From the Clinical Economics Research Unit (K.A.S., C.K.T.), the Lombardi Cancer Center (J.F.K.), the Division of General Internal Medicine (S.S.), the Division of Cardiology (B.J.G.), and the Department of Medicine (J.M.E.), Georgetown University Medical Center, Washington, D.C.; the Center for Clinical Epidemiology and Biostatistics and the Department of Biostatistics and Epidemiology (J.A.B.), and the Division of General Internal Medicine (S.W.), University of Pennsylvania School of Medicine, Philadelphia; Interactive Drama, Bethesda, Md. (W.H., R.D.); and the RAND Health Program, Santa Monica, Calif. (J.E.B., J.J.E.). William Ayers, M.D., Georgetown University Medical Center, Washington, D.C., was also an author.
When the proposed project involves human subjects and/or NIH-defined clinical research, the committee will evaluate the proposed plans for the inclusion (or exclusion) of individuals on the basis of sex/gender, race, and ethnicity, as well as the inclusion (or exclusion) of children to determine if it is justified in terms of the scientific goals and research strategy proposed. For additional information on review of the Inclusion section, please refer to the .
One assumption underlying self-identified race and ethnicity data collection is that the categories and designations are recognized and accepted by the populations questioned (CDC, 1993; Lin and Kelsey, 2000). Improving the likelihood that respondents can identify with the races and ethnicities offered as response options is therefore essential to the quality of the data collected. Challenges in capturing accurate and reliable OMB-level data include the lack of detailed categories to which individuals can relate and the format of the questions used to elicit Hispanic ethnicity.
A wide range of cultures, languages, and health-related behaviors are encompassed by each of the six OMB race and Hispanic ethnicity categories. For example, the Asian category blurs ancestry distinctions and vast cultural and geographic diversity (Holup et al., 2007). As a result, the Asian race identification may not resonate with all individuals of Pakistani, Vietnamese, or Filipino descent, for example, who might prefer to self-identify according to their ancestry (see ) (Laws and Heckscher, 2002).
Andrew J. Schoenfeld, Renuka Tipirneni, James H. Nelson, James E. Carpenter, Theodore J. Iwashyna. . (2014) The Influence of Race and Ethnicity on Complications and Mortality After Orthopedic Surgery. 52, 842-851.
Lenny López, Alexander R. Green, Aswita Tan-McGrory, Roderick S. King, Joseph R. Betancourt. . (2011) Bridging the Digital Divide in Health Care: The Role of Health Information Technology in Addressing Racial and Ethnic Disparities. 37:10, 437-445.
Response options: White; Black/African American; Indian (American); Alaska Native; Guamanian; Samoan; Other Pacific Islander; Asian Indian; Chinese; Filipino; Japanese; Korean; Vietnamese; Other Asian; Some other race; Refused; Don’t know
All possible combinations of just the six OMB categories results in 64 combinations. Introducing granular ethnicities would drastically increase the possible combinations.
This chapter has explained the subcommittee’s rationale for recommending continued use of the OMB race and Hispanic ethnicity categories, supplemented by locally relevant granular ethnicity categories. The health and health care needs of all racial and ethnic groups can be best addressed through comprehensive strategies that recognize the importance of documenting and addressing variations among and within the locally relevant groups, and that further provide procedures for aggregating data to provide regional or national profiles.
Lisa Vanderlinden. . (2011) Treating Ethnic Others: Cultural Sensitivity and Minority Stereotypes at a German Fertility Clinic. 70, 253-264.
shows models for the collection of data on race, Hispanic ethnicity, and granular ethnicity, taking into account that the capacity of information systems may limit the number of questions that can be asked. This report emphasizes the importance of collecting granular ethnicity data in addition to the OMB race and Hispanic ethnicity questions. Using the approach preferred by OMB of asking two separate questions about Hispanic ethnicity and race and then asking additionally about granular ethnicity requires collecting three separate variables, regardless of whether through paper-based or electronic collection modes (Model A). For organizations constrained to two data fields, one collection field would be used to collect responses to the OMB combined race and Hispanic ethnicity question, followed by a second collection field for granular ethnicity data (Model B).
Issues addressed should include use of the one- or two-question format for race and Hispanic ethnicity, whether all individuals understand and identify with the OMB race and Hispanic ethnicity categories, and the increasing size of populations identifying with “Some other race.”
Recommendation 3-3: To determine the utility for health and health care purposes, HHS should pursue studies on different ways of framing the questions and related response categories for collecting race and ethnicity data at the level of the OMB categories, focusing on completeness and accuracy of response among all groups.
Organizations may also want to use codes for tracking the current response status of individuals from whom they have attempted to collect race and ethnicity data, indicating unavailable (no response), declined (refused to answer), or unknown (respondent does not know) for those who fail to select a category.