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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.
Afiliação
  • Wang K; Equity Research and Innovation Center, General Internal Medicine, Yale School of Medicine, New Haven, CT, United States.
  • Grossetta Nardini H; Center for Medical Informatics, Yale School of Medicine, New Haven, CT, United States.
  • Post L; Harvey Cushing/John Hay Whitney Medical Library, Yale School of Medicine, New Haven, CT, United States.
  • Edwards T; Buehler Center for Health Policy and Economics, Feinberg School of Medicine, Chicago, IL, United States.
  • Nunez-Smith M; Division of Epidemiology, Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, United States.
  • Brandt C; Equity Research and Innovation Center, General Internal Medicine, Yale School of Medicine, New Haven, CT, United States.
J Med Internet Res ; 22(7): e14591, 2020 07 20.
Article em En | MEDLINE | ID: mdl-32706693
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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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Padrões de Referência / Etnicidade / Coleta de Dados / Grupos Raciais / Medicina de Precisão Tipo de estudo: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: J Med Internet Res Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Padrões de Referência / Etnicidade / Coleta de Dados / Grupos Raciais / Medicina de Precisão Tipo de estudo: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: J Med Internet Res Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos