title: Pharmacovigilance using Clinical Text.
abstract: 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.
authors.affiliation: Stanford University, Stanford, CA.
authors.forename: Paea
authors.initials: P
authors.lastname: Lependu
authors.forename: Srinivasan V
authors.initials: SV
authors.lastname: Iyer
authors.forename: Anna
authors.initials: A
authors.lastname: Bauer-Mehren
authors.forename: Rave
authors.initials: R
authors.lastname: Harpaz
authors.forename: Yohannes T
authors.initials: YT
authors.lastname: Ghebremariam
authors.forename: John P
authors.initials: JP
authors.lastname: Cooke
authors.forename: Nigam H
authors.initials: NH
authors.lastname: Shah