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dc.contributor.authorMartínez Costa, Catalina-
dc.contributor.authorCornet, Ronald-
dc.contributor.authorKarlsson, Daniel-
dc.contributor.authorSchulz, Stefan-
dc.contributor.authorKalra, Dipak-
dc.date.accessioned2025-02-03T07:44:12Z-
dc.date.available2025-02-03T07:44:12Z-
dc.date.issued2015-02-10-
dc.identifier.citationJournal of the American Medical Informatics Association, 2015, Vol. 22 (3), pp. 565-576es
dc.identifier.issnElectronic: 2574-2531-
dc.identifier.urihttp://hdl.handle.net/10201/149968-
dc.description© 2015 American Medical Informatics Association. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ This document is the Submitted Manuscript version of a Published Work that appeared in final form in Journal of the American Medical Informatics Association. To access the final edited and published work see https://doi.org/10.1093/jamia/ocu013-
dc.description.abstractObjective: To improve semantic interoperability of electronic health records (EHRs) by ontology-based mediation across syntactically heterogeneous representations of the same or similar clinical information. Materials and Methods: Our approach is based on a semantic layer that consists of: (1) a set of ontologies supported by (2) a set of semantic patterns. The first aspect of the semantic layer helps standardize the clinical information modeling task and the second shields modelers from the complexity of ontology modeling. We applied this approach to heterogeneous representations of an excerpt of a heart failure summary. Results: Using a set of finite top-level patterns to derive semantic patterns, we demonstrate that those patterns, or compositions thereof, can be used to represent information from clinical models. Homogeneous querying of the same or similar information, when represented according to heterogeneous clinical models, is feasible. Discussion: Our approach focuses on the meaning embedded in EHRs, regardless of their structure. This complex task requires a clear ontological commitment (ie, agreement to consistently use the shared vocabulary within some context), together with formalization rules. These requirements are supported by semantic patterns. Other potential uses of this approach, such as clinical models validation, require further investigation. Conclusion We show how an ontology-based representation of a clinical summary, guided by semantic patterns, allows homogeneous querying of heterogeneous information structures. Whether there are a finite number of top-level patterns is an open question.es
dc.formatapplication/pdfes
dc.languageenges
dc.publisherOxford University Presses
dc.relationThis work has been funded by the SemanticHealthNet Network of Excellence within the EU 7th Framework Program, Call: FP7-ICT-2011-7, agreement 288408, http://www.semantichealthnet.eu/.es
dc.rightsinfo:eu-repo/semantics/openAccesses
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectElectronic health recordes
dc.subjectTerminologyes
dc.subjectSNOMED CT reference terminologyes
dc.subjectOntologyes
dc.subjectSemanticses
dc.subjectKnowledge representationes
dc.titleSemantic enrichment of clinical models towards semantic interoperability. The heart failure summary use casees
dc.typeinfo:eu-repo/semantics/preprintes
dc.relation.publisherversionhttps://oxfordjournals.org/jamia/article-abstract/22/3/565/773633?redirectedFrom=fulltext-
dc.identifier.doihttps://doi.org/10.1093/jamia/ocu013-
dc.contributor.departmentDepartamento de Informática y Sistemas-
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