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Health Serv Res. 2015 Aug;50(4):946-60. doi: 10.1111/1475-6773.12295. Epub 2015 Mar 11.

Imputing Missing Race/Ethnicity in Pediatric Electronic Health Records: Reducing Bias with Use of U.S. Census Location and Surname Data.

Author information

1
The Children's Hospital of Philadelphia, Philadelphia, PA.
2
RAND Corporation, Santa Monica, CA.
3
DARTNet Institute, University of Colorado Denver, Aurora, CO.
4
University of Vermont, Burlington, VT.
5
Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.

Abstract

OBJECTIVE:

To assess the utility of imputing race/ethnicity using U.S. Census race/ethnicity, residential address, and surname information compared to standard missing data methods in a pediatric cohort.

DATA SOURCES/STUDY SETTING:

Electronic health record data from 30 pediatric practices with known race/ethnicity.

STUDY DESIGN:

In a simulation experiment, we constructed dichotomous and continuous outcomes with pre-specified associations with known race/ethnicity. Bias was introduced by nonrandomly setting race/ethnicity to missing. We compared typical methods for handling missing race/ethnicity (multiple imputation alone with clinical factors, complete case analysis, indicator variables) to multiple imputation incorporating surname and address information.

PRINCIPAL FINDINGS:

Imputation using U.S. Census information reduced bias for both continuous and dichotomous outcomes.

CONCLUSIONS:

The new method reduces bias when race/ethnicity is partially, nonrandomly missing.

KEYWORDS:

Multiple imputation; U.S. Census location and surname data; health disparities; race and ethnicity

PMID:
25759144
PMCID:
PMC4545341
DOI:
10.1111/1475-6773.12295
[Indexed for MEDLINE]
Free PMC Article

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