skip to page content
Talk to the Veterans Crisis Line now
U.S. flag
An official website of the United States government

Health Services Research & Development

Go to the ORD website
Go to the QUERI website

HSR&D Citation Abstract

Search | Search by Center | Search by Source | Keywords in Title

Assessing an electronic self-report method for improving quality of ethnicity and race data in the Veterans Health Administration.

Almklov E, Cohen AJ, Russell LE, Mor MK, Fine MJ, Hausmann LRM, Moy E, Washington DL, Jones KT, Long JA, Pittman J. Assessing an electronic self-report method for improving quality of ethnicity and race data in the Veterans Health Administration. JAMIA open. 2023 Jul 1; 6(2):ooad020.

Dimensions for VA is a web-based tool available to VA staff that enables detailed searches of published research and research projects.

If you have VA-Intranet access, click here for more information

VA staff not currently on the VA network can access Dimensions by registering for an account using their VA email address.
   Search Dimensions for VA for this citation
* Don't have VA-internal network access or a VA email address? Try searching the free-to-the-public version of Dimensions


OBJECTIVE: Evaluate self-reported electronic screening () in a VA Transition Care Management Program (TCM) to improve the accuracy and completeness of administrative ethnicity and race data. MATERIALS AND METHODS: We compared missing, declined, and complete (neither missing nor declined) rates between (1) (ethnicity and race entered into electronic tablet directly by patient using eScreening), (2) (Veteran-completed paper form plus interview, data entered by staff), and (3) (multiple processes, data entered by staff). The TCM-eScreening (? = 7113) and TCM-EHR groups (? = 7113) included post-9/11 Veterans. Standard-EHR Veterans included all non-TCM Gulf War and post-9/11 Veterans at VA San Diego (? = 92?921). RESULTS: : TCM-eScreening had lower rates of missingness than TCM-EHR and Standard-EHR (3.0% vs 5.3% and 8.6%, respectively, ? < .05), but higher rates of "decline to answer" (7% vs 0.5% and 1.2%, ? < .05). TCM-EHR had higher data completeness than TCM-eScreening and Standard-EHR (94.2% vs 90% and 90.2%, respectively, ? < .05). : No differences between TCM-eScreening and TCM-EHR for missingness (3.5% vs 3.4%, ? > .05) or data completeness (89.9% vs 91%, ? > .05). Both had better data completeness than Standard-EHR (? < .05), which despite the lowest rate of "decline to answer" (3%) had the highest missingness (10.3%) and lowest overall completeness (86.6%). There was strong agreement between TCM-eScreening and TCM-EHR for ethnicity (Kappa? = .92) and for Asian, Black, and White Veteran race (Kappas? = .87 to .97), but lower agreement for American Indian/Alaska Native (Kappa? = .59) and Native Hawaiian/Other Pacific Islander (Kappa? = .50) Veterans. CONCULSIONS: eScreening is a promising method for improving ethnicity and race data accuracy and completeness in VA.

Questions about the HSR&D website? Email the Web Team

Any health information on this website is strictly for informational purposes and is not intended as medical advice. It should not be used to diagnose or treat any condition.