We do not detect any socioeconomic barriers associated with making a first contact with primary health services for the users analyzed. However, we do note evidence of horizontal inequity in terms of attending health services, related to variables that ought to affect use of health care as well as socioeconomic factors (variables that ought not to affect use of health care). The user's origin is an important key in detecting different intensities of access and regular visits to primary health care services.

The CRG grouping system aids analysis at different levels for clinical administration. Due to its composition, this system allows better understanding of the use, costs and quality of the set of services received by a population.

ResumenEl objetivo de la presente investigación es analizar la influencia de las valoraciones de los hoteles en las redes sociales y cómo estas afectan los ingresos de los hoteles. A partir de los datos mensuales (entre agosto de 2014 y julio de 2015) de 48 hoteles de Colombia, Ecuador y Perú se analizaron principalmente las variables: GRI (Global Review Index), Oferta, Demanda, Venta, RevPAR (Revenue Per Avalable Room) y Ubicación; mediante análisis de conglomerados y un modelo lineal. Se encontró que un mejor GRI favorece a una mejor ratio entre las ventas y la oferta. En concreto, observamos que cuando el GRI se incrementa en una unidad, el RevPAR crece en 0,49%, manteniendo el resto de variables constantes. Es la primera investigación realizada en Sudamérica para analizar la incidencia de las redes sociales en los ingresos de los hoteles. Palabras clave: Redes sociales; Reputación Online; Satisfacción del huésped; Turismo; RevPAR. IMPACT OF SOCIAL NETWORKS ON HOTELS´ INCOMES IN COLOMBIA, ECUADOR AND PERU AbstractThe objective of this research is to analyze the influence of hotel ratings on social networks and how they affect hotel revenues. From 48 hotels´ monthly data (between August 2014 and July 2015) of Colombia, Ecuador and Peru, the following variables were analyzed: GRI (Global Review

A number of health economics works require patient cost estimates as a basic information input.However the accuracy of cost estimates remains in general unspecified. We propose to investigate how the allocation of indirect costs or overheads can affect the estimation of patient costs in order to allow for improvements in the analysis of patient costs estimates. Instead of focusing on the costing method, this paper proposes to highlight changes in variance explained observed when a methodology is chosen. We compare three overhead allocation methods for a specific Spanish population adjusted using the Clinical Risk Groups (CRG), and we obtain different series of full-cost group estimates. As a result, there are significant gains in the proportion of the variance explained, depending upon the methodology used.Furthermore, we find that the global amount of variation explained by risk adjustment models depends mainly on direct costs and is independent of the level of aggregation used in the classification system.