Signal detection of adverse events in medical devices using natural language processing: a case study in pelvic mesh.

Abstract

Disproportionality analysis is used to detect safety signals for post-market surveillance from adverse events reported to regulatory bodies but is challenging when reports contain unstructured free-text. We implemented a proof-of-concept system combining natural language processing of free-text data with disproportionality analysis, using a known safety signal from pelvic mesh. Free-text reports in an Australian spontaneous adverse event report database between 2012 and 2017 were classified usin