Journal article
Autonomous artificial intelligence for diabetic eye disease increases access and health equity in underserved populations
NPJ digital medicine, Vol.7(1), 196
07/22/2024
DOI: 10.1038/s41746-024-01197-3
PMCID: PMC11263546
PMID: 39039218
Abstract
Diabetic eye disease (DED) is a leading cause of blindness in the world. Annual DED testing is recommended for adults with diabetes, but adherence to this guideline has historically been low. In 2020, Johns Hopkins Medicine (JHM) began deploying autonomous AI for DED testing. In this study, we aimed to determine whether autonomous AI implementation was associated with increased adherence to annual DED testing, and how this differed across patient populations. JHM primary care sites were categorized as “non-AI” (no autonomous AI deployment) or “AI-switched” (autonomous AI deployment by 2021). We conducted a propensity score weighting analysis to compare change in adherence rates from 2019 to 2021 between non-AI and AI-switched sites. Our study included all adult patients with diabetes (>17,000) managed within JHM and has three major findings. First, AI-switched sites experienced a 7.6 percentage point greater increase in DED testing than non-AI sites from 2019 to 2021 (p < 0.001). Second, the adherence rate for Black/African Americans increased by 12.2 percentage points within AI-switched sites but decreased by 0.6% points within non-AI sites (p < 0.001), suggesting that autonomous AI deployment improved access to retinal evaluation for historically disadvantaged populations. Third, autonomous AI is associated with improved health equity, e.g. the adherence rate gap between Asian Americans and Black/African Americans shrank from 15.6% in 2019 to 3.5% in 2021. In summary, our results from real-world deployment in a large integrated healthcare system suggest that autonomous AI is associated with improvement in overall DED testing adherence, patient access, and health equity.
Details
- Title: Subtitle
- Autonomous artificial intelligence for diabetic eye disease increases access and health equity in underserved populations
- Creators
- Jane J. Huang - Johns Hopkins University School of MedicineRoomasa Channa - University of Wisconsin–MadisonRisa M. Wolf - Johns Hopkins UniversityYiwen Dong - Johns Hopkins UniversityMavis Liang - Johns Hopkins UniversityJiangxia Wang - Johns Hopkins UniversityMichael D. Abramoff - University of IowaT. Y. Alvin Liu - Johns Hopkins Medicine
- Resource Type
- Journal article
- Publication Details
- NPJ digital medicine, Vol.7(1), 196
- Publisher
- Nature Publishing Group UK
- DOI
- 10.1038/s41746-024-01197-3
- PMID
- 39039218
- PMCID
- PMC11263546
- ISSN
- 2398-6352
- eISSN
- 2398-6352
- Language
- English
- Date published
- 07/22/2024
- Academic Unit
- Electrical and Computer Engineering; Fraternal Order of Eagles Diabetes Research Center; Ophthalmology and Visual Sciences
- Record Identifier
- 9984658286102771
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