Assuring End-to-End Data Quality for Analytics on FHIR

Ziegler J, Fischer C, Volkmer PC, Erpenbeck MP, Mang JM, Ganslandt T, Prokosch HU, Gulden C (2025)

Publication Type: Book chapter / Article in edited volumes

Publication year: 2025

Publisher: IOS Press

Edited Volumes: dHealth 2025

Series: Studies in Health Technology and Informatics

Book Volume: 324

Pages Range: 57-62

DOI: 10.3233/SHTI250161

Abstract

BACKGROUND: The accumulation of Real-World Data (RWD) from Electronic Health Records (EHRs) and registries offers substantial potential for generating Real-World Evidence (RWE). However, the ability to generate robust evidence from real-world data hinges on its quality. This is especially critical when heterogeneous data is first transformed into standardized, research-ready data models. OBJECTIVE: This study presents an approach for assessing data completeness through a pipeline for extracting and transforming oncological RWD. METHODS: We introduce a technical solution that enables the assessment of data completeness across three data transformation stages, beginning with the initial data source and extending through Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) to CSV. RESULTS: Using Trino, a distributed SQL engine, we evaluate data completeness at the three transformation stages by comparing cancer diagnosis counts. The modular pipeline design, compatible with various data sources, allows for error detection in ETL processes. CONCLUSION: Future work will expand the system to address additional data quality dimensions, such as correctness and plausibility, improving the overall robustness of data analytics in federated environments.

Authors with CRIS profile

Jonathan Mang Medizinisches Zentrum für Informations- und Kommunikationstechnik (Medizinisches IK-Zentrum, MIK) Thomas Ganslandt Professur für Medical Data Science Hans-Ulrich Prokosch Lehrstuhl für Medizinische Informatik Christian Gulden Professur für Medical Data Science

Involved external institutions

Bayerisches Zentrum für Krebsforschung (BZKF) DE Germany (DE)

How to cite

APA:

Ziegler, J., Fischer, C., Volkmer, P.C., Erpenbeck, M.P., Mang, J.M., Ganslandt, T.,... Gulden, C. (2025). Assuring End-to-End Data Quality for Analytics on FHIR. In Martin Baumgartner, Dieter Hayn, Bernhard Pfeifer, Günter Schreier (Eds.), dHealth 2025. (pp. 57-62). IOS Press.

MLA:

Ziegler, Jasmin, et al. "Assuring End-to-End Data Quality for Analytics on FHIR." dHealth 2025. Ed. Martin Baumgartner, Dieter Hayn, Bernhard Pfeifer, Günter Schreier, IOS Press, 2025. 57-62.

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