eMERGE Phase IV Clinical Center at Partners HealthCare

Partners HealthCare 的 eMERGE IV 期临床中心

• 批准号: 10230561
• 负责人: ELIZABETH W KARLSON
• 金额: $ 88.31万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-06 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10230561
• 关键词: Address; Affect; Algorithms; Back; COVID-19; COVID-19 pandemic; Clinical; Code; Complex; Computer software; Data; Data Aggregation; Data Analyses; Data Collection; Disease; Electronic Health Record; Generations; Guidelines; Healthcare; Hospitals; Informatics; Intelligence; International; Life; Neuraxis; Patients; Phase; Policy Maker; Public Health; Pythons; Research; Rest; Running; Site; Trust; Update; Validation; Visualization; Work; clinical center; clinical research site; data quality; data visualization; health care delivery; informatics infrastructure; novel; phase 2 testing; research and development; statistics; tool; web site

The Coronavirus Disease 2019 (COVID-19) pandemic has caught the world off guard, reshaping ways of life, the economy, and healthcare delivery. Data in electronic health records (EHRs) should be widely available to study COVID-19 but have not yet been effectively shared across clinical sites, with public health agencies, or with policy makers. There are several large, national and international projects to build informatics infrastructure to analyze the EHR data of patients with COVID-19. However, aggregating data from multiple EHRs only works if you can trust the final results. This means being able to go back to each site and talk to the people who know the data best, to understand the local clinical guidelines, coding practices, data quality problems, and other factors that affect the data. In March, 2020, we launched an international effort called the Consortium for Clinical Characterization of COVID-19 by EHR (4CE). It brings together more than 100 informatics experts, statisticians, and ICU doctors from around the world. The novel aspect of 4CE is that we recognize the complexities of EHR data and the need to directly involve the local data experts, not only in the data collection, but also in the development of research questions and the data analyses. We try to move fast, believing that early intelligence is worth more than complete intelligence later. To do this, we avoid roadblocks that typically slow down informatics projects, such as building or installing new software, or the regulatory hurdles involved in sharing patient-level data. Instead, we ask participating sites to run analyses locally, using simple existing tools, like SQL, R, and Python scripts, and only share aggregate counts and statistics centrally with the rest of the 4CE consortium. We review and validate the data as a group, identify and fix data quality problems, and ask sites to repeat the analyses until everything is right. Through multiple cycles of data verification, we iteratively clean up the data and gain confidence that the findings we are seeing are real. Because we can do this quickly, we go from research question to results in just a few weeks. This proposed project will “productize” the 4CE approach, through three Specific Aims: (1) Transition 4CE to “Phase 2”, where sites will begin more complex local analyses. We will develop Phase 2 analysis scripts; update our data upload, validation, and visualization websites; and, test the Phase 2 scripts at three sites before expanding to the rest of the consortium. (2) Demonstrate and evaluate 4CE through two use cases. We will refine and validate an algorithm for identifying COVID-19 patients with “severe” disease and use 4CE to characterize central nervous system complications in COVID-19. (3) Develop a plan for integrating with complementary efforts and long-term sustainability. As part of this, we will create a guide that shows sites how to use 4CE data extracts and quality checks to support other COVID-19 informatics projects, including the generation of OMOP files.

2019 年冠状病毒病 (COVID-19) 大流行让世界措手不及，重塑了生活方式， 经济和医疗保健服务。电子健康记录 (EHR) 中的数据应广泛提供给 研究了 COVID-19，但尚未在临床中心、公共卫生机构之间有效共享，或 与政策制定者。有几个大型的国家和国际项目来建设信息学基础设施 分析 COVID-19 患者的 EHR 数据。然而，聚合来自多个 EHR 的数据才有效 如果你能相信最终的结果。这意味着能够返回每个站点并与了解的人交谈 最好的数据，了解当地的临床指南、编码实践、数据质量问题等 影响数据的因素。 2020 年 3 月，我们发起了一项名为临床联盟的国际努力 EHR 对 COVID-19 的表征 (4CE)。它汇集了100多名信息学专家、统计学家、 以及来自世界各地的 ICU 医生。 4CE 的新颖之处在于我们认识到 EHR 的复杂性 数据以及本地数据专家直接参与的必要性，不仅涉及数据收集，而且还涉及 研究问题的发展和数据分析。我们试图快速行动，相信早期的情报 比后来的完整情报更有价值。为此，我们避免了通常会减慢速度的障碍 信息学项目，例如构建或安装新软件，或共享所涉及的监管障碍 患者级别的数据。相反，我们要求参与站点使用简单的现有工具在本地运行分析，例如 SQL、R 和 Python 脚本，仅与 4CE 的其余部分集中共享聚合计数和统计数据 财团。我们作为一个整体审查和验证数据，识别并修复数据质量问题，并要求站点 重复分析，直到一切正确。通过多个周期的数据验证，我们迭代清理 数据并确信我们所看到的发现是真实的。因为我们可以很快做到这一点，所以我们去 从研究问题到结果只需几周时间。该拟议项目将“产品化”4CE 方法， 通过三个具体目标：(1) 将 4CE 过渡到“第 2 阶段”，站点将开始更复杂的本地分析。 我们将开发第二阶段分析脚本；更新我们的数据上传、验证和可视化网站；和， 在扩展到联盟的其他成员之前，在三个站点测试第二阶段脚本。 (2) 展示和 通过两个用例评估 4CE。我们将完善和验证识别 COVID-19 患者的算法 患有“严重”疾病并使用 4CE 来表征 COVID-19 中的中枢神经系统并发症。 (3) 制定一个整合互补努力和长期可持续性的计划。作为其中的一部分，我们将 创建一个指南，向网站展示如何使用 4CE 数据提取和质量检查来支持其他 COVID-19 信息学项目，包括生成 OMOP 文件。