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

Area of Science:

• Ophthalmology
• Public Health
• Artificial Intelligence

Background:

• Community health fairs offer a unique venue for health screenings.
• Limited access to regular eyecare is a significant public health concern.
• The integration of artificial intelligence (AI) in healthcare is rapidly expanding.

Purpose of the Study:

• To explore the implementation of AI-based vision screening in a community health fair.
• To assess the feasibility and impact of AI in improving access to eyecare.
• To identify barriers to eyecare and evaluate eye health literacy within the community.

Main Methods:

• A prospective cohort study was conducted during a community health fair.
• AI-based non-mydriatic fundus cameras were utilized for vision screening.
• Questionnaires were administered to gather data on eyecare barriers and health literacy.

Main Results:

• 53 individuals underwent AI-powered vision screening.
• Approximately 88% of participants scheduled follow-up appointments, with a 62% attendance rate.
• Lack of health insurance and transportation were the primary reported barriers to eyecare.

Conclusions:

• AI-based vision screening can be effectively integrated into community health fair settings.
• This approach has the potential to significantly enhance access to crucial eyecare services.
• Addressing socioeconomic factors like insurance and transportation is vital for improving eye health outcomes.