Using linked data for mining drug-drug interactions in electronic health records

Jyotishman Pathak, Richard C. Kiefer, Christopher G. Chute

Research output: Chapter in Book/Report/Conference proceedingConference contribution

18 Scopus citations

Abstract

By nature, healthcare data is highly complex and voluminous. While on one hand, it provides unprecedented opportunities to identify hidden and unknown relationships between patients and treatment outcomes, or drugs and allergic reactions for given individuals, representing and querying large network datasets poses significant technical challenges. In this research, we study the use of Semantic Web and Linked Data technologies for identifying drug-drug interaction (DDI) information from publicly available resources, and determining if such interactions were observed using real patient data. Specifically, we apply Linked Data principles and technologies for representing patient data from electronic health records (EHRs) at Mayo Clinic as Resource Description Framework (RDF), and identify potential drug-drug interactions (PDDIs) for widely prescribed cardiovascular and gastroenterology drugs. Our results from the proof-of-concept study demonstrate the potential of applying such a methodology to study patient health outcomes as well as enabling genome-guided drug therapies and treatment interventions.

Original languageEnglish (US)
Title of host publicationMEDINFO 2013 - Proceedings of the 14th World Congress on Medical and Health Informatics
PublisherIOS Press
Pages682-686
Number of pages5
Edition1-2
ISBN (Print)9781614992882
DOIs
StatePublished - Jan 1 2013
Event14th World Congress on Medical and Health Informatics, MEDINFO 2013 - Copenhagen, Denmark
Duration: Aug 20 2013Aug 23 2013

Publication series

NameStudies in Health Technology and Informatics
Number1-2
Volume192
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Other

Other14th World Congress on Medical and Health Informatics, MEDINFO 2013
CountryDenmark
CityCopenhagen
Period8/20/138/23/13

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Keywords

  • Drug-drug interactions
  • Electronic health records
  • Federated querying
  • Semantic Web

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

Cite this

Pathak, J., Kiefer, R. C., & Chute, C. G. (2013). Using linked data for mining drug-drug interactions in electronic health records. In MEDINFO 2013 - Proceedings of the 14th World Congress on Medical and Health Informatics (1-2 ed., pp. 682-686). (Studies in Health Technology and Informatics; Vol. 192, No. 1-2). IOS Press. https://doi.org/10.3233/978-1-61499-289-9-682