title: Semantic enrichment of clinical models towards semantic interoperability. The heart failure summary use case.
abstract: OBJECTIVE
  To improve semantic interoperability of electronic health records (EHRs) by ontology-based mediation across syntactically heterogeneous representations of the same or similar clinical information.
  
  
  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.
  
  
  CONCLUSIONS
  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.
  
  
  CONCLUSIONS
  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.
authors: Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria catalina.martinez@medunigraz.at.
authors: Catalina
authors: C
authors: Martínez-Costa
authors: Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands catalina.martinez@medunigraz.at.
authors: Ronald
authors: R
authors: Cornet
authors: Department of Biomedical Engineering, University of Linköping, Linköping, Sweden.
authors: Daniel
authors: D
authors: Karlsson
authors: Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria.
authors: Stefan
authors: S
authors: Schulz
authors: Centre for Health Informatics & Multiprofessional Education, University College London, London, UK.
authors: Dipak
authors: D
authors: Kalra
mesh_terms: D001185:Artificial Intelligence; D057286:Electronic Health Records; D006333:Heart Failure / Q000145:classification; D006801:Humans; D008498:Medical Record Linkage; D011381:Programming Languages; D012660:Semantics; D039061:Systematized Nomenclature of Medicine; D018511:Systems Integration; D009626:Terminology as Topic; D018875:Vocabulary, Controlled
keywords: Electronic health record; SNOMED CT reference terminology; knowledge representation; ontology; semantics; terminology