Anne Germain1, Rachel R Markwald2, Erika King3, Adam D Bramoweth4, Megan Wolfson5, Gilbert Seda6, Tony Han6, Erin Miggantz2,7, Brian O'Reilly8, Lars Hungerford6,9, Traci Sitzer6, Vincent Mysliwiec10, Joseph J Hout11, Meredith L Wallace12. 1. NOCTEM, LLC, 218 Oakland Avenue, Pittsburgh, PA, 15213, USA. anne@noctemhealth.com. 2. Warfighter Performance Department, Naval Health Research Center, 140 Sylvester Rd, San Diego, CA, 92106, USA. 3. Mental Health Division, Air Force Medical Readiness Agency, 2261 Hughes Ave, Suite 153, JBSA Lackland AFB, TX, 78236-9853, USA. 4. VA Pittsburgh Healthcare System, Research Office Building (151RU), University Drive C, Pittsburgh, PA, 15240, USA. 5. NOCTEM, LLC, 218 Oakland Avenue, Pittsburgh, PA, 15213, USA. 6. Naval Medical Center San Diego, 34800 Bob Wilson Dr, San Diego, CA, 92134, USA. 7. Leidos, Inc., 4161 Campus Point Ct., San Diego, 92121, USA. 8. Madigan Army Medical Center, 9040A Jackson Ave, Joint Base Lewis-McChord, WA, 98431, USA. 9. Defense and Veterans Brain Injury Center, Naval Medical Center San Diego, 34800 Bob Wilson Drive, San Diego, CA, 92134, USA. 10. Division of Behavioral Medicine, Department of Psychiatry, UT Health San Antonio, 7703 Floyd Curl Drive, MC 7747, San Antonio, TX, 78229-3900, USA. 11. Knowesis, Inc., 816 Camaron St. Suite 231, San Antonio, TX, 78212, USA. 12. University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA.
Abstract
BACKGROUND: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. METHODS: 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. DISCUSSION: 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 technologies that can promote quality care and result in clinically meaningful sleep improvements, positive systemic change, and enhanced readiness and health among service members. TRIAL REGISTRATION: ClinicalTrials.gov NCT04366284 . Registered on 28 April 2020.
RCT Entities:
BACKGROUND: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. METHODS: 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. DISCUSSION: 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 technologies that can promote quality care and result in clinically meaningful sleep improvements, positive systemic change, and enhanced readiness and health among service members. TRIAL REGISTRATION: ClinicalTrials.gov NCT04366284 . Registered on 28 April 2020.
Entities:
Keywords:
Behavioral sleep medicine; Cognitive-behavioral therapy for insomnia; Digital health technologies; Effectiveness; Implementation facilitation; Insomnia; Military personnel; Veterans
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