Predicting hospital readmissions for older adults after emergency department visits
Official title: GEMRA: Geriatric Emergency Medicine Risk Prediction Model for Return VisitAdmissions
Funded at Weill Medical Coll of Cornell Univ · NIH-11056123 · Data updated 2026-11-12
This study is working on a smart tool that helps doctors figure out which older patients might need to return to the emergency room soon after leaving the hospital, so they can get the right care and support to stay healthy.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Weill Medical Coll of Cornell Univ NIH-funded |
| Lab location | 1 site (New York, United States) |
| Project start | April 1, 2023 |
| Project end | February 29, 2028 |
| Funding year | 2025 |
| Award (this year) | $796,484 |
| NIH project number | 5R01AG076998-03 |
| Project ID | NIH-11056123 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are older adults who have been discharged from emergency departments and are at risk of returning within 72 hours.
✕Less likely to help
Patients who are younger than 21 years old or those who do not visit the emergency department will not benefit from this research.
What this research studies
This research aims to develop a machine learning model that predicts the likelihood of older adults returning to the emergency department within 72 hours of discharge, which often leads to hospital admissions. By analyzing clinical data collected during routine care, the model will provide healthcare professionals with a decision support tool to better assess the risks associated with discharging elderly patients. The goal is to enhance patient outcomes by identifying those at higher risk for complications and ensuring they receive appropriate follow-up care.
Why it matters
Potential benefit: If successful, this research could significantly reduce hospital readmissions and improve the overall health outcomes for older adults after emergency department visits.
How similar studies have gone: Previous research has shown success in using machine learning models for predicting patient outcomes in various medical settings, indicating a promising approach for this novel application in geriatric emergency medicine.
Where this research is happening
-
Weill Medical Coll of Cornell Univ
New York, United States Active
Researchers
- Principal investigator: Steel, Peter Arthur Deblieux — Weill Medical Coll of Cornell Univ
- Study coordinator: Steel, Peter Arthur Deblieux
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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.