Cover: Imputing Missing Race/Ethnicity in Pediatric Electronic Health Records

Imputing Missing Race/Ethnicity in Pediatric Electronic Health Records

Reducing Bias with Use of U.S. Census Location and Surname Data

Published in: Health Services Research, 2015

Posted on Apr 7, 2015

by Robert W. Grundmeier, Lihai Song, Mark J. Ramos, Alexander G. Fiks, Marc N. Elliott, Allen Fremont, Wilson D. Pace, Richard C. Wasserman, Russell Localio

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.

This report is part of the RAND external publication series. Many RAND studies are published in peer-reviewed scholarly journals, as chapters in commercial books, or as documents published by other organizations.

RAND is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.