globalchange  > 影响、适应和脆弱性
DOI: 10.7249/RR1162
报告号: RR-1162-COMMASS
报告题名:
When Race/Ethnicity Data Are Lacking: Using Advanced Indirect Estimation Methods to Measure Disparities
作者: Allen Fremont; Joel S. Weissman; Emily Hoch; Marc N. Elliott
出版者: RAND Corporation
出版年: 2016
发表日期: 2016
总页数: 8
国家: 美国
语种: 英语
英文关键词: Health Care Access ; Health Disparities ; Health Care Quality ; Statistical Analysis Methodology
英文摘要: A key aim of U.S. health care reforms is to ensure equitable care while improving quality for all Americans. Limited race/ethnicity data in health care records hamper efforts to meet this goal. Despite improvements in access and quality, gaps persist, particularly among persons belonging to racial/ethnic minority and low-income groups. This report describes the use of indirect estimation methods to produce probabilistic estimates of racial/ethnic populations to monitor health care utilization and improvement. One method described, called Bayesian Indirect Surname Geocoding, uses a person's Census surname and the racial/ethnic composition of their neighborhood to produce a set of probabilities that a given person belongs to one of a set of mutually exclusive racial/ethnic groups. Advances in methods for estimating race/ethnicity are enabling health plans and other health care organizations to overcome a long-standing barrier to routine monitoring and actions to reduce disparities in care. Though these new estimation methods are promising, practical knowledge and guidance on how to most effectively apply newly available race/ethnicity data to address disparities can be greatly extended.
URL: http://www.rand.org/content/dam/rand/pubs/research_reports/RR1100/RR1162/RAND_RR1162.pdf
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资源类型: 研究报告
标识符: http://119.78.100.158/handle/2HF3EXSE/27370
Appears in Collections:影响、适应和脆弱性
科学计划与规划
气候减缓与适应
气候变化事实与影响
气候变化与战略

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Recommended Citation:
Allen Fremont,Joel S. Weissman,Emily Hoch,et al. When Race/Ethnicity Data Are Lacking: Using Advanced Indirect Estimation Methods to Measure Disparities. 2016-01-01.
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