An economic evaluation of diabetic retinopathy screening among children revealed that autonomous artificial intelligence (AI) is a cost-effective strategy compared with standard examination by an eye care professional (ECP), according to an article published in JAMA Ophthalmology.
The study used decision analysis to model the cost-effectiveness of detecting and treating diabetic retinopathy and its sequelae among children with type 1 and type 2 diabetes. The parameters included out-of-pocket cost for autonomous AI screening, ophthalmology visits, and treating diabetic retinopathy, as well as the diagnosability of the ECP screening examination and autonomous AI screening.
The main outcomes were costs or savings to the patient and cost-effectiveness associated with the number of true-positive results identified by diabetic retinopathy screening.
The results found an incremental cost-effectiveness ratio of €26* for type 1 diabetes and €80* for type 2 diabetes for each additional case of diabetic retinopathy identified compared with standard practice. Furthermore, when more than 23 per cent of patients adhere to diabetic retinopathy screening recommendations, autonomous AI screening is the preferred strategy and delivers cost-saving for the patient.
Using point-of-care diabetic retinopathy screening using autonomous AI systems will increase screening rates, thus improving care and providing early identification of disease, the study authors say.
*converted from USD$.