Improving identification of Hispanic males in Medicare: use of surname matching.
OBJECTIVE
Medicare administrative and claims files maintained by the Centers for Medicare and Medicaid Services (CMS) are frequently used to examine racial and ethnic disparities in healthcare use. However, identification of Hispanic ethnicity for beneficiaries in the Medicare claims files is problematic, greatly limiting the use of these administrative data for examining race/ethnicity differences. This article reports on 2 studies assessing the effectiveness of a Hispanic surname match for improving the accuracy of race/ethnicity codes for elderly males in the Medicare data sets.


METHODS
Study 1 used survey data to compare a Medicare race code + Spanish surname composite indicator to self-identification as Hispanic. Study 2 used Medicare administrative files and U.S. Census 2000 data to identify how well the Medicare race code alone and the Medicare race code + Spanish surname composite indicator compared with estimates obtained from census data for 16 U.S. counties dispersed across 5 states.


RESULTS
Using self-identification as the gold standard, including the Spanish surname match increased accuracy for Hispanics and whites compared with the Medicare race code alone. The Spanish surname match also dramatically improved the Medicare code's estimation of elderly Hispanic and white males compared with county-level census data.


CONCLUSIONS
Augmenting the Medicare race code with a match to Spanish surnames yields substantial improvement in the identification of elderly Hispanic and white non-Hispanic male Medicare beneficiaries. Using surname information to supplement the Medicare race code could greatly enhance researchers' ability to examine healthcare equity.
Morgan
Robert O
RO
Houston Center for Quality of Care and Utilization Studies, Houston Veterans Affairs Medical Center, Houston, Texas 77030, USA. rmorgan@bcm.tmc.edu
Wei
Iris I
II
Virnig
Beth A
BA
D000368:Aged; D044383:Black People / Q000145:classification / Q000706:statistics & numerical data; D019352:Censuses; D014487:Centers for Medicare and Medicaid Services, U.S.; D003625:Data Collection / Q000379:methods; D016208:Databases, Factual / Q000592:standards*; D019538:Health Care Surveys; D006630:Hispanic or Latino / Q000145:classification* / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D008329:Managed Care Programs / Q000706:statistics & numerical data*; D006278:Medicare / Q000706:statistics & numerical data*; D008875:Middle Aged; D009275:Names; D012107:Research Design; D014481:United States; D014493:United States Department of Veterans Affairs; D014728:Veterans / Q000145:classification; D044465:White People / Q000145:classification / Q000706:statistics & numerical data; D001741:Black or African American