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Information Loss in Harmonizing Granular Race and Ethnicity Data: Descriptive Study of Standards

BACKGROUND: Data standards for race and ethnicity have significant implications for health equity research. OBJECTIVE: We aim to describe a challenge encountered when working with a multiple–race and ethnicity assessment in the Eastern Caribbean Health Outcomes Research Network (ECHORN), a research...

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Autores principales: Wang, Karen, Grossetta Nardini, Holly, Post, Lori, Edwards, Todd, Nunez-Smith, Marcella, Brandt, Cynthia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7399950/
https://www.ncbi.nlm.nih.gov/pubmed/32706693
http://dx.doi.org/10.2196/14591
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author Wang, Karen
Grossetta Nardini, Holly
Post, Lori
Edwards, Todd
Nunez-Smith, Marcella
Brandt, Cynthia
author_facet Wang, Karen
Grossetta Nardini, Holly
Post, Lori
Edwards, Todd
Nunez-Smith, Marcella
Brandt, Cynthia
author_sort Wang, Karen
collection PubMed
description BACKGROUND: Data standards for race and ethnicity have significant implications for health equity research. OBJECTIVE: We aim to describe a challenge encountered when working with a multiple–race and ethnicity assessment in the Eastern Caribbean Health Outcomes Research Network (ECHORN), a research collaborative of Barbados, Puerto Rico, Trinidad and Tobago, and the US Virgin Islands. METHODS: We examined the data standards guiding harmonization of race and ethnicity data for multiracial and multiethnic populations, using the Office of Management and Budget (OMB) Statistical Policy Directive No. 15. RESULTS: Of 1211 participants in the ECHORN cohort study, 901 (74.40%) selected 1 racial category. Of those that selected 1 category, 13.0% (117/901) selected Caribbean; 6.4% (58/901), Puerto Rican or Boricua; and 13.5% (122/901), the mixed or multiracial category. A total of 17.84% (216/1211) of participants selected 2 or more categories, with 15.19% (184/1211) selecting 2 categories and 2.64% (32/1211) selecting 3 or more categories. With aggregation of ECHORN data into OMB categories, 27.91% (338/1211) of the participants can be placed in the “more than one race” category. CONCLUSIONS: This analysis exposes the fundamental informatics challenges that current race and ethnicity data standards present to meaningful collection, organization, and dissemination of granular data about subgroup populations in diverse and marginalized communities. Current standards should reflect the science of measuring race and ethnicity and the need for multidisciplinary teams to improve evolving standards throughout the data life cycle.
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spelling pubmed-73999502020-08-17 Information Loss in Harmonizing Granular Race and Ethnicity Data: Descriptive Study of Standards Wang, Karen Grossetta Nardini, Holly Post, Lori Edwards, Todd Nunez-Smith, Marcella Brandt, Cynthia J Med Internet Res Original Paper BACKGROUND: Data standards for race and ethnicity have significant implications for health equity research. OBJECTIVE: We aim to describe a challenge encountered when working with a multiple–race and ethnicity assessment in the Eastern Caribbean Health Outcomes Research Network (ECHORN), a research collaborative of Barbados, Puerto Rico, Trinidad and Tobago, and the US Virgin Islands. METHODS: We examined the data standards guiding harmonization of race and ethnicity data for multiracial and multiethnic populations, using the Office of Management and Budget (OMB) Statistical Policy Directive No. 15. RESULTS: Of 1211 participants in the ECHORN cohort study, 901 (74.40%) selected 1 racial category. Of those that selected 1 category, 13.0% (117/901) selected Caribbean; 6.4% (58/901), Puerto Rican or Boricua; and 13.5% (122/901), the mixed or multiracial category. A total of 17.84% (216/1211) of participants selected 2 or more categories, with 15.19% (184/1211) selecting 2 categories and 2.64% (32/1211) selecting 3 or more categories. With aggregation of ECHORN data into OMB categories, 27.91% (338/1211) of the participants can be placed in the “more than one race” category. CONCLUSIONS: This analysis exposes the fundamental informatics challenges that current race and ethnicity data standards present to meaningful collection, organization, and dissemination of granular data about subgroup populations in diverse and marginalized communities. Current standards should reflect the science of measuring race and ethnicity and the need for multidisciplinary teams to improve evolving standards throughout the data life cycle. JMIR Publications 2020-07-20 /pmc/articles/PMC7399950/ /pubmed/32706693 http://dx.doi.org/10.2196/14591 Text en ©Karen Wang, Holly Grossetta Nardini, Lori Post, Todd Edwards, Marcella Nunez-Smith, Cynthia Brandt. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 20.07.2020. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Wang, Karen
Grossetta Nardini, Holly
Post, Lori
Edwards, Todd
Nunez-Smith, Marcella
Brandt, Cynthia
Information Loss in Harmonizing Granular Race and Ethnicity Data: Descriptive Study of Standards
title Information Loss in Harmonizing Granular Race and Ethnicity Data: Descriptive Study of Standards
title_full Information Loss in Harmonizing Granular Race and Ethnicity Data: Descriptive Study of Standards
title_fullStr Information Loss in Harmonizing Granular Race and Ethnicity Data: Descriptive Study of Standards
title_full_unstemmed Information Loss in Harmonizing Granular Race and Ethnicity Data: Descriptive Study of Standards
title_short Information Loss in Harmonizing Granular Race and Ethnicity Data: Descriptive Study of Standards
title_sort information loss in harmonizing granular race and ethnicity data: descriptive study of standards
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7399950/
https://www.ncbi.nlm.nih.gov/pubmed/32706693
http://dx.doi.org/10.2196/14591
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