Assessing an Electronic Self-report Method for Improving Quality of Ethnicity and Race Data in the Veterans Health Administration

Overview

Journal JAMIA Open

Date 2023 Apr 17

PMID 37063405

Authors

Erin Almklov

Alicia J Cohen

Lauren E Russell

Maria K Mor

Michael J Fine

Leslie R M Hausmann

Ernest Moy

Donna L Washington

Kenneth T Jones

Judith A Long

James Pittman

Affiliations

Soon will be listed here.

Abstract

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.

Citing Articles

Sociodemographic and Clinical Characteristics Associated With Veterans' Digital Needs.

Russell L, Cornell P, Halladay C, Kennedy M, Berkheimer A, Drucker E JAMA Netw Open. 2024; 7(11):e2445327.

PMID: 39546310 PMC: 11568462. DOI: 10.1001/jamanetworkopen.2024.45327.

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