一项将患者EHR数据与斯坦福医学中心外部死亡数据联系起来的研究
A study linking patient EHR data to external death data at Stanford Medicine
摘要：
本文探讨了在临床数据仓库（r-CDW）研究背景下将真实世界患者数据与外部死亡数据联系起来。我们具体介绍了斯坦福医疗保健（SHC）患者的电子健康记录（EHR）数据与美国商务部国家技术信息服务（NTIS）提供的社会保障管理局（SSA）有限访问死亡主文件（LADMF）的数据之间的联系。本手稿中提出的数据分析框架扩展了先前的方法，并且可推广到链接任何两个跨组织的真实患者数据源。电子健康记录（EHR）数据和NTIS LADMF是其他医疗中心大量使用的资源，我们希望这里介绍的方法和学习对其他人有价值。我们的研究结果表明，强联系是不完整的，弱联系是嘈杂的，即，不存在提供覆盖率和准确性的好的链接规则。此外，任何两个数据集的最佳链接规则不同于两个其他数据集的最佳链接规则，即，没有链接规则的一般化。最后，LADMF是r-CDW常用的外部死亡数据源，在死亡数据方面存在显著差距，使r-CDW有必要寻找一个以上的外部死亡数据源。我们预计，多个链接的呈现将使向最终用户呈现链接结果变得困难。本手稿是支持斯坦福医学STARR（斯坦福医学研究数据库）r-CDW的资源。这些数据作为PHI存储在我们符合HIPAA标准的数据中心并进行分析，并在STARR IRB的研发（R&D）活动中使用。
英文摘要：
This manuscript explores linking real-world patient data with external death data in the context of research Clinical Data Warehouses (r-CDWs). We specifically present the linking of Electronic Health Records (EHR) data for Stanford Health Care (SHC) patients and data from the Social Security Administration (SSA) Limited Access Death Master File (LADMF) made available by the US Department of Commerce's National Technical Information Service (NTIS). The data analysis framework presented in this manuscript extends prior approaches and is generalizable to linking any two cross-organizational real-world patient data sources. Electronic Health Record (EHR) data and NTIS LADMF are heavily used resources at other medical centers and we expect that the methods and learnings presented here will be valuable to others. Our findings suggest that strong linkages are incomplete and weak linkages are noisy i.e., there is no good linkage rule that provides coverage and accuracy. Furthermore, the best linkage rule for any two datasets is different from the best linkage rule for two other datasets i.e., there is no generalization of linkage rules. Finally, LADMF, a commonly used external death data resource for r-CDWs, has a significant gap in death data making it necessary for r-CDWs to seek out more than one external death data source. We anticipate that presentation of multiple linkages will make it hard to present the linkage outcome to the end user. This manuscript is a resource in support of Stanford Medicine STARR (STAnford medicine Research data Repository) r-CDWs. The data are stored and analyzed as PHI in our HIPAA-compliant data center and are used under research and development (R&D) activities of STARR IRB.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
