2065. Missing Race Data in VA
Based Disparities Research: A Systematic Review
JA Long, Center for Health Equity Research and Promotion, Leonard
Davis Institute of Health Economics, and University of Pennsylvania School of
Medicine, MI Bamba, Center for Health Equity Research and Promotion and
University of Pennsylvania School of Medicine, B Ling, Center for Health
Equity Research and Promotion and University of Pittsburgh, JA Shea,
Center for Health Equity Research and Promotion, Leonard Davis Institute of
Health Economics, and University of
Pennsylvania School of Medicine
Objectives: Many studies
evaluating racial disparities within the VHA are based on secondary data
analyses. Often race data are missing for at least a portion of the patients.
Knowing how investigators treat missing data is critical in evaluating potential
biases. The objectives of this systematic review were to quantify: (1) the data
sources for VHA disparity studies; (2) how missing data were handled; and (3)
the extent of missing data.
Methods: MEDLINE, EconLit,
and Sociological Abstracts were searched using these keywords: (race, racial
stock, ethnicity, ethnic groups, blacks, Hispanic Americans) and (United States
Department of Veterans Affairs, veterans, veterans hospitals, and VA).
Abstract exclusion criteria included: written before 1992; letters or
review papers; did not pertain to veterans; race not mentioned; race
self-reported. Two trained
reviewers independently abstracted each article.
Article exclusion criteria included: duplicate study populations; not a
secondary data analysis; race was not a focus of or important predictor in the
research.
Results: 69 of 118
articles met inclusion criteria. Race was the primary focus in 42 articles and
an important predictor in 27 articles. The Patient Treatment File (PTF) was the
most common source of race data (29). For
32 articles knowledge of race was required for inclusion in the analytic
population. Articles were grouped into the following mutually exclusive
categories: no missing race data (11); missing race data explicitly quantified
(8); missing race data explicitly grouped with other data but not quantified
(9); race data known for enumeration of the potential population (2); no mention
of missing race data but known to exist in the data source e.g., PTF (5); unable
to determine if there was missing race data (33). When missing race data was
quantified it ranged from 0% to 48%, median = 0%, mean = 8%.
Conclusions: Missing race
data is frequently present in VHA secondary data sources.
However, it is rarely explicitly discussed or quantified, even when it is
the primary focus of the research question.
Impact: Without clear descriptions of how much missing race data is present in studies using VHA secondary data sources, readers are unable to evaluate a very important potential source of bias.