Implementación del método de costos basados en actividades (ABC) en unidad de laboratorio médico

El presente estudio tiene por objetivo general, implementar el método de costos basados en actividades (ABC) en la unidad de laboratorio del centro de atención médico primario Central Salud Integral, C.A. Teóricamente, está soportado en la metodología de costos basados en actividades (ABC), la cual identifica las actividades realizadas, los recursos que se consumen y las actividades demandadas por cada servicio, contribuyendo así en la mejora de la eficiencia operativa de la organización. La metodología de la investigación, estuvo enmarcada en un proyecto factible y soportado en un trabajo de campo – documental desde un nivel descriptivo. El ABC permitió identificar las actividades que se realizan en el laboratorio de Central Salud Integral, C.A., determinar los recursos que estas consumen y asignar mediante inductores; el costo por actividad. The present study aims to implement the method of costs based on activities (ABC) in the laboratory unit of the medical center of primary care of CSICA. Theoretically, it is supported in the ABC methodology, which identifies the activities done, the consumed resources and the activities demanded by every service, contributing in the improvement of the operative efficiency of the organization. The investigation methodology used a feasible and supported fieldwork project as a framework in a descriptive level. Thus, the ABC allowed to identify the activities that are being executed in the laboratory of CSICA, to determine the resources that these consume and to assign by means of inducers; the cost for activity.

Approximate Bayesian Computation for Estimating Parameters of Data-Consistent Forbush Decrease Model

Realistic modeling of complex physical phenomena is always quite a challenging task. The main problem usually concerns the uncertainties surrounding model input parameters, especially when not all information about a modeled phenomenon is known. In such cases, Approximate Bayesian Computation (ABC) methodology may be helpful. The ABC is based on a comparison of the model output data with the experimental data, to estimate the best set of input parameters of the particular model. In this paper, we present a framework applying the ABC methodology to estimate the parameters of the model of Forbush decrease (Fd) of the galactic cosmic ray intensity. The Fd is modeled by the numerical solution of the Fokker–Planck equation in five-dimensional space (three spatial variables, the time and particles energy). The most problematic in Fd modeling is the lack of detailed knowledge about the spatial and temporal profiles of the parameters responsible for the creation of the Fd. Among these parameters, the diffusion coefficient plays a central role. We employ the ABC Sequential Monte Carlo algorithm, scanning the space of the diffusion coefficient parameters within the region of the heliosphere where the Fd is created. Assessment of the correctness of the proposed parameters is done by comparing the model output data with the experimental data of the galactic cosmic ray intensity. The particular attention is put on the rigidity dependence of the rigidity spectrum exponent. The proposed framework is adopted to create the model of the Fd observed by the neutron monitors and ground muon telescope in November 2004.