JMIR Publications

ABSTRACT

Background:

Data standards for collecting, storing, and indexing information on classification of social determinants of health, such as race and ethnicity, have significant ramifications in health equity research.

Objective:

We describe challenges encountered when working with multiple-race assessment in large health surveys in the Eastern Caribbean Health Outcomes Research Network (ECHORN), a collaborative of Barbados, Puerto Rico, Trinidad and Tobago, and U.S. Virgin Islands.

Methods:

We examined the data standards guiding research studies on race/ethnicity data collection and indexing, including Office of Management of Budget Directive 15 (OMB) and National Library Medicine’s Medical Subject Headings (MeSH), respectively, for a cohort study with multi-racial populations.

Results:

Among 1,211 participants in the ECHORN cohort study, 13% (n=117) selected Caribbean; 7.6% (n=58), Puerto Rican or Boricua; and 10% (n=122), multi-racial category. Over 18% selected two or more categories, with 15.2% (n=184) selecting two, and 2.6% (n=32) selecting three or more categories. With aggregation of ECHORN data into OMB categories, 24% of the participants are placed in the “more than one race” category. Moreover, searching for and retrieving articles related to multi-racial populations involves complicated keyword and synonyms searches and varies in number of articles retrieved (including terms such as biracial (n=863 articles), mixed race (n=6181articles), or multiracial (n=871 articles)).

Conclusions:

This analysis exposes the fundamental informatics challenges with current data standards, from data collection to indexing, that complicate meaningful collection and dissemination of accurate information for diverse and marginalized populations. Current standards should reflect the science of measuring race/ethnicity and the need for multi-disciplinary teams to improve evolving standards across the data lifecycle.