TY - JOUR
T1 - Application of Artificial Intelligence to Deliver Healthcare from the Eye
AU - Weinreb, Robert N.
AU - Lee, Aaron Y.
AU - Baxter, Sally L.
AU - Lee, Richard W.J.
AU - Leng, Theodore
AU - McConnell, Michael V.
AU - El-Nimri, Nevin W.
AU - Rhew, David C.
N1 - Publisher Copyright:
© 2025 American Medical Association. All rights reserved.
PY - 2025/6/20
Y1 - 2025/6/20
N2 - Importance: 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. Observations: 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. Conclusions and Relevance: With effective implementation and collaboration among key stakeholders, this approach has the potential to contribute to an equitable and effective health care system.
AB - Importance: 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. Observations: 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. Conclusions and Relevance: With effective implementation and collaboration among key stakeholders, this approach has the potential to contribute to an equitable and effective health care system.
UR - https://www.scopus.com/pages/publications/105005144765
U2 - 10.1001/jamaophthalmol.2025.0881
DO - 10.1001/jamaophthalmol.2025.0881
M3 - Review article
C2 - 40338607
AN - SCOPUS:105005144765
SN - 2168-6165
VL - 143
SP - 529
EP - 535
JO - JAMA Ophthalmology
JF - JAMA Ophthalmology
IS - 6
ER -