Beyond Black and White: Mapping Misclassification of Medicare Beneficiaries Race and Ethnicity.
Beyond Black and White: Mapping Misclassification of Medicare Beneficiaries Race and Ethnicity.
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DOI：
10.1177/1077558720935733
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发表时间：
2021-10
期刊：
影响因子：
--
通讯作者：
Jarrín OF
中科院分区：
文献类型：
--
作者：
Grafova IB;Jarrín OF
医疗保险和医疗补助服务中心的管理数据包含两个用于研究和评估健康差异的变量：注册数据库“EDB”受益人种族代码和三角研究研究所“RTI”种族代码。本文的目的是与家庭医疗保健期间收集的自我报告数据相比，检查 EDB 和 RTI 种族代码的种族/族裔错误分类的州级差异。研究人群包括 2015 年使用家庭医疗保健服务的 4,231,370 名医疗保险受益人。我们发现，各州在行政种族数据中对自我认定的西班牙裔、亚裔美国人/太平洋岛民和美洲印第安人/阿拉斯加原住民的错误分类存在很大差异。在根据医疗保险数据集中包含的现有种族变量解释州级医疗保健差异和少数族裔健康结果时应谨慎。在医疗保险受益人的日常护理期间收集的自我报告的种族/民族数据可用于提高少数族裔健康和健康差异报告和研究的准确性。
The Centers for Medicare and Medicaid Services administrative data contains two variables that are used for research and evaluation of health disparities: the enrollment database “EDB” beneficiary race code and the Research Triangle Institute “RTI” race code. The objective of this paper is to examine state-level variation in racial/ethnic misclassification of EDB and RTI race codes compared to self-reported data collected during home health care. The study population included 4,231,370 Medicare beneficiaries who utilized home health care services in 2015. We found substantial variation among states in misclassification of self-identified Hispanics, Asian Americans/Pacific Islanders, and American Indians/Alaskan Natives in administrative race data. Caution should be used when interpreting state-level healthcare disparities and minority health outcomes based on existing race variables contained in Medicare datasets. Self-reported race/ethnicity data collected during routine care of Medicare beneficiaries may be used to improve the accuracy of minority health and health disparities reporting and research.
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影响因子：
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作者：
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通讯作者：
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影响因子：
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作者：
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作者：
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影响因子：
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作者：
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DOI：
10.1097/phh.0b013e3182751cfb
发表时间：
2013-09-01
影响因子：
3.3
作者：
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通讯作者：
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