261-OR: Autonomous Artificial Intelligence (AI) Testing for Diabetic Eye Disease (DED) Closes Care Gap and Improves Health Equity on a Systems Level Free

We aimed to examine the change in adherence to annual diabetic eye disease (DED) testing in an integrated healthcare system (Johns Hopkins Community Physicians 30+ community based primary care clinics) before and after deployment of autonomous artificial intelligence (AI). Adherence to annual DED testing is defined as completed evaluation by either a human ophthalmology provider, or autonomous AI within a given calendar year. During the COVID pandemic, autonomous AI (IDx-DR, Digital Diagnostics, Coralville, IA) was deployed at multiple clinics, so that by 2021, some clinics had autonomous AI (AI sites), while others did not (non-AI sites). Overall adherence in 2019 (pre-AI) and 2021 (with AI) were compared, and stratified by demographics, using chi-square or Fisher’s exact test. Changes from 2019 to 2021 in odds of adherence within each subgroup were assessed for significant differences by site type (AI vs. non-AI), using logistic regression with a site type-by-time interaction term. From 2019 to 2021, the overall adherence rate increased from 42.6% to 55.5% at AI sites (1949 patients), and increased from 38.0% to 41.0% at non-AI sites (5379 patients). The increase in overall adherence rate at AI sites was significantly greater than that at non-AI sites (p<0.001). Various patient subgroups (M, F, ≥65 yo, <65 yo, Black, White, Medicare/military/commercial insurance) at AI sites demonstrated a significantly greater (p<0.05) compliance rate increase when compared to the same subgroups at non-AI sites. For Black patients, there was no difference in adherence rate between AI sites and non-AI sites (38.5% vs. 37.1%, p=0.45) in 2019, but the difference became significant (p<0.001) in 2021 due to increased adherence at the AI sites (58.0%) vs. 38.8% at non-AI sites. Autonomous AI improved DED testing adherence in a large, diverse patient cohort and decreased disparity in Black patients, a historically-disadvantaged subgroup.