TABLE 3.
Validation of the Medicare EDB and RTI race codes compared to beneficiary self‐reported race and Hispanic ethnicity, among survey respondents self‐reporting one race category only (N = 1,013,423).
| Classification by EDB race code a | Classification by RTI race code a | |||||||
|---|---|---|---|---|---|---|---|---|
| Sensitivity b | Specificity c | PPV d | NPV e | Sensitivity b | Specificity c | PPV d | NPV e | |
| White | 98.0% | 92.6% | 89.8% | 69.5% | 97.0% | 92.0% | 97.6% | 93.4% |
| Black | 98.0% | 99.8% | 92.5% | 99.1% | 97.6% | 99.7% | 95.2% | 99.4% |
| Hispanic | 28.6% | 91.0% | 96.1% | 99.8% | 86.5% | 98.1% | 90.8% | 98.8% |
| AANHPI | 60.7% | 98.6% | 92.4% | 99.8% | 77.9% | 99.2% | 89.5% | 99.7% |
| AIAN | 38.7% | 99.8% | 66.5% | 99.9% | 38.4% | 99.8% | 67.4% | 99.9% |
| Other | 5.1% | 99.5% | 1.4% | 98.2% | 3.0% | 99.5% | 2.0% | 99.3% |
Note: Data Sources: Data linked between Medicare Master Beneficiary Summary File (MBSF), Medicare Advantage Health Outcomes Survey (HOS), and the Medicare Advantage Consumer Assessment of Healthcare Providers and Systems (CAHPS) from 2015 to 2017.
Abbreviations: AANHPI, non‐Hispanic Asian American or Native Hawaiian Pacific Islander; AIAN, non‐Hispanic American Indian Alaska Native; EDB, Enrollment Database; NPV, negative predictive value; PPV, positive predictive value; RTI, Research Triangle Institute; N, number of beneficiaries; White, non‐Hispanic White; Black, non‐Hispanic Black; Hispanic, Hispanic any race; Other, non‐Hispanic Other race.
We take a strict interpretation of the Medicare race codes and validate the predictive performance of the EDB and RTI race codes for each race/ethnicity category by measuring how accurately a beneficiary in our study sample is classified between the six multiple categories. See eTable 3 (Supplemental material) for the full confusion matrices used to generate these metrics.
Sensitivity is defined as true positives/(true positives + false negatives).
Specificity is defined as true negatives/(true negatives + false positives).
Positive predictive value is defined as true positives/(true positives + false positives).
Negative predictive value is defined as true negatives/(true negatives + false negatives).