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Related Experiment Videos

Methodologic implications of allocating multiple-race data to single-race categories.

Jennifer D Parker1, Diane M Makuc

  • 1Division of Health Utilization and Analysis, National Center for Health Statistics, Hyattsville, MD 20782, USA.

Health Services Research
|April 13, 2002
PubMed
Summary

Comparing race data collection methods shows minimal impact on employer-sponsored health insurance estimates for most groups. However, American Indian/Alaska Native health insurance data comparability is affected by the 1977 (OMB-15) versus 1997 (OMB) standards.

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Area of Science:

  • Health Services Research
  • Health Disparities
  • Biostatistics

Background:

  • The U.S. Office of Management and Budget (OMB) revised its race data collection standards in 1997.
  • Comparing data collected under the 1977 (OMB-15) and 1997 OMB standards is crucial for accurate health services research.

Purpose of the Study:

  • To compare race data collected under the 1977 OMB-15 directive with data collected under the revised 1997 OMB standard.
  • To assess the impact of different race data allocation methods on health insurance estimates.

Main Methods:

  • Analysis of secondary data from the 1993-95 National Health Interview Surveys.
  • Calculation of race-specific employer-sponsored health insurance estimates using proposed OMB allocation methods.
  • Examination of estimates for overall populations and subgroups: children, those in poverty, and Hispanics.

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Main Results:

  • Race distributions differed across methods, but employer-sponsored health insurance estimates were generally similar.
  • The American Indian/Alaska Native group exhibited the most variation in health insurance estimates between methods.

Conclusions:

  • Employer-sponsored health insurance estimates for American Indian/Alaska Natives are not comparable between the 1977 OMB-15 and 1997 OMB standards.
  • Allocation method choice has minimal impact on insurance estimates for other racial/ethnic groups.
  • Further research is needed to evaluate these methods for other health service measures.