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Query: UMLS:C0085580 (essential hypertension)
 14,686 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

A core challenge in biomedical data integration is to enable semantic interoperability between its various stakeholders as well as other interested parties. Promoting the adoption of worldwide accepted information standards along with common controlled terminologies is the right path to achieve this. Our paper describes a solution to this fundamental problem by proposing an approach to semantic data integration based on information models serving as a common language to represent health data coupled with technology that is able to represent the data semantics. We used the HL7 v3 Reference Information Model (RIM) [1] to derive a specific data model for the integrated data, the Web Ontology Language (OWL) [2] to build an ontology that harmonizes the metadata from the disparate data sources, the Unified Modeling Language (UML) [3] to model the data representation, and the Object Constraint Language (OCL) [4] to specify UML model constraints. To illustrate the approach, we use the Essential Hypertension Summary CDA document and related models from Hypergenes, a European Commission funded project [5] exploring the Essential Hypertension disease model.
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PMID:A model-driven approach for biomedical data integration. 2084 67

The new generation of health information standards, where the syntax and semantics of the content is explicitly formalized, allows for interoperability in healthcare scenarios and analysis in clinical research settings. Studies involving clinical and genomic data include accumulating knowledge as relationships between genotypic and phenotypic information as well as associations within the genomic and clinical worlds. Some involve analysis results targeted at a specific disease; others are of a predictive nature specific to a patient and may be used by decision support applications. Representing knowledge is as important as representing data since data is more useful when coupled with relevant knowledge. Any further analysis and cross-research collaboration would benefit from persisting knowledge and data in a unified way. This paper describes a methodology used in Hypergenes, an EC FP7 project targeting Essential Hypertension, which captures data and knowledge using standards such as HL7 CDA and Clinical Genomics, aligned with the CEN EHR 13606 specification. We demonstrate the benefits of such an approach for clinical research as well as in healthcare oriented scenarios.
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PMID:A standard based approach for biomedical knowledge representation. 2189 35

Healthcare data interoperability can only be achieved when the semantics of the content is well defined and consistently implemented across heterogeneous data sources. Achieving these objectives of interoperability requires the collaboration of experts from several domains. This paper describes tooling that integrates Semantic Web technologies with common tools to facilitate cross-domain collaborative development for the purposes of data interoperability. Our approach is divided into stages of data harmonization and representation, model transformation, and instance generation. We applied our approach on Hypergenes, an EU funded project, where we use our method to the Essential Hypertension disease model using a CDA template. Our domain expert partners include clinical providers, clinical domain researchers, healthcare information technology experts, and a variety of clinical data consumers. We show that bringing Semantic Web technologies into the healthcare interoperability toolkit increases opportunities for beneficial collaboration thus improving patient care and clinical research outcomes.
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PMID:Large scale healthcare data integration and analysis using the semantic web. 2189 43