Application of Artificial Intelligence to Deliver Healthcare From the Eye.
Authors
Affiliations (10)
Affiliations (10)
- Viterbi Family Department of Ophthalmology, University of California, San Diego, La Jolla.
- Shiley Eye Institute, University of California, San Diego, La Jolla.
- Department of Ophthalmology, School of Medicine, University of Washington, Seattle.
- Division of Biomedical Informatics, Department of Medicine, University of California, San Diego, La Jolla.
- National Eye Institute, National Institutes of Health, Bethesda, Maryland.
- Department of Ophthalmology, Byers Eye Institute at Stanford, Stanford University School of Medicine, Palo Alto, California.
- Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California.
- Topcon Healthcare Inc, Oakland, New Jersey.
- Health & Life Sciences, Microsoft, Seattle, Washington.
- Division of Primary Care & Population Health, Department of Medicine, Stanford University School of Medicine, Stanford, California.
Abstract
Oculomics is the science of analyzing ocular data to identify, diagnose, and manage systemic disease. This article focuses on prescreening, its use with retinal images analyzed by artificial intelligence (AI), to identify ocular or systemic disease or potential disease in asymptomatic individuals. The implementation of prescreening in a coordinated care system, defined as Healthcare From the Eye prescreening, has the potential to improve access, affordability, equity, quality, and safety of health care on a global level. Stakeholders include physicians, payers, policymakers, regulators and representatives from industry, government, and data privacy sectors. The combination of AI analysis of ocular data with automated technologies that capture images during routine eye examinations enables prescreening of large populations for chronic disease. Retinal images can be acquired during either a routine eye examination or in settings outside of eye care with readily accessible, safe, quick, and noninvasive retinal imaging devices. The outcome of such an examination can then be digitally communicated across relevant stakeholders in a coordinated fashion to direct a patient to screening and monitoring services. Such an approach offers the opportunity to transform health care delivery and improve early disease detection, improve access to care, enhance equity especially in rural and underserved communities, and reduce costs. With effective implementation and collaboration among key stakeholders, this approach has the potential to contribute to an equitable and effective health care system.