Finding hidden obstructive sleep apnea in primary care
Undiagnosed Obstructive Sleep Apnea in Primary Care Clinics
This project uses electronic health records and machine learning to find people seen in primary care who likely have undiagnosed obstructive sleep apnea.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Ohio State University NIH-funded |
| Lab location | 1 site (Columbus, UNITED STATES) |
| Project ID | NIH-11164765 on NIH RePORTER |
What this research studies
If you get care at a participating primary care clinic, researchers will search routine electronic health records to identify signs that you might have obstructive sleep apnea (OSA) even if you were never diagnosed. They will combine data such as diagnoses, symptoms, and related conditions with machine-learning tools to flag likely cases, including those with excessive daytime sleepiness linked to higher heart risks. The flagged cases will be compared to objective diagnostic information when available to estimate how often OSA is missed in routine care. The team will also look at patient, clinician, and clinic factors that make under-diagnosis more or less likely.
Who could benefit from this research
Good fit: Adults who receive primary care at participating clinics and have electronic health records there—especially those with snoring, daytime sleepiness, high blood pressure, or other related conditions—are the main candidates for identification.
Not a fit: People without records in the participating clinics' EHRs, those already diagnosed and treated for OSA, or patients outside the study sites are unlikely to benefit directly from this project.
Why it matters
Potential benefit: If successful, this work could help find people with undiagnosed OSA sooner so they can get proper testing and treatment and potentially lower their risk of heart problems.
How similar studies have performed: Previous studies mostly used self-reported symptoms, but early work and preliminary data suggest that EHR-based algorithms and machine-learning approaches can help find undiagnosed OSA, although the methods are still being refined.
Where this research is happening
Columbus, UNITED STATES
- Ohio State University — Columbus, United States (Active)
Researchers
- Principal investigator: Magalang, Ulysses J — Ohio State University
- Study coordinator: Magalang, Ulysses J
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 below.