De-Identifying GRASCCO - A Pilot Study for the De-Identification of the German Medical Text Project (GeMTeX) Corpus.


Journal

Studies in health technology and informatics
ISSN: 1879-8365
Titre abrégé: Stud Health Technol Inform
Pays: Netherlands
ID NLM: 9214582

Informations de publication

Date de publication:
30 Aug 2024
Historique:
medline: 5 9 2024
pubmed: 5 9 2024
entrez: 5 9 2024
Statut: ppublish

Résumé

The German Medical Text Project (GeMTeX) is one of the largest infrastructure efforts targeting German-language clinical documents. We here introduce the architecture of the de-identification pipeline of GeMTeX. This pipeline comprises the export of raw clinical documents from the local hospital information system, the import into the annotation platform INCEpTION, fully automatic pre-tagging with protected health information (PHI) items by the Averbis Health Discovery pipeline, a manual curation step of these pre-annotated data, and, finally, the automatic replacement of PHI items with type-conformant substitutes. This design was implemented in a pilot study involving six annotators and two curators each at the Data Integration Centers of the University Hospitals Leipzig and Erlangen. As a proof of concept, the publicly available Graz Synthetic Text Clinical Corpus (GRASSCO) was enhanced with PHI annotations in an annotation campaign for which reasonable inter-annotator agreement values of Krippendorff's α ≈ 0.97 can be reported. These curated 1.4 K PHI annotations are released as open-source data constituting the first publicly available German clinical language text corpus with PHI metadata.

Identifiants

pubmed: 39234720
pii: SHTI240853
doi: 10.3233/SHTI240853
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

171-179

Auteurs

Christina Lohr (C)

Institute for Medical Informatics, Statistics, and Epidemiology, Leipzig University, Germany.
GeMTeX Consortium of the German Medical Informatics Initiative.

Franz Matthies (F)

Institute for Medical Informatics, Statistics, and Epidemiology, Leipzig University, Germany.
GeMTeX Consortium of the German Medical Informatics Initiative.

Jakob Faller (J)

Medical Center for Information and Communication Technology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
GeMTeX Consortium of the German Medical Informatics Initiative.

Luise Modersohn (L)

Institute of Artificial Intelligence and Informatics in Medicine, Medical Center rechts der Isar, Technical University Munich, Germany.
GeMTeX Consortium of the German Medical Informatics Initiative.

Andrea Riedel (A)

Medical Center for Information and Communication Technology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
GeMTeX Consortium of the German Medical Informatics Initiative.

Udo Hahn (U)

Institute for Medical Informatics, Statistics, and Epidemiology, Leipzig University, Germany.
GeMTeX Consortium of the German Medical Informatics Initiative.

Rebekka Kiser (R)

Institute of Artificial Intelligence and Informatics in Medicine, Medical Center rechts der Isar, Technical University Munich, Germany.

Martin Boeker (M)

Institute of Artificial Intelligence and Informatics in Medicine, Medical Center rechts der Isar, Technical University Munich, Germany.
GeMTeX Consortium of the German Medical Informatics Initiative.

Frank Meineke (F)

Institute for Medical Informatics, Statistics, and Epidemiology, Leipzig University, Germany.
GeMTeX Consortium of the German Medical Informatics Initiative.

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