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巴西癌症治疗的地理可及性:一项网络分析。

Geographic accessibility to cancer treatment in Brazil: A network analysis.

作者信息

Fonseca Bruna de Paula, Albuquerque Priscila Costa, Saldanha Raphael de Freitas, Zicker Fabio

机构信息

Centro de Desenvolvimento Tecnológico em Saúde (CDTS), Fundação Oswaldo Cruz (Fiocruz), Rio de Janeiro, Brazil.

Plataforma de Ciência de Dados Aplicada à Saúde (PCDaS), Instituto de Informação Científica e Tecnológica em Saúde (ICICT), Fundação Oswaldo Cruz (Fiocruz), Rio de Janeiro, Brazil.

出版信息

Lancet Reg Health Am. 2021 Dec 23;7:100153. doi: 10.1016/j.lana.2021.100153. eCollection 2022 Mar.


DOI:10.1016/j.lana.2021.100153
PMID:36777653
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9903788/
Abstract

BACKGROUND: Geographic accessibility to healthcare services is a fundamental component in achieving universal health coverage, the central commitment of the Brazilian Unified Health System (SUS). For cancer patients, poor accessibility has been associated with inadequate treatment, worse prognosis, and poorer quality of life. METHODS: We explored nationwide healthcare data from the SUS health information systems, and mapped the geographic accessibility to cancer treatment in two time-frames: 2009-2010 and 2017-2018. We applied social network analysis (SNA) to estimate the commuting route, flow, and distances travelled by cancer patients to undergo surgical, radiotherapy, and chemotherapy treatment. FINDINGS: A total of 12,751,728 treatment procedures were analyzed. Overall, more than half of the patients (49·2 to 60·7%) needed to travel beyond their municipality of residence for treatment, a fact that did not change over time. Marked regional differences were observed, as patients living in the northern and midwestern regions of the country had to travel longer distances (weighted average of 296 to 870 km). Cancer care hubs and attraction poles were mostly identified in the southeast and northeast regions, with Barretos being the main hub for all types of treatment throughout time. INTERPRETATION: Important regional disparities in the accessibility to cancer treatment in Brazil were revealed, suggesting the need to review the distribution of specialized care in the country. The data presented here contribute to ongoing research on improving access to cancer care and can provide reference to other countries, offering relevant data for oncological and healthcare service evaluation, monitoring, and strategic planning. FUNDING: This work was funded by the Oswaldo Cruz Foundation - Fiocruz (Inova - no. 8451635123 to BPF) and the National Council for Scientific and Technological Development - CNPq (no. 407060/2018-9 to BPF); Coordination for the Improvement of Higher Education Personnel - CAPES (scholarship to PCA, Finance Code 001); and Instituto Nacional de Ciência e Tecnologia de Inovação em Doenças de Populações Negligenciadas (INCT-IDPN). RESUMO: A acessibilidade geográfica aos serviços de saúde é um componente fundamental para o alcance da cobertura universal de saúde, compromisso central do Sistema Único de Saúde (SUS). Para pacientes com câncer, a baixa acessibilidade aos serviços especializados tem sido associada ao tratamento inadequado, piora no prognóstico e na qualidade de vida.Neste estudo, dados de saúde dos sistemas de informação em saúde do SUS foram utilizados para mapear a acessibilidade geográfica ao tratamento do câncer em dois períodos: 2009-2010 e 2017-2018. Aplicamos a análise de redes sociais (ARS) para estimar os fluxos de deslocamento e as distâncias percorridas por pacientes com câncer para receberem tratamento cirúrgico, radioterápico e quimioterápico.Um total de 12.751.728 procedimentos de tratamento foram analisados. Em geral, mais da metade dos pacientes (49,2 a 60,7%) precisaram se deslocar de seus municípios de residência para receber tratamento, fato que não mudou comparando os dois períodos de tempo analisados. Foram observadas importantes diferenças regionais no acesso. Pacientes residentes das regiões norte e centro-oeste do país tiveram que percorrer maiores distâncias para alcançar os serviços (média ponderada = 296 a 870 km). A maioria dos e polos de atração para atendimento oncológico foram identificados nas regiões Sudeste e Nordeste, sendo o município de Barretos o principal para todos os tipos de tratamento ao longo do tempo.As disparidades de acessibilidade para o tratamento de câncer, alertam para a necessidade de revisar a distribuição dos serviços de atenção especializada no país. A metodologia e os resultados apresentados neste estudo contribuem para as pesquisas sobre a melhoria do acesso ao tratamento do câncer e podem servir como referência para outros países, oferecendo dados relevantes para avaliação, monitoramento e planejamento estratégico de serviços oncológicos e de saúde em geral.

