Assessing the validity of race and ethnicity coding in administrative Medicare data for reporting outcomes among Medicare advantage beneficiaries from 2015 to 2017

39Citations
Citations of this article
8Readers
Mendeley users who have this article in their library.

Your institution provides access to this article.

Abstract

Objective: To assess the validity of race/ethnicity coding in Medicare data and whether misclassification errors lead to biased outcome reporting by race/ethnicity among Medicare Advantage beneficiaries. Data Sources and Study Setting: In this national study of Medicare Advantage beneficiaries, we analyzed individual-level data from the Health Outcomes Survey (HOS) and the Consumer Assessment of Healthcare Providers and Systems (CAHPS), race/ethnicity codes from the Medicare Master Beneficiary Summary File (MBSF), and outcomes from the Medicare Provider Analysis and Review (MedPAR) files from 2015 to 2017. Study Design: We used self-reported beneficiary race/ethnicity to validate the Medicare Enrollment Database (EDB) and Research Triangle Institute (RTI) race/ethnicity codes. We measured the sensitivity, specificity, and positive and negative predictive values of the Medicare EDB and RTI codes compared to self-report. For outcomes, we compared annualized hospital admission, 30-day, and 90-day readmission rates. Data Collection/Extraction Methods: Data for Medicare Advantage beneficiaries who completed either the HOS or CAHPS survey were linked to MBSF and MedPAR files. Validity was assessed for both self-reported multiracial and single-race beneficiaries. Principal Findings: For beneficiaries enrolled in Medicare Advantage, the EDB and RTI race/ethnicity codes have high validity for identifying non-Hispanic White or Black beneficiaries, but lower sensitivity for beneficiaries self-reported Hispanic any race (EDB: 28.3%, RTI: 85.9%) or non-Hispanic Asian American or Native Hawaiian Pacific Islander (EDB: 56.1%, RTI: 72.1%). Only 8.7% of beneficiaries self-reported non-Hispanic American Indian Alaska Native are correctly identified by either Medicare code, resulting in underreported annualized hospitalization rates (EDB: 31.5%, RTI: 31.6% vs. self-report: 34.6%). We find variation in 30-day readmission rates for Hispanic beneficiaries across race categories, which is not measured by Medicare race/ethnicity coding. Conclusions: Current Medicare race/ethnicity codes misclassify and bias outcomes for non-Hispanic AIAN beneficiaries, who are more likely to select multiple racial identities. Revisions to race/ethnicity categories are needed to better represent multiracial/ethnic identities among Medicare Advantage beneficiaries.

Cite

CITATION STYLE

APA

Huang, A. W., & Meyers, D. J. (2023). Assessing the validity of race and ethnicity coding in administrative Medicare data for reporting outcomes among Medicare advantage beneficiaries from 2015 to 2017. Health Services Research, 58(5), 1045–1055. https://doi.org/10.1111/1475-6773.14197

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free