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Updated: Sep 22, 2025

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Deep SNOMED CT Enabled Large Clinical Database About COVID-19.

Christophe Gaudet-Blavignac1,2, Julien Ehrsam1,2, Hugues Turbe1,2

  • 1Division of Medical Information Sciences, University Hospitals of Geneva.

Studies in Health Technology and Informatics
|May 25, 2022
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Summary

University Hospitals of Geneva (HUG) rapidly developed a unified COVID-19 database during the pandemic. This data infrastructure supports hospital governance and research by organizing clinical information for over 216,000 patients.

Keywords:
COVID-19SNOMED CTSemantic Interoperability

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Area of Science:

  • Health Informatics
  • Epidemiology
  • Clinical Data Management

Background:

  • The COVID-19 pandemic presented unprecedented challenges for healthcare systems, necessitating rapid data-driven decision-making.
  • University Hospitals of Geneva (HUG) faced the critical task of managing all COVID-19 inpatients during the initial European wave in spring 2020.
  • Limited knowledge and tools at the pandemic's outset highlighted significant challenges in clinical data pipeline processes.

Purpose of the Study:

  • To describe the development of a unified database for COVID-19 clinical data at HUG.
  • To support secondary data usage for hospital governance, predictive modeling, and research initiatives.
  • To address the urgent need for comprehensive and accessible COVID-19 patient data.

Main Methods:

  • Established core principles for the database: a clearly defined cohort, dataset, and semantics.
  • Implemented SNOMED CT for encoding over 28,000 variables, ensuring semantic interoperability.
  • Integrated data from over 216,000 patients and 590,000 inpatient stays.

Main Results:

  • Created a robust, unified database to manage COVID-19 patient data effectively.
  • The database supports daily operations, including the "Predict" dashboards and prediction reports at HUG.
  • Facilitated numerous research projects by providing structured and accessible clinical data.

Conclusions:

  • The developed unified database proved essential for HUG's response to multiple COVID-19 waves.
  • Standardized data management and semantic clarity were key to the database's success.
  • This data infrastructure enhances both clinical governance and scientific research capabilities during public health crises.