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评估医疗保健支出中的种族差异,使用一般化倾向性得分加权

Jiajun Liu¹, Yi Liu^2,3, Yunji Zhou⁴

¹Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, 27705, USA. jiajun.liu@duke.edu.

BMC medical research methodology

|March 7, 2025

概括

本研究引入了一般化倾向分数权重 (GPSW) 来分析种族群体之间的医疗保健准入差异. 在评估这些医疗保健支出差异方面,重叠加重平均治疗效应对治疗方法 (OWATT) 证明是最有效的.

科学领域:

因果推理的原因推理.
健康差异研究研究健康差异研究
量化方法量化方法

背景情况:

了解跨种族群体的医疗保健获取差异对于健康公平至关重要.
现有的倾向评分方法可能会面临多个组比较和阳性违规的挑战.

研究的目的:

扩大因果推理的倾向性得分权重方法,以评估跨多个种族群体的医疗保健获取差异.
评估不同倾向得分权重技术的表现,包括解决积极性假设违规问题.

主要方法:

利用通用倾向得分方法来分析白人,西班牙裔,亚洲人和黑人参与者之间的种族差异.
采用了四个因果估计的多值处理框架:ATT,ATT修剪,ATT截断和重叠加权的ATT (OWATT).
使用医学支出小组调查 (MEPS) 数据评估医疗支出差异.

主要成果:

在使用OWATT和ATT截断的白人参与者和其他种族/族群之间发现了显著的医疗保健支出差异.
由于差异估计较大,传统的ATT和ATT修剪显示出非显著的差异.
与其他方法相比,OWATT显示出更高的效率和可靠性,避免了主观性,并减轻了极端倾向得分权重.

结论:

一般化倾向分数权衡 (GPSW) 提供了有价值的定量工具,用于标准化和比较非可操纵组的结果.
OWATT是评估种族差异的有效和可靠的替代方案,特别是当正面性假设被违反时.
由于OWATT使用了整个数据集,并避免了用户定义的值,提高了估计可靠性和解释性.

关键词:

治疗对被治疗者的平均治疗效果.多项式回归的多项式回归.不易操纵的组成员身份组成员身份重叠重量重量重叠重量重量重叠重量重重量重量重量重量重量重量重量重量重量重重量重量重量重量重量重量重量重量重重量重量重量重量重量重量重量重量重量重量重量重量重量重量重量重量重量重量重量重量重量重量重量重量重量重量重量重量重量重量重量重量重量重量重量.调查样本调查样本

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