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
• community health screenings
• artificial intelligence
• diabetic retinopathy screening
• vision screening

Disclosure statement

No potential conflict of interest was reported by the author(s).

Statement of submission

This report has not been published anywhere previously, and it is not being considered for any other publication elsewhere.

Data availability statement

Dataset is available based on request to author.

Additional information

Funding

The author(s) reported that there is no funding associated with the work featured in this article.