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

Medicare ethnicity health inequities minority health racial groups validation study

Journal

Health services research
ISSN: 1475-6773
Titre abrégé: Health Serv Res
Pays: United States
ID NLM: 0053006

Informations de publication

Date de publication:
10 2023
Historique:
pmc-release: 01 10 2024
medline: 7 9 2023
pubmed: 26 6 2023
entrez: 25 6 2023
Statut: ppublish

Résumé

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. 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. 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 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. 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. 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.

Identifiants

pubmed: 37356821
doi: 10.1111/1475-6773.14197
pmc: PMC10480088
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

1045-1055

Subventions

Organisme : NIMHD NIH HHS
ID : R21 MD016147
Pays : United States

Informations de copyright

© 2023 Health Research and Educational Trust.

Références

Med Care. 2020 Jan;58(1):e1-e8
pubmed: 31688554
Health Serv Res. 2012 Jun;47(3 Pt 2):1300-21
pubmed: 22515953
Am J Public Health. 1996 May;86(5):712-6
pubmed: 8629724
Health Serv Res. 2006 Aug;41(4 Pt 1):1482-500
pubmed: 16899020
Health Care Financ Rev. 2008 Spring;29(3):27-42
pubmed: 18567241
Health Serv Res. 2023 Oct;58(5):1045-1055
pubmed: 37356821
Healthc (Amst). 2022 Dec;10(4):100662
pubmed: 36270180
JAMA Health Forum. 2022 Jul 1;3(7):e221812
pubmed: 36218996
JAMA. 2006 Oct 25;296(16):1998-2004
pubmed: 17062863
Health Serv Res. 2006 Aug;41(4 Pt 1):1444-50
pubmed: 16899017
Health Care Financ Rev. 2000 Summer;21(4):107-16
pubmed: 11481739
Health Qual Life Outcomes. 2004 Jul 12;2:33
pubmed: 15248895
Med Care. 2022 Aug 1;60(8):556-562
pubmed: 35797457
Am J Public Health. 2005 Mar;95(3):379-81
pubmed: 15727961
Health Aff (Millwood). 2022 Aug;41(8):1153-1159
pubmed: 35914194
Health Aff (Millwood). 2021 Jun;40(6):945-950
pubmed: 34097525
Med Care Res Rev. 2021 Oct;78(5):616-626
pubmed: 32633665
Health Aff (Millwood). 2022 May;41(5):663-670
pubmed: 35500179
JAMA. 2021 Aug 17;326(7):628-636
pubmed: 34402828
Med Care. 2017 Dec;55(12):e170-e176
pubmed: 29135782
N Engl J Med. 2021 Feb 4;384(5):474-480
pubmed: 33406325
Med Care. 2022 May 1;60(5):351-356
pubmed: 35319520
Health Aff (Millwood). 2017 Jan 1;36(1):91-100
pubmed: 28069851
Health Serv Res. 2019 Feb;54(1):13-23
pubmed: 30506674

Auteurs

Andrew W Huang (AW)

Department of Health Services, Policy and Practice, Brown University School of Public Health, Providence, Rhode Island, USA.

David J Meyers (DJ)

Department of Health Services, Policy and Practice, Brown University School of Public Health, Providence, Rhode Island, USA.

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