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 LookAHEAD (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 decrementswere for stroke (event,20.109; history,20.051 amputation(event,20.092;history,20.150),congestiveheart failure(event,20.051; history, 20.041), dialysis (event, 20.039), estimated glomerular filtration rate (eGFR)<30mL/min/1.73m2 (event,20.043; history,20.025), angina (history,20.028), and myocardial infarction (MI) (event, 20.028). 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.