BACKGROUND: An increasing number of patients suffering from diabetes require regular ophthalmological check-ups to diagnose and/or treat potential diabetic retinal disease. Some countries have already implemented systematic fundus assessments including artificial intelligence-based programs in order to detect sight-threatening retinopathy. The aim of this study was to improve the detection of diabetic fundus changes in Germany without examination by a doctor and to create an easy access to ophthalmological examinations. MATERIAL AND METHODS: In this prospective monocentric study 93 patients in need for a routine check-up for diabetic retinopathy were included. The study participants took up an offer of an examination (visual examination, non-mydriatic camera-based fundus examination) without doctor-patient contact. Patient satisfaction with the organization and examinations was assessed using a questionnaire. RESULTS: The mean age was 53.5 years (SD 13.6 years, 49.5% female) and 17 eyes (18.3%) showed a diabetic retinopathy which was detected using a camera-based examination. Within the small sample, no patient had to repeat the examination due to poor image quality. All categories of the questionnaire showed a good to very good satisfaction, indicating a high acceptance of the other examination form that took place at the ophthalmologist's premises. CONCLUSION: In our study in an ophthalmological practice a high level of acceptance among the patients interested in the screening for diabetic retinopathy without any direct patient-doctor contact was achieved. Our study shows a very good acceptance and feasibility. Future use of artificial intelligence in clinical practice may help to be able to screen many more patients as in this study imaging quality was very good.      «

BACKGROUND: An increasing number of patients suffering from diabetes require regular ophthalmological check-ups to diagnose and/or treat potential diabetic retinal disease. Some countries have already implemented systematic fundus assessments including artificial intelligence-based programs in order to detect sight-threatening retinopathy. The aim of this study was to improve the detection of diabetic fundus changes in Germany without examination by a doctor and to create an easy access to ophth...     »