Kleinert Philip, Gebhardt Marie, Buckow Karoline, Gruendner Julian, Ganslandt Thomas, Prokosch Hans-Ulrich, Semler Sebastian C
TMF - Technology, Methods, and Infrastructure for Networked Medical Research, Berlin, Germany.
Chair of Medical Informatics, University of Erlangen-Nürnberg, Erlangen, Germany.
Stud Health Technol Inform. 2024 Aug 22;316:1704-1708. doi: 10.3233/SHTI240751.
In the light of big data driven clinical research, fair access to real world clinical health data enables evidence to improve patient care. Germany's healthcare system provides an abundant data resource but unique challenges due to its federated nature, heterogeneity and high data-protection standards. The Medical Informatics Initiative (MII) developed concepts that are being implemented in the German Portal for Medical Research Data (FDPG) to grant access to distributed data-sources across state borders. The portal currently provides access to more than 10 million patient resources containing hundreds of millions of laboratory parameters, diagnostic reports, administered medications, procedures and specimens. Upcoming datasets include among others oncological data, molecular analysis results and microbiological findings. Here, we describe the philosophy, implementation and experience behind the framework: standardized access processes, interoperable fair data, software for in depth feasibility requests, tools to support researchers and hospital stakeholders alike as well as transparency measures to provide data use information for patients. Challenges remain to improve data quality and automatization of technical and organizational processes.
鉴于大数据驱动的临床研究，公平获取真实世界的临床健康数据能够为改善患者护理提供证据。德国的医疗保健系统提供了丰富的数据资源，但由于其联邦性质、异质性和高数据保护标准，也带来了独特的挑战。医学信息学倡议（MII）制定了相关概念，这些概念正在德国医学研究数据门户（FDPG）中实施，以实现对跨州边界的分布式数据源的访问。该门户目前提供对超过1000万患者资源的访问，其中包含数亿个实验室参数、诊断报告、用药记录、手术和样本。即将推出的数据集包括肿瘤学数据、分子分析结果和微生物学发现等。在此，我们描述该框架背后的理念、实施情况和经验：标准化的访问流程、可互操作的公平数据、用于深入可行性请求的软件、支持研究人员和医院利益相关者的工具，以及为患者提供数据使用信息的透明度措施。在提高数据质量以及技术和组织流程的自动化方面仍存在挑战。
