Storf Holger, Schaaf Jannik, Kadioglu Dennis, Göbel Jens, Wagner Thomas O F, Ückert Frank
Medical Informatics Group (MIG), Universitätsklinikum Frankfurt, Haus 33C, Theodor-Stern-Kai 7, 60590, Frankfurt, Deutschland.
Institut für Medizinische Biometrie, Epidemiologie und Informatik (IMBEI), Universitätsmedizin Mainz, Obere Zahlbacher Str. 69, 55131, Mainz, Deutschland.
Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz. 2017 May;60(5):523-531. doi: 10.1007/s00103-017-2536-7.
Meager amounts of data stored locally, a small number of experts, and a broad spectrum of technological solutions incompatible with each other characterize the landscape of registries for rare diseases in Germany. Hence, the free software Open Source Registry for Rare Diseases (OSSE) was created to unify and streamline the process of establishing specific rare disease patient registries. The data to be collected is specified based on metadata descriptions within the registry framework's so-called metadata repository (MDR), which was developed according to the ISO/IEC 11179 standard. The use of a central MDR allows for sharing the same data elements across any number of registries, thus providing a technical prerequisite for making data comparable and mergeable between registries and promoting interoperability.With OSSE, the foundation is laid to operate linked patient registries while respecting strong data protection regulations. Using the federated search feature, data for clinical studies can be identified across registries. Data integrity, however, remains intact since no actual data leaves the premises without the owner's consent. Additionally, registry solutions other than OSSE can participate via the OSSE bridgehead, which acts as a translator between OSSE registry networks and non-OSSE registries. The pseudonymization service Mainzelliste adds further data protection.Currently, more than 10 installations are under construction in clinical environments (including university hospitals in Frankfurt, Hamburg, Freiburg and Münster). The feedback given by the users will influence further development of OSSE. As an example, the installation process of the registry for undiagnosed patients at University Hospital Frankfurt is described in more detail.
德国罕见病注册系统的现状是，本地存储的数据量稀少，专家数量有限，且存在大量互不兼容的技术解决方案。因此，创建了免费软件“罕见病开源注册系统”（OSSE），以统一并简化建立特定罕见病患者注册系统的流程。要收集的数据是根据注册系统框架中所谓的元数据存储库（MDR）内的元数据描述来指定的，该存储库是根据ISO/IEC 11179标准开发的。使用中央MDR可以在任意数量的注册系统之间共享相同的数据元素，从而为使各注册系统之间的数据具有可比性和可合并性以及促进互操作性提供了技术前提条件。借助OSSE，在尊重严格的数据保护法规的同时，为运营关联的患者注册系统奠定了基础。利用联合搜索功能，可以跨注册系统识别临床研究数据。然而，由于未经所有者同意，实际数据不会离开其所在机构，因此数据完整性得以保持。此外，除OSSE之外的注册系统解决方案可以通过OSSE桥头堡参与进来，该桥头堡充当OSSE注册系统网络与非OSSE注册系统之间的转换器。假名化服务Mainzelliste进一步增强了数据保护。目前，临床环境中有10多个安装项目正在建设中（包括法兰克福、汉堡、弗莱堡和明斯特的大学医院）。用户给出的反馈将影响OSSE的进一步开发。例如，将更详细地描述法兰克福大学医院未确诊患者注册系统的安装过程。
