Novel Data‐Mining Methodologies for Adverse Drug Event Discovery and Analysis

Novel Data‐Mining Methodologies for Adverse Drug Event Discovery and Analysis

An important goal of the health system is to identify new adverse drug events (ADEs) in the postapproval period. Data‐mining methods that can transform data into meaningful knowledge to inform patient safety have proven essential for this purpose. New opportunities have emerged to harness data sourc...

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Veröffentlicht in:Clinical pharmacology and therapeutics 2012-06, Vol.91 (6), p.1010-1021
Hauptverfasser: Harpaz, R, DuMouchel, W, Shah, N H, Madigan, D, Ryan, P, Friedman, C
Format: Artikel
Sprache:eng
Schlagworte:
Artificial Intelligence
Case-Control Studies
Cohort Studies
Data Mining - methods
Databases, Bibliographic
Databases, Factual
Drug-Related Side Effects and Adverse Reactions - epidemiology
Humans
Multivariate Analysis
Pharmacovigilance
Research Design
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Zusammenfassung:An important goal of the health system is to identify new adverse drug events (ADEs) in the postapproval period. Data‐mining methods that can transform data into meaningful knowledge to inform patient safety have proven essential for this purpose. New opportunities have emerged to harness data sources that have not been used within the traditional framework. This article provides an overview of recent methodological innovations and data sources used to support ADE discovery and analysis. Clinical Pharmacology & Therapeutics (2012); 91 6, 1010–1021. doi:10.1038/clpt.2012.50
ISSN:0009-9236
1532-6535
DOI:10.1038/clpt.2012.50