Implementing Guidelines for Causality Assessment of Adverse Drug Reaction Reports: A Bayesian Network Approach

• Type: Article in International Conference Proceedings Book
• Date: 2017

Authors

Pedro Pereira Rodrigues (Author) FMUP; Santos, DF (Author) FMUP; Silva, A (Author) FMUP; Polonia, J (Author) FMUP; Vaz, IR (Author) FMUP

Conference proceedings International

Title: Artificial Intelligence in Medicine - 16th Conference on Artificial Intelligence in Medicine, AIME 2017, Vienna, Austria, June 21-24, 2017, Proceedings

Pages: 55-64

16th Conference on Artificial Intelligence in Medicine, AIME 2017

21 June 2017 through 24 June 2017

Indexing

Scopus - 2 Citations

Other information

Authenticus ID: P-00M-W67

DOI: 10.1007/978-3-319-59758-4_6

Abstract (EN): In pharmacovigilance, reported cases are considered suspected adverse drug reactions (ADR). Health authorities have thus adopted structured causality assessment methods, allowing the evaluation of the likelihood that a medicine was the causal agent of an adverse reaction. The aim of this work was to develop and validate a new causality assessment support system used in a regional pharmacovigilance centre. A Bayesian network was developed, for which the structure was defined by an expert, aiming at implementing the current guidelines for causality assessment, while the parameters were learnt from 593 completely-filled ADR reports evaluated by the Portuguese Northern Pharmacovigilance Centre expert between 2000 and 2012. Precision, recall and time to causality assessment (TTA) was evaluated, according to the WHO causality assessment guidelines, in a retrospective cohort of 466 reports (April to September 2014) and a prospective cohort of 1041 reports (January to December 2015). Results show that the network was able to easily identify the higher levels of causality (recall above 80%), although strugling to assess reports with a lower level of causality. Nonetheless, the median (Q1:Q3) TTA was 4 (2:8) days using the network and 8 (5:14) days using global introspection, meaning the network allowed a faster time to assessment, which has a procedural deadline of 30 days, improving daily activities in the centre.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 9