Advancing Diabetic Retinopathy Screening with AI and Telemedicine

Early detection of diabetic retinopathy is essential in preventing vision loss, yet access to specialized care remains limited.

To address this challenge, the Retina Read Risk project is transforming screening by integrating artificial intelligence (AI) and telemedicine solutions, making early diagnosis more efficient and widely accessible.

To test its feasibility, the RRR program was introduced in five primary care centers with two fully incorporating it into their daily practice. This implementation enabled the screening of 9,676 patients, among whom 774 were diagnosed with diabetic retinopathy, while 424 required further testing. By equipping primary care settings with advanced diagnostic tools, the project is narrowing the gap between patients and specialized ophthalmological care.

At the core of this initiative lies innovative technology that makes screening more accurate and accessible.

The Aurora retinal camera enables high-quality imaging without the need for pupil dilation, significantly reducing the chances of misdiagnosis.

To reach more patients, especially in rural or undeserved areas, VistaView mobile devices have been deployed.

To further refine diagnostic capabilities, AI-driven image analysis algorithms are constantly learning from thousands of retinal scans, allowing for personalized patient monitoring based on the severity and progression of the disease.

Before RRR, only 33% of patients had access to specialized diabetic retinopathy centers. With its implementation, this rate is expected to rise to 72%, ensuring faster, more effective care.

By reducing unnecessary consultations and improving patient management, the project could save up to €10 million in healthcare costs. This is made possible through the integration of RRR with telemedicine, enabling better coordination between healthcare professionals and optimizing patient management.

While patients have embraced the project, the integration of AI in healthcare brings key ethical and regulatory considerations.

Ensuring data confidentiality, securing communication, and conducting impact assessments are key steps in making this technology sustainable.