Orellana A

Language: Spanish
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ABSTRACT

The hospital information systems collect an important volume of data, however, they lack mechanisms to analyze the execution of the processes and identify variability. In practically every step of the care process and at various levels of grouping: population and individual the variability is present. From a population point of view, performance rates of a clinical procedure such as surgical interventions or hospital admissions, are compared over time. Process mining techniques analyze the real data of computer systems and are useful for the detection of variability in the execution of business processes. Based on a rigorous study of the state of the art, this research proposes the application of process mining techniques for the analysis of hospital processes from their information systems, providing a computational model. Model for Variability Detection (MDV) implemented successfully in the XAVIA HIS system developed by the UCI University of Informatics Sciences, where techniques of process mining were adapted and integrated. The MDV model contributes to the process of computerization of health in Cuba. The solution encourages the use of an emerging technology in areas such as industrial and business in the healthcare environment. This benefits important management functions such as control and planning of resources and health services.