Leveraging Data to Action: Accelerating Emergency Department OUD Care by Improving Data Access and Infrastructure

摘要 数据驱动的评估和干预措施改善了一系列急性护理的紧急护理 包括急性心肌梗死、中风和脓毒症--然而，类似的系统支持和 在患者预后恶化的情况下，OUD缺乏先进的急救护理。我们的团队完成了 基础数据基础设施工作揭示了教育数据系统中的差距，并确定了 利用美国急诊医师学会临床急诊科登记处(CEDR)作为 1000多个急诊科(ED)的国家数据主干，用于妇幼保健。我们建议创造新的 将生成嵌入CEDR生态系统的数据产品集合的数据流程，以 提高CEDR数据的及时性、质量、可获得性和有用性，以应对过量用药流行。 为了解决这些关键需求，我们提出了一个加速项目，该项目将利用我们之前的工作 开发和完善CEDR内外的电子健康记录OUD数据元素 注册表。该建议将：1)自动从参与站点提取与OUD相关的数据；2)将ED数据映射到 标准化、可扩展的观察性医疗结果伙伴关系(OMOP)公共数据模型(CDM) 3)将清洁发展机制内的关系数据转换为可供研究使用的数据集，算法扩展为 重要的OUD概念，以及4)创建面向站点和公众的EDUD过量预防仪表板 护理改善和监测。我们假设电子健康的自动化和集成化 将记录和管理药物使用障碍的数据输入CEDR将提高识别能力 改善急诊护理的机会，并推进未来的研究计划。在这项研究中，我们 计划评估CEDR内的数字就绪性，并设计增强型EDUD数据基础设施 适用于大规模观察性研究，支持未来的真实临床试验和标杆 仪表板(R61阶段)，并开发和部署跨临床、 研究和监督方面(R33阶段)。在研究完成后，我们预计会有更好的 使用标准化通用数据模型、自动化站点级ED OUD仪表板的国家ED数据登记处 为指导近乎实时的本地质量改进举措，独立的教育局注册处的存在 研究数据集，以及一个面向公众的、基于Web的近乎实时的ED OUD关怀仪表板。

Abstract Data-driven evaluation and interventions have improved emergency care across an array of acute care conditions including acute myocardial infarction, stroke and sepsis -- yet, similar systems to support and advance emergency care for OUD are lacking amidst worsening patient outcomes. Our team completed foundational data infrastructure work revealing gaps in ED data systems as well as identifying opportunities to utilize the American College of Emergency Physician's Clinical Emergency Department Registry (CEDR) as a national data backbone of over 1000 Emergency Departments (EDs) for OUD care. We propose to create new data processes that will generate a collection of data products embedded within the CEDR ecosystem to improve the timeliness, quality, accessibility, and usefulness of CEDR data to address the overdose epidemic. To address these critical needs, we propose an acceleration project that will leverage our prior work developing and refining electronic health record OUD data elements both within and outside of the CEDR registry. This proposal will: 1) automate OUD-related data extraction from participating sites, 2) map ED data to a standardized, scalable Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) 3) Translate relational data within the CDM into research ready datasets with algorithmic extension of important OUD concepts, and 4) create site and public facing ED OUD overdose prevention dashboards for care improvement and surveillance. We hypothesize that the automation and integration of electronic health record and administrative substance use disorder data into CEDR will improve the ability to identify opportunities for improvement in ED OUD care and advance future research initiatives. During this study we plan to assess digital readiness within CEDR and design an enhanced ED OUD data infrastructure suitable for large scale observational research, support of future real-world clinical trials and benchmarking dashboards (R61 phase) and develop and deploy an ED OUD digital infrastructure across clinical, research and surveillance dimensions (R33 phase). Upon study completion, we anticipate an improved national ED data registry using a standardized common data model, automated site level ED OUD dashboards to guide near-real time local quality improvement initiatives, the existence of an independent ED OUD Registry Research dataset, and a public facing, web based near-real time ED OUD care dashboard.