PED-DATA: A Privacy-Preserving Framework for Data-Driven, Pediatric Multi-Center Studies Article Swipe
YOU?
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· 2025
· Open Access
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· DOI: https://doi.org/10.3233/shti251409
Introduction: Data-driven analysis of clinical databases is an efficient method for clinical knowledge generation, which is especially suitable when exceptional ethical and practical restrictions apply, such as in pediatrics. In the multi-center PEDREF 2.0 study, we are analyzing children’s laboratory test results, diagnoses, and procedures from more than 20 German tertiary care centers to establish pediatric reference intervals. The PEDREF 2.0 study uses the framework of the German Medical Informatics Initiative, but the specific study needs require the development of a customized module for distributed pediatric analyses. Methods: We developed the Pediatric Distributed Analysis, Anonymization, and Aggregation Module (PED-DATA), which is a containerized application that we deployed to all participating centers. PED-DATA transforms the input datasets to a harmonized internal representation and enables their decentralized analysis in compliance with data protection rules, resulting in an anonymous output dataset that is transferred for central analysis. Results: In a preliminary analysis of data from 15 centers, we analyzed 52,807,236 laboratory test results from 753,774 different patients (323,943 to 4,338,317 test results per laboratory test), enabling us to establish pediatric reference intervals with previously unmatched precision. Conclusion: PED-DATA facilitates the implementation of pediatric data-driven multicenter studies in a decentralized and privacy-respecting manner, and its use throughout German University Hospitals in the PEDREF 2.0 study demonstrates its usefulness in a real-world use case.
Related Topics
- Type
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- Language
- en
- Landing Page
- https://doi.org/10.3233/shti251409
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- Related Works
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- OpenAlex ID
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Raw OpenAlex JSON
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https://openalex.org/W4413956477Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3233/shti251409Digital Object Identifier
- Title
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PED-DATA: A Privacy-Preserving Framework for Data-Driven, Pediatric Multi-Center StudiesWork title
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articleOpenAlex work type
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enPrimary language
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2025Year of publication
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2025-09-03Full publication date if available
- Authors
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Gorkem Yilmaz, Jonathan M. Mang, Markus Metzler, Hans‐Ulrich Prokosch, Manfred Rauh, Jakob ZierkList of authors in order
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https://doi.org/10.3233/shti251409Publisher landing page
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://doi.org/10.3233/shti251409Direct OA link when available
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Computer science, German, Test (biology), Medical diagnosis, Informatics, Data mining, Center (category theory), Data science, Medicine, Engineering, Pathology, Electrical engineering, Archaeology, History, Paleontology, Chemistry, Biology, CrystallographyTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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