OBJECTIVES: To create a model for assessing the cost-effectiveness of chronic weight management interventions in a commercially insured adult population in the United States (US).

METHODS: This study adapted the Core Obesity Model (COM), a previously published and validated model, to evaluate chronic weight management interventions within the context of a large US payer. Most adapted model parameters and transition probabilities were derived from an analysis of the Healthcare Integrated Research Database, a retrospective US administrative claims database integrated with clinical data.

RESULTS: The COM, a closed-cohort Markov model, encompasses obesity-related health states, including prediabetes, type 2 diabetes (T2D), acute coronary syndrome (including myocardial infarction and angina), stroke, and cancer. Treatment effects are integrated through key health indicators, including body mass index (BMI), systolic blood pressure, high-density lipoprotein, total cholesterol, and hemoglobin A1c. Risk equations that include these indicators govern the transition between health states. The adapted model mirrors this structure but excludes cancer and prediabetes as distinct health states. It also incorporates treatment effects on new biomarkers (i.e., diastolic blood pressure, triglycerides, and fasting glucose). Finally, the model employs payor-specific risk equations tailored to the population of interest rather than relying on risk equations from previous cohorts. Patients in the population of interest (N = 1,209,646) are 43% male, with a mean age of 46 years and a mean BMI of 36 kg/m². Upon entering the model, 11% have T2D, and 7% have a history of cardiovascular disease.

CONCLUSIONS: The adapted model offers a robust framework to understand and quantify the effect of weight management interventions from the perspective of a large US commercial payor.