ORIGINAL ARTICLE
Inequality in the distribution of resources and health care in the poverty quintiles: Evidence from Peruvian comprehensive health insurance 2018-2019
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1
Graduate School, Universidad Nacional Federico Villarreal, Lima, PERU
2
Graduate School, Universidad Nacional Mayor de San Marcos, Lima, PERU
3
Graduate School, Pontificia Universidad Católica del Perú, Lima, PERU
4
School of Biomedical Engineering, Faculty of Engineering, Universidad Tenológica del Perú, Lima, PERU
5
Faculties of Health Science, Universidad Privada del Norte, Lima, PERU
Publication date: 2024-01-26
Electron J Gen Med 2024;21(1):em568
KEYWORDS
ABSTRACT
Introduction:
In many regions of the world, healthcare is inequitable and limited, affecting poor populations who
need greater health opportunities. Given that Peru’s comprehensive health insurance (SIS) seeks to enhance its
coverage for the entire population, it is important to know if its coverage benefits the poorest populations.
Objectives:
To determine the allocation of SIS resources and care to the poorest quintile during 2018 and 2019 in
Peru.
Methods:
We conducted a secondary analysis of data from five Peruvian technical institutions. In 39,8207 Peruvian
households, we analyzed the per capita budget assigned to the population affiliated with SIS in microregions of
quintile 1 and quintile 2 (poor), and quintile 4 and quintile 5 (non-poor), health coverage, and the level of poverty
considering the human development index (HDI) and the regional competitiveness index (RCI).
Results:
The poorest regions are inversely correlated with HDI and RCI and have an average service of 25.0%
affiliates. In poor areas, the allocated budget was lower (approximately $303,000 to $2.2 million), but the
proportion of members requiring care was higher (>70.0%). The budget allocated to health was unfair (p<0.05)
between poor areas (maximum resources from .28 to 8.14) and non-poor areas (maximum resources from
0.00 to 2.43). Low budget allocations and low household per capita income contributed to poverty in
quintile 1 and quintile 2 (p<0.01).
Conclusions:
The poorest regions have greater inequity and the majority of affiliates do not use or do not have
access to SIS services, but they have a greater need for health care. In addition, poor regions have a high amount
of population without SIS coverage, and low allocated budgets, which affects competitiveness and regional
development.
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