Abstract
AbstractProcess mining is an effective method to discover information about the sequence of event execution in the business. Process mining helps interconnect event logs data and find any patterns in the process flows. Process mining (PM) provides a simple visualization to identify and organize data available in the healthcare system. We collected information from the hospital and applied PM methods. We processed structured and unstructured data and models using PM algorithms. Hospitals generate events logs that are considered complex and inconsistent. We found deviations and inconsistencies by comparing an existing process model with the event logs. In this paper, we created the design of Petri nets and analyzed the abnormality of the process flow. We propose an effective model to detect deviations using the event logs. Then, the abnormal activities are identified and displayed on the Petri nets. The Petri nets create clusters of dependent activities. The healthcare information from the hospital is used in the research process to convey our work. Experimental results show improvement in the effectiveness and efficiency of the proposed hospital information system.KeywordsCluster analysisEvent logPetri netProcess mining
Published Version
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