Oculomics is the study of how features seen in the eye — especially on retinal and OCT images — can reflect disease elsewhere in the body. The retina is the only place where blood vessels and neurons can be directly visualized, making it a natural place to look for clues about overall health.
Interest in the field is growing exponentially with studies showing how fundus photos can link retinal changes with systemic diseases, including heart disease, kidney disease, and neurological diseases like Alzheimer’s.
The idea is appealing: a quick, noninvasive image could give insight into conditions that usually require lab work or specialized testing. But turning that idea into clinical reality has many challenges.
1.Workflow and Implementation
The biggest barrier is workflow, not technology. Even good tools fail if they don’t fit how care is delivered.
Years ago, I placed a fundus camera in a primary-care colleague’s office to help screen for diabetic retinopathy. It seemed simple enough: take a photo, send it for interpretation, and close a care gap. In practice, the camera was rarely used. It didn’t fit the clinic’s routine, and within a few weeks, staff had stopped remembering it was there. That experience showed me how hard it is to change established workflows, even when the technology makes sense.
The same problem applies to oculomics. In a busy primary-care or retail setting, any extra step can be a deal breaker.
Solution
Oculomic screening needs to be automated and embedded. Image capture, analysis and reporting should happen in the background, with results flowing directly into the EMR. Staff shouldn’t need to remember a separate process. When taking a retinal photo feels as normal as checking blood pressure, adoption will follow.
2.Regulation, Reimbursement and Value-Based Care
The next challenge is regulation and payment. Right now, only one autonomous AI system in ophthalmology—for diabetic retinopathy—has its own CPT code (92229). There’s no established path for reimbursement when using fundus images to predict cardiovascular or neurologic risk.
These tools sit in a gray zone. They estimate risk rather than diagnose a specific disease, which complicates both FDA approval and payer coverage. Regulators will expect prospective data that shows using oculomics actually improves outcomes. Most research so far has been retrospective or exploratory.
If less expensive methods exist, like the Framingham risk calculator, payers will ask why they should reimburse for a fundus-based alternative. Until oculomics shows that it provides earlier or more actionable information, reimbursement will remain uncertain.
Still, there may be opportunity in value-based care models. Health systems that are accountable for outcomes—rather than volume—are already looking for ways to identify risk earlier. Oculomics could help detect disease before it becomes expensive to treat, aligning well with the goals of population health programs.
Solution
The path forward is to focus on prospective validation and partnerships with health systems operating under value-based contracts. If oculomics can demonstrate that it prevents downstream costs or improves chronic disease management, it will have a stronger case for both regulatory and payer adoption.
3.The Setting of Care
Oculomics is also expanding beyond the clinic. Fundus cameras are showing up in pharmacies, wellness centers and workplace screenings. While this helps with accessibility, it creates new questions. Who interprets the results? Who ensures the findings are accurate and acted upon?
These images will often flag eye diseases like diabetic retinopathy, glaucoma, or macular degeneration — conditions that require an optometrist or ophthalmologist to manage. Keeping eye care providers in the loop is essential. Without their oversight, both ocular and systemic findings risk being lost or misunderstood.
Solution
The best path forward is collaboration. AI can handle image capture and triage, but licensed eye care professionals should confirm findings and guide next steps. As this becomes more common, the public may start to view the eye as an important indicator of overall health — not in a symbolic way, but as a practical part of preventive care.
Where Things Stand
Oculomics could make eye exams more useful by providing insight into both ocular and systemic health. But getting there will require progress in three areas:
- Integration into normal clinical workflows.
- Evidence that meets regulatory and payer standards.
- Collaboration between primary care, eye care and population health systems.
The science is moving fast, but health care systems and reimbursement models haven’t caught up yet. Once those pieces align, oculomics has the potential to quietly improve how we detect and manage disease — starting with the part of the body we already look at every day.
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