Can ethnicity data collected at an organizational level be useful in addressing health and healthcare inequities?
Abstract
OBJECTIVE: Following arguments made in the USA, the UK and New Zealand regarding the importance of population-level ethnicity data in understanding health and healthcare inequities, health authorities in several Canadian provinces are considering plans to collect ethnicity data from patients at the point of care within selected healthcare organizations. The purpose of this paper is to examine the potential quality, utility and relevance of ethnicity data collected at an organizational level as a means of addressing health and healthcare inequities. DESIGN: We draw on findings from a recent Canadian study that examined the implications of collecting ethnicity data in healthcare contexts. Using a qualitative design, data were collected in a large city, and included interviews with 104 patients, community and healthcare leaders, and healthcare workers within diverse clinical contexts. Data were analyzed using interpretive thematic analysis. RESULTS: Our results are discussed in relation to discourses reflected in the current literature that require consideration in relation to the potential utility and relevancy of ethnicity data collected at the point of care within healthcare organizations. These discourses frame excerpts from the ethnographic data that are used as illustrative examples. Three key challenges to the potential relevance and utility of ethnicity data collected at the level of local healthcare organizations are identified: (a) issues pertaining to quality of the data, (b) the fact that data quality is most problematic for those with the greatest vulnerability to the negative effects of health inequities, and (c) the lack of data reflecting structural disadvantages or discrimination. CONCLUSION: The quality of ethnicity data collected within healthcare organizations is often unreliable, particularly for people from racialized or visible minority groups, who are most at risk, seriously limiting the usefulness of the data. Quality measures for collecting data reflecting ethnocultural identity in specific healthcare organizations may be warranted - but only if mechanisms exist or are developed for linking ethnicity with measures of perceived discrimination, stigmatization, income level, and other known contributors to inequities. Methods for linking these kinds of data, however, remain underdeveloped or non-existent in most healthcare organizations.
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Such measures are often deployed in limited ways comparing care or outcomes for specific groups defined by a single demographic characteristic.
“such measures are often deployed in limited ways comparing care or outcomes of care for specific groups of people defined by a single demographic characteristic (e.g., a particular ethnocultural or racialized group) [15, 16].”
From Using a health equity lens to measure patient experiences of care in diverse health care settings (2024) · cites this paper as [16]
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- Authors
- Browne, A. J., Varcoe, C. M., Wong, S. T., Smye, V. L., & Khan, K. B.
- Affiliations
- University of British Columbia (CA)
- Corresponding author
- Browne, Annette J.
- Venue
- Ethnicity & Health
- Publisher
- Informa UK Limited
- Published
- 2013-08-02
- Volume
- 19
- Issue
- 2
- Pages
- 240-254
- ISSN
- 1355-7858 (ISSN-L)
- 1465-3419
- OpenAlex
- W2020478017
- Cited by
- 20
- References
- 40
- Citations by year
- 2025: 1 · 2024: 2 · 2023: 1 · 2022: 7 · 2021: 2 · 2019: 2 · 2018: 4 · 2016: 1
- FWCI
- 1.03
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Ethnicity and Health (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Michael Smith Health Research BC
- Topics
- Social Sciences › Sociology and Political Science › Cultural Competency in Health Care
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Race, Genetics, and Society
- Social Sciences › Sociology and Political Science › Racial and Ethnic Identity Research
- Keywords
- ethnicity data, health disparities, health care inequities, data quality, racialized communities, structural discrimination, ethnocultural identity, data linkage, patient perspectives, Canada
- MeSH terms
- Canada, Data Collection, Ethnicity, Humans, Interviews as Topic, Minority Groups, Reproducibility of Results, Focus Groups, Qualitative Research, Health Status Disparities, Healthcare Disparities, Social Discrimination
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