Implementation and comparison of two text mining methods with a standard pharmacovigilance method for signal detection of medication errors

Implementation and comparison of two text mining methods with a standard pharmacovigilance method for signal detection of medication errors

Abstract Background Medication errors have been identified as the most common preventable cause of adverse events. The lack of granularity in medication error terminology has led pharmacovigilance experts to rely on information in individual case safety reports’ (ICSRs) codes and narratives for sign...

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Bibliographic Details
Main Authors: Nadine Kadi Eskildsen, Robert Eriksson, Sten B. Christensen, Tamilla Stine Aghassipour, Mikael Juul Bygsø, Søren Brunak, Suzanne Lisbet Hansen
Format: Article
Language:English
Published: BMC 2020-05-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Signal detection
Pharmacovigilance
Individual case reports
Medication errors
Natural language processing
Text mining
Online Access:http://link.springer.com/article/10.1186/s12911-020-1097-0

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http://link.springer.com/article/10.1186/s12911-020-1097-0

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