Predicting Outcomes for Psychosis Using Health Records
4/5-Clinical Outcome Prediction of Psychosis from EHRs (COPPER)
This project uses artificial intelligence to help predict how psychosis might progress for individuals, aiming to improve personalized 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 ID | NIH-11184442 on NIH RePORTER |
What this research studies
Many areas of medicine use tools to predict how a condition might unfold, but psychiatry currently has very few. This work aims to change that for psychosis-related disorders, which affect many people and have diverse long-term outcomes. We are building prediction tools using machine learning, combining information from long-term electronic health records, detailed patient characteristics, and genetic data. Our goal is to identify different patterns of outcomes among people with schizophrenia, which could lead to more tailored treatment plans.
Who could benefit from this research
Good fit: This work focuses on individuals with schizophrenia and psychosis-related disorders whose health information is available in large electronic health record databases.
Not a fit: Patients who do not have psychosis-related disorders or whose data is not part of the analyzed health record systems may not directly benefit from this specific research.
Why it matters
Potential benefit: If successful, this work could lead to more personalized treatment plans, better monitoring of outcomes, and improved preventive care for individuals with psychosis.
How similar studies have performed: While clinical predictors are common in other medical fields, quantitative predictors for psychiatric decision-making are still very limited, making this a novel approach in psychiatry.
Where this research is happening
Manhasset, United States
- Feinstein Institute for Medical Research — Manhasset, United States (Active)
Researchers
- Principal investigator: Lencz, Todd — Feinstein Institute for Medical Research
- Study coordinator: Lencz, Todd
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.