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

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 aggregat

SUBMITTER: Haas A 

PROVIDER: S-EPMC6338295 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature