Digital CBT for Insomnia Is Linked to Reductions in Healthcare Use in Real-world Settings at Henry Ford Health
Recommended Citation
Miller C, Bradley D, Wood I, Willens D, Nair A, Brennan B, Bole S, Poisson L, Hall S, Thomson G, Hirata M, Kalmbach D, Drake C. Digital CBT for Insomnia Is Linked to Reductions in Healthcare Use in Real-world Settings at Henry Ford Health. Sleep 2025; 48:A236.
Document Type
Conference Proceeding
Publication Date
5-19-2025
Publication Title
Sleep
Abstract
Introduction: Digital CBT-I offers a scalable solution for insomnia treatment, but evidence of its real-world adoption and impact in U.S. clinical settings is limited. This study evaluates the implementation and effects of digital CBT-I within a U.S. healthcare system, utilizing Normalization Process Theory to integrate it into clinical workflows. We compare healthcare utilization between patients who engaged with digital CBT-I and those who were offered but did not use it. Methods: Patients with insomnia were offered digital CBT-I via electronic and clinical workflows at the Internal Medicine and Sleep clinics within Henry Ford Health, Detroit, Michigan. Normalization Process Theory guided implementation. Electronic order rates and patient sign-ups assessed implemen tation success and workflow acceptability. Clinician training sessions and educational materials supported uptake. A propen sity-matched case-control design compared healthcare utilization rates between 340 digital CBT-I users and 340 matched controls, who were offered digital CBT-I but did not use it. We analyzed patient chart data and standardized time across patients. We evaluated the odds of medication fills and visits before and after. Results: A total of 340 patients utilizing digital CBT-I from treat ing practitioners were matched with 340 controls who did not. Digital CBT-I patients exhibited a 64% reduction in medication fills (for any condition) during the post-treatment period rela tive to before (p< 0.001), and were 53% less likely to fill insom nia-specific prescriptions compared to pre-treatment (p=0.013). Controls showed no significant changes. Time-varied logistic regression indicated that digital CBT-I patients had 37% higher odds of using outpatient services within the initial 30-60 days (p=0.048), but subsequently showed 28% lower odds at 120-150 days (p=0.041), and 41% lower odds at 150-180 days (p=0.039). Conclusion: Normalization Process Theory effectively facilitated the integration of digital CBT-I into clinical workflows, providing immediate access with minimal workflow disruptions. Training ses sions and ongoing clinician reminders promoted patient uptake of standard care for insomnia management. Findings indicate that dig ital CBT-I is associated with reduced medication fills and decreased odds of outpatient visits over time, suggesting its potential as an effective, scalable treatment for insomnia in clinical settings
Volume
48
First Page
A236
