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Semantic processing of EHR data for clinical research.
Sun, Hong; Depraetere, Kristof; De Roo, Jos; Mels, Giovanni; De Vloed, Boris; Twagirumukiza, Marc; Colaert, Dirk.
Afiliación
  • Sun H; Advanced Clinical Applications Research Group, Agfa HealthCare, Moutstraat 100, 9000 Gent, Belgium. Electronic address: hong.sun@agfa.com.
  • Depraetere K; Advanced Clinical Applications Research Group, Agfa HealthCare, Moutstraat 100, 9000 Gent, Belgium.
  • De Roo J; Advanced Clinical Applications Research Group, Agfa HealthCare, Moutstraat 100, 9000 Gent, Belgium.
  • Mels G; Advanced Clinical Applications Research Group, Agfa HealthCare, Moutstraat 100, 9000 Gent, Belgium.
  • De Vloed B; Advanced Clinical Applications Research Group, Agfa HealthCare, Moutstraat 100, 9000 Gent, Belgium.
  • Twagirumukiza M; Advanced Clinical Applications Research Group, Agfa HealthCare, Moutstraat 100, 9000 Gent, Belgium.
  • Colaert D; Advanced Clinical Applications Research Group, Agfa HealthCare, Moutstraat 100, 9000 Gent, Belgium.
J Biomed Inform ; 58: 247-259, 2015 Dec.
Article en En | MEDLINE | ID: mdl-26515501
There is a growing need to semantically process and integrate clinical data from different sources for clinical research. This paper presents an approach to integrate EHRs from heterogeneous resources and generate integrated data in different data formats or semantics to support various clinical research applications. The proposed approach builds semantic data virtualization layers on top of data sources, which generate data in the requested semantics or formats on demand. This approach avoids upfront dumping to and synchronizing of the data with various representations. Data from different EHR systems are first mapped to RDF data with source semantics, and then converted to representations with harmonized domain semantics where domain ontologies and terminologies are used to improve reusability. It is also possible to further convert data to application semantics and store the converted results in clinical research databases, e.g. i2b2, OMOP, to support different clinical research settings. Semantic conversions between different representations are explicitly expressed using N3 rules and executed by an N3 Reasoner (EYE), which can also generate proofs of the conversion processes. The solution presented in this paper has been applied to real-world applications that process large scale EHR data.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Semántica / Investigación Biomédica / Registros Electrónicos de Salud Idioma: En Revista: J Biomed Inform Asunto de la revista: INFORMATICA MEDICA Año: 2015 Tipo del documento: Article Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Semántica / Investigación Biomédica / Registros Electrónicos de Salud Idioma: En Revista: J Biomed Inform Asunto de la revista: INFORMATICA MEDICA Año: 2015 Tipo del documento: Article Pais de publicación: Estados Unidos