Making hemodialysis blood-access decisions easier
Official title: Improving the patient experience of hemodialysis vascular access decision making
Funded at University of California Los Angeles · NIH-11167797 · Data updated 2026-11-12
This project will build an easy-to-use, evidence-based guide to help people on or approaching hemodialysis and their doctors choose the best type of vascular access for their situation.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California Los Angeles NIH-funded |
| Lab location | 1 site (Los Angeles, United States) |
| Project start | September 1, 2022 |
| Project end | August 31, 2027 |
| Funding year | 2025 |
| Award (this year) | $423,035 |
| NIH project number | 5R01DK129810-04 |
| Project ID | NIH-11167797 on NIH RePORTER |
Who could benefit from this research
✓Could help
Adults with end-stage kidney disease who are on or approaching hemodialysis and facing a choice about an arteriovenous fistula, graft, or central venous catheter are the ideal candidates for the guide's use.
✕Less likely to help
People who do not need hemodialysis, pediatric patients, or those whose vascular access choice is already finalized may not directly benefit from this project.
What this research studies
If you need hemodialysis, choosing between a fistula, graft, or catheter can be confusing; researchers will link large national registries and Medicare data to see real-world outcomes of different access types. They will create prediction models using traditional statistics and machine-learning methods (for example, Bayesian networks and random forests) to estimate outcomes that matter to patients, like repeat surgeries or the need for revisions. From those models they will build an interactive guide that presents likely short- and long-term outcomes in plain language. The team will also identify how clinicians can use the guide during visits so you can make clearer, more personalized decisions with your care team.
Why it matters
Potential benefit: If successful, this work could give patients and clinicians clearer, personalized information to reduce repeat procedures and improve satisfaction with vascular access decisions.
How similar studies have gone: While decision aids exist for dialysis choices, combining large linked registries with machine-learning prognostic models to produce an interactive vascular access guide is relatively new.
Where this research is happening
-
University of California Los Angeles
Los Angeles, United States Active
Researchers
- Principal investigator: Woo, Karen — University of California Los Angeles
- Study coordinator: Woo, Karen
Related research
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Improving how patients choose their hemodialysis access
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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.