Publication date: Sep 09, 2025
This study aimed to evaluate the diabetic eye disease screening continuum at two academic centers and identify its barriers. We analyzed health records from the University of California, San Francisco and University of California, Irvine to identify primary care patients needing diabetic eye screening. We tracked referrals, screenings, diagnoses, and treatments to evaluate predictors and the impact of an automated referral system. We analyzed physician notes using GPT-4o to determine reasons for missed screenings. Of 8,240 unscreened patients with type 2 diabetes mellitus (T2DM), 43% received a referral, and only 16% completed screening within 1 year. Demographic, provider, and socioeconomic factors predicted adherence, with referrals being the strongest predictor. An automated referral system could improve screening rates to 22-34%. Clinician notes cited comorbidities, scheduling challenges, logistical issues, coronavirus disease 2019, and personal circumstances as barriers. Many patients with T2DM remain unscreened after primary care visits. Although an automated referral system may partially improve adherence, additional tailored strategies are needed.
| Concepts | Keywords |
|---|---|
| Academic | Analyzed |
| California | Automated |
| Coronavirus | Barriers |
| Diabetes | California |
| T2dm | Care |
| Diabetic | |
| Evaluate | |
| Eye | |
| Identify | |
| Primary | |
| Referral | |
| Referrals | |
| Screening | |
| Screenings | |
| System |
Semantics
| Type | Source | Name |
|---|---|---|
| disease | MESH | eye disease |
| disease | MESH | type 2 diabetes mellitus |
| disease | MESH | coronavirus disease 2019 |