title: Early identification of adverse drug reactions from search log data.
abstract: The timely and accurate identification of adverse drug reactions (ADRs) following drug approval is a persistent and serious public health challenge. Aggregated data drawn from anonymized logs of Web searchers has been shown to be a useful source of evidence for detecting ADRs. However, prior studies have been based on the analysis of established ADRs, the existence of which may already be known publically. Awareness of these ADRs can inject existing knowledge about the known ADRs into online content and online behavior, and thus raise questions about the ability of the behavioral log-based methods to detect new ADRs. In contrast to previous studies, we investigate the use of search logs for the early detection of known ADRs. We use a large set of recently labeled ADRs and negative controls to evaluate the ability of search logs to accurately detect ADRs in advance of their publication. We leverage the Internet Archive to estimate when evidence of an ADR first appeared in the public domain and adjust the index date in a backdated analysis. Our results demonstrate how search logs can be used to detect new ADRs, the central challenge in pharmacovigilance.
authors.affiliation: Microsoft Research, Redmond, WA, United States. Electronic address: ryenw@microsoft.com.
authors.forename: Ryen W
authors.initials: RW
authors.lastname: White
authors.affiliation: University of Illinois at Urbana Champaign, Urbana, IL, United States.
authors.forename: Sheng
authors.initials: S
authors.lastname: Wang
authors.affiliation: Bing Predicts Team, Microsoft Bing, Bellevue, WA, United States.
authors.forename: Apurv
authors.initials: A
authors.lastname: Pant
authors.affiliation: Oracle Health Sciences, Bedford, MA, United States.
authors.forename: Rave
authors.initials: R
authors.lastname: Harpaz
authors.affiliation: Bing Predicts Team, Microsoft Bing, Bellevue, WA, United States.
authors.forename: Pushpraj
authors.initials: P
authors.lastname: Shukla
authors.affiliation: Bing Predicts Team, Microsoft Bing, Bellevue, WA, United States.
authors.forename: Walter
authors.initials: W
authors.lastname: Sun
authors.affiliation: Oracle Health Sciences, Bedford, MA, United States.
authors.forename: William
authors.initials: W
authors.lastname: DuMouchel
authors.affiliation: Microsoft Research, Redmond, WA, United States.
authors.forename: Eric
authors.initials: E
authors.lastname: Horvitz
mesh_terms: D016907:Adverse Drug Reaction Reporting Systems; D016208:Databases, Factual; D064420:Drug-Related Side Effects and Adverse Reactions / Q000145:classification*; D006801:Humans; D008492:Medical Informatics Computing; D060735:Pharmacovigilance; D014481:United States
keywords: Adverse drug reactions; Pharmacovigilance; Search log analysis