Secondary use of patient data within decentralized studies using the example of rare diseases in Germany: a data scientist's exploration of process and lessons learned
Objective - Unlocking the potential of routine medical data for clinical research requires the analysis of data from multiple healthcare institutions. However, according to German data protection regulations, data can often not leave the individual institutions and decentralized approaches are neede...
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| Main Authors: | , , , , , , , , , , , , , , , , , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
Sep 2024
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| In: |
Digital health
Year: 2024, Volume: 10, Pages: 1-11 |
| ISSN: | 2055-2076 |
| DOI: | 10.1177/20552076241265219 |
| Online Access: | Verlag, kostenfrei, Volltext: https://journals.sagepub.com/doi/epub/10.1177/20552076241265219 Verlag, kostenfrei, Volltext: https://doi.org/10.1177/20552076241265219 
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| Author Notes: | Michele Zoch, Christian Gierschner, Anne-Katrin Andreeff, Elisa Henke, Martin Sedlmayr, Gabriele Müller, Jenny Tippmann, Helge Hebestreit, Daniela Choukair, Georg F. Hoffmann, Fleur Fritz-Kebede, Nicole Toepfner, Reinhard Berner, Stephanie Biergans, Raphael Verbücheln, Jannik Schaaf, Julia Fleck, Felix Nikolaus Wirth, Josef Schepers, and Fabian Prasser |
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| 245 | 1 | 0 | |a Secondary use of patient data within decentralized studies using the example of rare diseases in Germany |b a data scientist's exploration of process and lessons learned |c Michele Zoch, Christian Gierschner, Anne-Katrin Andreeff, Elisa Henke, Martin Sedlmayr, Gabriele Müller, Jenny Tippmann, Helge Hebestreit, Daniela Choukair, Georg F. Hoffmann, Fleur Fritz-Kebede, Nicole Toepfner, Reinhard Berner, Stephanie Biergans, Raphael Verbücheln, Jannik Schaaf, Julia Fleck, Felix Nikolaus Wirth, Josef Schepers, and Fabian Prasser |
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| 520 | |a Objective - Unlocking the potential of routine medical data for clinical research requires the analysis of data from multiple healthcare institutions. However, according to German data protection regulations, data can often not leave the individual institutions and decentralized approaches are needed. Decentralized studies face challenges regarding coordination, technical infrastructure, interoperability and regulatory compliance. Rare diseases are an important prototype research focus for decentralized data analyses, as patients are rare by definition and adequate cohort sizes can only be reached if data from multiple sites is combined. - Methods - Within the project “Collaboration on Rare Diseases”, decentralized studies focusing on four rare diseases (cystic fibrosis, phenylketonuria, Kawasaki disease, multisystem inflammatory syndrome in children) were conducted at 17 German university hospitals. Therefore, a data management process for decentralized studies was developed by an interdisciplinary team of experts from medicine, public health and data science. Along the process, lessons learned were formulated and discussed. - Results - The process consists of eight steps and includes sub-processes for the definition of medical use cases, script development and data management. The lessons learned include on the one hand the organization and administration of the studies (collaboration of experts, use of standardized forms and publication of project information), and on the other hand the development of scripts and analysis (dependency on the database, use of standards and open source tools, feedback loops, anonymization). - Conclusions - This work captures central challenges and describes possible solutions and can hence serve as a solid basis for the implementation and conduction of similar decentralized studies. | ||
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