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Accepted for/Published in: JMIR mHealth and uHealth

Date Submitted: Jan 25, 2025
Date Accepted: Dec 25, 2025

The final, peer-reviewed published version of this preprint can be found here:

Digital Cognitive Behavioral Therapy for Chronic Insomnia in South Korea: Cost-Effectiveness Analysis Using Decision Tree and Markov Modeling Based on a Secondary Analysis of a Randomized Clinical Trial

Kim JH, Sohn M, Woo J, Shin J, Han E

Digital Cognitive Behavioral Therapy for Chronic Insomnia in South Korea: Cost-Effectiveness Analysis Using Decision Tree and Markov Modeling Based on a Secondary Analysis of a Randomized Clinical Trial

JMIR Mhealth Uhealth 2026;14:e71750

DOI: 10.2196/71750

PMID: 41554115

PMCID: 12865351

Digital Cognitive Behavioral Therapy for Chronic Insomnia in South Korea: A Cost-Effectiveness Analysis Using Decision Tree and Markov Modeling Based on a Secondary Analysis of a Randomized Clinical Trial

  • Jung Hyun Kim; 
  • Minjeong Sohn; 
  • Jimin Woo; 
  • Jaeyong Shin; 
  • Euna Han

ABSTRACT

Background:

Insomnia, a prevalent sleep disorder characterized by difficulty initiating or maintaining sleep, has significant health and economic consequences, with its global prevalence rising, particularly during the COVID-19 pandemic. Cognitive behavioral therapy (CBT) is recommended as the first-line treatment, while pharmacotherapy, though widely used, is linked to adverse effects and increased indirect costs. Digital therapeutics, such as Somzz—a mobile application delivering CBT-based interventions—offer an innovative solution to address accessibility challenges and improve treatment outcomes.

Objective:

This study evaluates the cost-effectiveness of implementing Somzz, a commercial digital therapeutic for insomnia, compared to conventional treatments combining CBT and pharmacotherapy, within the South Korean healthcare system.

Methods:

A decision tree model simulated a cohort of 100,000 individuals in South Korea in 2023 to assess cost-effectiveness using quality-adjusted life years (QALYs) as the primary outcome measure. Both healthcare system and societal perspectives were analyzed, accounting for direct costs (e.g., consultations, medications) and indirect costs (e.g., absenteeism, productivity loss, workplace accidents). Participants were randomized to receive either digital CBT via Somzz or standard care. Clinical trials informed QALY derivations from the SF-6D Health State Short Form. Sensitivity analyses were conducted to validate incremental cost-effectiveness ratio (ICER) estimates by varying key parameters, including treatment costs, healthcare utilization, and workplace impacts. This comprehensive approach ensures a robust evaluation of the economic and clinical benefits of digital CBT in real-world settings.

Results:

Digital CBT modestly increased healthcare costs while improving health outcomes compared to standard care. Over a 6.5-month period, it produced an additional 0.0092 QALYs per patient at an incremental cost of 79,691 KRW, resulting in an ICER of 8,719,727 KRW per QALY gained—well below Korea's willingness-to-pay (WTP) threshold of $30,000/QALY. From a societal perspective, digital CBT demonstrated cost-benefit, achieving a negative ICER due to reduced healthcare expenses, lower workplace accident risks, and enhanced productivity associated with higher remission rates. The cost-effectiveness of digital CBT was influenced by the direct costs associated with the intervention and the remission probabilities in both the treatment and control groups. Despite these sensitivities, the digital CBT approach consistently demonstrated advantages under all scenarios within the thresholds of $30,000 and $15,000. These findings highlight the economic and clinical advantages of digital CBT, driven by its higher remission rates and reductions in insomnia-related indirect costs.

Conclusions:

Early integration of digital CBT into insomnia treatment shows strong potential to improve outcomes and cost-effectiveness, making it a valuable addition to routine care. Future research should focus on expanding access and evaluating real-world effectiveness, considering factors like access, engagement, and implementation challenges.


 Citation

Please cite as:

Kim JH, Sohn M, Woo J, Shin J, Han E

Digital Cognitive Behavioral Therapy for Chronic Insomnia in South Korea: Cost-Effectiveness Analysis Using Decision Tree and Markov Modeling Based on a Secondary Analysis of a Randomized Clinical Trial

JMIR Mhealth Uhealth 2026;14:e71750

DOI: 10.2196/71750

PMID: 41554115

PMCID: 12865351

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