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Patient and Provider Experience with Artificial Intelligence Screening Technology for Diabetic Retinopathy in a Rural
Brian Nolan1, Emma R Daybranch2, Kerri Barton3
1Internal Medicine, MaineHealth, Norway, Maine.
Journal of Maine Medical Center
|August 9, 2024
Summary
Artificial intelligence (AI) for diabetic retinopathy (DR) screening is well-received by patients and primary care providers, improving access to care. Despite initial implementation challenges, the technology shows promise for early detection of vision-threatening retinopathy.
Area of Science:
- Ophthalmology
- Artificial Intelligence
- Primary Care Medicine
Background:
- Diabetic retinopathy (DR) screening is crucial for preventing vision loss in diabetic patients.
- Point-of-care DR screening using AI can improve access in primary care settings.
- The EyeArt system by EyeNuk offers autonomous AI for DR image interpretation.
Purpose of the Study:
- To describe patient and provider experiences with the EyeArt AI DR screening technology.
- To evaluate the perceptions of AI-driven DR screening during its implementation at Western Maine Primary Care.
Main Methods:
- A non-randomized, single-center, prospective observational study.
- Surveyed 102 patients and 13 primary care providers on their experiences.
- Assessed perceptions of the AI screening intervention.
Main Results:
- All providers believed the AI tool would enhance access and annual screening rates.
- 75% of patients were open to more frequent screenings; 81% desired screenings at the primary care site.
- Providers noted initial challenges with photographer availability and appointment timing.
Conclusions:
- The AI DR screening technology was generally viewed favorably by patients.
- Implementation challenges for providers included staffing and scheduling.
- Further investigation in primary care is supported, especially for improving access to DR screenings and early detection of vision-threatening retinopathy.
