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<jats:title>Abstract</jats:title> <jats:sec> <jats:title>Study Objectives</jats:title> <jats:p>To examine the cost-effectiveness and potential net monetary benefit of a fully automated digital cognitive behavioral therapy (CBT) intervention for insomnia compared with no insomnia treatment in the United States (US). Similar relative comparisons were made for pharmacotherapy and clinician-delivered CBT (individual and group).</jats:p> </jats:sec> <jats:sec> <jats:title>Methods</jats:title> <jats:p>We simulated a Markov model of 100,000 individuals using parameters calibrated from the literature including direct (treatment) and indirect costs (e.g., insomnia-related healthcare expenditure, lost workplace productivity). Health utility estimates were converted into quality-adjusted life years (QALYs) and one QALY was worth $50,000. Simulated individuals were randomized equally to one of five arms (digital CBT, pharmacotherapy, individual CBT, group CBT or no insomnia treatment). Sensitivity was assessed by bootstrapping the calibrated parameters. Cost estimates were expressed in 2019 US dollars.</jats:p> </jats:sec> <jats:sec> <jats:title>Results</jats:title> <jats:p>Digital CBT was cost-beneficial when compared with no insomnia treatment and had a positive net monetary benefit of $681.06 (per individual over 6-months). Bootstrap sensitivity analysis demonstrated that the net monetary benefit was positive in 94.7% of simulations. Relative to other insomnia treatments, digital CBT was the most cost-effective treatment because it generated the smallest incremental cost-effectiveness ratio (-$3,124.73).</jats:p> </jats:sec> <jats:sec> <jats:title>Conclusions</jats:title> <jats:p>Digital CBT was the most cost-effective insomnia treatment followed by group CBT, pharmacotherapy, and individual CBT. It is financially prudent and beneficial from a societal perspective to utilize automated digital CBT to treat insomnia at a population scale.</jats:p> </jats:sec>

Original publication

DOI

10.1093/sleep/zsaa223

Type

Journal article

Journal

Sleep

Publisher

Oxford University Press (OUP)

Publication Date

05/11/2020