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Data Quality in Medical Real-World Data – An Oncological Use Case
Julia Gehrmann, Oya Beyan
9 - 13
10.3233/SHTI240332
Research Article
Studies in Health Technology and Informatics
Volume 316: Digital Health and Informatics Innovations for Sustainable Health Care Systems
Abstract

Data quality deficiencies significantly limit the applicability of real-world data in data-driven medical research. In this study, using an oncological use case, we report and discuss common quality deficiencies in real-world medical datasets, such as missing data, class imbalances, and timeliness issues. We compiled a multi-departmental real-world dataset comprising 13861 cancer cases diagnosed at University Hospital Cologne and examined data quality throughout the data integration process.

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