Bridging the Digital Divide in Ophthalmic Telemedicine: Challenges, Equity Gaps, and Strategies for Inclusive Vision Care - Review

Purpose: This narrative review aims to evaluate the current state of artificial intelligence (AI) integration in teleophthalmology and to identify the socio-technical barriers, specifically the "digital divide," that hinder equitable access to digital vision care. Materials and Methods: A comprehensive literature review was conducted using PubMed, Scopus, and Web of Science databases, covering studies from 2013 to 2026. The search focused on AI diagnostic performance in major ocular diseases (DR, glaucoma, AMD) and socio-behavioral studies regarding technology adoption among visually impaired and underserved populations. Results: AI algorithms demonstrated expert-level diagnostic accuracy, with autonomous systems for diabetic retinopathy achieving sensitivities over 87% in real-world settings. However, a significant "socio-technological paradox" was identified: while technology reduces physical barriers, nearly 50% of visually impaired users require external assistance to navigate digital platforms. Furthermore, data poverty and algorithmic bias across different ethnic groups (with AUC variances up to 0.08) represent critical equity gaps. Global implementation models, such as the "Hub-and-Spoke" system in India, show promise in mitigating these divides through frugal innovation. Conclusions: While teleophthalmology and AI have the potential to transform vision care, their success depends on a strategic shift toward universal design and health-justice principles. To prevent the deepening of existing health disparities, technological innovation must be integrated with professional leadership and community-based digital literacy initiatives.