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1.
BMC Med ; 17(1): 184, 2019 10 01.
Artigo em Inglês | MEDLINE | ID: mdl-31570106

RESUMO

BACKGROUND: The healthcare system can be understood as the dynamic result of the interaction of hospitals, patients, providers, and government configuring a complex network of reciprocal influences. In order to better understand such a complex system, the analysis must include characteristics that are feasible to be studied in order to redesign its functioning. The analysis of the emergent patterns of pregnant women flows crossing municipal borders for birth-related hospitalizations in a region of São Paulo, Brazil, allowed to examine the functionality of the regional division in the state using a complex systems approach and to propose answers to the dilemma of concentration vs. distribution of maternal care regional services in the context of the Brazilian Unified Health System (SUS). METHODS: Cross-sectional research of the areas of influence of hospitals using spatial interaction methods, recording the points of origin and destination of the patients and exploring the emergent patterns of displacement. RESULTS: The resulting functional region is broader than the limits established in the legal provisions, verifying that 85% of patients move to hospitals with high technology to perform normal deliveries and cesarean sections. The region has high independence rates and behaves as a "service exporter." Patients going to centrally located hospitals travel twice as long as patients who receive care in other municipalities even when the patients' conditions do not demand technologically sophisticated services. The effects of regulation and the agents' preferences reinforce the tendency to refer patients to centrally located hospitals. CONCLUSIONS: Displacement of patients during delivery may affect indicators of maternal and perinatal health. The emergent pattern of movements allowed examining the contradiction between wider deployments of services versus concentration of highly specialized resources in a few places. The study shows the potential of this type of analysis applied to other type of patients' flows, such as cancer or specialized surgery, as tools to guide the regionalization of the Brazilian Health System.


Assuntos
Procedimentos Clínicos/estatística & dados numéricos , Parto Obstétrico/estatística & dados numéricos , Serviços de Saúde Materna/estatística & dados numéricos , Transferência de Pacientes/estatística & dados numéricos , Adulto , Brasil/epidemiologia , Cesárea/estatística & dados numéricos , Cidades/epidemiologia , Cidades/estatística & dados numéricos , Procedimentos Clínicos/organização & administração , Procedimentos Clínicos/normas , Estudos Transversais , Atenção à Saúde/organização & administração , Atenção à Saúde/normas , Parto Obstétrico/métodos , Parto Obstétrico/normas , Feminino , Hospitalização/estatística & dados numéricos , Humanos , Serviços de Saúde Materna/organização & administração , Serviços de Saúde Materna/normas , Transferência de Pacientes/organização & administração , Gravidez , Indicadores de Qualidade em Assistência à Saúde , Encaminhamento e Consulta/estatística & dados numéricos , Análise de Sistemas , Transporte de Pacientes/estatística & dados numéricos
2.
Rev. saúde pública (Online) ; 53: 49, jan. 2019. tab, graf
Artigo em Inglês | LILACS | ID: biblio-1004511

RESUMO

ABSTRACT OBJECTIVE To analyze the environmental and socioeconomic risk factors of malaria transmission at municipality level, from 2010 to 2015, in the Brazilian Amazon. METHODS The municipalities were stratified into high, moderate, and low transmission based on the annual parasite incidence. A multinomial logistic regression that compared low with medium transmission and low with high transmission was performed. For each category, three models were analyzed: one only with socioeconomic risk factors (Gini index, illiteracy, number of mines and indigenous areas); a second with the environmental factors (forest coverage and length of the wet season); and a third with all covariates (full model). RESULTS The full model showed the best performance. The most important risks factors for high transmission were Gini index, length of the wet season and illiteracy, OR 2.06 (95%CI 1.19-3.56), 1.73 (95%CI 1.19-2.51) and 1.10 (95%CI 1.03-1.17), respectively. The medium transmission showed a weaker influence of the risk factors, being illiteracy, forest coverage and indigenous areas statistically significant but with marginal influence. CONCLUSIONS As a disease of poverty, the reduction in wealth inequalities and, therefore, health inequalities, could reduce the transmission considerably. Besides, environmental risk factors as length of the wet season should be considered in the planning, prevention and control. Municipality-level and fine-scale analysis should be done together to improve the knowledge of the local dynamics of transmission.


Assuntos
Humanos , Florestas , Transmissão de Doença Infecciosa/estatística & dados numéricos , Malária/transmissão , Malária/epidemiologia , Estações do Ano , Fatores Socioeconômicos , Fatores de Tempo , Brasil/epidemiologia , Modelos Logísticos , Incidência , Fatores de Risco , Cidades/epidemiologia , Análise Espaço-Temporal
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