This paper is in the following e-collection/theme issue:

Implementation Report (32) Clinical Informatics (1050) eHealth Infrastructures (357) mHealth in a Clinical Setting (624) Decision Support for Health Professionals (1210) Secondary Use of Clinical Data for Research and Surveillance (375) Electronic Health Records (1068) Knowledge Translation and Implementation Science (407)

Published on in Vol 12 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/50194, first published .
Implementing a Biomedical Data Warehouse From Blueprint to Bedside in a Regional French University Hospital Setting: Unveiling Processes, Overcoming Challenges, and Extracting Clinical Insight

Implementing a Biomedical Data Warehouse From Blueprint to Bedside in a Regional French University Hospital Setting: Unveiling Processes, Overcoming Challenges, and Extracting Clinical Insight

Implementing a Biomedical Data Warehouse From Blueprint to Bedside in a Regional French University Hospital Setting: Unveiling Processes, Overcoming Challenges, and Extracting Clinical Insight

Authors of this article:

Matilde Karakachoff1 Author Orcid Image ;   Thomas Goronflot1 Author Orcid Image ;   Sandrine Coudol1 Author Orcid Image ;   Delphine Toublant1, 2 Author Orcid Image ;   Adrien Bazoge1, 3 Author Orcid Image ;   Pacôme Constant Dit Beaufils1, 4 Author Orcid Image ;   Emilie Varey1, 5 Author Orcid Image ;   Christophe Leux6 Author Orcid Image ;   Nicolas Mauduit6 Author Orcid Image ;   Matthieu Wargny1 Author Orcid Image ;   Pierre-Antoine Gourraud1, 7 Author Orcid Image
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Journals

  1. Golinvaux E, Goronflot T, Cadiet J, Senage T, Rozec B, Boissier E, Bigot-Corbel E, Lakhal K. Hemolysis Index, Carboxyhemoglobin, and Methemoglobin for the Early Identification of Patients at Risk for Cardiac Surgery–Associated Acute Kidney Injury. Journal of Cardiothoracic and Vascular Anesthesia 2024;38(12):3086 View