AI Eye Screening Can Revolutionize Diabetic Retinopathy Detection and Prevention

Diabetic retinopathy (DR), a disorder that damages the retina and can cause blindness or vision loss if untreated, is a risk factor for people with diabetes. DR needs periodic screening so that alterations can be observed before the emergence of the symptoms. Nevertheless, not all patients get these screenings, especially those who attend federally qualified health centres (FQHCs). Some of the problems they experience include long queues, hard travelling, lack of insurance and complexity of referral procedures.

The Diabetic Retinopathy Screening Point-of-Care Artificial Intelligence (DRES-POCAI) trial was developed by the researchers to address this gap by examining how AI will accelerate and make the screening of the eyes simpler and more accessible (1^✔ ✔Trusted Source
Autonomous Artificial Intelligence in Diabetic Retinopathy Testing-Lessons Learned on Successful Health System Adoption

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AI-Powered Screening System To Ease Diabetic Retinopathy Screening

EyeArt is an FDA-approved AI-based screening tool, used in the DRES-POCAI study, which is capable of identifying early and advanced stages of DR using simple retinal images, without necessarily having to visit an eye specialist. Since the system is directly incorporated into primary care clinics, patients can be screened in the course of doctor visits.

The AI system examines retinal images immediately and sends the results to the electronic health record (EHR) using a specialised non-dilating camera. The results create an automatic risk-based referral whereby the patients with ungradable or positive results are referred to an eye specialist, and the patients with normal results will continue with a follow-up screening.

Researchers are evaluating how well this AI-based model works to improve early detection of DR and boost screening completion rates, expedite referrals, and enhance patient satisfaction and confidence in the care process.

By offering on-the-spot eye screening, DRES-POCAI could:

• Save time and costs for both patients and clinics
• Prevent vision loss by catching disease earlier
• Reduce missed referrals and follow-up failures
• Support healthcare teams by streamlining workflow

By lowering burnout, boosting productivity, and integrating screening results into clinical workflows, it also benefits primary care doctors. This approach aligns with the healthcare quadruple aim.

References:

1. Autonomous Artificial Intelligence in Diabetic Retinopathy Testing—Lessons Learned on Successful Health System Adoption - (https://www.ophthalmologyscience.org/article/S2666-9145(25)00233-7/fulltext)

Source-Ophthalmology Science