The validity of race and ethnicity in enrollment data for Medicare beneficiaries.

Many analyses of racial/ethnic differences in use of services and quality of care under the Medicare program rely on the race/ethnicity variable in Medicare administrative files, linking them to measures of utilization and guideline-recommended care from claims data and Medicare quality measures to assess disparities in health and health care (Ayanian et al. 1993; Guadagnoli et al. 1995; Schneider, Zaslavsky, and Epstein 2002; Virnig et al. 2002, 2004; McBean et al. 2003; Trivedi et al. 2005, 2006). Because current self-report is commonly accepted as defining racial and ethnic identity (Ulmer et al. 2009), the validity of Medicare's administrative data relative to self-reported race/ethnicity is of critical importance to the interpretation of study results. As described by Arday et al. (2000) and McBean (2006), racial/ethnic variables in the Medicare Enrollment Database (EDB) were originally based on information from the Master Beneficiary Record of the Social Security Administration (SSA), which until 1980 used only the categories “White,” “Negro,” or “Other” (Scott 1999). These categories were expanded in SSA files in 1980 and in the Medicare EDB in 1994, but there have been only limited opportunities to update data for the current cohort of beneficiaries, most of whom would have registered with SSA before 1980. SSA race values for beneficiaries who completed new SS-5 registration forms to report a change in SSA status were incorporated into Medicare files in 1994, 1997, and annually since 2000, and since 1999 the Indian Health Service has provided the Medicare system with information on those it serves. The Centers for Medicare and Medicaid Services (CMS) also conducted a mail survey in 1997 targeted to beneficiaries identified as other or unknown race or with Spanish surnames. These measures have improved identification of groups not identified in the pre-1980 data, but substantial gaps remain. Furthermore, even the current coding used by SSA and CMS falls short of the level of detail mandated under the 1997 Office of Management and Budget (OMB) standards (Office of Management and Budget 1997) that are now used in federally sponsored surveys by combining Asians and Pacific Islanders and disallowing multiple racial/ethnic identifications. A pioneering study by Arday et al. (2000) examined the relationship between race/ethnicity in administrative data and contemporary self-report data from the Medicare Current Beneficiary Survey (MCBS). Arday et al. found that the EDB had poor sensitivity for groups other than Whites and Blacks, although it was improved by updates over the 1990s. This study had limited precision for estimates involving smaller racial/ethnic groups, due to the modest size of the MCBS survey. Furthermore, the analysis was limited to tabulations of EDB by survey race/ethnicity classifications but did not analyze other characteristics of the groups falling into various cells of this cross-classification. More recent studies by Waldo (2004) and Eicheldinger and Bonito (2008) have confirmed these findings. Underascertainment of a minority group may bias estimates for both that group and the majority White group to which some of its members are mistakenly assigned or vice versa. The effect of a given error on group estimates, however, would generally be greater for estimates concerning a relatively small minority than for the much larger White group. In an analysis of racial/ethnic disparities using Medicare data on health care, we might ideally compare groups defined by a recent self-report of racial/ethnic identity using the more refined categories currently mandated under the 1997 OMB standards. However, analyses using administrative data are limited to the categories in use at the time racial/ethnic identification was most recently reported to the SSA or CMS. To evaluate the relationship between these two variables, we need a dataset that contains both types of information, such as the Consumer Assessments of Healthcare Providers and Systems (CAHPS) surveys. These surveys have been conducted in Medicare among managed care (currently Medicare Advantage [MA]) beneficiaries since 1998 and among fee-for-service (traditional Medicare or FFS) beneficiaries since 2001; the cumulative sample now exceeds 2 million respondents. While the primary purpose of the survey is to collect information on the quality of services provided, it also collects demographic data, including self-identified race/ethnicity according to current OMB standards. The main objective of this study is to use CAHPS data to investigate the relationships between race/ethnicity as reported in administrative files and by self-report, extending the results of Arday et al. (2000). We first assess the concordance of EDB and CAHPS race/ethnicity variables. We also investigate the association of EDB race/ethnicity and survey responses, conditional on self-reported race/ethnicity, to better characterize the groups that are identified in the EDB and provide insight into the interpretation of patterns of health and health care detected in analyses that rely on the EDB data, thereby illuminating their utility for research on disparities.