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In this work we will examine the activity of the Emergency Department (ED) of an Italian primary Hospital by
way of real data. Data will be analyzed both via econometrics and data mining (namely: dimensions reduction) models.
Our findings demonstrate that using a quantitative exploratory approach to the study of ED data makes it possible to gain
suitable information for both the hospital's management and the policymaker, hence contributing to a better understanding
of EDs activity and to address its accurate programming. The new approach we suggest is intended to put at decisionmaker
disposal a set of tools that surfing on the available data make it possible to skim the very relevant information (and
hence to reject negligible elements) extracting from the whole set of determinants only those of effective relevance. This,
in our opinion, could be a key issue to both verifying the actual performance, and to put forth new policies to improve
efficiency and quality as well.