摘要

背景:医疗服务的地理可及性是实现全民健康覆盖的基本要素,全民健康覆盖是巴西统一卫生系统(SUS)的核心承诺。对于癌症患者而言,可及性差与治疗不充分、预后较差以及生活质量较低有关。 方法:我们探索了SUS健康信息系统中的全国医疗数据,并在两个时间段(2009 - 2010年和2017 - 2018年)绘制了癌症治疗的地理可及性图。我们应用社会网络分析(SNA)来估计癌症患者接受手术、放疗和化疗治疗时的通勤路线、流量和出行距离。 研究结果:共分析了12,751,728例治疗程序。总体而言,超过一半的患者(49.2%至60.7%)需要前往居住地以外的地区接受治疗,这一情况随时间未发生变化。观察到明显的地区差异,居住在该国北部和中西部地区的患者需要出行更长的距离(加权平均距离为296至870公里)。癌症治疗中心和吸引极点大多位于东南部和东北部地区,巴雷图斯一直是各类治疗的主要中心。 解读:研究揭示了巴西癌症治疗可及性方面存在重要的地区差异,这表明有必要重新审视该国专科护理的分布情况。此处呈现的数据有助于正在进行的改善癌症治疗可及性的研究,并可为其他国家提供参考,为肿瘤学和医疗服务评估、监测及战略规划提供相关数据。 资金来源:本研究由奥斯瓦尔多·克鲁兹基金会 - Fiocruz(Inova - 编号8451635123给予BPF)、国家科学技术发展委员会 - CNPq(编号407060/2018 - 9给予BPF)、高等教育人员改进协调办公室 - CAPES(给予PCA奖学金,财务代码001)以及国家被忽视人群疾病创新科学技术研究所(INCT - IDPN)资助。 摘要:医疗服务的地理可及性是实现全民健康覆盖的基本组成部分,全民健康覆盖是统一卫生系统(SUS)的核心承诺。对于癌症患者来说,专科服务可及性低与治疗不足、预后和生活质量变差有关。在本研究中,利用SUS健康信息系统的健康数据,在两个时期(2009 - 2010年和2017 - 2018年)绘制癌症治疗的地理可及性图。我们应用社会网络分析(SNA)来估计癌症患者接受手术、放疗和化疗治疗时的出行流量和距离。总共分析了12,751,728例治疗程序。总体而言,超过一半的患者(49.2%至60.7%)需要离开其居住市接受治疗,这一事实在比较两个分析时间段时没有改变。在可及性方面观察到重要的地区差异。该国北部和中西部地区的居民前往服务机构需要走更远的距离(加权平均距离 = 296至870公里)。大多数癌症治疗中心和肿瘤治疗吸引极点位于东南部和东北部地区,巴雷图斯市长期以来一直是各类治疗的主要中心。癌症治疗可及性的差异提醒人们需要重新审视该国专科护理服务的分布。本研究中提出的方法和结果有助于关于改善癌症治疗可及性的研究,并可作为其他国家的参考,为肿瘤学和一般医疗服务的评估、监测及战略规划提供相关数据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6398/9903788/d294ccfd9441/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6398/9903788/bba8938a15bf/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6398/9903788/b9e168c41763/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6398/9903788/fd910b075c72/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6398/9903788/6f5ad64f9d08/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6398/9903788/d67bf2939bf6/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6398/9903788/d294ccfd9441/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6398/9903788/bba8938a15bf/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6398/9903788/b9e168c41763/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6398/9903788/fd910b075c72/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6398/9903788/6f5ad64f9d08/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6398/9903788/d67bf2939bf6/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6398/9903788/d294ccfd9441/gr6.jpg

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