The integrated Translational Health Research Institute of Virginia (iTHRIV): Using Data to Improve Health

SARS-CoV-2 大流行的未知和不断变化的特征对我们的工作提出了严峻的挑战。 美国（U.S.）医疗保健系统。解决许多这些挑战的关键是数据和 信息共享。为此，需要将不同系统中的个人健康数据汇集到一起 一个通用结构，可对其进行分析以获得有关 COVID-19 的重要问题的答案。 在健康信息学界，有两种整合数据进行分析的方法：(1) 联合数据共享，将数据保存在各个位置并允许聚合查询；(2) 统一的存储库，使用通用数据模型将不同站点的数据连接到一个数据库中 允许单独或行级查询。虽然联合方法更容易实现并且 更广泛地使用，协调方法是应对 COVID-19 挑战所需要的 大流行，因为它将能够对围绕这种疾病的科学问题进行更有影响力的数据分析。 弗吉尼亚大学 (UVA)，跨州综合转化健康研究的领先站点 弗吉尼亚研究所 (iTHRIV) 处于有利地位，可以作为协调一致的数据的初始试点提供商， 国家转化科学促进中心 (NCATS) 正在收集分析数据库 被称为国家新冠肺炎队列协作组织 (N3C)。 iTHRIV 能够在 UVA 做到这一点有四个原因：1) iTHRIV 实施了观察医疗结果合作伙伴关系 (OMOP) 通用数据模型 (CDM)，这不仅是数据传输到 N3C 的公认 CDM，而且也是目标数据传输模型 对于 N3C，这将使 iTHRIV CDM 成为验证数据转换的良好选择； 2) iTHRIV 信息学 团队一直积极参与 OMOP 中 COVID-19 表型实施的开发 从而可以快速实现数据查询； 3) iTHRIV 数据共享采用的架构 包括多个 CDM，这使我们能够将数据采集扩展到所有合作机构 iTHRIV 并快速响应数据采集和传输所需的变化； 4) 大学 弗吉尼亚州与 SMART IRB 签订了 IRB 信赖协议，并且可以依赖任何符合以下条件的非 UVA IRB： 与 SMART IRB 签订了 IRB 信赖协议，这将简化我们的参与启动流程。 因此，UVA 的 iTHRIV 为 N3C 项目提供了一个理想的试点，并带来了 iTHRIV Commons 和 iTHRIV 合作机构迅速支持向其他清洁发展机制的快速扩张，作为更大范围的清洁发展机制的典范 财团。 Commons 还在 N3C 的后续阶段提供领先的团队科学平台 弗吉尼亚州的研究人员可以与来自美国和世界各地的其他人合作分析 N3C 项目在集中存储库中收集数据，并解决有影响的健康问题 社区。

The unknown and changing characteristics of the SARS-CoV-2 pandemic have severely challenged the United States (U.S.) health care systems. The key to addressing many of these challenges is data and information sharing. To do this requires bringing together individual level health data from disparate systems into a common structure that can be analyzed for answers to the important questions about COVID-19. Within the health informatics community there are two approaches to integrating data for analysis: (1) Federated data sharing which keeps the data at individual locations and allows for aggregated queries and (2) Harmonized repository that joins the data from the different sites into one database with a common data model that allows for individual or row level queries. While the federated approach is easier to implement and much more widely used, the harmonization approach is what is needed to address the challenges of the COVID-19 pandemic since it will enable more impactful data analysis on the scientific questions surrounding this disease. The University of Virginia (UVA), the lead site for the cross-state integrated Translational Health Research Institute of Virginia (iTHRIV), is well positioned to serve as an initial, pilot provider of data for the harmonized, analytic database being assembled by the National Center for Advancing Translational Sciences (NCATS) known as the National COVID Cohort Collaborative (N3C). There four reasons iTHRIV can do this at UVA: 1) iTHRIV has implemented the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) and this is not only the accepted CDM for data transfer to N3C but it also the target data transfer model for N3C, which will make the iTHRIV CDM a good choice to validate data transforms; 2) The iTHRIV informatics team have been active participants in the development of the COVID-19 Phenotype implementation in OMOP and we can thus quickly implement the data queries; 3) The iTHRIV data Commons utilizes an architecture which includes multiple CDM and this gives us the capability to expand data acquisition to all partner institutions in iTHRIV and to rapidly respond to changes required in data acquisition and transfer; and 4) The University of Virginia has an IRB Reliance Agreement in place with SMART IRB and can rely on any non-UVA IRB that also has an IRB Reliance Agreement with SMART IRB, which will streamline our start-up process for participation. iTHRIV at UVA therefore provides an ideal pilot site for the N3C project, and brings the iTHRIV Commons and the iTHRIV partners institutions to rapidly support rapid expansion to other CDM as a model for the larger consortium. The Commons also provides a leading team-science platform during the follow-on phases of N3C where researchers within Virginia can collaborate with others from around the U.S. and the world to analyze the data collected in centralized repository by the N3C project and address impactful health problems for the community.