Health information systems have a large amount of data, but they lack of mechanisms to analyze the execution of their processes. Process mining techniques analyze the real data of computer systems and are useful for the detection of variability in the execution of business processes. The present research is oriented to the development of a model for the detection of variability in hospital processes, providing the necessary elements to support the hospital management from its information systems. The two components of the Model for Variability Detection (MVD) are the generation of event logs and a set of process mining techniques. Was developed a procedure to guide the process of detection and analysis of variability. The model was successfully implemented in the XAVIA HIS system developed by the University of Informatics Sciences, where process mining techniques were adapted and integrated; Thus, the MVD model contributes to the process of health informatization in Cuba. In order to corroborate the pertinence, scientific value and its ability to detect variability, a set of scientific techniques and methods were applied.
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