Beyond Aggregated Race and Ethnicity Codes: An Examination of Additional Methods to Identify Asian American and Native Hawaiian and Other Pacific Islander Veteran Subgroups in Administrative Databases.

INTRODUCTION

Veterans who identify either as Asian American or as Native Hawaiian and Other Pacific Islander (NHPI) are growing (in percentage points) more rapidly than veterans of other racial groups. Substantial variation in COVID-19 death rates among Americans of Asian and NHPI ethnic origins underscored within-Asian and-NHPI health disparities-disparities that healthcare systems need to identify and measure. Yet healthcare utilization data within the U.S. Department of Veterans Affairs (VA) aggregates Asian American and NHPI groups, making it challenging to distinguish VA patients by subgroup membership and hampering efforts to identify subgroup variations.

MATERIALS AND METHODS

We piloted the combined use of 2 administrative data sources-the VA Corporate Data Warehouse (CDW) and DaVINCI, derived from the U.S. DoD Military Health System-to identify Asian American and NHPI VA-enrolled veterans. Our sample consisted of individuals within CDW whose fiscal year (FY) 2022 records included a veteran flag and non-missing values for race and ethnicity. We examined all variables related to race and ethnicity; however, we primarily used CDW's race variable, which categorized individuals as Asian, NHPI, White, Black, and/or American Indian/Alaska Native. We used DaVINCI's ethnicity variable in FY2022 records to identify individuals belonging to Asian subgroups (i.e., Chinese, Filipino, Japanese, Korean, Indian, Vietnamese, and Other Asian) or NHPI subgroups (i.e., Guamanian, Melanesian, Micronesian, Pacific Islander NEC, and Polynesian). We created 4 groups of VA-enrolled veterans by race: (1) Asian, (2) NHPI, (3) both Asian and NHPI, and (4) neither Asian nor NHPI. Within each group, we then calculated counts and proportion of individuals by Asian or NHPI ethnic subgroup.

RESULTS

The merging of CDW and DaVINCI provided information on 1,300,499 unique veterans. In group (1) (Asian race; n = 38,384), nearly half reported at least one Asian ethnicity. In group (2) (NHPI race; n = 20,282), 15% reported at least one NHPI ethnicity and 16% reported Asian ethnicity. In group (3) (both Asian and NHPI; n = 1,468), 34.3% reported Asian ethnicity and 10% reported NHPI ethnicity. In group (4) (neither Asian nor NHPI; n = 1,240,365), 0.4% reported at least one Asian or NHPI ethnicity. Among VA-enrolled veterans with reported Asian or NHPI race in CDW, 26,166 had additional information from DaVINCI about Asian or NHPI subgroup membership.

CONCLUSIONS

Our study is the first, to the best of our knowledge, to merge administrative datasets to characterize VA-enrolled veterans of Asian or NHPI race with a corresponding Asian or NHPI ethnicity. Despite incomplete ethnicity data, the merging of CDW race and DaVINCI ethnicity variables (over the use of one or the other) may inform research and quality improvement studies, e.g., by enabling recruitment of vulnerable veterans from diverse ethnic backgrounds. This effort to disaggregate data is key to expanding our knowledge of heterogeneity in the health of veterans in Asian and NHPI communities.