解决种族和种族报告中的数据聚合和数据不平等问题以及对乳腺癌差异的影响
Brianna Wilson1, Jane Mendez2, Lisa Newman3
1UT Southwestern Medical School, Dallas, TX, USA.
Annals of surgical oncology
|October 15, 2023
概括
收集种族和种族数据对于解决健康差异至关重要. 不准确的数据限制了针对性干预和对健康结果的理解,特别是对于边缘化群体.
科学领域:
- 公共卫生 公共卫生
- 健康差距 研究 研究 研究 研究
- 数据科学数据科学数据科学
背景情况:
- 在美国,健康差异仍然存在,不成比例地影响弱势群体.
- 准确的种族和民族数据对于识别和解决这些差异至关重要.
- 目前的联邦数据收集标准,最后一次更新于1997年,对于边缘化群体来说是不够的.
研究的目的:
- 检查数据不平等对健康差异研究的影响.
- 分析数据公平性不足如何影响预防和干预工作.
- 探索公共卫生倡议在资源分配方面的影响.
主要方法:
- 对有关种族,种族和健康差异的现有文献进行审查.
- 分析联邦数据收集标准及其局限性.
- 检查案例研究,包括乳腺癌结果,以说明数据缺口.
主要成果:
- 联邦机构使用的广泛的种族/民族类别 (例如,OMB标准) 已经过时,缺乏细节性.
- 数据不平等阻碍了在不同人群中识别特定的健康需求.
- 数据不足限制了针对性的健康干预措施的开发和实施.
结论:
- 过时和不公平的数据收集做法阻碍了减少健康差距的进展.
- 需要更新,全面,以公平为中心的数据流程.
- 提高数据质量对于有效的公共卫生政策和资源分配至关重要.
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