Pharmacovigilance using Clinical Text

Paea Lependu, Srinivasan V Iyer, Anna Bauer-Mehren, Rave Harpaz, Yohannes T Ghebremariam, John P Cooke, Nigam H Shah

Research output: Contribution to journalArticle


The current state of the art in post-marketing drug surveillance utilizes voluntarily submitted reports of suspected adverse drug reactions. We present data mining methods that transform unstructured patient notes taken by doctors, nurses and other clinicians into a de-identified, temporally ordered, patient-feature matrix using standardized medical terminologies. We demonstrate how to use the resulting high-throughput data to monitor for adverse drug events based on the clinical notes in the EHR.

Original languageEnglish (US)
Pages (from-to)109
JournalAMIA Joint Summits on Translational Science proceedings AMIA Summit on Translational Science
StatePublished - 2013


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