Toward enhanced pharmacovigilance using patient-generated data on the internet.
The promise of augmenting pharmacovigilance with patient-generated data drawn from the Internet was called out by a scientific committee charged with conducting a review of the current and planned pharmacovigilance practices of the US Food and Drug Administration (FDA). To this end, we present a study on harnessing behavioral data drawn from Internet search logs to detect adverse drug reactions (ADRs). By analyzing search queries collected from 80 million consenting users and by using a widely recognized benchmark of ADRs, we found that the performance of ADR detection via search logs is comparable and complementary to detection based on the FDA's adverse event reporting system (AERS). We show that by jointly leveraging data from the AERS and search logs, the accuracy of ADR detection can be improved by 19% relative to the use of each data source independently. The results suggest that leveraging nontraditional sources such as online search logs could supplement existing pharmacovigilance approaches.
Microsoft Research, Redmond, Washington, USA.
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White
Center for Biomedical Informatics Research, Stanford University, Stanford, California, USA.
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Harpaz
Center for Biomedical Informatics Research, Stanford University, Stanford, California, USA.
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Shah
1] Oracle Health Sciences, Burlington, Massachusetts, USA [2] Observational Medical Outcomes Partnership, Foundation for the National Institutes of Health, Bethesda, Maryland, USA.
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DuMouchel
Microsoft Research, Redmond, Washington, USA.
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Horvitz
D016907:Adverse Drug Reaction Reporting Systems / Q000592:standards / Q000639:trends*; D057225:Data Mining / Q000592:standards / Q000639:trends*; D016208:Databases, Factual / Q000592:standards / Q000639:trends*; D057286:Electronic Health Records / Q000592:standards / Q000639:trends*; D006801:Humans; D020407:Internet / Q000592:standards / Q000639:trends*; D060735:Pharmacovigilance