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The need for, and value of, a spatial scan statistical tool for tackling social health inequalities

机译:解决社会卫生不平等问题的空间扫描统计工具的需求和价值

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摘要

Today, one important challenge in developed countries is health inequalities. Research conducted in public health policy issues supply little evidence for effective interventions aiming to improve population health and to reduce health inequalities. There is a need for a powerful tool to support priority setting and guide policy makers in their choice of health interventions, and that maximizes social welfare. This paper proposes to divert a spatial tool based on Kulldorff's scan method to investigate social inequalities in health. This commentary argues that this spatial approach can be a useful tool to tackle social inequalities in health by guiding policy makers at three levels: (i) supporting priority setting and planning a targeted intervention; (ii) choosing actions or interventions which will be performed for the whole population, but with a scale and intensity proportionate to need; and (iii) assessing health equity of public interventions.
机译:今天,发达国家的一项重要挑战是健康不平等。在公共卫生政策问题上进行的研究几乎没有证据表明旨在改善人口健康和减少健康不平等的有效干预措施。需要一种功能强大的工具来支持优先重点的确定并指导决策者选择健康干预措施,从而最大程度地提高社会福利。本文提出了一种基于库尔多夫扫描方法的空间工具来调查健康方面的社会不平等现象。这篇评论认为,这种空间方法可以通过在三个层面上指导政策制定者来解决健康方面的社会不平等现象:(i)支持重点确定和计划有针对性的干预措施; (ii)选择将在整个人口中执行的行动或干预措施,但其规模和强度应与需要成比例; (iii)评估公共干预措施的健康公平性。

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