Arquitectura de consolidación de la información para seguros de la salud mediante Big Data

Abstract

The identification of data that is in various sources of information and its consolidation to deliver it as useful is achieved with Big Data. The overall objective of this work is to develop an information consolidation architecture design for health insurance using Big Data. For this research proposal, the analytical empirical method is used, of a quasi-experimental type with a quantitative approach, through the analysis of relevant references and specification of the architecture components. The results of this research allow categorizing different computational architectures for health insurance through a review of relevant literature, developing an architectural model of a computational system for an Ecuadorian health insurance company oriented to the consolidation of information, and evaluating the study methodology used to establish feasible factors of the model. The contribution of this work allows us to determine the applicability of the model to national or foreign health insurance companies by contrasting feasible factors in a specific company of the environment. It is concluded that the different sources of information or types of data used in the field of health insurance allow to know several edges of data analysis through a Big Data architecture, in addition to obtaining indicators to improve decision making; 73% of the established factors are viable in an Ecuadorian health insurance company.