Autonomous AI for diabetic eye disease at primary care improves ophthalmic access for at-risk patients

Abstract

We examined which subgroups of patients benefit the most from deployment of autonomous artificial intelligence (AI) for diabetic eye disease (DED) testing at primary care clinics through improved patient access to ophthalmic care. Patients (n = 3,745) were referred to ophthalmology either via standard of care (primary care provider placed a referral) or AI (referral was made after a positive or non-diagnostic autonomous AI result). Both groups presented with good vision (median best-corrected visual acuity BCVA of worse-seeing eye was Snellen 20/25), without significant difference in the presenting BCVA between both groups. BCVA was not associated with the referral pathway in multivariable regression analysis. However, patients from the AI referral pathway were more likely to be Black (p < 0.001) and have hypertension (p = 0.001), suggesting that deployment of autonomous AI is associated with improved ophthalmic access for patients with a higher baseline risk for poor DED outcome before vision loss has occurred.