Validity of Race and Ethnicity Codes in Medicare Administrative Data Compared With Gold-standard Self-reported Race Collected During Routine Home Health Care Visits

Med Care. 2020 Jan;58(1):e1-e8. doi: 10.1097/MLR.0000000000001216.

Abstract

Background: Misclassification of Medicare beneficiaries' race/ethnicity in administrative data sources is frequently overlooked and a limitation in health disparities research.

Objective: To compare the validity of 2 race/ethnicity variables found in Medicare administrative data [enrollment database (EDB) and Research Triangle Institute (RTI) race] against a gold-standard source also available in the Medicare data warehouse: the self-reported race/ethnicity variable on the home health Outcome and Assessment Information Set (OASIS).

Subjects: Medicare beneficiaries over the age of 18 who received home health care in 2015 (N=4,243,090).

Measures: Percent agreement, sensitivity, specificity, positive predictive value, and Cohen κ coefficient.

Results: The EDB and RTI race variable have high validity for black race and low validity for American Indian/Alaskan Native race. Although the RTI race variable has better validity than the EDB race variable for other races, κ values suggest room for future improvements in classification of whites (0.90), Hispanics (0.87), Asian/Pacific Islanders (0.77), and American Indian/Alaskan Natives (0.44).

Discussion: The status quo of using "good-enough for government" race/ethnicity variables contained in Medicare administrative data for minority health disparities research can be improved through the use of self-reported race/ethnicity data, available in the Medicare data warehouse. Health services and policy researchers should critically examine the source of race/ethnicity variables used in minority health and health disparities research. Future work to improve the accuracy of Medicare beneficiaries' race/ethnicity data should incorporate and augment the self-reported race/ethnicity data contained in assessment and survey data, available within the Medicare data warehouse.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Aged
  • Aged, 80 and over
  • Ethnicity / statistics & numerical data*
  • Female
  • Health Status Disparities
  • Healthcare Disparities
  • Home Care Services / statistics & numerical data*
  • Humans
  • Male
  • Medicare / statistics & numerical data*
  • Outcome Assessment, Health Care
  • Predictive Value of Tests
  • Racial Groups / statistics & numerical data*
  • Reproducibility of Results
  • Self Report / statistics & numerical data*
  • Sensitivity and Specificity
  • United States