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.

A standard based approach for biomedical knowledge representation / A. Farkash, H. Neuvirth, Y. Goldschmidt, C. Conti, F. Rizzi, S. Bianchi, E. Salvi, D.M. Cusi, A. Shabo (STUDIES IN HEALTH TECHNOLOGY AND INFORMATICS). - In: User Centred Networked Health Care / [a cura di] A. Moen, S.K. Andersen, J. Aarts, P. Hurlen. - [s.l] : IOS Press, 2011. - ISBN 9781607508052. - pp. 689-693 (( Intervento presentato al 23. convegno Conference of the European Federation of Medical Informatics (MIE) : August, 28-31 tenutosi a Forum Databehandling Helsesektoren Oslo (Norway) nel 2011 [10.3233/978-1-60750-806-9-689].

A standard based approach for biomedical knowledge representation

C. Conti;F. Rizzi;E. Salvi;D.M. Cusi
Penultimo
;
2011

Abstract

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.
CEN EHR 13606; HL7/ISO CDA R2; HL7/ISO clinical genomics; HL7/ISO RIM; knowledge representation
Settore MED/14 - Nefrologia
European Federation for Medical Informatics
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2434/164490
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