Identifying Incident Proliferative Diabetic Retinopathy Using EHR Data: A Comparison of Methods

Music City Center 

Proliferative Diabetic Retinopathy (PDR), the advanced stage of diabetic retinopathy (DR), causes abnormal retinal vessel growth and vision loss. Accurately identifying incident PDR in electronic health records is important for disease monitoring and evaluating interventions. This study evaluates classification methods for identifying incident PDR cases, using the UCSF De-identified Clinical Data Warehouse. Patients aged ≥ 18 with at least one DR diagnosis by an eye provider and available de-identified clinical notes were included. 321 patients were randomly selected for chart review by an ophthalmologist (gold standard), confirming 158 PDR cases. Six methods were evaluated: first ICD9/10 code with no lookback period, first ICD9/10 with a one-year lookback period in any department, first ICD9/10 with a one-year lookback period in ophthalmology, rule-based NLP on clinical notes, best-performing ICD9/10 method with NLP, and a generative AI model. Each method will be compared against the gold standard using sensitivity, specificity, PPV, NPV, and F1 score. The proposed methodologies will provide insights into the use of structured and unstructured data for identifying incident PDR.

Electronic Health Records (EHR)

Ophthalmology

Incident Disease 

Section on Statistics in Epidemiology