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考虑公共政策流行病学分析中的多个治理层次。

Considering multiple governance levels in epidemiologic analysis of public policies.

机构信息

Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA; Department of Health Management and Policy, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA.

The Ubuntu Center on Racism, Global Movements & Population Health Equity, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA; Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA.

出版信息

Soc Sci Med. 2022 Dec;314:115444. doi: 10.1016/j.socscimed.2022.115444. Epub 2022 Oct 14.

Abstract

Epidemiology is increasingly asking questions about the use of policies to address structural inequities and intervene on health disparities and public health challenges. However, there has been limited explicit consideration of governance structures in the design of epidemiologic policy analysis. To advance empirical and theoretical inquiry in this space, we propose a model of governance analysis in which public health researchers consider at what level 1) decision-making authority for policy sits, 2) policy is implemented, 3) and accountability for policy effects appear. We follow with examples of how these considerations might improve the evaluation of the policy drivers of population health. Consideration and integration of multiple levels of governance, as well as interactions between levels, can help epidemiologists design studies including new opportunities for quasi-experimental designs and stronger counterfactuals, better quantify the policy drivers of inequities, and aid research evidence and policy development work in targeting multiple levels of governance, ultimately supporting evidence-based policy making.

摘要

流行病学越来越多地提出关于利用政策解决结构性不平等问题以及干预健康差异和公共卫生挑战的问题。然而,在设计流行病学政策分析时,对治理结构的明确考虑有限。为了推进这一领域的实证和理论研究,我们提出了一个治理分析模型,其中公共卫生研究人员考虑以下三个方面:1)决策权力所在的政策层面;2)政策的实施层面;3)政策效果的问责层面。我们接着举例说明了这些考虑因素如何改进对人口健康政策驱动因素的评估。考虑和整合多个治理层面,以及各层面之间的相互作用,可以帮助流行病学家设计研究,包括为准实验设计和更强有力的反事实提供新的机会,更好地量化不平等的政策驱动因素,并为研究证据和政策制定工作提供支持,以针对多个治理层面,最终支持基于证据的政策制定。

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