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Data Science for Dynamic Intervention Decision-making Lab

National Institutes of Health (NIH) – R01 MH099898
Daniel Almirall (Direct Sponsor: UM Dept of Psychiatry; PI: Amy Kilbourne)

Despite the availability of psychosocial evidence-based practices (EBPs), quality and outcomes for persons with mental disorders remain suboptimal because of organizational barriers to implementation. Simply put, not all organizations that treat persons with mental disorders are able to implement or successfully implement EBPs, which has consequences for the quality of life and mental health outcomes for patients at these organizations. One approach to addressing this problem is to intervene on organizations in order to promote the use of psychosocial treatments. Replicating Effective Programs (REP) is an implementation intervention used to promote the use of psychosocial treatments in community-based practices. However, REP still results in only a fraction of sites (organizations) actually sustaining the use of EBPs. This suggests that an adaptive approach is needed whereby the implementation intervention is tailored (or individualized) to the specific needs of the site. However, many questions remain about how best to tailor intervention to the needs of the site, for example, by augmenting REP with an External Facilitator (EF) alone or with EF plus an Internal Facilitator (a costlier approach). The overarching goal of this study is to build the most cost-effective adaptive implementation intervention involving REP, EF and IF in order to improve the uptake of an evidence-based psychosocial intervention for mood disorders (known as Life Goals) in community settings and, therefore, patient outcomes. A representative cohort of 80 community-based outpatient clinics (over 1,200 patients) from different U.S. regions (Michigan, Colorado, and Arkansas) will be included in this study. In a first study of its kind, the study uses a cluster-randomized Sequential Multiple Assignment Randomized Trial (SMART) design to build the best possible adaptive implementation intervention. 

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