Screening strategy in ocular diabetes with automatic detection system in the Chilean public health system

Abstract

Summary: Diabetic retinopathy (DR) is the leading cause of blindness among working-age persons in high-income countries. A public system strategy was developed to improve screening, using telemedicine, automatic detection using artificial intelligence (A/I) and medical reporting. In the current work, we evaluated program efficiency. Material: We conducted a cross-sectional study using information from an institutional database of retinographies submitted to the A/I platform in 2019. With a positive test, a medical report was made using the international scale. Results: In 2019, 220,994 retinographies were reported, corresponding to 24.0% of diabetic patients. Around half (53.0%) of cases were discarded by A/I, being different in each regional health service. The medical analysis discarded diabetic retinopathy in 30.2% of exams, 11.5% had diabetic retinopathy, including 2.3% with risk of blindness, while 3.7% could not be evaluated. Discussion: The use of A/I allowed optimizing the medical resources, discarded 53% of cases, which helped in the screening of diabetic retinopathy. Coverage is still insufficient, and detection of macular edema must be improved.

Keywords

• automatic detection
• diabetic retinopathy
• screening