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Emerging Issues

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Emerging Issues

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  1. Emerging Issues Olivia Carter-Pokras, Ph.D. HHS Office of Minority Health

  2. Key Questions • Should we collect racial/ethnic data? • How should racial/ethnic data be collected? Reported? • What do observed differences mean? • How do we monitor these differences?

  3. Key Questions • Should we collect racial/ethnic data?

  4. Why do we need racial & ethnic data? • Monitor trends over time at national, state and local levels (growing socioeconomic inequality & worsening health with acculturation among Hispanics) • Evaluate programs • Understand etiologic process and identify points of intervention • Monitor and enforce Civil Rights Act

  5. NIH Policy on Reporting Race and Ethnicity Data:Subjects in Clinical Research (8/8/01) • Collection of this information and use of these categories is required for research that meets NIH definition of clinical research. • Applies to new applications and proposals, annual progress reports, competing continuation applications, competing supplement applications for research grants, contracts and intramural projects as of 1/10/02.

  6. Quality of Care Across Entire System • Do all parts of the population have access to needed and appropriate services? • Do services meet or exceed their expectations? • Is their health status improving?

  7. Continuing concerns regarding use of genetic tests--I • From 1960’s until 1993, Lawrence Berkeley National Laboratory secretly tested black employees for sickle cell anemia until workers filed lawsuit that resulted in 1998 decision by US Ninth Circuit Court of Appeals that preemployment testing for genetic illness (e.g, sickle cell anemia) violates ADA unless employer can prove it had a clear business-related reason for conducting the tests.

  8. Continuing concerns regarding use of genetic tests--II • US Military finally allowed African-Americans to train as pilots if genetic tests showed a trait for sickle cell anemia after class action suit delivered evidence that disproved the claim that pilots with this trait were likely to pass out when deprived of oxygen

  9. Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care (IOM, 2002) • 7-1. Collect and report data on healthcare access and utilization by patient’s race, ethnicity, socioeconomic status, and where possible, primary language. • 7-2. Include measures of racial and ethnic disparities in performance measurement. • 7-3 Monitor progress toward the elimination of healthcare disparities.

  10. Unequal Treatment--II • 7-4. Report racial and ethnic data by OMB categories, but use subpopulation groups where possible.

  11. Concerns Regarding Collection of Racial/Ethnic Data • Confusion regarding legality of collecting information on racial/ethnic data • Potential misuse or misinterpretation of data • Lack of standards or enforcement • Technical difficulties in collecting or using data • Confidentiality/privacy

  12. Racial Privacy Initiative • Ward Connerly has sponsored the Racial Privacy Initiative (RPI), a California Ballot initiative slated for the November 2002 general election. • RPI would prohibit state & local governments, public universities & school districts from collecting/using information about race/ethnicity/color/national origin.

  13. Key Questions • How should racial/ethnic data be collected? Reported?

  14. How Collected? • Self-report (e.g., household interview) • Report by proxy (e.g., mailed questionnaire) • Observation (e.g., funeral director) • Linkage to other source (e.g., linked infant birth-death files)

  15. Collection Issues • Although Federal agency standards exist for racial/ethnic data, collection is not generally required by Federal government • HHS October 1997 inclusion policy for racial and ethnic data only covers HHS maintained data collection systems

  16. HHS Directory of Health and Human Services Data Resources http://aspe.os.dhhs.gov/ datacncl/datadir

  17. Minimum Categories For Race: • American Indian or Alaska Native • Asian • Native Hawaiian or other Pacific Islander • Black or African American • White

  18. Minimum Categories for Ethnicity • Hispanic or Latino • Not Hispanic or Latino

  19. US Census 2000 United States Census 2000, US Department of Commerce, Bureau of the Census

  20. Changes to Federal Standards • Recommend Self-Identification • Recommend 2 separate questions on race and ethnicity with ethnicity first • Allow identification of >1 race • “Asian”; “Native Hawaiian/Pacific Islanders” • “Hispanic or Latino”; “Black or African American” • Can identify all Hispanics

