Literature DB >> 31688554

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

Olga F Jarrín1,2, Abner N Nyandege2, Irina B Grafova3, XinQi Dong2, Haiqun Lin1.   

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.

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Year:  2020        PMID: 31688554      PMCID: PMC6904433          DOI: 10.1097/MLR.0000000000001216

Source DB:  PubMed          Journal:  Med Care        ISSN: 0025-7079            Impact factor:   3.178


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