Using advanced racial and ethnic identity demographics to improve surveillance of work-related conditions in an occupational clinic setting

Abstract

Background: Although racial and ethnic identities are associated with a multitude of disparate medical outcomes, surveillance of these subpopulations in the occupational clinic setting could benefit enormously from a more detailed and nuanced recognition of racial and ethnic identity.

Methods: The research group designed a brief questionnaire to capture several dimensions of this identity and collected data from patients seen for work-related conditions in four occupational medicine clinics from May 2019 through March 2020. Responses were used to calculate the sensitivity and specificity of extant racial/ethnic identity data within our electronic health records system, and were compared to participants' self-reported industry and occupation, coded according to North American Industry Classification System and Standard Occupational Classification System listings.

Results: Our questionnaire permitted collection of data that defined our patients' specific racial/ethnic identity with far greater detail, identified patients with multiple ethnic identities, and elicited their preferred language. Response rate was excellent (94.2%, n = 773). Non-White participants frequently selected a racial/ethnic subcategory (78.1%-92.2%). Using our race/ethnicity data as a referent, the electronic health record (EHR) had a high specificity (>87.1%), widely variable sensitivity (11.8%-82.2%), and poorer response rates (75.1% for race, 82.5% for ethnicity, as compared to 93.8% with our questionnaire). Additional analyses revealed some industries and occupations disproportionately populated by patients of particular racial/ethnic identities.

Conclusions: Our project demonstrates the usefulness of a questionnaire which more effectively identifies racial/ethnic subpopulations in an occupational medicine clinic, permitting far more detailed characterization of their occupations, industries, and diagnoses.

Keywords: NAICS; OIICS; SOC system; clinical surveillance; electronic health record; occupational coding; occupational health; racial and ethnic disparities.