient Inclusion Criteria: diagnosed with major depressive disorder by a physician using DSM-V criteria able to provide informed consent patients must confirm that they are comfortable being treated for depression by their physician, who may propose a range of treatment options, such as medications or psychotherapies, consistent with best practice guidelines for depression which are included in the application. Physicians will be required, as in usual practice, to explain treatments to patients and patients will be able to give and withdraw consent for treatment in general or for specific treatments as in usual practice. Patient Exclusion Criteria: bipolar disorder of any type inability or unwillingness of the individual to give informed consent inability to manage patient in an outpatient setting (i.e. imminent suicidality) active major depression is not the main condition being treated (i.e. the patient has depressive symptoms in the context of severe substance abuse or a psychotic disorder, but a primary diagnosis of major depressive episode (MDE) cannot be made or would result in inappropriate care). inability to use the tool (i.e. patient cannot interface with a mobile phone or computer due to delirium, or another medical condition)* *Note that for patients who do not have access to mobile or desktop devices but are able to use them or to be trained to use them, these will be provided to them at no cost. Physician Inclusion Criteria: any family doctor/primary care physician or psychiatrist accredited in Canada or the USA who treats patients with depression on at least a monthly basis, as well as residents from these specialities supervised by a participating physician able to provide informed consent comfortable prescribing the range of potential treatments which could have probabilities provided for them by the CDA No Physician Exclusion Criteria

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Treatment
Allocation: Randomized
Intervention Model: Parallel Assignment
Interventional Model Description: The Clinical Decision Aid is a digital health platform that collects patient data and provides reports and analyses to clinicians that can assist them in their decision making about treatment selection and management.
Masking: Double


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: Active Intervention<br>Intervention delivered to patients by digital health platform. | Device: Clinical Decision Support System<br>* Clinical Decision Support System using Measurement-Based Care and Digital Decision Support Platform<br>|
| Active Comparator: Active Control<br>Intervention delivered to patients by digital health platform. | Device: Clinical Decision Support System<br>* Clinical Decision Support System using Measurement-Based Care and Digital Decision Support Platform<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Rate of Safety - Adverse Events | Adverse and Serious Adverse Events | 3 months | 
| Effectiveness in Reduction of Depression Symptoms | This is approved as a physician partially-blinded study and, as such, physicians are blinded to the primary outcome. | 3 months | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Time to Remission | To evaluate time to remission between groups. The hypothesis is that time to remission will be shorter in the active intervention group compared to the active control group. | 3 months | 
| Response Rate | To evaluate response rate between groups. The hypothesis is that the response rate (defined as 50% improvement in symptoms) and time to response, will be higher and lower, respectively, in the active intervention group compared to the active control group. | 3 months | 
| Patient Disability with WHODAS rating scale | To evaluate between-group differences in patient disability outcomes. The hypothesis is that the physicians in the active intervention arm will produce superior patient outcomes to those physicians using usual guideline-informed practice, in terms of patient function as measured by a rating scale (WHODAS). | 3 months | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Depression, Treatment Selection, Decision Support, Artificial Intelligence (AI), Machine Learning (ML)