Attributes for causal inference in electronic healthcare databases - Reps, Jenna; Garibaldi, Jonathan M.; Aickelin, Uwe; Soria, Daniele; Gibson, Jack E.; Hubbard, Richard B. (2013)
Side effects of prescription drugs present a serious issue. Existing algorithms that detect side effects generally require further analysis to confirm causality. In this paper we investigate attributes based on the Bradford-Hill causality criteria that could be used by a classifying algorithm to definitively identify side effects directly. We found that it would be advantageous to use attributes based on the association strength, temporality and specificity criteria.