Improving how patients' health information is accessed using advanced language models
Official title: Trustworthy and High-Performance Question Answering for Electronic Health Records
Funded at University of Texas Hlth Sci Ctr Houston · NIH-10858562 · Data updated 2026-11-12
This study is working on making it easier for doctors to get accurate information about patients from electronic health records by using smart technology that understands everyday questions, so they can provide better care without worrying about wrong information.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Texas Hlth Sci Ctr Houston NIH-funded |
| Lab location | 1 site (Houston, United States) |
| Project start | September 16, 2024 |
| Project end | August 31, 2028 |
| Funding year | 2024 |
| Award (this year) | $351,000 |
| NIH project number | 1R01LM014508-01 |
| Project ID | NIH-10858562 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are patients whose health information is stored in electronic health records and who are receiving care from clinicians utilizing the improved question-answering systems.
✕Less likely to help
Patients who do not have their health information recorded in electronic health records or those receiving care outside of a clinical setting may not benefit from this research.
What this research studies
This research focuses on enhancing the accessibility of patient information stored in electronic health records (EHRs) by developing advanced question-answering systems. It aims to utilize large language models to create an intuitive interface that allows healthcare providers to ask natural language questions and receive accurate answers about patient data. The project addresses the challenge of misinformation, or 'hallucinations,' that can occur with these models, ensuring that the information retrieved is reliable and clinically relevant. By integrating structured data from EHRs with these advanced models, the research seeks to improve the overall usability and safety of EHR systems for clinicians.
Why it matters
Potential benefit: If successful, this research could lead to more accurate and efficient access to patient health information, ultimately improving clinical decision-making and patient outcomes.
How similar studies have gone: Other research has shown promise in using advanced language models for medical question answering, but this specific approach to integrating structured EHR data is relatively novel.
Where this research is happening
-
University of Texas Hlth Sci Ctr Houston
Houston, United States Active
Researchers
- Principal investigator: Roberts, Kirk Edward — University of Texas Hlth Sci Ctr Houston
- Study coordinator: Roberts, Kirk Edward
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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.