Rep. Miller-Meeks Backs Efforts to Expand AI-Driven Eye Exams for Diabetics in Rural America
Washington, D.C. – U.S. Representative Mariannette Miller-Meeks (IA-01), an ophthalmologist and longtime champion of healthcare innovation, applauded language included in the FY26 House Labor-HHS-Education Appropriations Report that promotes autonomous artificial intelligence (AI) for expanding diabetic eye care access in rural communities.
“Diabetic retinopathy is both preventable and treatable, yet millions of Americans—especially in rural areas—are not getting the annual eye exams they need,” said Dr. Miller-Meeks. “We must embrace FDA-cleared technologies like autonomous AI to close this dangerous gap, free up specialists to practice at the top of their license, and deliver earlier, better care to our constituents. I’m proud to help lead this effort in Congress.”
"We commend Representative Miller-Meeks for her leadership in advancing tools that can expand access to critical eye care services in rural communities," said Dr. Michael Repka, President, American Academy of Ophthalmology. "Her support for autonomous AI as a scalable, proven solution to increase diabetic retinopathy screenings is an important step and the Academy shares her commitment to reducing preventable vision loss nationwide."
Dr. Michael Abramoff, Founder of Digital Diagnostics, added:
"Thanks to Representative Miller-Meeks' leadership as both a lawmaker and ophthalmologist, Congress is recognizing the importance of empowering primary care providers to catch disease early with autonomous AI. This appropriations language marks an important milestone for health equity and AI innovation in the United States."
"President Trump’s Executive Order makes clear that American leadership in artificial intelligence must be backed by real-world applications that improve people’s lives. This report language supports the use of proven AI technology to help detect diabetic eye disease earlier and make care more accessible in rural areas. It is a practical step to improve screenings while strengthening local health systems and America’s leadership in next-generation technologies,” added Rep. Robert Aderholt (R AL), Chair, House Appropriations Subcommittee on Labor, Health and Human Services, and Education, and Related Agencies.
Background:
The report urges the Health Resources and Services Administration (HRSA) to support the deployment of FDA-cleared autonomous AI technology at Federally Qualified Health Centers (FQHCs) to address gaps in diabetic retinopathy screening—the leading cause of blindness among working-age adults. In 2024, more than 32 million patients received care at Federally Qualified Health Centers (FQHCs) across the country, according to HRSA’s Uniform Data System. This vast reach makes FQHCs a vital platform for expanding access to diabetic eye screenings through autonomous AI.
The provision builds on a Capitol Hill briefing hosted earlier this year by Rep. Miller-Meeks, featuring Dr. Michael Abramoff, a retina specialist and founder of Digital Diagnostics, the company behind LumineticsCore®, the first FDA-cleared autonomous AI system to make a medical diagnosis without physician involvement.
The appropriations language encourages HRSA to:
- Support FQHCs serving diabetic populations with low screening adherence
- Expand access to autonomous AI to improve screening rates
- Establish referral pathways from primary care to ophthalmologists
- Collaborate with physician specialty societies to ensure responsible deployment
This initiative supports President Trump’s 2025 Executive Order on Removing Barriers to American Leadership in Artificial Intelligence, which promotes the U.S. as a global AI leader by removing regulatory obstacles and deploying practical AI technologies in healthcare and other sectors.
The use of CPT® code 92229, created by the American Medical Association and now included on the Medicare Physician Fee Schedule, allows for FDA-cleared autonomous AI-based diabetic eye screening without a physician interpreting the images, reducing costs and administrative burdens.
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