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Simulation as a Sensor of Emergency Departments: Providing Data for Knowledge Discovery

Authors:
Eva Bruballa
Manel Taboada
Eduardo Cabrera
Dolores Rexachs
Emilio Luque

Keywords: Agent-Based Modeling and Simulation (ABMS); Data-Intensive;Data Mining (DM); Decision Support Systems (DSS); Emergency Department (ED); Knowledge Discovery.

Abstract:
Simulation of unusual or extreme situations of Hospital Emergency Departments (ED) makes it possible to get extra knowledge about the behavior of the system which could not be obtained in other way. There is no real data available of such situations, but simulation allows us to obtain this information. In this paper, we show how the data obtained by simulation of scenarios representing special real situations expand the real available data. That provides further information, which will allow us to reach more reliable models of real system behavior, avoiding extrapolation methods, which imply important errors, especially in nonlinear systems as ED. The objective pursued in this ongoing research is to extract the information contained in all this data to observe patterns and translate them into relationships and behavior models about variables which may influence the Hospital Emergency Department’s performance and quality of service. A methodology to obtain new knowledge from intensive data, based on the use of the simulator as a sensor of the real system, and so as the main source of data, is proposed. As immediate future work, we intend to prove this methodology in a case of study which aim is to gain knowledge from a specific set of data, obtained through the simulation of a reduced set of scenarios of the real system.

Pages: 209 to 212

Copyright: Copyright (c) IARIA, 2014

Publication date: October 12, 2014

Published in: conference

ISSN: 2308-4537

ISBN: 978-1-61208-371-1

Location: Nice, France

Dates: from October 12, 2014 to October 16, 2014