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BMC Health Serv Res ; 24(1): 285, 2024 Mar 05.
Artigo em Inglês | MEDLINE | ID: mdl-38443888

RESUMO

BACKGROUND: Disasters are events that bring with them effects that contribute to the disruption of the normality of a population and thus highlight the vulnerabilities of the health system. In Mariana and Brumadinho, the collapse of the dam of ore tailings brought with it several impacts that were felt in the short term and will be felt in the medium and long term. And that by being intensely intertwined with issues of economic and productive nature, has as its meaning an uninterrupted result of its activities. METHODS: Through the DATASUS database, two specific variables were chosen to perform the analysis: the approved amount and the approved value. For this research, a methodological device, the segmented regression line, was used to observe the influences that the disasters that occurred in Mariana and Brumadinho had on the ambulatory health systems. RESULTS: The results of the segmented regression line show that, with Mariana, the amount approved continued to grow throughout the period, which shows that there was no change because of the disaster. There was a reduction in spending. In Brumadinho, regarding the amount approved, there was an upward trend in the disaster's month, which did not change immediately afterwards, and regarding expenditure, the growth pattern was maintained in all three periods. Corroborating this data, the relative and absolute base elements show an increase in the amount approved and in the number of services provided at various posts compared with Minas Gerais. CONCLUSIONS: Based on the findings, it was possible to understand that although disasters exert an influence that may have some effect on the health system, the lack of significance sometimes cannot be interpreted as a lack of impact on the disaster. The segmented regression line outlines some effects that are not conclusive but indicative of a numerical interpretation and a trend interpretation.


Assuntos
Assistência Ambulatorial , Desastres , Humanos , Brasil , Bases de Dados Factuais , Emoções
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