Interactive Bottleneck Detection in Data Driven Business Process Simulation in Healthcare: Egyptian Case Study

Abstract

Using the data logged during the execution of business processes, process mining techniques can be utilized to examine those processes. These methods are used in a variety of fields, including healthcare, where they are primarily used to analyze organizational, diagnostic, and therapeutic processes. The organization is able to verify the effects of the suggested process modifications before implementing them thanks to simulation, despite the enormous volume of data that humans and equipment involved in healthcare operations are generating in healthcare information systems. Information systems are being used in the healthcare industry to store a growing amount of process execution data. With the use of bottleneck detection and data-driven process modelling, this information could be utilized, for instance, to assist medical facility management with capacity management decisions. However, data quality problems in healthcare real-world event logs frequently compromise the accuracy of simulation results. In this work, we use datasets gathered from Egyptian healthcare facilities to show the effects of incorporating bottleneck detection to the data driven process simulation as well as the importance of domain expertise, taking into account the event log's data quality.