Exploring the Complexity of Real‐World Health Data Record Linkage—An Exemplary Study Linking Cancer Registry and Claims Data
Linkage of German claims and cancer registry data based on quasi-identifiers does result in insufficient linkage quality since subjects cannot be uniquely identified. It is advisable to use unique identifiers from a subsample, if available, to derive informed linkage algorithms for the entire sample. In this case, the machine learning technique gradient boosting has been found to outperform other methods.
Authors
- Timm Intemann (ORCID: https://orcid.org/0000-0001-7836-3643)
- Bianca Kollhorst (ORCID: https://orcid.org/0000-0001-5964-954X)
- Nadja Lendle
Institutions
- Leibniz Institute for Prevention Research and Epidemiology - BIPS (DE)
Publication Details
- Journal
- Pharmacoepidemiology and Drug Safety
- Published
- 2025-03-25
- DOI
- https://doi.org/10.1002/pds.70120
- Primary Topic
- Data Quality and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Deutsche Forschungsgemeinschaft