Using machine learning to reduce unnecessary hospitalizations
Using Machine Learning and Patient-Reported Outcomes to Identify Unnecessary Hospitalizations
This study is looking at how smart computer programs can help figure out when hospital stays are really needed, especially for patients from different backgrounds who might be affected more by unnecessary visits, so we can improve care and reduce waste in healthcare.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California Los Angeles NIH-funded |
| Lab location | 1 site (Los Angeles, United States) |
| Project ID | NIH-10696203 on NIH RePORTER |
What this research studies
This research investigates how machine learning can be utilized to identify unnecessary hospitalizations, which often do not provide any benefit to patients and can even cause harm. By combining traditional claims data with detailed electronic health records and patient-reported outcomes, the study aims to develop a more accurate method for determining when hospitalizations are truly needed. The goal is to minimize medical waste and improve patient care, particularly for racial and ethnic minorities who are disproportionately affected by unnecessary hospitalizations.
Who could benefit from this research
Good fit: Ideal candidates for this research include patients who frequently experience hospitalizations for conditions like heart failure and may be at risk of unnecessary admissions.
Not a fit: Patients who are currently hospitalized for acute conditions requiring immediate care may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more efficient healthcare delivery and improved patient outcomes by reducing unnecessary hospitalizations.
How similar studies have performed: Other research has shown promise in using machine learning to improve healthcare outcomes, indicating that this approach could be effective.
Where this research is happening
Los Angeles, United States
- University of California Los Angeles — Los Angeles, United States (Active)
Researchers
- Principal investigator: Leuchter, Richard K — University of California Los Angeles
- Study coordinator: Leuchter, Richard K
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.