Multi-Stakeholder Consensus Approach to Problem Consolidation and Strategic Use of Electronic Health Record (EHR) Data Standards for Clinical Research and Regulatory Reporting

项目总结/摘要 使用电子健康记录（EHR）系统作为“真实世界数据”（RWD）的来源具有很大的潜力 来改变和改进研究。尽管RWD具有潜在价值和公共卫生需求，但 从EHR系统中提取和使用数据进行研究是有限的，因为缺乏明确定义， 统一实施的标准，表示临床数据的语义含义，包括上下文 和编码的特异性。一个特别的挑战是，用于EHR数据的临床编码系统通常具有 非常精细的代码，支持详细诊断和高度特定测试的文档， 药物治疗这些细粒度代码必须被分组为广泛的概念，以便进行研究分析， 提交，但一致和可重复的数据聚合方法，保留重要的语义 缺乏用于研究目的的临床RWD的意义和背景。我们建议使用一个消息灵通的 环境扫描，有针对性的文献审查，以及一个由标准专家组成的多方利益相关者小组，以确定 尚未解决的方法学问题和重大挑战-并阐明 标准化或协调化-可以支持短期内利用RWD的战略行动， 建立更强大的临床研究基础设施，以支持未来的研究需求。多方利益有关者 该小组将包括来自临床信息学和研究数据标准的数据和标准专家 社区.

Project Summary/Abstract The use of electronic health record (EHR) systems as a source of “real-world data” (RWD) has great potential to transform and improve research. Despite the potential value and public health need for RWD, the ability to extract and use data from EHR systems for research is limited due to the absence of clearly defined and uniformly implemented standards that represent the semantic meaning of clinical data, including the context and specificity of coding. A particular challenge is that clinical coding systems used for EHR data often have very granular codes to support documentation of detailed diagnoses and highly specific tests and packaged medications. These granular codes must be grouped into broad concepts for research analyses and submissions, but consistent and reproducible data aggregation methods that preserve important semantic meaning and context of clinical RWD for research purposes are lacking. We propose to use a well-informed environmental scan, targeted literature review, and a multi-stakeholder group of standards experts to identify unresolved methodological issues and critical challenges – and delineate alternative approaches for standardization or harmonization - that can support strategic action for leveraging RWD in the short term and enable a more robust clinical research infrastructure to support future research needs. The multi-stakeholder group will include data and standards experts from both clinical informatics and research data standards communities.