title: Decision support methods for the detection of adverse events in post-marketing data.
abstract: Spontaneous reporting is a crucial component of post-marketing drug safety surveillance despite its significant limitations. The size and complexity of some spontaneous reporting system databases represent a challenge for drug safety professionals who traditionally have relied heavily on the scientific and clinical acumen of the prepared mind. Computer algorithms that calculate statistical measures of reporting frequency for huge numbers of drug-event combinations are increasingly used to support pharamcovigilance analysts screening large spontaneous reporting system databases. After an overview of pharmacovigilance and spontaneous reporting systems, we discuss the theory and application of contemporary computer algorithms in regular use, those under development, and the practical considerations involved in the implementation of computer algorithms within a comprehensive and holistic drug safety signal detection program.
authors.affiliation: Pfizer, New York, USA. Manfred.hauben@Pfizer.com
authors.forename: M
authors.initials: M
authors.lastname: Hauben
authors.forename: A
authors.initials: A
authors.lastname: Bate
mesh_terms: D016907:Adverse Drug Reaction Reporting Systems / Q000458:organization & administration*; D000465:Algorithms; D020000:Decision Support Systems, Clinical / Q000458:organization & administration; D003661:Decision Support Techniques; D004345:Drug Industry / Q000379:methods / Q000458:organization & administration; D064420:Drug-Related Side Effects and Adverse Reactions; D006801:Humans; D016571:Neural Networks, Computer; D011358:Product Surveillance, Postmarketing / Q000379:methods*