Personalized depression treatment in primary care
Improving Outcomes in Depression in Primary Care
This project will use routine clinic information and computer learning to match people with moderate to severe depression to the antidepressant or brief behavioral therapy most likely to help them.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Harvard Medical School NIH-funded |
| Lab location | 1 site (Boston, United States) |
| Project ID | NIH-11087662 on NIH RePORTER |
What this research studies
From your point of view, the team will collect information you can give in a regular clinic visit — symptoms, history, and simple measures — and use machine learning to build a rule that predicts whether an antidepressant or a short behavioral therapy (the Healthy Activity Program) is more likely to work. Patients will be assigned either according to this rule or by chance so researchers can compare who gets better and at what cost. The study aims to increase the number of people who reach remission and to spot those who should be referred quickly to specialist care. It will also compare the overall costs to see if choosing treatments this way saves resources.
Who could benefit from this research
Good fit: People with moderate to severe depression receiving care in participating primary care clinics who are willing to try an antidepressant or brief behavioral therapy are the ideal candidates.
Not a fit: Individuals already in specialty psychiatric care, those with only mild symptoms, or people requiring urgent inpatient or specialist treatment may not be included or benefit from this project.
Why it matters
Potential benefit: If successful, this could help more people with moderate to severe depression recover by guiding clinicians to the treatment most likely to work for each person.
How similar studies have performed: Prior trials have shown that generic antidepressants and the culturally adapted Healthy Activity Program can be effective in primary care, but using a machine‑learning precision treatment rule to pick the best option for each person is a newer approach with promising but not yet widespread proof.
Where this research is happening
Boston, United States
- Harvard Medical School — Boston, United States (Active)
Researchers
- Principal investigator: Patel, Vikram H — Harvard Medical School
- Study coordinator: Patel, Vikram H
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.