Study Shows High Patient Satisfaction with AI Eye Screenings

Eye care nonprofit Orbis International announces new findings supporting the use of artificial intelligence (AI) to detect diabetic retinopathy in patients; anyone with diabetes is at risk of developing the condition, which can lead to irreversible blindness. Conducted in Rwanda in partnership with the Rwanda International Institute of Ophthalmology, the study demonstrates that AI-based screening for diabetic retinopathy is not only feasible at diabetes clinics in sub-Saharan Africa, but also leads to high levels of patient satisfaction. Published in the British Journal of Ophthalmology, this is one of the first clinical studies on the practical applications of AI in diabetic retinopathy screening in Africa.

"This study has the potential to make a big impact for patients with diabetes in Africa," says Dr. Ciku Mathenge, Medical Advisor for Orbis International and the study's principal investigator. "In the study, we found that most patients had not had a recent full eye exam despite worrying about their vision and knowing their risks for developing diabetic retinopathy. Our research findings show that access to easy-to-use and conveniently located screening technologies allows patients to get the care they need and to prevent vision loss or blindness from diabetic retinopathy. The key now will be to ensure that such technologies become affordable and accessible to all."

The study looked at the satisfaction levels of patients screened for diabetic retinopathy and other eye conditions using Orbis's Cybersight AI tool. The screenings were conducted during routine appointments at four diabetes clinics in and near Kigali, Rwanda, in 2021.

The research found that patient satisfaction with AI screening was high, at over 99%. More than 63% of the study participants preferred AI over human graders. Factors that may have contributed to high participant satisfaction include:

• Receiving the exam during their diabetes appointment, as opposed to scheduling a separate appointment with an eye clinic, saved time and the cost of travel, an important barrier for rural patients, who composed nearly half the participants.
• The AI screening model was integrated into the existing workflow at the four diabetes clinics where the study took place.
• Most patients were not required to have their pupils dilated to undergo AI screening, which reduces time commitment and avoids temporarily blurred vision.
• Printed reports, available immediately during the screening, provided an opportunity for patients to learn about the condition and their risks while at their appointment, as opposed to waiting for delayed reporting from human grading.
• The study showed Cybersight AI performed well and led to accurate referrals from diabetes clinics.

Diabetes is on the rise globally, and diabetic retinopathy is the leading cause of vision loss among working-age people around the world. Recent reports show the prevalence of diabetic retinopathy is increasing in sub-Saharan Africa, more than in any other region. Access to diabetic retinopathy screening is critical to preventing visual impairment as most patients with diabetes do not realize they have the disease until their vision is already affected irreversibly. Low-resource settings, such as Rwanda, lack the infrastructure and trained personnel to implement the screenings effectively.

There is an extremely low number of eye doctors in sub-Saharan Africa, averaging 3.7 ophthalmologists per 1 million people. Training other medical personnel to conduct diabetic retinopathy screenings is an alternative and effective model in low- and middle-income countries that also preserves ophthalmologists' time for care only they can manage. AI makes the screening process accessible for medical personnel and patients alike in non-ophthalmic settings.

"It was like a miracle," said Etienne Uwingabire, Senior Nurse and Director of the Rwanda Diabetes Association, after receiving the AI screening camera at the clinic in Kigali. "This camera gives a direct response, and the patient is very happy to know the status of their eyes."

Uwingabire and the diabetes clinic team spent two sessions learning how to use the camera. Uwingabire is now able to supervise other members of the clinic in the use of the technology.

"Anyone can do it [AI screening] with the training," said Dr. Raban Susabimana, a medical doctor at the Rwanda Diabetes Association clinic who recently completed his residency and was trained to use the AI camera. "It cannot take a long time at all to learn how it works."

Orbis's new study is a follow-up to one the organization published last year in Ophthalmology Science showing that AI screening led to patients' increased uptake of diabetic retinopathy referral services.