Patient and Provider Experience with Artificial Intelligence Screening Technology for Diabetic Retinopathy in a Rural Primary Care Setting.

Abstract

Introduction: The development of autonomous artificial intelligence for interpreting diabetic retinopathy (DR) images has allowed for point-of-care testing in the primary care setting. This study describes patient and provider experiences and perceptions of the artificial intelligence DR screening technology called EyeArt by EyeNuk during implementation of the tool at Western Maine Primary Care in Norway, Maine.

Methods: This non-randomized, single-center, prospective observational study surveyed 102 patients and 13 primary care providers on their experience of the new screening intervention.

Results: All surveyed providers agreed that the new screening tool would improve access and annual screening rates. Some providers also identified initial challenges in incorporating the tool into the primary care visit (31%). Patients expressed a favorable view of the service, sharing an openness to being screened more regularly (75%) and a desire to have screenings performed at Western Maine Primary Care going forward (81%).

Discussion: Patients were generally favorable about their experience with the new DR screening technology. Providers indicated challenges due to the limited availability of trained medical assistant photographers during the initial implementation of DR screening, as well as timing issues in coordinating screening with regular office appointments.

Conclusions: This study supports further investigation of this technology in primary care, particularly in areas with challenges to care access. The potential benefits of this innovative tool in caring for people with diabetes includes improving access to retinopathy screenings and supporting wider detection of vision-threatening retinopathy.