A principal objective of pharmacovigilance is to detect adverse drug reactions that are unknown or novel in terms of their clinical severity or frequency. One method is through inspection of spontaneous reporting system databases, which consist of millions of reports of patients experiencing adverse effects while taking one or more drugs. For such large databases, there is an increasing need for quantitative and automated screening tools to assist drug safety professionals in identifying drug-event combinations (DECs) worthy of further investigation. Existing algorithms can effectively identify problematic DECs when the frequencies are high. However these algorithms perform differently for low-frequency DECs.