Improving Access to Eye Care Through Community Health Screenings Using Artificial Intelligence

Abstract

Purpose: To the best of our knowledge, implementation of artificial intelligence (AI)-based vision screening in community health fair settings has not been previously studied. This prospective cohort study explored the incorporation of AI in a community health fair setting to improve access to eyecare.

Methods: Vision screening was implemented during a community health fair event using an AI-based non-mydriatic fundus camera. In addition, a questionnaire was provided to survey the various barriers to eyecare and assess eye health literacy.

Results: A total of 53 individuals were screened at this event. Notably, about 88% of participants had follow-up appointments scheduled accordingly with an approximate 62% attendance rate. The most reported barrier to eyecare was lack of health insurance followed by transportation.

Conclusion: The addition of AI-based vision screening in community health fairs may ultimately help improve access to eye care.

Keywords: Eye care; artificial intelligence; community health screenings; diabetic retinopathy screening; vision screening.