Race and Ethnicity Modeling Applied to Linked Heath Data

Linked data enable robust analyses using variables from more than one source and can be used to validate those on either. The National Center for Health Statistics (NCHS) links survey and administrative data to expand the analytic utility of its surveys. The National Hospital Care Survey collects administrative claims or electronic health record (EHR) data on patients from participating hospitals. Reporting of race/ethnicity in these records is sparse and inconsistent. To support health equity research, we have modeled race/ethnicity using last name and geographic race/ethnicity frequencies from the 2010 Census data in a Bayesian framework. To evaluate the quality of imputations from this model, we make use of linked datasets from the NCHS data linkage program and compare the imputed values to those in administrative data. Further validation is made by applying the model to NCHS's National Health Interview Survey (NHIS). NHIS collects self-reported race/ethnicity, which is considered the gold standard. This presentation will describe the imputation methodology and validation methods used and will highlight how this method can be applied to other sources for health equity research.