Implementation of a National Framework to Promote Health Data SharingThe German Medical Informatics Initiative
22 April 2018 (eFirst)
Sharing health data has been a major topic in medical informatics research in Germany in the last two decades. The latest developments show that the interdisciplinary collaboration between the fields of medical bioinformatics and systems medicine has remarkably progressed, and innovative solutions to foster health data sharing have been presented by various German research groups, e.g., requirements for data integration platforms , the role of medical informatics for systems medicine , the interconnection of system architectures for rare disease registries, or information technology (IT) supported patient recruitment.
However, the various types of heterogeneous health data produced by patient care and research turned out to be insufficiently integrated . Often, research data only show a molecular snapshot of an individual disease. Intelligent correlation with clinical data is expected to offer new potential for patient care and biomedical research. Medical data semantic integration and joined analysis may not only lead to a better prediction of individualized decisions but also to a better understanding of the disease, and can be the base for new individualized prevention, diagnosis, and therapeutic measures.
Therefore, the German Ministry of Education and Research (BMBF) has launched the Medical Informatics Initiative (MI-I) to translate data sharing potential into effective practical use and to solve the prerequisites of data sharing like patient consent and semantic interoperability, starting with university medical centers but already being designed to be rolled out to all hospitals and to outpatient care organizations throughout Germany in the later stages of the program.
- 1 Ganzinger M, Knaup P. Requirements for data integration platforms in biomedical research networks: a reference model. PeerJ 2015; 3: e755
- 2 Bauer CRKD, Ganslandt T, Baum B, Christoph J, Engel I, Löbe M. et al. Integrated Data Repository Toolkit (IDRT). A Suite of Programs to Facilitate Health Analytics on Heterogeneous Medical Data. Methods Inf Med 2016; 55 (02) 125-35
- 3 Bauer CR, Knecht C, Fretter C, Baum B, Jendrossek S, Rühlemann M. et al. Interdisciplinary approach towards a systems medicine toolbox using the example of inflammatory diseases. Brief Bioinform 2017; 18 (03) 479-87
- 4 Gietzelt M, Löpprich M, Karmen C, Knaup P, Ganzinger M. Models and Data Sources Used in Systems Medicine. A Systematic Literature Review. Methods Inf Med 2016;55(2)
- 5 Deserno TM, Haak D, Brandenburg V, Deserno V, Classen C, Specht P. Integrated image data and medical record management for rare disease registries. A general framework and its instantiation to the German Calciphylaxis Registry. J Digit Imaging 2014; 27 (06) 702-13
- 6 Trinczek B, Köpcke F, Leusch T, Majeed RW, Schreiweis B, Wenk J. et al. Design and multicentric implementation of a generic software architecture for patient recruitment systems re-using existing HIS tools and routine patient data. Appl Clin Inform 2014; 5 (01) 264-83
- 7 Dixon BE, Vreeman DJ, Grannis SJ. The long road to semantic interoperability in support of public health: Experiences from two states. J Biomed Inform 2014; 49: 3-8
- 8 Berges I, Bermúdez J, Illarramendi A. Toward semantic interoperability of electronic health records. IEEE Trans Inf Technol Biomed 2012; 16 (03) 424-31
- 9 Maier C, Lang L, Storf H, Vormstein P, Bieber R, Bernarding J. et al. Towards Implementation of OMOP in a German University Hospital Consortium. Appl Clin Inform 2018; 9 (01) 54-61
- 10 Haverkamp C, Ganslandt T, Horki P, Boeker M, Dörfler A, Schwab S. et al. Regional Differences in Thrombectomy Rates: Secondary use of Billing Codes in the MIRACUM (Medical Informatics for Research and Care in University Medicine) Consortium. Clin Neuroradiol 2018