West Virginia Clinical and Translational Science Institute: A Statewide Organization Building Research Excellence and Engaging Communities to Improve Health

摘要 2020年，国家数据中心成立了国家COVID队列协作(N3C)，以 健康(CD2H)与国家翻译科学推进中心(NCATS)合作 用于新冠肺炎患者预后研究的集中式国家电子健康记录数据资源。 在过去的3年里，西弗吉尼亚州临床和翻译科学研究所(WVCTSI)利用 N3C计划作为一股跨全球的协作力量。此外，N3C还推动了 临床和翻译研究机构发展奖(IDEA- CTR)计划，以推动有意义的科学倡议，以改善IDEA中人口的结果 各州，特别是代表不足的少数群体和服务不足的人口。WVCTSI有效地领先了12 IDEA-CTR通过各种活动在富有成效的N3C协作中发挥作用。IDEA的第4年-CTR N3C WVCTSI将继续提供网络范围的基础设施，以推动相关的科学和 工作效率，每月组织“全员上甲板”会议，并确保IDEA-CTR站点的完整性 按季度报告生产效率。我们将通过以下几种方式培养分析能力：1)整合 使用隐私保护记录链接对外部数据集(例如，Medicare、Medicaid)进行第4年分析 (PPRL)，2)在N3C项目中扩大机器学习(ML)和人工智能(AI)的使用，利用 现有知识丰富的想法-这些领域的CTR调查人员，以及3)引入空间分析的使用，以 调查新冠肺炎相关成果的地理差异。我们还将积极接触调查人员 在与各州人口相关的高质量新冠肺炎数据项目中提供支持 提供给调查人员，包括审查和响应帮助台票据，从而加快解决 所有创意-CTR生成的罚单。我们还将协调开展有关座谈会和研讨会。 到新的分析技术、ML/AI和空间流行病学。最后，我们将增加EHR的频率 每月从WVU上传数据。

ABSTRACT In 2020, the National COVID Cohort Collaborative (N3C) was established by the National Center for Data to Health (CD2H) in partnership with the National Center for Advancing Translational Sciences (NCATS) as a centralized national electronic health record (EHR) data resource for the study of COVID-19 patient outcomes. Over the past 3 years, the West Virginia Clinical and Translational Science Institute (WVCTSI) has leveraged the N3C initiative as a collaborative force across WV. In addition, N3C has served as an impetus to form a collaborative network among Institutional Development Award for Clinical and Translational Research (IDeA- CTR) programs to drive meaningful scientific initiatives to improve outcomes among populations in IDeA states, particularly underrepresented minority and underserved populations. WVCTSI has effectively led 12 IDeA-CTRs in productive N3C collaborations through a variety of activities. For Year 4 of the IDeA-CTR N3C initiative, WVCTSI will continue to provide network-wide infrastructure to drive relevant science and productivity, organizing monthly “All Hands On Deck” meetings and ensuring IDeA-CTR sites complete productivity reporting on a quarterly basis. We will build analytic capacity in several ways: 1) incorporating into Year 4 analyses of external datasets (e.g., Medicare, Medicaid) using privacy-preserving record linkage (PPRL), 2) expanding use of machine learning (ML) and artificial intelligence (AI) in N3C projects, leveraging existing knowledgeable IDeA-CTR investigators in those areas, and 3) introducing use of spatial analyses to investigate geographic disparities in COVID-19 related outcomes. We will also actively engage investigators in high quality COVID-19 data projects relevant to populations in their respective states by providing support to investigators that includes reviewing and responding to help desk tickets, thereby expediting resolution of all IDeA-CTR-generated tickets. We will also coordinate and conduct relevant symposia and workshops related to novel analytic techniques, ML/AI, and spatial epidemiology. Finally, we will increase frequency of EHR data uploads from WVU to occur monthly.