Enhancing behavioral sleep care with digital technology: study protocol for a hybrid type 3 implementation-effectiveness randomized trial

• Published in: Current controlled trials in cardiovascular medicine 2021-01, Vol.22 (1), p.46-46, Article 46
• Main Authors: Germain, Anne, Markwald, Rachel R, King, Erika, Bramoweth, Adam D, Wolfson, Megan, Seda, Gilbert, Han, Tony, Miggantz, Erin, O'Reilly, Brian, Hungerford, Lars, Sitzer, Traci, Mysliwiec, Vincent, Hout, Joseph J, Wallace, Meredith L
• Format: Article
• Language: English
• Subjects: Anxiety; Behavioral health care; Behavioral sleep medicine; Care and treatment; Chronic pain; Cognitive Behavioral Therapy; Cognitive therapy; Comorbidity; Complex patients; Cost analysis; Customization; Demographic aspects; Digital health technologies; E-health; Effectiveness; Evaluation; Humans; Insomnia; Medicine; Military personnel; Patient outcomes; Post traumatic stress disorder; Randomized Controlled Trials as Topic; Response rates; Sleep; Sleep Initiation and Maintenance Disorders - diagnosis; Sleep Initiation and Maintenance Disorders - therapy; Study Protocol; Technology application; Telemedicine; Treatment Outcome; Veterans
• ISSN: 1745-6215; 1745-6215
• DOI: 10.1186/s13063-020-04974-z

Insomnia affects almost one in four military service members and veterans. The first-line recommended treatment for insomnia is cognitive-behavioral therapy for insomnia (CBTI). CBTI is typically delivered in-person or online over one-to-four sessions (brief versions) or five-to-eight sessions (standard versions) by a licensed doctoral or masters-level clinician with extensive training in behavioral sleep medicine. Despite its effectiveness, CBTI has limited scalability. Three main factors inhibit access to and delivery of CBTI including restricted availability of clinical expertise; rigid, resource-intensive treatment formats; and limited capacities for just-in-time monitoring and treatment personalization. Digital technologies offer a unique opportunity to overcome these challenges by providing scalable, personalized, resource-sensitive, adaptive, and cost-effective approaches for evidence-based insomnia treatment. This is a hybrid type 3 implementation-effectiveness randomized trial using a scalable evidence-based digital health software platform, NOCTEM™'s Clinician-Operated Assistive Sleep Technology (COAST™). COAST includes a clinician portal and a patient app, and it utilizes algorithms that facilitate detection of sleep disordered patterns, support clinical decision-making, and personalize sleep interventions. The first aim is to compare three clinician- and system-centered implementation strategies on the reach, adoption, and sustainability of the COAST digital platform by offering (1) COAST only, (2) COAST plus external facilitation (EF: assistance and consultation to providers by NOCTEM's sleep experts), or (3) COAST plus EF and internal facilitation (EF/IF: assistance/consultation to providers by NOCTEM's sleep experts and local champions). The second aim is to quantify improvements in insomnia among patients who receive behavioral sleep care via the COAST platform. We hypothesize that reach, adoption, and sustainability and the magnitude of improvements in insomnia will be superior in the EF and EF/IF groups relative to the COAST-only group. Digital health technologies and machine learning-assisted clinical decision support tools have substantial potential for scaling access to insomnia treatment. This can augment the scalability and cost-effectiveness of CBTI without compromising patient outcomes. Engaging providers, stakeholders, patients, and decision-makers is key in identifying strategies to support the deployment of digital health techno