Creating a system to prevent overcrowding in emergency departments
Official title: Building and Implementing a predictive decision support system based on a proactive full capacity protocol to mitigate emergency overcrowding problem
Funded at University of Alabama at Birmingham · NIH-10930907 · Data updated 2026-11-12
This study is working on a smart system that uses technology to help emergency departments manage patient flow better, so that when you arrive, your care can be quicker and safer, and overcrowding can be reduced.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Alabama at Birmingham NIH-funded |
| Lab location | 1 site (Birmingham, United States) |
| Project start | September 30, 2023 |
| Project end | September 29, 2025 |
| Funding year | 2024 |
| Award (this year) | $144,740 |
| NIH project number | 5R21HS029410-02 |
| Project ID | NIH-10930907 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are patients who require emergency medical care and are affected by long wait times and overcrowding in EDs.
✕Less likely to help
Patients who do not seek emergency care or those who are not affected by overcrowding in EDs may not benefit from this research.
What this research studies
This research focuses on developing a predictive decision support system designed to address the issue of overcrowding in emergency departments (EDs). By utilizing artificial intelligence and predictive analytics, the project aims to enhance patient flow from the moment they arrive until they are either admitted or discharged. The system will proactively manage patient capacity by predicting patient flow measures, allowing for timely interventions before overcrowding occurs. This approach seeks to improve patient safety and the overall quality of healthcare services in emergency settings.
Why it matters
Potential benefit: If successful, this research could significantly enhance patient safety and reduce wait times in emergency departments.
How similar studies have gone: Previous research has shown that implementing predictive analytics in healthcare settings can lead to improved patient flow and reduced overcrowding, indicating a promising approach.
Where this research is happening
-
University of Alabama at Birmingham
Birmingham, United States Active
Researchers
- Principal investigator: Ahmed, Abdulaziz — University of Alabama at Birmingham
- Study coordinator: Ahmed, Abdulaziz
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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.