title: Large scale healthcare data integration and analysis using the semantic web.
abstract: 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.
authors: IBM Almaden Research Center 640 Harry Rd, San Jose, CA 95120, US.
authors: John
authors: J
authors: Timm
authors: Sondra
authors: S
authors: Renly
authors: Ariel
authors: A
authors: Farkash
mesh_terms: D022126:Access to Information; D000465:Algorithms; D001331:Automation; D016208:Databases, Factual; D006801:Humans; D006973:Hypertension / Q000188:drug therapy* / Q000453:epidemiology / Q000235:genetics; D016247:Information Storage and Retrieval / Q000379:methods*; D020407:Internet; D008490:Medical Informatics / Q000379:methods*; D010597:Pharmacogenetics / Q000379:methods; D011381:Programming Languages; D012660:Semantics; D018511:Systems Integration