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. 2019 Feb;54(1):13-23.
doi: 10.1111/1475-6773.13099. Epub 2018 Dec 3.

Imputation of race/ethnicity to enable measurement of HEDIS performance by race/ethnicity

Ann Haas  1 , Marc N Elliott  2 , Jacob W Dembosky  1 , John L Adams  3 , Shondelle M Wilson-Frederick  4 , Joshua S Mallett  2 , Sarah Gaillot  5 , Samuel C Haffer  6 , Amelia M Haviland  1   7
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Imputation of race/ethnicity to enable measurement of HEDIS performance by race/ethnicity

Ann Haas et al. Health Serv Res. 2019 Feb.

Abstract

Objective: To improve an existing method, Medicare Bayesian Improved Surname Geocoding (MBISG) 1.0 that augments the Centers for Medicare & Medicaid Services' (CMS) administrative measure of race/ethnicity with surname and geographic data to estimate race/ethnicity.

Data sources/study setting: Data from 284 627 respondents to the 2014 Medicare CAHPS survey.

Study design: We compared performance (cross-validated Pearson correlation of estimates and self-reported race/ethnicity) for several alternative models predicting self-reported race/ethnicity in cross-sectional observational data to assess accuracy of estimates, resulting in MBISG 2.0. MBISG 2.0 adds to MBISG 1.0 first name, demographic, and coverage predictors of race/ethnicity and uses a more flexible data aggregation framework.

Data collection/extraction methods: We linked survey-reported race/ethnicity to CMS administrative and US census data.

Principal findings: MBISG 2.0 removed 25-39 percent of the remaining MBISG 1.0 error for Hispanics, Whites, and Asian/Pacific Islanders (API), and 9 percent for Blacks, resulting in correlations of 0.88 to 0.95 with self-reported race/ethnicity for these groups.

Conclusions: MBISG 2.0 represents a substantial improvement over MBISG 1.0 and the use of CMS administrative data on race/ethnicity alone. MBISG 2.0 is used in CMS' public reporting of Medicare Advantage contract HEDIS measures stratified by race/ethnicity for Hispanics, Whites, API, and Blacks.

Keywords: HEDIS; Medicare; biostatistical methods; quality of care/patient safety (measurement); racial/ethnic differences in health and health care.

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