Cost-effectiveness of digital cognitive behavioral therapy (Sleepio) for insomnia: a Markov simulation model in the United States.

Journal Article (Journal Article)

STUDY OBJECTIVES: To examine the cost-effectiveness and potential net monetary benefit (NMB) 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). METHODS: 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 and 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. RESULTS: Digital CBT was cost beneficial when compared with no insomnia treatment and had a positive NMB of $681.06 (per individual over 6 months). Bootstrap sensitivity analysis demonstrated that the NMB 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). CONCLUSIONS: 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.

Full Text

Duke Authors

Cited Authors

  • Darden, M; Espie, CA; Carl, JR; Henry, AL; Kanady, JC; Krystal, AD; Miller, CB

Published Date

  • April 9, 2021

Published In

Volume / Issue

  • 44 / 4

PubMed ID

  • 33151330

Electronic International Standard Serial Number (EISSN)

  • 1550-9109

Digital Object Identifier (DOI)

  • 10.1093/sleep/zsaa223

Language

  • eng

Conference Location

  • United States