The EHR-Driven Dysglycemia Risk Score (D-RISK) Predicts Future Development of Type 2 Diabetes

OBJECTIVE To evaluate whether the electronic health record (EHR)-derived Dysglycemia Risk Score (D-RISK), previously validated for detecting prevalent, undiagnosed diabetes and prediabetes, predicts future development of type 2 diabetes over 5 years. RESEARCH DESIGN AND METHODS We used baseline data from a cross-sectional diabetes screening study (2015–2017) to predict future development of diabetes using Cox proportional hazards models. Adults without diabetes were included and followed using EHR data through October 2024. D-RISK (age, race and ethnicity, BMI, hypertension, and random blood glucose) was calculated using baseline EHR data. Incident type 2 diabetes was identified using a validated computable phenotype requiring two or more criteria (HbA1c ≥6.5%, diagnostic codes, or glucose-lowering prescriptions). Predictive performance of D-RISK was compared with U.S. Preventive Services Task Force (USPSTF) and American Diabetes Association (ADA) guidelines and the ADA Risk Test. RESULTS Among 502 participants (mean age 47.5 years, 69.9% female, 68.5% Hispanic), 12% developed type 2 diabetes over a mean follow-up of 5.8 years. The area under curve for D-RISK was 0.67 (95% CI 0.53–0.80) to predict incident type 2 diabetes. A D-RISK score ≥10 predicted a 7.8% 5-year risk of developing type 2 diabetes (hazard ratio [HR] 2.56, 95% CI 1.06–6.17). Performance was similar to the ADA Risk Test (≥5 points) (HR 2.32, 95% CI 1.01–5.30) and superior to the USPSTF (HR 1.6, 95% CI 0.55–4.68) and ADA (HR 0.60, 95% CI 0.08–4.44) screening guidelines. CONCLUSIONS D-RISK predicts future type 2 diabetes using routinely available EHR data. Its ability to both detect prevalent dysglycemia and forecast incident type 2 diabetes may support system-level diabetes risk assessment and screening.