Race/ethnicity misclassification of persons reported with AIDS. The AIDS Mortality Project Group and The Supplement to HIV/AIDS Surveillance Project Group.
ABSTRACT To examine differences in race/ethnicity classifications of persons with AIDS among three reporting sources and to estimate the effect of these differences on calculated AIDS rates.
We reviewed case reports from the national AIDS surveillance database, interview (self-reported) data from 11 state/local health departments, and death certificate information from 16 state/local health departments for agreement in race/ethnicity coding among persons reported with AIDS.
Race/ethnicity coding inconsistencies with AIDS case reports were greatest for persons identified as American Indians/Alaska natives on death certificates (46% [47/102] disagreement) and by self-report (57% 8/14 disagreement). Agreement with AIDS case reports was highest either for persons identified as white from death certificates (4% [1314/31,070] disagreement) and white from self-reports (2% [26/1068] disagreement) or black from death certificates (3% [440/13,592] disagreement) and black from self-reports (3% [21/736] disagreement). For other racial/ethnic groups, disagreement with AIDS case reports was intermediate; for Asians/Pacific Islanders, 12% [45/377] disagreement with death certificates and 33% 4/12 disagreement with self-reports; and for Hispanics, 14% [1151/8527] disagreement with death certificates and 24% [59/249] disagreement with self-reports.
For certain racial/ethnic groups, classification by race/ethnicity can differ substantially by surveillance data source. Because allocation of public health resources may be determined by estimates of disease impact on different population groups, periodic evaluations of the accuracy of race and ethnicity reporting are needed to assure appropriate distribution of these resources.
- SourceAvailable from: Kathleen Call
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- "Studies have examined the quality of racial and ethnic designations in administrative data from specific states (Baumeister et al. 2000; Boehmer et al. 2002), in public health care programs such Medicare (Pan et al. 1999; Waldo 2005), clinic records (Gomez et al. 2005) and surveillance systems for conditions such as cancer or AIDS (Kelly et al. 1996; Swallen et al. 1997). Few have pursued such questions in a Medicaid population even though they are often the focus of health disparities research. "
ABSTRACT: This paper measures agreement between survey and administrative measures of race/ethnicity for Medicaid enrollees. Level of agreement and the demographic and health-related characteristics associated with misclassification on the administrative measure are examined. Minnesota Medicaid enrollee files matched to self-report information from a telephone/mail survey of 4,902 enrollees conducted in 2003. Measures of agreement between the two measures of race/ethnicity are computed. Using logistic regression, we also assess whether misclassification of race/ethnicity on administrative files is associated with demographic factors, health status, health care utilization, or ratings of quality of health care. Race/ethnicity fields from administrative Medicaid files were extracted and merged with self-report data. The administrative data correctly classified 94 percent of cases on race/ethnicity. Persons who self-identified as Hispanic and those whose home language was English had the greater odds (compared with persons who self-identified as white and those whose home language was not English) of being misclassified in administrative data. Persons classified as unknown/other on administrative data were more likely to self-identify as white. In this case study in Minnesota, researchers can be reasonably confident that the racial designations on Medicaid administrative data comport with how enrollees self-identify. Moreover, misclassification is not associated with common measures of health status, utilization, and ratings of quality of care. Further replication is recommended given variation in how race information is collected and coded by Medicaid agencies in different states.Health Services Research 01/2008; 42(6 Pt 2):2373-88. DOI:10.1111/j.1475-6773.2007.00771.x · 2.78 Impact Factor
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- "The number of APIs with HIV or AIDS is probably underestimated partly owing to race/ ethnicity misclassification in medical records, one of the main sources of information for HIV/AIDS case reports. APIs with Spanish–sounding names (especially for members of the Latin American diaspora of Asians and Filipinos) are often classified as Hispanic (Kelly, Chu, Diaz, Leary, Buehler, 1996; Sy et al., 1998 "
ABSTRACT: Although the percentage of overall AIDS diagnoses remains low among Asian and Pacific Islanders (APIs) in the United States compared with other racial/ethnic groups, research on API risk behaviors and health status suggest that the low number of AIDS cases may not provide a full picture of the epidemic and issues faced by this understudied and underserved population. Data from national HIV/AIDS surveillance systems and the Behavioral Risk Factor Surveillance System (BRFSS) were examined to delineate the magnitude and course of the HIV/AIDS epidemic among APIs in the United States. Same-sex sexual activity is the main HIV risk for API men, whereas heterosexual contact is for API women. APIs are significantly less likely to report being tested for HIV despite the fact that a similar proportion of APIs and other racial/ethnic groups reported having HIV risk in the past 12 months. Given the enormous diversity among APIs in the United States it is important to collect detailed demographic information to improve race/ethnicity and HIV risk classification, conduct better behavioral and disease monitoring for informing prevention planning, and addressing cultural, linguistic, economic and legal barriers to HIV prevention among APIs.AIDS Education and Prevention 11/2005; 17(5):405-17. DOI:10.1521/aeap.2005.17.5.405 · 1.59 Impact Factor
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ABSTRACT: We examined racial misidentification of American Indians/Alaska Natives (AI/AN) reported to the human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) Reporting Systems (HARS) of five U.S. states and one county. To identify AI/AN records with misidentified race, we linked HARS data from 1984 through 2002 to the Indian Health Service National Patient Information and Reporting System (NPIRS), excluding non-AI/AN dependents, using probabilistic matching with clerical review. We used chi-square tests to examine differences in proportions and logistic regression to examine the associations of racial misidentification with HARS site, degree of AI/AN ancestry, mode of exposure to HIV, and urban or rural location of residence at time of diagnosis. A total of 1,523 AI/AN individuals was found in both NPIRS and HARS; race was misidentified in HARS for 459 (30%). The percentages of racially misidentified ranged from 3.7% (in Alaska) to 55% (in California). AI/AN people were misidentified as white (70%), Hispanic (16%), black (11%), and Asian/Pacific Islander (2%); for 0.9%, race was unspecified. Logistic regression results (data from all areas, all variables) indicated that urban residence at time of diagnosis, degree of AI/AN ancestry, and mode of exposure to HIV were significantly associated with racial misidentification of AI/AN people reported to HARS. Our findings add to the evidence that racial misidentification of AI/AN in surveillance data can result in underestimation of AI/AN HIV/AIDS case counts. Racial misidentification must be addressed to ensure that HIV/ AIDS surveillance data can be used as the basis for equitable resource allocation decisions, and to inform and mobilize public health action.Public Health Reports 122(3):382-92. · 1.55 Impact Factor