Impact of structural racism on hospital/clinic closures, community assets, and health outcomes in urban communities

项目总结/摘要 结构性种族主义，被定义为社会通过相互歧视 强化不公平的制度，已成为一个重要的社会风险因素，并导致健康状况不佳 种族/少数民族的结果（Egede 2020，Bailey 2017）。结构性种族主义抓住了上游历史 种族主义事件（如奴隶制，黑人法典法，吉姆克劳法和学校种族隔离）和最近的州 以红线的形式制裁种族主义法律。划红线是指系统地否认各种 为特定社区/社区的居民提供服务，通常基于种族/民族（Bailey 2020）。 历史性红线与健康结果之间的第一个重要联系可能与医疗保健有关 医院和社区诊所的无障碍形式以及这些设施的质量。一 第二个重要的联系之间的历史红线和健康结果可能与方式， 结构性种族主义（以红线的形式）系统地剥夺了社区的经济利益， 机会，因此，有能力以住房价值的形式建立个人和社区资产， 为居民提供就业和教育机会。这些结构性种族主义、获取机会、 此外，社区资产和健康差距也与当前的政策相关， 趋势显示，由于COVID-19大流行，越来越多的医院和诊所关闭（Ellison 2021）。 然而，历史性的红线与城市医院和诊所关闭之间的联系以及 对社区资产和社区卫生成果了解甚少。该项目的目标是告知 我们对结构性种族主义（定义为历史性红线），城市医院和 诊所关闭，社区资产和健康结果;并进一步为有助于减少 结构性种族主义对医院和诊所关闭造成的健康差距的影响。本研究 试图通过使用最近开发的因果和可解释的机器学习来实现这一目标 方法，沿着计量经济学反事实分析，以解决以下目标：1）检查 区域性结构性种族主义与医院和诊所关闭倾向之间的关系。 2)研究医院和诊所关闭与社区就业、收入和 教育，以及社区健康成果。3)预测城市医院和诊所关闭的风险 不成比例地为来自社区的种族/少数民族提供服务， 种族主义4)让利益攸关方参与解决防止未来关闭的问题和/或审查 减少医院和诊所关闭对社区的潜在不利影响。本研究具有创新性， 审查结构性种族主义与健康结果之间的联系; 减少结构性种族主义永久影响的政策渠道;以及其方法学上对广泛的 一套混合的方法来实现这些目标。

Project Summary/Abstract Structural racism, defined as the ways in which societies foster discrimination through mutually reinforcing inequitable systems, has emerged as an important social risk factor and contributor to poor health outcomes for racial/ethnic minorities (Egede 2020, Bailey 2017). Structural racism captures upstream historic racist events (such as slavery, black code laws, Jim Crow laws, and school segregation) and more recent state sanctioned racist laws in the form of redlining. Redlining refers to the practice of systematically denying various services to residents of specific neighborhoods/communities, often based on race/ethnicity (Bailey 2020). A first important link between historic redlining and health outcomes is likely related to health care access in the form of accessible hospital and neighborhood clinics, as well as the quality of these facilities. A second important linkage between historic redlining and health outcomes is likely associated with the way in which structural racism (in the form of redlining) has systematically deprived neighborhoods of economic opportunities, and as such, of the ability to build individual and community assets in the form of housing value, employment, and educational opportunities for its residents. These linkages between structural racism, access, community assets, and health disparities, are furthermore of significant current policy relevance as recent trends indicate a growing number of hospital and clinic closures due to the COVID-19 pandemic (Ellison 2021). However, the link between historic redlining and urban hospital and clinic closures as well as community assets and community health outcomes are poorly understood. The goal of this project is to inform our understanding of the pathways between structural racism (defined as historic redlining), urban hospital and clinic closures, community assets, and health outcomes; and to further inform policies that can help reduce the impact of structural racism on health disparities caused by hospital and clinic closures. The present study seeks to accomplish this objective by using recently developed causal and interpretable machine learning methods, along with econometric counterfactual analysis, to address the following aims: 1) Examine the relationship between regional exposure to structural racism and the propensity of hospital and clinic closures. 2) Examine the relationship between hospital and clinic closures and community employment, income, and education, as well as community health outcomes. 3) Predict risk of closure among urban hospitals and clinics that are disproportionately serving racial/ethnic minorities from neighborhoods with exposure to structural racism. 4) Undertake stakeholder engagement to address prevention of future closures and/or examine ways to decrease the potential adverse community impact of hospital and clinic closures. The study is innovative in its examination of the linkages between structural racism and health outcomes; its emphasis on identifying policy channels for reducing the perpetual impact of structural racism; and its methodological use of a broad set of mixed methods to achieve these aims.