NorthStar Node of the Clinical Trials Network

在CTN-0076-Ot（医疗环境中阿片类药物使用障碍的临床决策支持：EMR中的试点可用性测试（EHR））中，我们的团队迭代开发并试点了一个基于网络和电子健康记录（EHR）集成的阿片类药物使用障碍（OUD）临床决策支持（CDS）系统，为初级保健提供者（PCP）提供诊断和管理OUD的专家指导。OUD-CDS被称为阿片类向导，在一个大型医疗系统的EPIC EHR中实施，并与55名提供者进行了试点，以确保内容的有效性和提供者的满意度。通过CTN-0095（CTNTE 2.0），我们的团队现在将在一项大型多中心临床随机对照试验中实施阿片类药物向导，以评估其对实践过程措施和患者结局的影响。我们还旨在为可扩展性做好准备（即，研究完成后，将其纳入常规初级保健实践），并通过评估实施的促进者和障碍，确定实施和维持的成本，以及评估阿片类药物向导的短期成本影响来传播。 该研究将包括三个大型的多样化护理系统，并随机分配至少30个诊所接受阿片类药物向导或常规护理（UC）。在干预诊所，阿片类药物向导将识别OUD高风险或诊断为OUD的患者;使用存储在EHR中的每个合格患者的数据，根据每个患者的当前需求收集治疗建议;通过阿片类药物向导用户界面向PCP显示这些建议;并存储所有目标访问的分析数据。在UC诊所，阿片类药物向导将在后台无形地运行，以识别高风险或OUD患者，根据每个合格患者的需求收集治疗建议，并存储来自所有目标访问的分析数据。 这项研究是NIH帮助结束长期成瘾（HEAL）计划的一部分，旨在加速科学解决国家阿片类药物公共卫生危机。NIH HEAL倡议支持整个NIH的研究，以改善阿片类药物滥用和成瘾的治疗。

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.