RAE cHealth: A digital community support tool to promote recovery from substance use disorder

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PROJECT SUMMARY The research project outlined in this Fast track SBIR submission will develop the RAE cHealth platform into a tool to address digital inequities and support peer-based collaborative recovery for individuals with substance use disorder. In this proposal, the investigators intend to develop and deploy the RAE cHealth system- consisting of a wearable sensor and a smartphone app. RAE cHealth combines objective physiologic data analysis to identify stress and craving, collection of important user driven data on social determinants of health and barriers to recovery, visualization to understand special and temporal relationships, and constant connection to peer recovery personnel via in-app multiple communications options, including telehealth. The specific aims are to Aim 1) Conduct a needs assessment to understand current barriers and facilitators of digital health use in individuals with socioeconomic disadvantage and SUD who engage with peer recovery services. We will conduct semi-structured interviews with key stakeholders to understand required features Aim 2) Iteratively pilot test RAE cHealth in three cohorts of N= 5 subjects for compliance and usability in our target population. Prior to transitioning to Phase II, we will develop the fully functional RAE cHealth app based on three prototype audit/feedback cycles, and achieve an average system usability score of 68. Aim 3) Deploy RAE cHealth within peer support-based SUD collaborative care organizations. We will conduct an observational trial of RAE cHealth through three community-based outreach programs to assess retention in services, healthcare resource utilization, return to substance use, employment data, psychosocial functioning, and usability, and Aim 4) Explore additional features based on SDoH data to enhance algorithms for the detection of stress and craving and those predictive of treatment-related outcomes. Upon completion, RAE cHealth will be a ready-for-market collaborative digital clinical decision intervention to support community- based recovery programs, and a value-added tool for SUD treatment programs to improve outcomes with objective data, and ultimately to support recovery. Findings from this work will not only inform the development in this specific use case but will be broadly applicable to the personalization of mHealth across disease states, which is ultimately needed to bridge the digital divide and make digital healthcare widely accessible.