Process mining case study approach: Extraction of unconventional event logs to improve performance in Hospital Information Systems (HIS)

Background: Due to recent advancements in the computing technologies, process-mining algorithms can consequently apply complex numerical calculations in big data analysis with quick repetitions. It involved primarily in real-time systems such as banking, transport, and hospitals. However, process mining tending to play a vital role in the healthcare domain with promising results. Objective: The goal is to extract the unconventional event log file from the process to improve system performance and to propose solutions to enhance system performance Methods: The present research incorporated the performance filter technique to sort out misbehaved event logs from the process. We consider a sample of 100,000 patient cases over three-years from the local Hospital information systems (HIS). Results: Results were emphasized with precise coordination, performance assessment by specific mining tool has done. Percentage of time taken to process unconventional event log files is validated as 63.67%, which means system performance getting low due to these events Conclusion: In particular, to gain competitive advantage hospitals are trying to streamline their processes through an accurate view of the care flows. Several studies were done to integrate these techniques with hospital software systems, and we are come up with the contemporary idea of event log filtering Keywords: Process mining, Process discovery, Event logs, HIS, and Process enhancement.