Scientific Data (Sep 2023)

Towards interoperability in infection control: a standard data model for microbiology

  • Eugenia Rinaldi,
  • Cora Drenkhahn,
  • Benjamin Gebel,
  • Kutaiba Saleh,
  • Hauke Tönnies,
  • Friederike D. von Loewenich,
  • Norbert Thoma,
  • Claas Baier,
  • Martin Boeker,
  • Ludwig Christian Hinske,
  • Luis Alberto Peña Diaz,
  • Michael Behnke,
  • Josef Ingenerf,
  • Sylvia Thun

DOI
https://doi.org/10.1038/s41597-023-02560-x
Journal volume & issue
Vol. 10, no. 1
pp. 1 – 13

Abstract

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Abstract The COVID-19 pandemic has made it clear: sharing and exchanging data among research institutions is crucial in order to efficiently respond to global health threats. This can be facilitated by defining health data models based on interoperability standards. In Germany, a national effort is in progress to create common data models using international healthcare IT standards. In this context, collaborative work on a data set module for microbiology is of particular importance as the WHO has declared antimicrobial resistance one of the top global public health threats that humanity is facing. In this article, we describe how we developed a common model for microbiology data in an interdisciplinary collaborative effort and how we make use of the standard HL7 FHIR and terminologies such as SNOMED CT or LOINC to ensure syntactic and semantic interoperability. The use of international healthcare standards qualifies our data model to be adopted beyond the environment where it was first developed and used at an international level.