Patient Health Utility Equations for a Type 2 Diabetes Model

Abstract

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) 2 (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 2. 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.