Abstract
BackgroundAdverse drug reactions and adverse drug events (ADEs) are major public health issues. Many different prospective tools for the automated detection of ADEs in hospital databases have been developed and evaluated. The objective of the present study was to evaluate an automated method for the retrospective detection of ADEs with hyperkalaemia during inpatient stays.MethodsWe used a set of complex detection rules to take account of the patient’s clinical and biological context and the chronological relationship between the causes and the expected outcome. The dataset consisted of 3,444 inpatient stays in a French general hospital. An automated review was performed for all data and the results were compared with those of an expert chart review. The complex detection rules’ analytical quality was evaluated for ADEs.ResultsIn terms of recall, 89.5% of ADEs with hyperkalaemia “with or without an abnormal symptom” were automatically identified (including all three serious ADEs). In terms of precision, 63.7% of the automatically identified ADEs with hyperkalaemia were true ADEs.ConclusionsThe use of context-sensitive rules appears to improve the automated detection of ADEs with hyperkalaemia. This type of tool may have an important role in pharmacoepidemiology via the routine analysis of large inter-hospital databases.
Highlights
Adverse drug reactions and adverse drug events (ADEs) are major public health issues
The definition of Adverse drug reactions (ADRs) The World Health Organisation (WHO) defines ADRs as “a response to a medicinal product which is noxious and unintended, and which occurs at doses used in man for prophylaxis, diagnosis or therapy” [5]
In order to take account of the chronology of events and the clinical and biological context, we have developed a set of complex detection rules
Summary
Adverse drug reactions and adverse drug events (ADEs) are major public health issues. The definition of ADRs The World Health Organisation (WHO) defines ADRs as “a response to a medicinal product which is noxious and unintended, and which occurs at doses used in man for prophylaxis, diagnosis or therapy” [5] This definition refers to reactions that occurs at “normal” therapeutic dose levels and excludes medication errors. Knowing the proportion of ADEs related to medication errors is essential from an epidemiological point of view because the latter can (at least in theory) be avoided. For this reason, we chose to study ADEs in general (i.e. events including preventable ADEs and ADRs)
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