Resumen

JOYANES-AGUILAR, Luis; CASTANO, Néstor J  y  OSORIO, José H. Simulation and data mining model for identifying and prediction budget changes in the care of patients with hypertension. Rev. salud pública [online]. 2015, vol.17, n.5, pp.789-800. ISSN 0124-0064.  https://doi.org/10.15446/rsap.v17n5.39610.

Objective To present a simulation model that establishes the economic impact to the health care system produced by the diagnostic evolution of patients suffering from arterial hypertension. Methodology The information used corresponds to that available in Individual Health Records (RIPs, in Spanish). A statistical characterization was carried out and a model for matrix storage in MATLAB was proposed. Data mining was used to create predictors. Finally, a simulation environment was built to determine the economic cost of diagnostic evolution. Results 5.7 % of the population progresses from the diagnosis, and the cost overrun associated with it is 43.2 %. Conclusions Results shows the applicability and possibility of focussing research on establishing diagnosis relationships using all the information reported in the RIPS in order to create econometric indicators that can determine which diagnostic evolutions are most relevant to budget allocation.

Palabras clave : Computer simulation; data mining; forecasting; public health.

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