This clinical trial focuses on testing the efficacy of different digital interventions to promote re-engagement in cancer-related long-term follow-up care for adolescent and young adult (AYA) survivors of childhood cancer.
This study refines and optimizes the EMBED\* clinical decision support (CDS; see NCT03658642) to increase number of ED physicians following standard of care for the administration of buprenorphine to appropriate patients with opioid use disorder. This study does not have open enrollment. Investigators will use a Multiphase Optimization STrategy (MOST) framework study with preparation, optimization, and confirmatory phases. Optimization Phase: This phase has two stages. In stage 1, investigators will conduct a 2x2x2 factorial trial to expand EMBED is expanded to include sustainable implementation strategies: nurse prompt for withdrawal assessment, and targeted clinician prompts to use the CDS along with individualized patient resources to promote equity and motivate readiness to start treatment. In Stage 2, investigators will improve CDS usability via serial randomized testing to inform iterative refinement of the CDS interface and workflow to minimize user errors, task disruption, and abandonment through identification of specific targets for improvement via application of novel CDS outcome measures in serial randomized tests. Evaluation phase: Investigators will conduct a randomized trial to compare the efficacy effectiveness of the optimized package compared to the original on ED-initiation of buprenorphine rates in patients with OUD. \*EMBED is a user user-centered, clinician clinician-facing clinical decision support system integrated into the electronic health record workflow to facilitate initiating buprenorphine in the emergency department by: diagnosing opioid use disorder with a checklist based on the diagnostic criteria of the DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, fifth edition), assessing the severity of withdrawal with the Clinical Opioid Withdrawal Scale (COWS), motivating patients to accept treatment with a scripted brief negotiation interview, and automating the electronic health record workflow, including clinical and after visit documentation, order entry, prescribing, and referral for ongoing treatment in the community
Adaptive Decision Support for Addiction Treatment (ADAPT)
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
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Sponsor: Yale University
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.