Abstract
BackgroundData collection on race and ethnicity is critical in the assessment of racial disparities related to health. Studies comparing clinical and administrative data show discrepancies in race documentation and attribution.MethodsSelf-reported data from two studies were compared to demographics in the electronic health record (EHR) extracted from the Biomedical Translational Research Information System (BTRIS) repository. McNemar and Bhapkar analyses were conducted to quantify the agreement of ethnicity and race between self-reported and EHR data. Pearson’s chi-square tests were used to explore the relationship between acculturation, length of time in the USA, country of residence, and how individuals self-reported their race.ResultsThe sample (n = 280) was predominantly female (52.1 %), with a mean age of 47 (SD ± 13.74), mean years in the USA were 12.8 (SD ± 11.67) and the majority were born outside of the USA. (55.6 %). Those who self-identified as Hispanic (n = 208) scored a mean of 5.5 (SD ± 3.07) on the short acculturation scale (SAS) that ranges 4 to 20; lower scores indicate less acculturation. A significant difference was found between the way race is reported in the electronic medical record and self-reported data among those people who identified as Hispanic, with significant differences in the white (p < 0.0001) and other (p < 0.0001) categories.ConclusionsThe misclassification of race is most frequent in those individuals who self-identified as Hispanic. As the Hispanic population in the USA continues to grow, understanding the factors that affect the way that individuals from this heterogeneous population self-report race may provide important guidance in tailoring care to address health disparities.
Highlights
Ethnicity and race are complex social constructs that influence personal identity and group social relations
The misclassification of race is most frequent in those individuals who self-identified as Hispanic
Inaccurate or inconsistent data stratified by race and ethnicity can impede analysis needed to identify improvements in health care and for the identification of population groups that might be the focus of health interventions to decrease health disparities [3]
Summary
Ethnicity and race are complex social constructs that influence personal identity and group social relations. Racial and ethnic identification are fluid and specific to place, time, and context [1, 2] Despite their fluidity, federal ethnic and racial categories serve as the basis to ensure inclusion of minorities in research as well as identify and address health disparities in the US health care system [2]. Inaccurate or inconsistent data stratified by race and ethnicity can impede analysis needed to identify improvements in health care and for the identification of population groups that might be the focus of health interventions to decrease health disparities [3]. Data collection on race and ethnicity is critical in the assessment of racial disparities related to health. Methods Self-reported data from two studies were compared to demographics in the electronic health record (EHR) extracted from the Biomedical Translational Research Information System (BTRIS) repository. A significant difference was found between the way race is reported in the electronic medical record and self-reported data among those people who identified as Hispanic, with significant differences in the white (p < 0.0001) and other (p < 0.0001) categories
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