Diabetes and age-related eye diseases are common reasons people lose their vision in the United States. According to the Centers for Disease Control and Prevention (CDC), about 37 million Americans have diabetes, and nearly 96 million more have prediabetes. Diabetic retinopathy can cause blindness if it is not found or treated in time. People in underserved groups, especially Latino/x communities, have higher risks and face more challenges getting eye screenings.
An example is the LifeLong Medical Care health center in Richmond, California. Before using AI tools, fewer than 10% of diabetic patients there got yearly diabetic retinopathy screenings. This low rate is common in many community clinics in the US because of transportation problems, language differences, and complex healthcare systems.
New technology is making it easier and more accurate to diagnose eye diseases. Spect, a Silicon Valley start-up, made a small eye exam device that uses an iPhone with a special camera to check for diabetes eye problems right in primary care clinics. Medical assistants or doctors can take good retinal pictures without a specialist nearby.
Clinics using Spect have seen big improvements. At the Richmond clinic, diabetic eye exam rates went from 10% to 40% in one year. Specialists help by reviewing images remotely and giving reports quickly. This lets primary care providers offer screenings without knowing a lot about eye diseases while still making sure patients get care.
The California Health Care Foundation gave $475,000 to Spect’s technology to help people in underserved, mainly monolingual Latino/x areas, many living in rural places. Non-specialized staff can run the device, which lowers costs and makes screening easier and possible on a larger scale.
Besides portable devices in clinics, new home-based systems let people check their eyes often without visiting the doctor. For diseases like age-related macular degeneration (AMD), especially the wet form (nAMD), finding problems early is very important to avoid vision loss. These home devices use AI and remote retinal imaging to watch disease progress outside the clinic.
One example is the ForeseeHome system by Notal Vision, which the FDA approved and Medicare covers. ForeseeHome uses AI to detect early changes when intermediate AMD turns into nAMD. A clinical trial with over 1,500 patients showed it works well and stopped early because of clear benefits. Patients using ForeseeHome kept their vision much more often than those with usual care.
Nearly 40,000 patients across the country have used this system for remote monitoring. Other tools include myVisionTrack, a mobile app finding small visual changes, and Heru Prime, a wearable device that cuts exam times by about one-third. These tools help patients watch their eye health more often with AI support, making treatments more timely.
AI not only helps doctors make faster diagnoses but can also find other health problems besides eye diseases. Machine learning can look at retinal images and find signs for conditions like heart disease, Parkinson’s, and early Alzheimer’s.
Dr. Michael Leung from Spect called the eye a “check engine light of the body.” The retina shows unique details about blood vessels and nerves. This means AI could turn eye exams into a way to check overall health in primary care.
New AI programs approved by the FDA, like LumineticsCore and EyeArt, show better accuracy and speed for diabetic retinopathy screening. These systems help doctors by grading images automatically, making clinics run smoother and patients get care sooner.
AI also changes how clinics work every day. For medical leaders and IT teams, using AI can cut down paperwork, move patients through faster, and improve how clinics run.
In eye care, AI can analyze images, spot urgent cases, set appointments, and help with referrals. This helps clinics handle more patients without lowering care quality.
Remote monitoring centers have specialists who review AI alerts. This model fits well with normal clinic work and lets providers care for more patients without overloading staff.
Spect’s system gives real-time virtual support so people without eye specialist training can perform eye exams. Home OCT devices with AI allow patients to scan their eyes by themselves, helping create personalized treatment plans for nAMD.
Despite the good points, there are challenges to using AI and home tools widely. Keeping data private and linking AI data to electronic health records (EHRs) are big issues. Clinics must follow HIPAA rules while using AI results in their daily work.
Clinician trust and training are also key. Dr. Eric Topol said AI should be a “co-pilot” for doctors, not replace them. Clear AI decisions and continuous checks with real-world data help build trust among healthcare workers.
Also, health differences between groups remain. Systems need to work for many kinds of patients, including people who speak only one language or face money challenges. Investments like those by the California Health Care Foundation in Spect show how important it is to build fair systems that suit all.
For clinic leaders and owners in the US, using AI-powered, portable, and home-based eye tools can improve care and results. These tools help lower vision loss in patients with diabetes and retinal diseases.
Using portable AI tools in primary care can make diabetic retinopathy screening faster, raise patient follow-up, and reach people who miss specialty visits. Home monitoring fits with telehealth and value-based care, putting patients at the center.
IT managers are important in connecting these tools to clinic systems, keeping data safe, and enabling smooth communication between providers and remote services. Training front office and clinical staff well will help clinics get the most benefits from these new technologies.
Eye health monitoring in the United States is changing because of AI and new devices. As healthcare moves toward easier, more predictive, and patient-friendly care, eye doctors and their teams must learn about and get ready for these changes to serve patients well. When used carefully, these advances can find eye diseases early, reduce vision loss, improve clinics, and provide better care for many people across the country.
Access and transportation challenges were significant barriers, particularly for a predominantly monolingual Latino/x population. Many patients felt uncomfortable navigating the healthcare system outside their community clinic and reported issues like lack of reliable transportation and time off from work.
Spect enabled in-house diabetes eye screenings using a portable device, allowing clinics to perform exams on-site. Within a year of implementation, screening rates at LifeLong Medical Care increased from about 10% to 40%.
Spect utilizes a specialized camera attached to an iPhone, enabling medical assistants or physicians to conduct eye exams with remote assistance from a virtual team that analyzes the images and provides reports.
The investment aims to increase equitable access to diabetes eye exams, particularly for underserved demographics such as Latino/x and those on Medi-Cal, reducing long-term complications of diabetes.
Providers receive real-time guidance and support from Spect technicians during eye exams. After image capture, ophthalmologists analyze the images and send diagnostic reports, simplifying the process for primary care providers.
Undiagnosed diabetic retinopathy can lead to preventable vision loss and blindness, exacerbating other serious diabetes complications such as cardiovascular disease and kidney failure.
Spect aims to leverage AI to detect other health conditions beyond diabetic retinopathy, including neurodegenerative diseases and cardiovascular risks, enhancing its role in preventive health.
Portable devices like Spect’s camera reduce reliance on stationary and expensive equipment, enabling community clinics to provide essential services directly to patients, thereby increasing healthcare accessibility.
Spect’s founders envision a future where eye screening devices are common in households, allowing individuals to monitor their eye health and potentially detect other health issues early.
Spect’s approach allows primary care providers to address multiple health issues during a single visit, promoting comprehensive care that aligns with value-based care goals to improve patient outcomes.
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