Center for Health Policy Research, University of California, Los Angeles.
Los Angeles Fielding School of Public Health, University of California.
Milbank Q. 2023 Apr;101(S1):302-332. doi: 10.1111/1468-0009.12605.
Policy Points Despite decades of research exposing health disparities between populations and communities in the US, health equity goals remain largely unfulfilled. We argue these failures call for applying an equity lens in the way we approach data systems, from collection and analysis to interpretation and distribution. Hence, health equity requires data equity. There is notable federal interest in policy changes and federal investments to improve health equity. With this, we outline the opportunities to align these health equity goals with data equity by improving the way communities are engaged and how population data are collected, analyzed, interpreted, made accessible, and distributed. Policy priority areas for data equity include increasing the use of disaggregated data, increasing the use of currently underused federal data, building capacity for equity assessments, developing partnerships between government and community, and increasing data accountability to the public.
政策要点 尽管数十年来的研究揭示了美国人口和社区之间的健康差距,但健康公平目标仍未得到充分实现。我们认为,这些失败要求我们在数据系统的处理方式上应用公平视角,从数据的收集、分析到解释和分配。因此,健康公平需要数据公平。联邦政府对政策变革和联邦投资以改善健康公平表现出浓厚的兴趣。有鉴于此,我们概述了通过改善社区参与的方式以及收集、分析、解释、提供和分配人口数据的方式,将这些健康公平目标与数据公平联系起来的机会。数据公平的政策重点领域包括增加对分类数据的使用、增加对目前使用不足的联邦数据的使用、建立公平评估能力、发展政府与社区之间的伙伴关系,以及提高数据对公众的责任。