Long-Term Cost and Health Impact of a Digital Obesity Intervention in Germany: Economic Modeling Study

Obesity imposes a substantial economic burden, accounting for an estimated 10% of total health care expenditures in Germany. Digital health apps (DHAs) have demonstrated effectiveness in supporting weight management among individuals with obesity; however, evidence regarding their long-term economic impact remains limited.

This study aimed to evaluate the long-term cost-effectiveness of the Oviva Direkt app for obesity treatment in the German health care context.

We developed a cohort-based Markov model, informed by the Core Obesity Model, to evaluate the cost-effectiveness of a DHA for weight management vs care as usual over a 10-year time horizon from a societal perspective. The model simulates disease progression using 6-month and annual cycles after an initial 6-week phase and includes health states for key obesity-related comorbidities such as type 2 diabetes (T2D), acute coronary syndrome, stroke, cancer, and obstructive sleep apnea. Patients enter the model at age 46 years with a BMI of 30 to 45 kg/m², based on trial data. The analysis considered direct and indirect costs, life-years, and quality-adjusted life-years (QALYs). The primary outcome was the incremental cost-effectiveness ratio, complemented by net monetary benefit analysis. Weight trajectories were extrapolated from trial results using 3 scenarios (base-case decay model, weight maintenance, and full regain). Sensitivity analyses were conducted to assess uncertainty.

Under base-case assumptions, the DHA dominated care as usual, yielding cost savings of €3511.85 (€1=US $1.127 as of May 2025) and a QALY gain of 0.0683 (approximately 3.6 weeks in perfect health). Direct medical costs were reduced by nearly €520. The prevalence of T2D was 1.6 percentage points lower, reducing time lived with diabetes by 8 months. Scenario analyses confirmed consistent cost-effectiveness.

DHAs for weight management are cost-effective and clinically beneficial for individuals with obesity in Germany. These results add to the growing evidence for digital health solutions, aligning with findings from applications for other conditions such as depression and multiple sclerosis.