Quantifying the Impact of Anonymization-Induced Clinical Data Quality Loss: Methodological Quantitative Case Study Using Primary Diagnosis Codes and Hospital Length of Stay
- DOI
- 10.2196/97661
- Published
- 2026-09-11
- Container
- JMIR Medical Informatics
- Publisher
- JMIR Publications Inc.
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.2196/97661,
title = {Quantifying the Impact of Anonymization-Induced Clinical Data Quality Loss: Methodological Quantitative Case Study Using Primary Diagnosis Codes and Hospital Length of Stay},
author = {Gaetan Kamdje Wabo and Piotr Pawel Sokolowski and Mahboubeh Jannesari Ladani and Michael Hagmann and Thomas Ganslandt and Fabian Siegel},
year = {2026},
journal = {JMIR Medical Informatics},
doi = {10.2196/97661},
url = {https://doi.org/10.2196/97661}
}RIS
TY - JOUR TI - Quantifying the Impact of Anonymization-Induced Clinical Data Quality Loss: Methodological Quantitative Case Study Using Primary Diagnosis Codes and Hospital Length of Stay AU - Gaetan Kamdje Wabo AU - Piotr Pawel Sokolowski AU - Mahboubeh Jannesari Ladani AU - Michael Hagmann AU - Thomas Ganslandt AU - Fabian Siegel PY - 2026 JO - JMIR Medical Informatics DO - 10.2196/97661 UR - https://doi.org/10.2196/97661 ER -
APA
Wabo, G. K., Sokolowski, P. P., Ladani, M. J., Hagmann, M., Ganslandt, T., & Siegel, F. (2026). Quantifying the Impact of Anonymization-Induced Clinical Data Quality Loss: Methodological Quantitative Case Study Using Primary Diagnosis Codes and Hospital Length of Stay. JMIR Medical Informatics. https://doi.org/10.2196/97661
Source records
- crossref · retrieved 2026-09-24T22:27:02.735Z