  21. Question Wording? Categories? • OMB standards are MINIMUM standards, many collect information on subgroups • Can be open-ended (e.g., death certificate), card with list of categories for in-person interview, list of categories for mailed or telephone questionnaire or form • OMB clearance & implementation date for new standard are opportunities to update

  22. Key Issues • How should racial/ethnic data be reported?

  23. Reporting of Redistricting File Data on Race: 63 categories • White alone • Black or African American alone • American Indian or Alaska Native alone • Asian alone • Native Hawaiian and Other Pacific Islander alone • Some other race alone • 57 combinations of these six categories

  24. Reporting of Race Data for Demographic Profiles: 7 categories • White alone • Black or African American alone • American Indian or Alaska Native alone • Asian alone • Native Hawaiian and Other Pacific Islander alone • Some other race alone • Two or more races

  25. Guidance on Aggregation and Allocation of Data on Race for Use in Civil Rights Monitoring and Enforcement OMB (BULLETIN NO. 00-02) -I • Aggregation • five single race categories • four double race combinations • American Indian/Alaska Native and White • Asian and White • Black/African American and White • AI/AN and Black/African American • other combinations that rep. >1% of pop. in a jurisdiction

  26. Guidance on Aggregation and Allocation of Data on Race for Use in Civil Rights Monitoring and Enforcement OMB (BULLETIN NO. 00-02) -II • Allocation • Responses in the five single race categories are not allocated. • Responses that combine one minority race and white are allocated to the minority race.

  27. Guidance on Aggregation and Allocation of Data on Race for Use in Civil Rights Monitoring and Enforcement OMB (BULLETIN NO. 00-02) -III • Allocation (continued) • Responses that include >2 minority races: • If the enforcement action is in response to a complaint, allocate to the race that the complainant alleges the discrimination was based on. • If the enforcement action requires assessing disparate impact or discriminatory patterns, analyze the patterns based on alternative allocations to each of the minority groups.

  28. Two or More Races Population: 2000 (Census, 2001) • 6.8 million people or 2.4% reported more than one race. • Of these, 93% reported exactly two races. • 40% lived in the West, 27% in the South, 18% in the Northeast, and 15% in the Midwest; 64% in 10 states • More likely to be under 18 (42% v.s. 25%)

  29. Who reported more than one race? (Census, 2001) • 2.5% of Whites* • 4.8% of Blacks* • 13.9% of Asians* • 17.1% of Some other race* • 39.9% of Amer. Indian & Alaska Natives* • 54.4% of Native Hawaiians & Other Pacific Islanders* • *Alone or in combination

  30. Comparison with Data Collected Under Old Standard • Census Quality Survey was conducted in summer of 2001 of ~50,000 households to produce a data file that will assist users in developing ways to make comparisons between Census 2000 data on race, where respondents were asked to report one or more races, and data on race from other sources that asked for only a single race.

  31. Comparison--II • OMB issued provisional guidance on the implementation of the 1997 standards for federal data on race and ethnicity in January 2001. • National Center for Health Statistics and states have engaged in discussions in how to present multiracial data for vital events.

  32. % No Health Insurance for Bridge Tabulation: NHIS 1993-5 • White 13.4% (13.4%-13.5%) • Black 18.1% (18%) • AIAN 32.2% (26.7%-32.3%) • API 18.9% (18.2%-18.9%)

  33. Percent Distribution of Race for Bridge Tabulation: NHIS, 1993-5 • White 80.3% (79.4%-80.8%) • Black 12.7% (12.7%-12.9%) • AIAN 0.9% (0.8%-1.8%) • API 3.5% (3.4%-3.8%)

  34. Deterministic Whole Assignment • Largest Group: Responses with >=2 racial groups are assigned into group with largest number as single race. • Plurality: Responses are assigned based on data from the National Health Interview Survey (NHIS). All multiracial responses are assigned to group with the highest proportion of responses on the NHIS follow-up question about main race (one race with which they most closely identify).

