Real-World Implementation and Impact of Digital CBT for Insomnia on Healthcare Utilization: A Propensity-Matched Controlled Study
Recommended Citation
Miller CB, Bradley D, Wood I, Willens D, Nair A, Brennan B, Bole S, Poisson L, Hall S, Thomson G, Hirata M, Kalmbach DA, and Drake CL. Real-World Implementation and Impact of Digital CBT for Insomnia on Healthcare Utilization: A Propensity-Matched Controlled Study. Implement Res Pract 2025;6.
Document Type
Article
Publication Date
10-1-2025
Publication Title
Implement Res Pract
Keywords
cognitive behavioral therapy for insomnia; digital health; healthcare utilization; implementation science; normalization process theory; real-world evidence
Abstract
Background: Chronic insomnia disorder affects 10-15% of adults, causing significant individual and societal burden. Despite Cognitive Behavioral Therapy for Insomnia (CBT-I) being the recommended first-line, sleep medications remain more common due to limited access to trained providers. Digital CBT-I offers a scalable solution, but evidence of its real-world impact in U.S. clinical settings is lacking.
Method: This study evaluates real-world implementation and impact of digital CBT-I in U.S. clinical settings, using Normalization Process Theory (NPT) to guide integration at Henry Ford Health, Detroit, Michigan. Implementation success was assessed through order rates, patient sign-ups and workflow acceptability. We assess the effect on healthcare utilization through a propensity-matched observational treatment-control design.
Results: Implementation was successful, with 1,162 patients offered digital CBT-I. From this cohort, we analyzed a sample of 340 patients with sufficient chart data and established care (120 days) who utilized digital CBT-I, comparing them to 340 matched standard care controls. Patients who used digital CBT-I had a 64% reduction in the odds of any medication fill during the postwindow period (p < .001) and were 53% less likely to fill insomnia medication prescriptions compared with the preperiod (p = .013). Controls did not have any significant reductions in medication fill rates. Time-varied analysis showed digital CBT-I patients had transiently higher outpatient visit odds at 30-60 days, followed by sustained reductions of 28% (120-150 days) and 31% (150-180 days). After covariate adjustment, early differences were nonsignificant while later reductions remained significant.
Conclusions: NPT facilitated integration of digital CBT-I into existing workflows, allowing immediate access while minimizing disruption to routine practice. Provider training sessions and reminders effectively promoted suitable patient uptake. Digital CBT-I was associated with reduced medication fills pre-to-post with an initial rise and then sustained reduction in outpatient service utilization patterns over time. A key limitation is the use of individuals who declined digital CBT-I as comparators, which may introduce selection bias. Generalizability may be limited as the study was conducted within a single healthcare system.
Trial Registration: Not applicable-the assignment of the medical intervention to patients was not at the discretion of the investigators.
PubMed ID
41181516
Volume
6
First Page
26334895251386306
Last Page
26334895251386306
