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2021-05-18Zeitschriftenartikel
Transformation of microbiology data into a standardised data representation using OpenEHR
dc.contributor.authorWulff, Antje
dc.contributor.authorBaier, Claas
dc.contributor.authorBallout, Sarah
dc.contributor.authorTute, Erik
dc.contributor.authorSommer, Kim Katrin
dc.contributor.authorKaase, Martin
dc.contributor.authorSargeant, Anneka
dc.contributor.authorDrenkhahn, Cora
dc.contributor.authorInfection Control Study Group
dc.contributor.authorSchlüter, Dirk
dc.contributor.authorMarschollek, Michael
dc.contributor.authorScheithauer, Simone
dc.date.accessioned2024-08-26T17:29:40Z
dc.date.available2024-08-26T17:29:40Z
dc.date.issued2021-05-18none
dc.identifier.other10.1038/s41598-021-89796-y
dc.identifier.urihttp://edoc.rki.de/176904/11984
dc.description.abstractThe spread of multidrug resistant organisms (MDRO) is a global healthcare challenge. Nosocomial outbreaks caused by MDRO are an important contributor to this threat. Computer-based applications facilitating outbreak detection can be essential to address this issue. To allow application reusability across institutions, the various heterogeneous microbiology data representations needs to be transformed into standardised, unambiguous data models. In this work, we present a multi-centric standardisation approach by using openEHR as modelling standard. Data models have been consented in a multicentre and international approach. Participating sites integrated microbiology reports from primary source systems into an openEHR-based data platform. For evaluation, we implemented a prototypical application, compared the transformed data with original reports and conducted automated data quality checks. We were able to develop standardised and interoperable microbiology data models. The publicly available data models can be used across institutions to transform real-life microbiology reports into standardised representations. The implementation of a proof-of-principle and quality control application demonstrated that the new formats as well as the integration processes are feasible. Holistic transformation of microbiological data into standardised openEHR based formats is feasible in a real-life multicentre setting and lays the foundation for developing cross-institutional, automated outbreak detection systems.eng
dc.language.isoengnone
dc.publisherRobert Koch-Institut
dc.rights(CC BY 3.0 DE) Namensnennung 3.0 Deutschlandger
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/de/
dc.subject.ddc610 Medizin und Gesundheitnone
dc.titleTransformation of microbiology data into a standardised data representation using OpenEHRnone
dc.typearticle
dc.identifier.urnurn:nbn:de:0257-176904/11984-6
dc.type.versionpublishedVersionnone
local.edoc.container-titlescientific reportsnone
local.edoc.container-issn2045-2322none
local.edoc.pages12none
local.edoc.type-nameZeitschriftenartikel
local.edoc.container-typeperiodical
local.edoc.container-type-nameZeitschrift
local.edoc.container-urlhttps://www.nature.com/srep/none
local.edoc.container-publisher-nameSpringer Naturenone
local.edoc.container-volume11none
local.edoc.container-reportyear2021none
dc.description.versionPeer Reviewednone

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