Extracting Association Rules from Emergency Department Data

Data mining represents a technique, applied in different fields, for discovering useful information or patterns from the large datasets. In this work, we extract association rules, based on the apriori algorithm, from the data collected, either from triage evaluation or from electronic health records, during patients' visits at the emergency department. The aim of this paper is to identify the correlation among the different chief complaints or diseases reported by the patients at triage evaluation, but also the relationship between different chief complaints and past medical history or the outpatient medication. An analysis and discussion of the first results is given.