What are the factors associated with catastrophic health expenditure in Colombia? A multi-level analysis
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Updated: Jul 21, 2025

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Published on: January 8, 2020
Juan Luis Ramirez-Agudelo1, Monica Pinilla-Roncancio1
1School of Medicine, Universidad de los Andes, Bogotá, Colombia.
Introduction:
Target 3.8 of the Sustainable Development Goals calls for the guaranteeing of universal health service coverage without generating financial risks for households and individuals. In Colombia, there is no up-to-date information on the proportion of households that suffer catastrophic health expenditure (CHE), nor about how these expenses are associated with the place of residence. To contribute to an understanding of these issues, this study analyses the differences in the levels of CHE among Colombian households, and their association with the province and area (urban or rural) of residence.
Methods:
This is a descriptive and analytical cross-sectional study using the 2016-2017 National Household Budget Survey, the household and population Census 2018, and the Register of Health Providers 2017. We used the definition of CHE proposed by the World Health Organization, with a threshold of 20%. We estimated the percentage of households facing CHE, and its intensity, and estimated a multi-level logistic regression model, using as the dependent variable the question of whether a household experienced CHE, and the province as a second level, where explanatory variables related to the province were included.
Results:
We found differences in CHE levels according to the province of residence. At the national level, 1.77% of households experienced CHE, and households in the provinces of Boyacá (5.04%), Nariño (4.04%), Cauca (3.82%), and Chocó (3.78%) faced the highest CHE. For most households with CHE in these provinces, spending on medicines and medical consultations represented close to 50% of their out-of-pocket spending. The multi-level logistic regression model indicated that there are significant variations in CHE attributed to the provinces under study, where the contextual variables of hospital-bed density (AOR = 0.91; 95% CI 0.86-0.96) and incidence of multi-dimensional poverty (AOR = 1.13; 95% CI 1.01-1.30) were factors associated with CHE. For an urban household, 6.58% of the CHE variation is attributed to the province in question, while for a rural household the corresponding variation is 1.56%.
Conclusions:
The geographical location of the household is a key factor when studying CHE in Colombia, where rural households present higher levels of CHE, mainly in the delivery of medicines and medical consultations. The findings reveal the need to analyse financial protection at the local level and establish policies to protect households, especially poor households, from CHE.
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