Cost-effectiveness of automated digital CBT (Daylight) for generalized anxiety disorder: A Markov simulation model in the United States

Abstract

This study examines the cost-effectiveness and cost-benefit of a fully automated smartphone-delivered digital cognitive behavioral therapy (CBT) intervention for Generalized Anxiety Disorder (GAD). In a simulated Markov model, 100,000 individuals with GAD were studied under one of five (n = 20,000 per arm) treatments (digital CBT [Daylight], individual CBT, group CBT, pharmacotherapy, or no GAD treatment). Model inputs were determined from the literature and included direct treatment costs and disease costs. Net monetary benefit (NMB) determined whether digital CBT is cost-beneficial from both a private payer and societal perspective in the United States in 2020. Digital CBT was found to generate the lowest 12-month total cost ($167.02m) and the second highest number of total quality-adjusted life years (14,711.86). Digital CBT showed a positive NMB relative to each alternative treatment and to no treatment for GAD in both a payer and societal perspective. Relative to no treatment, the average NMB of digital CBT was $1,836.83 from the payer perspective and $4,126.88 from the societal perspective. Digital CBT generates the most value in both a payer and societal perspective, and results were robust to sensitivity analysis with respect to effectiveness, pricing, and attrition parameters.