Literature DB >> 31099021

Imputing race and ethnic information in administrative health data.

Yishu Xue1, Ofer Harel1, Robert H Aseltine2.   

Abstract

OBJECTIVE: To improve on existing methods to infer race/ethnicity in health care data through an analysis of birth records from Connecticut. DATA SOURCE: A total of 162 467 Connecticut birth records from 2009 to 2013. STUDY
DESIGN: We developed a logistic model to predict race/ethnicity using data from US Census and patient-level information. Model performance was tested and compared to previous studies. Five performance measures were used for comparison. PRINCIPAL
FINDINGS: Our full model correctly classifies 81 percent of subjects and shows improvement over extant methods. We achieved substantially improved sensitivity in predicting black race.
CONCLUSIONS: Predictive models using Census information and patients' demographic characteristics can be used to accurately populate race/ethnicity information in health care databases, enhancing opportunities to investigate and address disparities in access to, utilization of, and outcomes of care. © Health Research and Educational Trust.

Entities:  

Keywords:  health disparities; health insurance claims; imputation; missing data

Mesh：

Year:  2019        PMID： 31099021      PMCID： PMC6606547          DOI： 10.1111/1475-6773.13171

Source DB:  PubMed          Journal:  Health Serv Res        ISSN： 0017-9124            Impact factor:   3.402


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Journal:  Rand Health Q       Date:  2016-06-20

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7.  Validity of infant race/ethnicity from birth certificates in the context of U.S. demographic change.

Authors:  Lisa Reyes Mason; Yunju Nam; Youngmi Kim
Journal:  Health Serv Res       Date:  2013-07-05       Impact factor: 3.402

8.  Imputing race and ethnic information in administrative health data.

Authors:  Yishu Xue; Ofer Harel; Robert H Aseltine
Journal:  Health Serv Res       Date:  2019-05-17       Impact factor: 3.402

9.  Surveillance of health status in minority communities - Racial and Ethnic Approaches to Community Health Across the U.S. (REACH U.S.) Risk Factor Survey, United States, 2009.

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Review 10.  Disparities in cardiovascular disease risk in the United States.

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  3 in total

1.  Imputing race and ethnic information in administrative health data.

Authors:  Yishu Xue; Ofer Harel; Robert H Aseltine
Journal:  Health Serv Res       Date:  2019-05-17       Impact factor: 3.402

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3.  Variation in Reporting of the Race and Ethnicity of COVID-19 Cases and Deaths Across US States: April 12, 2020, and November 9, 2020.

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  3 in total

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