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Assessing the Use of German Claims Data Vocabularies for Research in the Observational Medical Outcomes Partnership Common Data Model: Development and Evaluation Study

Assessing the Use of German Claims Data Vocabularies for Research in the Observational Medical Outcomes Partnership Common Data Model: Development and Evaluation Study

To address this challenge, we focus first on the vocabularies used in German claims data as they build the basis for further semantic mapping to the OMOP CDM. In an initial analysis of the current coverage of German claims data vocabularies in the OMOP CDM by Henke et al [12], it was shown that 55% (11/20) of the vocabularies are not available. Only 15% (3/20) of the vocabularies are currently present in Athena.

Elisa Henke, Michéle Zoch, Michael Kallfelz, Thomas Ruhnke, Liz Annika Leutner, Melissa Spoden, Christian Günster, Martin Sedlmayr, Franziska Bathelt

JMIR Med Inform 2023;11:e47959

The Value of Extracting Clinician-Recorded Affect for Advancing Clinical Research on Depression: Proof-of-Concept Study Applying Natural Language Processing to Electronic Health Records

The Value of Extracting Clinician-Recorded Affect for Advancing Clinical Research on Depression: Proof-of-Concept Study Applying Natural Language Processing to Electronic Health Records

Using tools built around ontologies (controlled vocabularies), like SNOMED-CT (Systematized Nomenclature of Medicine-Clinical Terms) [11], NLP has enabled researchers to automate the capture of information in clinical narratives [10].

Vanessa Panaite, Andrew R Devendorf, Dezon Finch, Lina Bouayad, Stephen L Luther, Susan K Schultz

JMIR Form Res 2022;6(5):e34436