The value of robust and responsible data sharing in clinical research and healthcare is recognized by patients, patient advocacy groups, researchers, journal editors, and the healthcare industry globally. Privacy and security concerns acknowledged, the act of exchanging data (interoperability) along with its meaning (semantic interoperability) across studies and between partners has been difficult, if not elusive. For shared data to retain its value, a recommendation has been made to follow the Findable, Accessible, Interoperable, Reusable (FAIR) principles. Without applying appropriate data exchange standards with domain-relevant content standards and accessible rich metadata that uses applicable terminologies, interoperability is burdened by the need for transformation and/or mapping. These obstacles to interoperability limit the findability, accessibility and reusability of data, thus diminishing its value and making it impossible to adhere to FAIR principles.

One effort to standardize data collection has been through common data elements (CDEs). CDEs are data collection units comprising one or more questions together with a set of valid values. Some CDEs contain standardized terminology concepts that define the meaning of the data, and others include links to unique terminology concept identifiers and unique identifiers for each CDE; however, usually CDEs are defined for specific projects or collaborations and lack traceable or machine readable semantics. While the name implies that these are ‘common’, this has not necessarily been a requirement, and many CDEs have not been commonly used. The National Institutes of Health (NIH) CDEs are, in fact, a conglomerate of CDEs developed in silos by various NIH institutes. Therefore, CDEs have not brought the anticipated benefit to the industry through widescale interoperability, nor is there widespread reuse of CDEs. Certain institutes in the NIH recommend, albeit do not enforce, institute-specific preferred CDEs; however, at the NIH level a preponderance of choice and a lack of any overarching harmonization of CDEs or consistency in linking them to controlled terminology or common identifiers create confusion for researchers in their efforts to identify the best CDEs for their protocol. The problem of comparing data among studies is exacerbated when researchers select different CDEs for the same variable or data collection field. This manuscript explores reasons for the disappointingly low adoption of CDEs and the inability of CDEs or other clinical research standards to broadly solve the interoperability and data sharing problems. Recommendations are offered for rectifying this situation to enable responsible data sharing that will help in adherence to FAIR principles and the realization of Learning Health Systems for the sake of all of us as patients.

病人，病人辩护团体，研究人员，期刊编辑以及全球医疗保健行业都认可可靠且负责任的数据共享在临床研究和医疗保健中的价值。众所周知，出于隐私和安全方面的考虑，研究之间以及合作伙伴之间交换数据（互操作性）及其含义（语义互操作性）的行为非常困难，甚至难以捉摸。为了使共享数据保持其价值，建议遵循可查找，可访问，可互操作，可重用（FAIR）原则。如果不使用与域相关的内容标准和使用适用术语的可访问的丰富元数据来应用适当的数据交换标准，则互操作性将由转换和/或映射的需求所负担。这些互操作性障碍限制了可发现性，

标准化数据收集的一项努力是通过通用数据元素（CDE）。CDE是包含一个或多个问题以及一组有效值的数据收集单元。一些CDE包含定义数据含义的标准化术语概念，另一些CDE包含指向唯一术语概念标识符和每个CDE唯一标识符的链接。但是，通常CDE是为特定项目或协作定义的，并且缺乏可追溯的或机器可读的语义。尽管名称暗示这些是“普通的”，但这并不一定是必需的，并且许多CDE尚未普遍使用。实际上，美国国立卫生研究院（NIH）CDE是由各种NIH研究所在筒仓中开发的CDE的集团。因此，CDE并没有通过广泛的互操作性给业界带来预期的收益，也没有广泛使用CDE。NIH中的某些机构建议，尽管不执行特定机构的首选CDE。但是，在NIH级别上，大量的选择以及CDE的总体协调性不足或将它们与受控术语或通用标识符链接在一起的一致性给研究人员在寻找适合其方案的最佳CDE时造成了困惑。当研究人员为同一变量或数据收集字段选择不同的CDE时，研究之间比较数据的问题更加严重。本手稿探讨了令人失望的CDE普及率低以及CDE或其他临床研究标准无法广泛解决互操作性和数据共享问题的原因。为纠正这种情况提供了建议，以实现负责任的数据共享，这将有助于遵守FAIR原则，并为我们所有人（患者）实现学习卫生系统。