Depression
Conditions
Keywords
Depression, Treatment Selection, Decision Support, Artificial Intelligence (AI), Machine Learning (ML)
Brief summary
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.
Interventions
Clinical Decision Support System using Measurement-Based Care and Digital Decision Support Platform
Sponsors
McGill University
Aifred Health
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
TREATMENT
Masking
DOUBLE (Subject, Investigator)
Masking description
Patient and Rater blinded, Physician partially blinded
Intervention 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.
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
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
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Rate of Safety - Adverse Events | 3 months | Adverse and Serious Adverse Events |
| Effectiveness in Reduction of Depression Symptoms | 3 months | This is approved as a physician partially-blinded study and, as such, physicians are blinded to the primary outcome. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Response Rate | 3 months | 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. |
| Time to Remission | 3 months | 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. |
| Patient Disability with WHODAS rating scale | 3 months | 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). |
Other
| Measure | Time frame | Description |
|---|---|---|
| Number of ER visits, admissions, and re-admissions | 3 months | We will examine impact of health resource utilization by comparing rates of visits, admissions, and re-admissions between groups. |
| Patient Questionnaire Response Rate | 3 months | We will assess the frequency at which patients complete the questionnaires in the digital health platform in both groups. |
| Medication Adherence Rates | 3 months | We will asses medication adherence rates, as measured by the Brief Adherence Rating Scale, after each visit for the duration of the study and compare between groups. |
Countries
Canada, United States
Outcome results
None listed