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新冠肺炎队列协作组织（N3 C）， 健康（CD 2 H）与国家推进转化科学中心（NCATS）合作， 集中的国家电子健康记录（EHR）数据资源，用于研究COVID-19患者结局。 在过去的3年里，西弗吉尼亚州临床和转化科学研究所（WVCTSI）利用 N3 C倡议作为整个西弗吉尼亚州的协作力量。此外，N3 C还推动了 临床和转化研究机构发展奖（IDEA- CTR）计划，以推动有意义的科学举措，改善IDEA人群的结局 国家，特别是代表性不足的少数群体和得不到充分服务的人口。WVCTSI有效地领导了12个 通过各种活动在生产性N3 C协作中开展IDEA-CTR。对于IDEA-CTR N3 C的第4年 WVCTSI将继续提供网络范围的基础设施，以推动相关科学和 生产力，组织每月的“全员参与”会议，并确保IDEA-CTR站点完成 每季度报告一次生产力。我们将通过几种方式建立分析能力：1）将 外部数据集的第4年分析（例如，Medicare、Medicaid）使用隐私保护记录链接 （PPRL），2）在N3 C项目中扩大机器学习（ML）和人工智能（AI）的使用， 现有的知识渊博的IDEA-CTR研究人员在这些领域，和3）引入使用空间分析， 调查COVID-19相关结果的地理差异。我们还将积极与调查人员合作， 通过提供支持，参与与各自州人口相关的高质量COVID-19数据项目 包括审查和回复服务台故障单，从而加快解决 所有IDEA-CTR生成的票证。我们还将协调和举办相关的研讨会和讲习班， 新的分析技术，ML/AI和空间流行病学。最后，我们将增加电子健康记录的频率 每月从西弗吉尼亚大学上传数据。

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.