Diabetic Retinopathy Screening Among Federally Qualified Health Center Patients Using Point-of-Care Artificial Intelligence (AI): Diabetic Retinopathy Screening Point-of-Care Artificial Intelligence (DRES-POCAI): A Trial Protocol
Authors' conclusion
DRES-POCAI will determine the effectiveness of an AI-powered DRS intervention to increase DRS rates in FQHC primary care workflows.
Study context
- Population
- Active FQHC patients aged 22 years or older with diabetes, no diabetic retinopathy screening (DRS) in prior 11 months, scheduled medical visits; 2 FQHC sites of San Ysidro Health, San Diego County, Californiatarget 848
- Comparison
- Point-of-care AI-powered DRS in primary care vs usual-care referral to eye care
- Primary endpoint
- DRS completion status
Methodological detailsprotocol, patient-level, multiclinic, open-label, parallel, superiority, Started June 2024; recruitment anticipated to conclude August 2025; follow-up until February 2026
- Protocol
- Patient-level
- Multiclinic
- Open-label
- Parallel
- Superiority
- Started June 2024; recruitment anticipated to conclude August 2025; follow-up until February 2026
Primary result
As reported in the abstract
- Findings will be disseminated after data collection and analysis
Original publication
Diabetic Retinopathy Screening Among Federally Qualified Health Center Patients Using Point-of-Care AI: DRES-POCAI: A Trial Protocol. JAMA Netw Open. Published 1 October 2025. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →