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

TitleImputing Missing Race/Ethnicity in Pediatric Electronic Health Records: Reducing Bias with Use of U.S. Census Location and Surname Data.
Publication TypeJournal Article
Year of Publication2015
AuthorsGrundmeier RW, Song L, Ramos MJ, Fiks AG, Elliott MN, Fremont A, Pace WD, Wasserman RC, Localio R
JournalHealth Serv Res
Volume50
Issue4
Pagination946-60
Date Published08/2015
ISSN1475-6773
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.

DOI10.1111/1475-6773.12295
Alternate JournalHealth Serv Res
PubMed ID25759144
PubMed Central IDPMC4545341
Grant ListP30 HS021645 / HS / AHRQ HHS / United States
UB5MC20286 / / PHS HHS / United States