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Medical Data Engineering – Theory and Practice

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Advances in Model and Data Engineering in the Digitalization Era (MEDI 2021)

Abstract

Data integration and exchange are becoming more crucial with the increasing amount of distributed systems and ever-growing amounts of data. This need is also widely known in medical research and not yet comprehensively solved. Practical implementation steps will demonstrate the different challenges in the context of the National Medical Informatics Initiative in Germany. Top-down versus bottom-up approaches as general methods of standard-based data integration in healthcare will be discussed and illustrated in the process of building up Medical Data Integration Centers. As practical examples, the use cases Infection Control, Cardiology, and Molecular Tumor Board, will be presented. Finally, limitations that prevent the use of theoretically recommended data integration methods in the particular field of medical informatics are illustrated.

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Acknowledgements

This work is funded by the German Federal Ministry of Education and Research (BMBF) as part of the Medical Informatics Initiative Germany, Grand IDs 01ZZ1802Z and 01ZZ1802T.

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Correspondence to Ann-Kristin Kock-Schoppenhauer .

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Kock-Schoppenhauer, AK. et al. (2021). Medical Data Engineering – Theory and Practice. In: Bellatreche, L., Chernishev, G., Corral, A., Ouchani, S., Vain, J. (eds) Advances in Model and Data Engineering in the Digitalization Era. MEDI 2021. Communications in Computer and Information Science, vol 1481. Springer, Cham. https://doi.org/10.1007/978-3-030-87657-9_21

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  • DOI: https://doi.org/10.1007/978-3-030-87657-9_21

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