The setup can be placed in any dimly lit room, and patients place their face on the chin and forehead rests and stare into the camera while a technician takes images of each eye.

The American Diabetes Association recommends that people with Type 2 diabetes get screened every one to two years, yet only about 60% of people living with diabetes get yearly eye exams, said Robert Gabbay, the ADA’s chief scientific and medical officer. The rates can be as low as 35% for people with diabetes age 21 or younger.

In swaths of the U.S., a shortage of optometrists and ophthalmologists can make appointments hard to schedule, sometimes booking for months out. Plus, the barriers of traveling to an additional appointment to get their eyes dilated — which means time off work or school and securing transportation — can be particularly tricky for low-income patients, who also have a higher risk of Type 2 diabetes.

“Ninety percent of our patients are blue-collar,” said Espinoza of his Southern California clinics, which largely serve minority populations. “They don’t eat if they don’t work.”

One potential downside of not having a doctor do the screening is that the algorithm solely looks for diabetic retinopathy, so it could miss other concerning diseases, like choroidal melanoma, Lee said. The algorithms also generally “err on the side of caution” and over-refer patients.

But the technology has shown another big benefit: Follow-up after a positive result is three times as likely with the AI system, according to a recent study by Stanford University.

That’s because of the “proximity of the message,” said David Myung, an associate professor of ophthalmology at the Byers Eye Institute at Stanford. When it’s delivered immediately, rather than weeks or even months later, it’s much more likely to be heard by the patient and acted upon.

Myung launched Stanford’s automated teleophthalmology program in 2020, originally focusing on telemedicine and then shifting to AI in its Bay Area clinics. That same year, the National Committee for Quality Assurance expanded its screening standard for diabetic retinopathy to include the AI systems.

Myung said it took about a year to sift through the Stanford health system’s cybersecurity and IT systems to integrate the new technology. There was also a learning curve, especially for taking quality photos that the AI can decipher, Myung said.

“Even with hitting our stride, there’s always something to improve,” he added.

...continued

©2024 KFF Health News. Distributed by Tribune Content Agency, LLC.