El acceso al seguro integral de salud y su relación con los factores socioeconómicos en Loreto, año 2019

Descripción del Articulo

The present investigation, entitled: "Access to comprehensive health insurance and its relationship with socioeconomic factors in Loreto 2019", aims to analyze the impact of socioeconomic factors such as income level, spending level, hours of work, belonging to the formal and informal sect...

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Detalles Bibliográficos
Autor: Flores Chavez, Alberto Wilber
Formato: tesis de grado
Fecha de Publicación:2022
Institución:Universidad Nacional De La Amazonía Peruana
Repositorio:UNAPIquitos-Institucional
Lenguaje:español
OAI Identifier:oai:repositorio.unapiquitos.edu.pe:20.500.12737/8532
Enlace del recurso:https://hdl.handle.net/20.500.12737/8532
Nivel de acceso:acceso abierto
Materia:Indicadores socioeconómicos
Condiciones de vida
Seguro de salud
https://purl.org/pe-repo/ocde/ford#5.06.02
Descripción
Sumario:The present investigation, entitled: "Access to comprehensive health insurance and its relationship with socioeconomic factors in Loreto 2019", aims to analyze the impact of socioeconomic factors such as income level, spending level, hours of work, belonging to the formal and informal sector, being poor or not poor, years of education and gender of individuals in access to comprehensive health insurance in the Loreto Region. Currently, the SIS has taken the lead in obtaining certain types of insurance, going from 14.9% in 2004 to 46.3% in 2016, and reached 81% of the total number of insured in 2020. In Loreto, we have a similar situation, according to INEI data, the population with some type of medical insurance was 25.8% in 2004 and 74.5% in 2019. Therefore, the main purpose of this study is to point out which socioeconomic factors are the determinants of access to comprehensive health insurance in the Loreto region, during 2019 and the impact of each of these variables on access to the SIS. This research is of a non-experimental quantitative causal nature, using data from the National Household Survey (ENAHO) for the estimation of a binary dependent variable model of data grouping, specifically a Probit model.
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