Simulation and Big Data: A Way to Discover Unusual Knowledge in Emergency Departments: Work-in-Progress Paper

摘要

Here a work in progress is reported on within research that aims to obtain knowledge about variables which may influence a hospital emergency department's performance and quality of service. Knowledge discovery will be achieved through the analysis of intensive data generated by the simulation of any possible scenario in the real system. The challenge is to provide knowledge of critical, non-usual or extreme situations. Simulation is the only way to obtain information about these kinds of situations, as it is not possible to test such scenarios in the real system. We show how simulation of the real system through advanced computing is a source of big data, as it allows rapid and massive data generation. The potential of high performance computing makes it possible to generate a very large amount of data within a reasonable time, store this data, then process and analyze it to obtain knowledge. We describe the methodology proposed for this goal, which is based on the use of the simulator as a sensor of the real system, and so as the main source of data. The application of data mining techniques will open the doors to knowledge. To verify that the proposed methodology works, we propose a case study in which the aim is to obtain knowledge from a set of data already available, obtained from the simulation of a reduced set of scenarios of the real system.