A Review of Recent Developments in Artificial Intelligence and Big Data Technologies for Ophthalmology Referrals and Clinical Practice

Ophthalmology is undergoing rapid transformation through the integration of smart technologies such as artificial intelligence (AI), big data analytics, and clinical decision support systems (CDSS). With increasing pressure to improve clinical efficiency and manage growing patient volumes, the potential for smart technologies to streamline ophthalmic care warrants more exploration. To date, smart technologies have demonstrated potential as practical adjunctive tools that support ophthalmic referrals and clinical practice in ophthalmology. Smart technologies that support ophthalmic referrals now include CDSS that contain algorithms with the capacity to more efficiently identify suspected ophthalmic diseases that may be urgent or require prompt treatment in the primary care setting, compared with traditional referral models. These approaches also include installation of AI-powered ophthalmic imaging machines and electronic health records-analytical packages in primary care offices, where they can be used to screen for structural, historical, or symptomatic manifestations of ophthalmic diseases requiring ophthalmologist evaluation. Meanwhile, smart technologies that support ophthalmology practices include AI and big data simulations for optimized patient encounter schedules and chatbot-facilitated appointment confirmations. Amidst a smart technology renaissance, review is needed to capture existing smart technologies to inform integration in the practices of ophthalmic and general practitioners. This article aims to review the clinical utility of emerging smart technology relevant to ophthalmic referrals and ophthalmology practice.