Improving accuracy of HIV research that uses medical records
Official title: Statistical methods and designs for correlated outcome and covariate errors in studies of HIV/AIDS
Funded at Vanderbilt University Medical Center · NIH-11469944 · Data updated 2026-11-12
This work creates ways to combine routine electronic health records with smaller, carefully checked samples to give more accurate results for people living with HIV.
Quick facts
| Grant type | R37 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Vanderbilt University Medical Center NIH-funded |
| Lab location | 1 site (Nashville, United States) |
| Project start | January 25, 2018 |
| Project end | January 31, 2028 |
| Funding year | 2026 |
| Award (this year) | $30,654 |
| NIH project number | 3R37AI131771-09S4 |
| Project ID | NIH-11469944 on NIH RePORTER |
Who could benefit from this research
✓Could help
People living with HIV whose clinic or hospital records are part of participating electronic health record systems or international HIV databases (for example, sites contributing to IeDEA) are the records that could be included.
✕Less likely to help
Patients who do not have electronic health records at participating clinics, who receive care outside the contributing databases, or who want direct clinical treatment rather than research participation may not see direct benefit.
What this research studies
Electronic health records and routinely collected clinic data often contain mistakes that can skew HIV research. This project will pair the large but error-prone record sets with smaller groups of records checked against gold-standard measurements, then use new statistical methods and multi-step designs to correct biases and tighten estimates. The team will build software tools and apply these approaches to international HIV clinic data (for example, IeDEA) so findings reflect real patient outcomes more reliably. By targeting which records to validate and how to combine data, the approach aims to make conclusions from existing HIV data sources more trustworthy.
Why it matters
Potential benefit: If successful, this could make many HIV research findings—such as rates of complications or treatment effects—more accurate, supporting better clinical and policy decisions.
How similar studies have gone: Earlier work by this group and others has shown that combining validated subsamples with routine data can improve accuracy, and this project expands and optimizes those methods for HIV datasets.
Where this research is happening
-
Vanderbilt University Medical Center
Nashville, United States Active
Researchers
- Principal investigator: Shepherd, Bryan Earl — Vanderbilt University Medical Center
- Study coordinator: Shepherd, Bryan Earl
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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.