Evidence map›Paper›PMID 25670758›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2015

Semantic enrichment of clinical models towards semantic interoperability. The heart failure summary use case.

Catalina Martínez-Costa, Ronald Cornet, Daniel Karlsson, Stefan Schulz, Dipak Kalra

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Article in Journal of the American Medical Informatics Association : JAMIA, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

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0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

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  12. AMIA--Setting the Standard.Journal of the American Medical Informatics Association : JAMIA · 2015
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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Catalina Martínez-CostaInstitute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria catalina.martinez@medunigraz.at.
Ronald CornetAcademic Medical Center, University of Amsterdam, Amsterdam, The Netherlands catalina.martinez@medunigraz.at.
Daniel KarlssonDepartment of Biomedical Engineering, University of Linköping, Linköping, Sweden.
Stefan SchulzInstitute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria.
Dipak KalraCentre for Health Informatics & Multiprofessional Education, University College London, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo 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

methodsOur 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.

resultsUsing 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.

conclusionWe 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.

Indexed as

Electronic Health RecordsHeart FailureMedical Record LinkageVocabulary, ControlledArtificial IntelligenceHumansProgramming LanguagesSemanticsSystematized Nomenclature of MedicineSystems IntegrationTerminology as TopicElectronic health recordknowledge representationontologysemanticsSNOMED CT reference terminologyterminology

Identifiers

PMID25670758
PMCPMC11737585

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.