Using AI to understand nurse workload and burnout
Official title: AI modeling of nursing workload to understand burnout
Funded at University of Utah · NIH-10936933 · Data updated 2026-11-12
This study is looking at how artificial intelligence can help understand and reduce burnout among nurses by analyzing their work patterns, which could lead to better care for patients.
Quick facts
| Grant type | Career grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Utah NIH-funded |
| Lab location | 1 site (Salt Lake City, United States) |
| Project start | July 3, 2024 |
| Project end | June 30, 2027 |
| Funding year | 2024 |
| Award (this year) | $163,768 |
| NIH project number | 1K01NR021256-01 |
| Project ID | NIH-10936933 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for participation or benefit from this research include patients receiving care in settings with high nurse workloads, such as primary care and community health.
✕Less likely to help
Patients who are not receiving care in environments affected by nurse burnout may not see direct benefits from this research.
What this research studies
This research investigates how artificial intelligence can model nursing workloads to better understand and address nurse burnout. By analyzing electronic health record data, the project aims to identify patterns and factors contributing to burnout among nurses. The approach involves advanced data science techniques and computational modeling to provide insights that could improve nursing work environments. Patients may benefit indirectly as improved nurse well-being can enhance the quality of care they receive.
Why it matters
Potential benefit: If successful, this research could lead to improved working conditions for nurses, ultimately enhancing patient care and outcomes.
How similar studies have gone: Other research has shown success in using data science and AI to improve healthcare systems, indicating potential for this approach to yield meaningful results.
Where this research is happening
-
University of Utah
Salt Lake City, United States Active
Researchers
- Principal investigator: Tiase, Victoria Lynn — University of Utah
- Study coordinator: Tiase, Victoria Lynn
Related research
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Understanding and reducing burnout in community health centers using systems thinking
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-
Improving Nurse Practitioner Practice Environments to Prevent Burnout
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-
Helping VA primary care teams avoid burnout
This project uses expert-guided quality improvement and team input to create and pilot ways to reduce burnout among VA primary care providers and staff.
-
Reducing burnout and improving resilience in community health centers
This project tries systems changes to cut work burden and burnout for doctors, nurses, and staff at community health centers.
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.