Predicting Psychosis Outcomes from Electronic Health Records
Official title: 4/5-Clinical Outcome Prediction of Psychosis from EHRs (COPPER)
Funded at Feinstein Institute for Medical Research · NIH-11377600 · Data updated 2026-11-12
This project uses machine learning on routine health records to predict long-term outcomes for people with psychosis and tailor their care.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Feinstein Institute for Medical Research NIH-funded |
| Lab location | 1 site (Manhasset, United States) |
| Project start | September 6, 2024 |
| Project end | May 31, 2029 |
| Funding year | 2026 |
| Award (this year) | $427,234 |
| NIH project number | 5R01MH137681-03 |
| Project ID | NIH-11377600 on NIH RePORTER |
Who could benefit from this research
✓Could help
Individuals diagnosed with schizophrenia or related psychosis-related disorders, whose health records are included in the study databases and who consent to data use for research.
✕Less likely to help
Patients whose data are not representative of broader populations or whose records do not contribute to the predictive models may not benefit directly.
What this research studies
Researchers will combine longitudinal electronic health records, detailed clinical data, and genetic information to build models that predict future outcomes and identify subgroups among schizophrenia patients. The approach includes handling real-world data from two large databases and examining how psychosocial and ethical factors influence predictive tools. The goal is to support personalized treatment planning, closer monitoring, and preventive interventions in psychiatry. The work will also address how clinicians and patients might responsibly use predictive information in care decisions.
Why it matters
Potential benefit: If successful, patients with psychosis could receive more personalized treatment plans and proactive care to improve outcomes and reduce adverse effects.
How similar studies have gone: Previous studies have shown that ML models using EHR data can predict certain psychiatric outcomes, supporting the potential of this approach, though this exact method is novel in its integration and subtyping.
Where this research is happening
-
Feinstein Institute for Medical Research
Manhasset, United States Active
Researchers
- Principal investigator: Lencz, Todd — Feinstein Institute for Medical Research
- Study coordinator: Lencz, Todd
Related research
Other NIH-funded projects on the same topics.
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Psychosis in diverse settings across the world
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Psychosis in Diverse Settings: Understanding Symptoms and Treatment Across Global South
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Computational analysis of facial expression in early psychosis
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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.