Feasibility of Prioritizing Drug-Drug-Event Associations Found in Electronic Health Records.

ABSTRACT:

Background and 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-d

SUBMITTER: Banda JM 

PROVIDER: S-EPMC4712252 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature