Patient Health Utility Equations for a Type 2 Diabetes Model

OBJECTIVE: To estimate the health utility impact of diabetes-related complications in a large, longitudinal U.S. sample of people with type 2 diabetes. RESEARCH DESIGN AND METHODS: We combined Health Utilities Index Mark 3 data on patients with type 2 diabetes from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) and Look AHEAD (Action for Health in Diabetes) trials and their follow-on studies. Complications were classified as events if they occurred in the year preceding the utility measurement; otherwise, they were classified as a history of the complication. We estimated utility decrements associated with complications using a fixed-effects regression model. RESULTS: Our sample included 15,252 persons with an average follow-up of 8.2 years and a total of 128,873 person-visit observations. The largest, statistically significant (P < 0.05) health utility decrements were for stroke (event, -0.109; history, -0.051), amputation (event, -0.092; history, -0.150), congestive heart failure (event, -0.051; history, -0.041), dialysis (event, -0.039), estimated glomerular filtration rate (eGFR) <30 mL/min/1.73 m2 (event, -0.043; history, -0.025), angina (history, -0.028), and myocardial infarction (MI) (event, -0.028). There were smaller effects for laser photocoagulation and eGFR <60 mL/min/1.73 m2. Decrements for dialysis history, angina event, MI history, revascularization event, revascularization history, laser photocoagulation event, and hypoglycemia were not significant (P ≥ 0.05). CONCLUSIONS: With use of a large study sample and a longitudinal design, our estimated health utility scores are expected to be largely unbiased. Estimates can be used to describe the health utility impact of diabetes complications, improve cost-effectiveness models, and inform diabetes policies.