title: Feasibility of Prioritizing Drug-Drug-Event Associations Found in Electronic Health Records.
abstract: OBJECTIVE
  Several studies have demonstrated the ability to detect adverse events potentially related to multiple drug exposure via data mining. However, the number of putative associations produced by such computational approaches is typically large, making experimental validation difficult. We theorized that those potential associations for which there is evidence from multiple complementary sources are more likely to be true, and explored this idea using a published database of drug-drug-adverse event associations derived from electronic health records (EHRs).
  
  
  METHODS
  We prioritized drug-drug-event associations derived from EHRs using four sources of information: (1) public databases, (2) sources of spontaneous reports, (3) literature, and (4) non-EHR drug-drug interaction (DDI) prediction methods. After pre-filtering the associations by removing those found in public databases, we devised a ranking for associations based on the support from the remaining sources, and evaluated the results of this rank-based prioritization.
  
  
  RESULTS
  We collected information for 5983 putative EHR-derived drug-drug-event associations involving 345 drugs and ten adverse events from four data sources and four prediction methods. Only seven drug-drug-event associations (<0.5 %) had support from the majority of evidence sources, and about one third (1777) had support from at least one of the evidence sources.
  
  
  CONCLUSIONS
  Our proof-of-concept method for scoring putative drug-drug-event associations from EHRs offers a systematic and reproducible way of prioritizing associations for further study. Our findings also quantify the agreement (or lack thereof) among complementary sources of evidence for drug-drug-event associations and highlight the challenges of developing a robust approach for prioritizing signals of these associations.
authors.affiliation: Stanford Center for Biomedical Informatics Research, 1265 Welch Road, MSOB, Stanford, CA, 94305, USA. jmbanda@stanford.edu.
authors.forename: Juan M
authors.identifier: http://orcid.org/0000-0001-8499-824X
authors.initials: JM
authors.lastname: Banda
authors.affiliation: Stanford Center for Biomedical Informatics Research, 1265 Welch Road, MSOB, Stanford, CA, 94305, USA.
authors.forename: Alison
authors.initials: A
authors.lastname: Callahan
authors.affiliation: Stanford Center for Biomedical Informatics Research, 1265 Welch Road, MSOB, Stanford, CA, 94305, USA.
authors.forename: Rainer
authors.initials: R
authors.lastname: Winnenburg
authors.affiliation: Wolters Kluwer Health, San Diego, CA, USA.
authors.forename: Howard R
authors.initials: HR
authors.lastname: Strasberg
authors.affiliation: Division of Emergency Medicine, Boston Children's Hospital, Boston, MA, USA.|Department of Pediatrics, Harvard Medical School, Boston, MA, USA.
authors.forename: Aurel
authors.initials: A
authors.lastname: Cami
authors.affiliation: Division of Emergency Medicine, Boston Children's Hospital, Boston, MA, USA.|Department of Pediatrics, Harvard Medical School, Boston, MA, USA.
authors.forename: Ben Y
authors.initials: BY
authors.lastname: Reis
authors.affiliation: Department of Biomedical Informatics, Columbia University Medical Center, New York, NY, USA.
authors.forename: Santiago
authors.initials: S
authors.lastname: Vilar
authors.affiliation: Department of Biomedical Informatics, Columbia University Medical Center, New York, NY, USA.
authors.forename: George
authors.initials: G
authors.lastname: Hripcsak
authors.affiliation: Stanford Center for Biomedical Informatics Research, 1265 Welch Road, MSOB, Stanford, CA, 94305, USA.
authors.forename: Michel
authors.initials: M
authors.lastname: Dumontier
authors.affiliation: Stanford Center for Biomedical Informatics Research, 1265 Welch Road, MSOB, Stanford, CA, 94305, USA.
authors.forename: Nigam Haresh
authors.initials: NH
authors.lastname: Shah
mesh_terms: D016907:Adverse Drug Reaction Reporting Systems; D057225:Data Mining / Q000379:methods*; D016208:Databases, Factual; D004347:Drug Interactions; D064420:Drug-Related Side Effects and Adverse Reactions / Q000453:epidemiology*; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D005240:Feasibility Studies; D006801:Humans