Impact of artificial intelligence on the availability, accessibility, acceptability and quality of ophthalmic disease screening services: a scoping review

Comprehensive Summary

This scoping review, presented by Lin et al., examines how artificial intelligence (AI) impacts eye disease screening services by evaluating availability, accessibility, acceptability, and quality across 42 studies. To do this, researchers compared traditional manual screening methods against AI-assisted and fully automated approaches, finding that most studies focused heavily on availability while accessibility and service quality received less attention. The majority of studies demonstrated strong methodological quality, with 24 scoring 5/5 and 15 scoring 4/5 using the Mixed Methods Appraisal Tool. Researchers found that AI screening showed significant potential for improving cost-effectiveness and extending services to remote or underserved regions where access to ophthalmologists is limited. This also highlighted that patients demonstrated high satisfaction with AI-based screening and showed improved referral compliance. The authors finish their claims by explaining that while AI shows promise for transforming eye disease screening programs, large-scale long-term clinical trials are still needed before these technologies can be effectively integrated into redesigned screening workflows and comprehensive eye health service systems.

Outcomes and Implications

This research is important to the medical field because it highlights AI as a potentially transformative tool for addressing gaps in ophthalmic care delivery, particularly for populations with limited access to specialists. Eye diseases like diabetic retinopathy and glaucoma benefit significantly from early detection, but many communities lack adequate screening infrastructure. In terms of its clinical importance, understanding how AI performs across different screening contexts can give healthcare systems evidence-based strategies for scaling population-level programs. The demonstrated cost-effectiveness and patient acceptance suggests that this technology is already supported by practical advantages beyond just diagnostic accuracy. With AI showing promise for deployment in underserved areas, the approach becomes more viable for reducing healthcare disparities. While further studies are needed to address gaps in accessibility research and establish quality assurance frameworks, this review lays the foundation for AI to become a routine part of eye disease screening programs in the future.