EVENT DATA VISUALIZATION THROUGH PROCESS MINING: A CASE FOR EMERGENCY MEDICAL SERVICE SYSTEM IN ADANA

Abstract

Increasing amount of data enables researchers the opportunity of applying new scientific methods to manage and visualize the systems and processes. Process mining is an emerging tool for discovering real processes using event data of complex systems such as communication, information, health care systems, transportation and etc. Emergency Medical Service (EMS) system is an integral part of health care systems and aims to respond cases on time in order to decrease mortality. Although the EMS system process is assumed to be known, related data may indicate some deviations from the real process. Aim of this study is to discover and visualize EMS system in Adana city, in Turkey. EMS system event logs are filtered and visualized by using plug-ins in ProM platform such as Simple Heuristic Filtering plug-in and Log visualizer, respectively. Other plug-ins such as Fuzzy Miner and Inductive Miner are used for discovering process model. The deviations are obtained in EMS system process model showing irregular or rare events that cannot be representable throughout the process. The results indicate that the process of transportation between hospitals should be investigated in order to improve the process of Adana EMS system.

Keywords

• Process mining,Petri nets,Fuzzy miner,Inductive miner,Event logs

Supporting Institution

TÜBİTAK

Project Number

1059B191601225

Thanks

This study is a part of research granted by The Scientific and Technical Research Council of Turkey (TUBITAK) International Post-Doctoral Research Fellowship Program in the framework of TUBITAK-BIDEB 2219. Thanks to Data Science Centre in Technology University of Eindhoven for their support and hospitality and also Adana Provincial Directorate of Health Center for providing data.

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