  35. Deterministic Fractional Assignment • Deterministic Equal Fractions--Assigns each of the multiple responses to equal fractions to each racial group identified. • Deterministic NHIS Fractions--Assigns responses by fractions to each racial group identified, with the fractions drawn from empirical results from the NHIS.

  36. Strategies for Users--I • If don’t need to bridge data, leave multiple racial responses as separate categories; avoid reallocating back to single racial categories. • Plurality method or one of the Fractional Allocation methods provided the closest approximations to a past distribution. SOURCE: Sharon M. Lee, Using the New Racial Categories in the 2000 Census, Prepared for the Anne E. Casey Foundation. March 2001.

  37. Strategies for Users--II • If interested in particular racial category, choice of method depends on whether user wants to err on the side of inclusion or exclusion. • Choice of bridging method depends on the topic or characteristic examined (e.g., unemployment rate and labor force participation rate by race) SOURCE: Sharon M. Lee, Using the New Racial Categories in the 2000 Census Prepared for the Anne E. Casey Foundation. March 2001.

  38. Strategies for Users--III • If interested in numerically small population and want to maximize numbers for analysis, Smallest Group method and Largest Group Other than White method would yield larger counts for the category--this could raise problems of misclassification of race for a certain proportion of responses. SOURCE: Sharon M. Lee, Using the New Racial Categories in the 2000 Census Prepared for the Anne E. Casey Foundation. March 2001.

  39. Strategies for Users--IV • Another strategy is to collect race directly from clients and use findings for bridging purposes (e.g., National Health Interview Survey asks a followup question on main race). SOURCE: Sharon M. Lee, Using the New Racial Categories in the 2000 Census Prepared for the Anne E. Casey Foundation. March 2001.

  40. Bottom Line: • There are many many possible bridging methods. • »There is no right answer. What works best will depend on the characteristics of the populations, on the purposes of the analyses, and on other factors. • »There will be problems no matter what. • Lou McClelland, CU Boulder Planning, Budget and Analysis, March 2001

  41. »Data users will have to make educated choices and understand the rationale for their choice. »As data users negotiate the transition to the new standards of racial reporting, it will help to remain flexible, to stay focused on the purpose of racial data, and to remember that there is no single best option for all purposes and data users. Sharon M. Lee, Using the New Racial Categories in the 2000 Census, Prepared for the Anne E. Casey Foundation. March 2001.

  42. Key Questions • What do observed differences mean?

  43. Socioeconomic Status (SES) is Powerful Determinant of Health • Inverse gradient between individual & household SES, & morbidity & mortality is well established. • Association of SES and health has been found in different populations, using different indicators of SES and different health outcomes (e.g., Dubois, 1899). • Impact of income is strongest at lowest levels (not linear).

  44. Unexplained Health Disparities Could Reflect: • Inadequate control for differences in current social class • Failure to consider the effects of social class in earlier life (including childhood) • Intergenerational effects of social class • Influences of other variables not considered (e.g., psychosocial stress, nutrition, noneconomic aspects of racism)

  45. Infant Mortality, LBW & SES • Infants of Black college-educated mothers had higher infant mortality due to higher rates of LBW (Schoendorf, 1992). • Poor black and poor white mothers did not differ significantly in their risk of having a LBW baby when poverty was measured when the women were teenagers and again when pregnancy began (Starfield, 1991).

  46. Key Questions • How do we monitor these differences?

  47. Disparity Definitions: • NC 2010: differences in health status among distinct segments of the population including differences that occur by gender, race or ethnicity, education or income, disability or living in various geographic localities.

  48. Disparity Definitions--II • WA State Board of Health: disproportionate burden of disease, disability and death among a particular population or group when compared to the proportion of the population. • NIH: differences in the incidence, prevalence, mortality, and burden of diseases and other adverse health conditions that exist among specific population groups in the United States.

  49. Disparity Definitions--III • IOM’s Unequal Treatment: Disparities in healthcare are racial or ethnic differences in the quality of healthcare that are not due to access-related factors or clinical needs, preferences and appropriateness of intervention.