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

Abstract

Objective: Evaluate self-reported electronic screening (eScreening) 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) TCM-eScreening (ethnicity and race entered into electronic tablet directly by patient using eScreening), (2) TCM-EHR (Veteran-completed paper form plus interview, data entered by staff), and (3) Standard-EHR (multiple processes, data entered by staff). The TCM-eScreening (n ¼ 7113) and TCM-EHR groups (n ¼ 7113) included post-9/11 Veterans. Standard-EHR Veterans included all non-TCM Gulf War and post-9/11 Veterans at VA San Diego (n ¼ 92 921). Results: Ethnicity: TCM-eScreening had lower rates of missingness than TCM-EHR and Standard-EHR (3.0% vs 5.3% and 8.6%, respectively, P < .05), but higher rates of “decline to answer” (7% vs 0.5% and 1.2%, P < .05). TCM-EHR had higher data completeness than TCM-eScreening and Standard-EHR (94.2% vs 90% and 90.2%, respectively, P < .05). Race: No differences between TCM-eScreening and TCM-EHR for missingness (3.5% vs 3.4%, P > .05) or data completeness (89.9% vs 91%, P > .05). Both had better data completeness than Standard-EHR (P