Multi-Centric Quality Analysis of Oncological Data in FHIR

Fischer C, Gulden C, Quell D, Ziegler J, Hellwig D, Ganslandt T, Pukrop T, Pallaoro P (2026)

Publication Type: Journal article

Publication year: 2026

Journal

Studies in Health Technology and Informatics IOS Press

Book Volume: 336

Pages Range: 1257-1261

DOI: 10.3233/SHTI260400

Abstract

Ensuring the reliability and impact of data-driven research requires high-quality data. The more complex the source system and data processing pipelines are, the higher the risk of poor data quality (DQ) during analysis, which in turn compromises the research outcomes. Even for well-structured and standardized data, such as the oncological standardized dataset (oBDS), medical research projects must assess DQ to ensure the reliability of their results. This study assesses the quality of the oncological standardized dataset mapped to FHIR resources across six German university hospitals. Automated DQ checks using Pathling and Great Expectations were implemented on the FHIR resources to evaluate key dimensions of DQ. It demonstrates that DQ varies across data sources, indicating that high DQ cannot be assumed to be uniform even if the dataset is standardized. The results of this assessment will be integrated into the Real World Data Platform of the Bavarian Cancer Research Center (BZKF), enhancing its ability to provide researchers with high-quality oncological data for scientific studies.

Authors with CRIS profile

Christian Gulden Professur für Medical Data Science

Involved external institutions

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

How to cite

APA:

Fischer, C., Gulden, C., Quell, D., Ziegler, J., Hellwig, D., Ganslandt, T.,... Pallaoro, P. (2026). Multi-Centric Quality Analysis of Oncological Data in FHIR. Studies in Health Technology and Informatics, 336, 1257-1261. https://doi.org/10.3233/SHTI260400

MLA:

Fischer, Clara, et al. "Multi-Centric Quality Analysis of Oncological Data in FHIR." Studies in Health Technology and Informatics 336 (2026): 1257-1261.

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