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NorthStar Node of the Clinical Trials Network

NorthStar Node of the Clinical Trials Network
临床试验网络的 NorthStar 节点
批准号:
10358343
负责人:
GAVIN BART
金额:
$23.07万
依托单位国家:
美国
项目类别:
财政年份:
2015
资助国家:
美国
项目状态:
未结题
起止时间:
2015-09-01 至 2025-02-28
关键词:
AddressAdoptionAlgorithmsAmericanArtificial IntelligenceBig DataCannabisCardiovascular DiseasesCaringChildhoodChronicChronic DiseaseClinicClinicalClinical ResearchClinical SciencesClinical TreatmentClinical Trials NetworkCommunitiesComparative Effectiveness ResearchCounselingCountyCriminal JusticeData ScienceDevelopmentDiagnosisDiseaseDisease OutcomeDoseDrug KineticsDrug abuseDrug userElectronic Health RecordEnsureFederally Qualified Health CenterFellowship ProgramGuidelinesHIVHealthHealth PersonnelHealth Services ResearchHealth systemHealthcareHomelessnessHousingHuman ResourcesInfrastructureInstitutesInstitutionIntegrated Health Care SystemsInterventionIowaLearningMachine LearningMajor Depressive DisorderMedicalMedicineMental disordersMentorsMethamphetamineMidwestern United StatesMinnesotaMissionModelingMulti-Institutional Clinical TrialNational Institute of Drug AbuseNatural Language ProcessingNeurosciencesNorth DakotaOpioidOutcomePatient CarePatient-Focused OutcomesPatientsPharmaceutical PreparationsPoliciesPopulationPopulation HeterogeneityPositioning AttributePrimary Health CareProtocols documentationPsychiatryPublic Health InformaticsRandomized Controlled TrialsRecoveryResearchResearch PersonnelRuralSECTM1 geneScientistSiteSocial WorkSouth DakotaStudent Health ServicesSubstance Use DisorderSumTechnology TransferTestingTrainingTraining ProgramsTranslatingTranslational ResearchTranslationsTreatment outcomeUnderrepresented MinorityUniversitiesViral hepatitisWisconsinWorkforce Developmentaddictionadolescent healthbasecareerclinical practicecognitive trainingcollaborative carecommunity based participatory researchcommunity engagementcomorbidityevidence basehealth care deliveryhealth care service utilizationillicit drug useimplementation scienceimprovedinnovationmachine learning algorithmmedical specialtiesmethamphetamine usenovel therapeutic interventionnovel therapeuticspersonalized medicinepragmatic trialprecision medicinepredictive modelingresearch and developmentresearch data disseminationrural areasafety netscreeningspecial interest groupsubstance usetreatment programuniversity studenturban Native Americanurban areaworking group

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In CTN-0076-Ot (Clinical Decision Support for Opioid Use Disorders in Medical Settings: Pilot Usability Testing in an EMR (COMPUTE)), our team iteratively developed and piloted a web-based and electronic health record (EHR)-integrated Opioid Use Disorder (OUD) Clinical Decision Support (CDS) system to offer expert guidance to primary care providers (PCPs) on the diagnosis and management of OUD. The OUD-CDS, referred to as Opioid Wizard, was implemented within the EPIC EHR of one large care system and piloted with 55 providers to ensure content validity and provider satisfaction. Through CTN-0095 (COMPUTE 2.0), our team will now implement Opioid Wizard in a large multi-site clinic-randomized controlled trial to evaluate its impact on practice process measures and patient outcomes. We also aim to prepare for scalability (i.e., integration into usual primary care practice after the study is complete) and dissemination by evaluating facilitators and barriers to implementation, determining the costs of implementation and maintenance, and assessing the short-term cost impacts of Opioid Wizard. The study will include three large diverse care systems and randomize a minimum of 30 clinics to receive Opioid Wizard or usual care (UC). In intervention clinics, Opioid Wizard will identify patients who are at high risk` for OUD or diagnosed with OUD; use data stored in the EHR for each eligible patient to assemble treatment recommendations tailored to each patient’s current needs; display these recommendations to PCPs via the Opioid Wizard user interface; and store analytic data from all targeted visits. In UC clinics, Opioid Wizard will run invisibly in the background to identify high-risk or OUD patients, assemble treatment recommendations tailored to each eligible patient’s needs, and store analytic data from all targeted visits. This study is part of the NIH’s Helping to End Addiction Long-term (HEAL) initiative to speed scientific solutions to the national opioid public health crisis. The NIH HEAL Initiative bolsters research across NIH to improve treatment for opioid misuse and addiction.
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