Mining anti-coagulant drug-drug interactions from electronic health records using linked data

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

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

1 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 potential drug-drug interaction (PDDI) 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 PDDIs for widely prescribed anti-coagulant Warfarin. Our results from the proof-of-concept study demonstrate the potential of applying such a methodology to study prescription trends based on gender and age as well as patient health outcomes.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages128-140
Number of pages13
Volume7970 LNBI
DOIs
StatePublished - 2013
Event9th International Conference on Data Integration in the Life Sciences, DILS 2013 - Montreal, QC, Canada
Duration: Jul 11 2013Jul 12 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7970 LNBI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other9th International Conference on Data Integration in the Life Sciences, DILS 2013
CountryCanada
CityMontreal, QC
Period7/11/137/12/13

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Keywords

  • Drug-drug interactions
  • DrugBank
  • Electronic Health Records
  • Federated querying
  • SPARQL

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Pathak, J., Kiefer, R. C., & Chute, C. G. (2013). Mining anti-coagulant drug-drug interactions from electronic health records using linked data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7970 LNBI, pp. 128-140). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7970 LNBI). https://doi.org/10.1007/978-3-642-39437-9_11