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

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.