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The applications of process mining, which is a business process management technique, in the field of healthcare are increasing day by day. In process mining, it is possible to analyze the process for three main purposes: discovery of the process, compliance control and process improvement, based on event logs recorded in information systems. Transforming patient-based healthcare processes data into process and event-based event logs is the first step of a process mining project in order to apply process mining techniques to human-centered, distributed, complex and multidisciplinary healthcare processes and to improve the quality of health care services. The process model discovered in multi-perspective process mining is expanded from different perspectives such as control flow, organizational, data, time and function, and the discovered process becomes more understandable. In this study, and in order to apply multi-perspective process mining, a method is proposed to convert the healthcare processes data recorded in hospital information systems into event logs. Data transformation method consists of six steps: data collection and data privacy, data integration, data conversion, data preprocessing, feature selection and extraction, and multi-perspective process mining analysis. The proposed method was validated by a case study by transforming the surgery process data of a university hospital in Turkey into an event log. The process discovery algorithm was applied to the surgery process data of the case study and the actual process was discovered, and the applicability of the data transformation method was shown on the real data. With the guiding feature of the method for healthcare professionals, it is expected to contribute to the applications of multi-perspective process mining in the field of healthcare in Turkey. [ABSTRACT FROM AUTHOR]

Current process management systems require a fully defined workflow design to implement a specific business process. Designing a business process is a complex and time-consuming task. Mostly workflow processes are different from those that are desired. Therefore, various algorithms have been developed for the discovery of actual processes rather than ideal processes. The first step for the discovery algorithms is to extract event logs that contain details about the process. In this study, Alpha algorithm which is used to generate a process model in event logs recorded in information technology (IT) systems is introduced. Process models are discovered using the basic activities performed in the recruitment processes. It has been shown that the alpha algorithm can successfully model a business process. [ABSTRACT FROM AUTHOR]