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Improving Access to Eye Care Through Community Health Screenings Using Artificial Intelligence
Bhakti Panchal1, Samuel Asanad1, Rana Malek2
1Department of Ophthalmology and Visual Sciences, University of Maryland, Baltimore, Maryland, USA.
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.
