Predicting preventable hospital visits for homecare patients
Official title: Homecare-CONCERN: Building risk models for preventable hospitalizations and emergency department visits in homecare
Funded at Visiting Nurse Service of New York · NIH-10664876 · Data updated 2026-11-12
This study is working on a new tool to help homecare patients who might need extra support to avoid unnecessary hospital visits, making it easier for healthcare providers to spot those who could benefit from more care.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Visiting Nurse Service of New York NIH-funded |
| Lab location | 1 site (New York, United States) |
| Project start | September 30, 2020 |
| Project end | July 31, 2025 |
| Funding year | 2023 |
| Award (this year) | $382,317 |
| NIH project number | 5R01HS027742-04 |
| Project ID | NIH-10664876 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are older adults receiving homecare services who may be at risk for hospital admissions or emergency department visits.
✕Less likely to help
Patients who are not receiving homecare services or those with conditions that do not lead to preventable hospitalizations may not benefit from this research.
What this research studies
This research focuses on developing a risk prediction model called Homecare-CONCERN to identify homecare patients at risk of preventable hospitalizations and emergency department visits. By analyzing clinical notes using advanced data science techniques, the project aims to enhance the timely identification of patients who may need additional care. The research team will validate this model and create a clinical decision support tool to assist healthcare providers in making informed decisions about patient care. Ultimately, the goal is to reduce unnecessary hospital visits and improve patient outcomes in homecare settings.
Why it matters
Potential benefit: If successful, this research could significantly reduce preventable hospitalizations and emergency department visits for homecare patients, leading to better health outcomes and lower healthcare costs.
How similar studies have gone: Other research has shown success in using predictive modeling and data science approaches to improve patient outcomes in healthcare settings, indicating that this approach has potential.
Where this research is happening
-
Visiting Nurse Service of New York
New York, United States Active
Researchers
- Principal investigator: Topaz, Maxim — Visiting Nurse Service of New York
- Study coordinator: Topaz, Maxim
Related research
Other NIH-funded projects on the same topics.
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Homecare-CONCERN: smarter home health care to prevent hospital visits
A pragmatic trial tests a machine-learning based decision support system to help 65+ patients receiving home health care stay out of the hospital or ER.
-
Helping caregivers of adults at home with heart failure and cognitive impairment manage stress and self-care
This grant tests a virtual coaching program designed to support caregivers of adults with heart failure and cognitive impairment to improve their own well-being and caregiving skills.
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Quality of life and emotional wellbeing after major surgery for people with chronic conditions
This project follows people with chronic conditions who begin home healthcare after major or genital reconstructive surgery to understand how their physical and mental wellbeing change over time.
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How family caregivers impact home health care for older adults with Alzheimer's disease
This study is looking at how family caregivers help older adults with Alzheimer's and related conditions at home, and it wants to find out how to better support these caregivers so they can provide the best care possible.
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.