Department of Health Services, Policy and Practice, Brown University School of Public Health, Providence, Rhode Island, USA.
Health Serv Res. 2023 Oct;58(5):1045-1055. doi: 10.1111/1475-6773.14197. Epub 2023 Jun 25.
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 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.
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.
评估医疗保险数据中种族/民族编码的有效性,以及医疗保险优势受益人的种族/民族分类错误是否会导致结果报告存在偏差。
在这项针对医疗保险优势受益人的全国性研究中,我们分析了来自健康结果调查(HOS)和医疗保健提供者和系统消费者评估(CAHPS)的个人水平数据、医疗保险主受益摘要文件(MBSF)中的种族/民族代码,以及来自 2015 年至 2017 年的医疗保险提供者分析和审查(MedPAR)文件中的结果。
我们使用受益人的自我报告种族/民族来验证医疗保险登记数据库(EDB)和研究三角研究所(RTI)的种族/民族代码。我们测量了 EDB 和 RTI 代码与自我报告相比的敏感性、特异性、阳性预测值和阴性预测值。对于结果,我们比较了年化住院、30 天和 90 天再入院率。
数据收集/提取方法:完成 HOS 或 CAHPS 调查的医疗保险优势受益人的数据与 MBSF 和 MedPAR 文件相关联。对多民族和单一民族的自我报告受益人的有效性进行了评估。
对于参加医疗保险优势计划的受益人群,EDB 和 RTI 种族/民族代码在识别非西班牙裔白人和黑人受益人群方面具有较高的有效性,但对自我报告为西班牙裔任何种族的受益人群(EDB:28.3%,RTI:85.9%)或非西班牙裔亚裔或夏威夷原住民和太平洋岛民(EDB:56.1%,RTI:72.1%)的敏感性较低。只有 8.7%的自我报告为非西班牙裔美洲印第安人/阿拉斯加原住民的受益人群被 Medicare 代码正确识别,这导致年化住院率报告不足(EDB:31.5%,RTI:31.6%,而自我报告:34.6%)。我们发现,西班牙裔受益人群的 30 天再入院率因种族类别而异,而 Medicare 种族/民族编码无法衡量这一点。
目前的医疗保险种族/民族代码对更有可能选择多种族身份的非西班牙裔 AIAN 受益人群进行了错误分类和结果偏差。需要对种族/民族类别进行修订,以更好地反映医疗保险优势受益人群中的多种族/族裔身份。