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All Of Us 研究计划的数据模型协调:将 i2b2 数据转换为 OMOP 通用数据模型。

Data model harmonization for the All Of Us Research Program: Transforming i2b2 data into the OMOP common data model.

机构信息

Research Information Science and Computing, Partners Healthcare, Boston, Massachusetts, United States of America.

Harvard Medical School, Boston, Massachusetts, United States of America.

出版信息

PLoS One. 2019 Feb 19;14(2):e0212463. doi: 10.1371/journal.pone.0212463. eCollection 2019.

Abstract

BACKGROUND

The All Of Us Research Program (AOU) is building a nationwide cohort of one million patients' EHR and genomic data. Data interoperability is paramount to the program's success. AOU is standardizing its EHR data around the Observational Medical Outcomes Partnership (OMOP) data model. OMOP is one of several standard data models presently used in national-scale initiatives. Each model is unique enough to make interoperability difficult. The i2b2 data warehousing and analytics platform is used at over 200 sites worldwide, which uses a flexible ontology-driven approach for data storage. We previously demonstrated this ontology system can drive data reconfiguration, to transform data into new formats without site-specific programming. We previously implemented this on our 12-site Accessible Research Commons for Health (ARCH) network to transform i2b2 into the Patient Centered Outcomes Research Network model.

METHODS AND RESULTS

Here, we leverage our investment in i2b2 high-performance transformations to support the AOU OMOP data pipeline. Because the ARCH ontology has gained widespread national interest (through the Accrual to Clinical Trials network, other PCORnet networks, and the Nebraska Lexicon), we leveraged sites' existing investments into this standard ontology. We developed an i2b2-to-OMOP transformation, driven by the ARCH-OMOP ontology and the OMOP concept mapping dictionary. We demonstrated and validated our approach in the AOU New England HPO (NEHPO). First, we transformed into OMOP a fake patient dataset in i2b2 and verified through AOU tools that the data was structurally compliant with OMOP. We then transformed a subset of data in the Partners Healthcare data warehouse into OMOP. We developed a checklist of assessments to ensure the transformed data had self-integrity (e.g., the distributions have an expected shape and required fields are populated), using OMOP's visual Achilles data quality tool. This i2b2-to-OMOP transformation is being used to send NEHPO production data to AOU. It is open-source and ready for use by other research projects.

摘要

背景

全美研究计划(AOU)正在建立一个包含一百万名患者电子病历和基因组数据的全国性队列。数据互操作性对该计划的成功至关重要。AOU 正在围绕观察医学结局伙伴关系(OMOP)数据模型标准化其电子病历数据。OMOP 是目前在国家规模计划中使用的几个标准数据模型之一。每个模型都有足够的独特性,使得互操作性变得困难。i2b2 数据仓库和分析平台在全球 200 多个站点使用,该平台使用灵活的基于本体的方法进行数据存储。我们之前证明了这个本体系统可以驱动数据重构,无需特定于站点的编程即可将数据转换为新格式。我们之前在我们的 12 个可访问研究健康共同体(ARCH)网络上实现了这一点,将 i2b2 转换为患者为中心的结果研究网络模型。

方法和结果

在这里,我们利用我们在 i2b2 高性能转换方面的投资来支持 AOU OMOP 数据管道。由于 ARCH 本体已经获得了广泛的全国性关注(通过临床试验网络、其他 PCORnet 网络和内布拉斯加州词典),我们利用站点对这个标准本体的现有投资。我们开发了一个由 ARCH-OMOP 本体和 OMOP 概念映射字典驱动的 i2b2 到 OMOP 的转换。我们在 AOU 新英格兰 HPO(NEHPO)中展示和验证了我们的方法。首先,我们将一个虚假患者数据集从 i2b2 转换为 OMOP,并通过 AOU 工具验证数据在结构上符合 OMOP。然后,我们将合作伙伴医疗保健数据仓库中的一部分数据转换为 OMOP。我们开发了一个检查表来确保转换后的数据具有自我完整性(例如,分布具有预期的形状,并且必填字段已填充),使用 OMOP 的视觉 Achilles 数据质量工具。这个 i2b2 到 OMOP 的转换正在用于将 NEHPO 生产数据发送到 AOU。它是开源的,并准备供其他研究项目使用。

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