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68. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS)

17.09. - 21.09.23, Heilbronn

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Deployment of the Data Sharing Framework at German University Hospitals – Lessons Learned

Meeting Abstract

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  • Hauke Hund - GECKO Institute, Heilbronn University of Applied Sciences, Heilbronn, Germany
  • Reto Wettstein - Institute for Medical Informatics, Heidelberg University Hospital, Heidelberg, Germany
  • Alexander Kiel - Leipzig Research Centre for Civilization Diseases, Leipzig University, Leipzig, Germany
  • Maximilian Kurscheidt - GECKO Institute, Heilbronn University of Applied Sciences, Heilbronn, Germany
  • Simon Tobias Schweizer - GECKO Institute, Heilbronn University of Applied Sciences, Heilbronn, Germany
  • Christoph Zilske - GECKO Institute, Heilbronn University of Applied Sciences, Heilbronn, Germany
  • Simon Mödinger - GECKO Institute, Heilbronn University of Applied Sciences, Heilbronn, Germany
  • Christian Fegeler - GECKO Institute, Heilbronn University of Applied Sciences, Heilbronn, Germany

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie. 68. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS). Heilbronn, 17.-21.09.2023. Düsseldorf: German Medical Science GMS Publishing House; 2023. DocAbstr. 103

doi: 10.3205/23gmds007, urn:nbn:de:0183-23gmds0072

Published: September 15, 2023

© 2023 Hund et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License. See license information at http://creativecommons.org/licenses/by/4.0/.

Outline

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Motivated by the German Medical Informatics Initiative, infrastructure components have been created to improve access to real-word patient data for biomedical researchers. This follows a global trend of better leveraging existing data sources. With our Data Sharing Framework (DSF) research processes can be executed and coordinated across organizational boundaries. This includes cohort size estimation, record linkage, pseudonymization and data transfers. The DSF uses HL7 FHIR resources to communicate information and executes business processes using the BPMN 2.0 notation. Initially developed for the HiGHmed consortium, the DSF has now been deployed to a large number of German University Hospitals and other research organizations. With this paper, we share lessons learned from using the DSF in different research contexts and present upcoming improvements.

The authors declare that they have no competing interests.

The authors declare that an ethics committee vote is not required.