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追踪巴西圣保罗孕妇的流动:通过模式的出现实现区域化的复杂系统方法。

Tracking pregnant women displacements in Sao Paulo, Brazil: a complex systems approach to regionalization through the emergence of patterns.

机构信息

School for International Training, São Paulo, Brazil.

Institute of Physics, University of Sao Paulo, Sao Carlos Campus, Brazil.

出版信息

BMC Med. 2019 Oct 1;17(1):184. doi: 10.1186/s12916-019-1416-4.

DOI:10.1186/s12916-019-1416-4
PMID:31570106
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6771099/
Abstract

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.

摘要

背景

医疗保健系统可以被理解为医院、患者、提供者和政府之间相互作用的动态结果,构成了一个复杂的相互影响网络。为了更好地理解这样一个复杂的系统,分析必须包括可行的特征,以便重新设计其功能。对巴西圣保罗州一个地区跨越市政边界进行分娩相关住院治疗的孕妇流动的涌现模式进行分析,允许使用复杂系统方法来研究州内区域划分的功能,并针对巴西统一卫生系统(SUS)背景下母性保健区域服务集中与分配的困境提出答案。

方法

使用空间相互作用方法对医院的影响区域进行横截面研究,记录患者的起点和终点,并探索流动的涌现模式。

结果

得出的功能区域比法律规定的界限更广泛,这表明 85%的患者会转移到具有高科技的医院进行正常分娩和剖腹产。该区域的独立性率较高,表现为“服务出口国”。前往中心医院的患者的行程是在其他城市接受治疗的患者的两倍,即使患者的病情不需要复杂的技术服务也是如此。监管的影响和代理人的偏好加强了将患者转诊到中心医院的趋势。

结论

分娩期间的患者转移可能会影响母婴健康的指标。流动的涌现模式允许检查服务范围扩大与少数地方高度专业化资源集中之间的矛盾。该研究展示了这种类型的分析应用于其他类型的患者流动(如癌症或专业手术)的潜力,作为指导巴西卫生系统区域化的工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e6/6771099/ce77c1095dcd/12916_2019_1416_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e6/6771099/641e1ba8458a/12916_2019_1416_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e6/6771099/14502f1e3ea3/12916_2019_1416_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e6/6771099/3546f9e8747a/12916_2019_1416_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e6/6771099/5349ccefbf3a/12916_2019_1416_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e6/6771099/469a932bb40d/12916_2019_1416_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e6/6771099/ce77c1095dcd/12916_2019_1416_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e6/6771099/641e1ba8458a/12916_2019_1416_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e6/6771099/14502f1e3ea3/12916_2019_1416_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e6/6771099/3546f9e8747a/12916_2019_1416_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e6/6771099/5349ccefbf3a/12916_2019_1416_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e6/6771099/469a932bb40d/12916_2019_1416_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e6/6771099/ce77c1095dcd/12916_2019_1416_Fig6_HTML.jpg

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