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Towards interoperability in infection control: a standard data model for microbiology.
Rinaldi, Eugenia; Drenkhahn, Cora; Gebel, Benjamin; Saleh, Kutaiba; Tönnies, Hauke; von Loewenich, Friederike D; Thoma, Norbert; Baier, Claas; Boeker, Martin; Hinske, Ludwig Christian; Diaz, Luis Alberto Peña; Behnke, Michael; Ingenerf, Josef; Thun, Sylvia.
Afiliação
  • Rinaldi E; Berlin Institute of Health, Charité Universitätsmedizin, Berlin, Germany. eugenia.rinaldi@bih-charite.de.
  • Drenkhahn C; Institute of Medical Informatics (IMI), University of Lübeck, Lübeck, Germany.
  • Gebel B; Klinik für Infektiologie und Mikrobiologie, Universitätsklinikum Schleswig-Holstein, Campus Lübeck, Lübeck, Germany.
  • Saleh K; Data Integration Center, Jena University Hospital, Jena, Germany.
  • Tönnies H; Universitätsklinikum Münster, Münster, Germany.
  • von Loewenich FD; Institute of Virology, University of Mainz, Mainz, Germany.
  • Thoma N; Institute for Hygiene and Environmental Medicine, Charité Universitätsmedizin, Berlin, Germany.
  • Baier C; Hannover Medical School, Institute for Medical Microbiology and Hospital Epidemiology, Hannover, Germany.
  • Boeker M; Technische Universität München, München, Germany.
  • Hinske LC; Institute for Digital Medicine, University Hospital Augsburg, Augsburg, Germany.
  • Diaz LAP; Institute for Hygiene and Environmental Medicine, Charité Universitätsmedizin, Berlin, Germany.
  • Behnke M; Institute for Hygiene and Environmental Medicine, Charité Universitätsmedizin, Berlin, Germany.
  • Ingenerf J; Institute of Medical Informatics (IMI), University of Lübeck, Lübeck, Germany.
  • Thun S; Berlin Institute of Health, Charité Universitätsmedizin, Berlin, Germany.
Sci Data ; 10(1): 654, 2023 09 23.
Article em En | MEDLINE | ID: mdl-37741862
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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: COVID-19 Limite: Humans País/Região como assunto: Europa Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: COVID-19 Limite: Humans País/Região como assunto: Europa Idioma: En Ano de publicação: 2023 Tipo de documento: Article