Health plan administrative records versus birth certificate records: quality of race and ethnicity information in children (original) (raw)
Related papers
Health Services Research, 2015
Objective. To assess the utility of imputing race/ethnicity using U.S. Census race/ethnicity, residential address, and surname information compared to standard missing data methods in a pediatric cohort. Data Sources/Study Setting. Electronic health record data from 30 pediatric practices with known race/ethnicity. Study Design. In a simulation experiment, we constructed dichotomous and continuous outcomes with pre-specified associations with known race/ethnicity. Bias was introduced by nonrandomly setting race/ethnicity to missing. We compared typical methods for handling missing race/ethnicity (multiple imputation alone with clinical factors, complete case analysis, indicator variables) to multiple imputation incorporating surname and address information. Principal Findings. Imputation using U.S. Census information reduced bias for both continuous and dichotomous outcomes. Conclusions. The new method reduces bias when race/ethnicity is partially, nonrandomly missing.
2009
This brief presents findings from a recent study conducted by the Kaiser Family Foundation to examine how racial/ethnic disparities in access among Medicaid-enrolled children compare with disparities among privately insured and uninsured children. The analysis is based on data for a pooled sample of 15,280 African American, Latino, and White children aged 1-18, from the 2003 and 2004 Medical Expenditure Panel Survey (MEPS). We analyze data on four indicators of access to care-two that examine entry into the health care system and two measures of perceived ability to obtain access. We identify a racial/ethnic difference as a disparity only if statistically significant at p<0.05. Key findings are as follows: • While the vast majority of children fared well on the indicators examined, access problems persist for some children. In 2003-2004, about 8.6% of children lacked a usual source of care (USC), 27.1% had no ambulatory medical visit in the prior year, 9.6% of children with a prior medical visit reported problems getting necessary care, and 22.0% of children needing specialty care reported problems seeing a specialist. • Medicaid was on par with private insurance with regard to racial/ethnic disparities in children's access. Racial/ethnic disparities in access were no more likely among children in Medicaid than among privately insured children on these four indicators of access. • The presence and magnitude of disparities varied by the combination of a child's race/ethnicity and insurance group, and by the access measure examined. African American and Latino children lagged behind White children on the usual source of care measure in all three insurance groups; the disparity was largest-nearly threefold between uninsured Latino and White children. Privately insured African Americans and Latinos fared worse than Whites on the ambulatory visit measure, but in the Medicaid group, Latinos experienced no disadvantage, and in the uninsured group, African Americans experienced no gap. Evidence of racial/ethnic disparities
Journal of Racial and Ethnic Health Disparities, 2016
Background Data collection on race and ethnicity is critical in the assessment of racial disparities related to health. Studies comparing clinical and administrative data show discrepancies in race documentation and attribution. Methods Self-reported data from two studies were compared to demographics in the electronic health record (EHR) extracted from the Biomedical Translational Research Information System (BTRIS) repository. McNemar and Bhapkar analyses were conducted to quantify the agreement of ethnicity and race between self-reported and EHR data. Pearson's chisquare tests were used to explore the relationship between acculturation, length of time in the USA, country of residence, and how individuals self-reported their race. Results The sample (n = 280) was predominantly female (52.1 %), with a mean age of 47 (SD ± 13.74), mean years in the USA were 12.8 (SD ± 11.67) and the majority were born outside of the USA. (55.6 %). Those who self-identified as Hispanic (n = 208) scored a mean of 5.5 (SD ± 3.07) on the short acculturation scale (SAS) that ranges 4 to 20; lower scores indicate less acculturation. A significant difference was found between the way race is reported in the electronic medical record and self-reported data among those people who identified as Hispanic, with significant differences in the white (p < 0.0001) and other (p < 0.0001) categories. Conclusions The misclassification of race is most frequent in those individuals who self-identified as Hispanic. As the Hispanic population in the USA continues to grow, understanding the factors that affect the way that individuals from this heterogeneous population self-report race may provide important guidance in tailoring care to address health disparities.
Improving Hospital Reporting of Patient Race and Ethnicity-Approaches to Data Auditing
Health services research, 2015
To investigate new metrics to improve the reporting of patient race and ethnicity (R/E) by hospitals. California Patient Discharge Database (PDD) and birth registry, 2008-2009, Healthcare and Cost Utilization Project's State Inpatient Database, 2008-2011, cancer registry 2000-2008, and 2010 US Census Summary File 2. We examined agreement between hospital reported R/E versus self-report among mothers delivering babies and a cancer cohort in California. Metrics were created to measure root mean squared differences (RMSD) by hospital between reported R/E distribution and R/E estimates using R/E distribution within each patient's zip code of residence. RMSD comparisons were made to corresponding "gold standard" facility-level measures within the maternal cohort for California and six comparison states. Maternal birth hospitalization (linked to the state birth registry) and cancer cohort records linked to preceding and subsequent hospitalizations. Hospital discharges we...
Race and Ethnicity: Comparing Medical Records to Self-Reports
Journal of the National Cancer Institute Monographs, 2005
Understanding and eliminating health disparities requires accurate data on race/ethnicity. To assess the quality of race/ethnicity data, we compared medical record classifi cations to self-report of a study of prophylactic mastectomy. A total of 788 women had race/ethnicity from both sources; 69.9% were 55 years of age or older, 38.3% were at least college graduates, and 67.8% were married or living with someone. There were 817 race/ thnicity classifi cations for the 788 women, of which 758 (92.3%) were identical in the medical record and self-report. Sensitivity and positive predictive value were high (86.7% -97.2%) for whites, Asians, and blacks and moderate (64.0% and 68.1%) for Latinas. However, only one of 18 Native Americans was correctly identifi ed in her medical record. Our results indicate that even if the overall accuracy of medical record classifi cations for race/ethnicity is high, such a fi nding may obscure substantial inaccuracies in the recording for racial/ ethnic minorities, especially Latinas and Native Americans. [J Natl Cancer Inst Monogr 2005;35:72 -4]
Validity of Infant Race/Ethnicity from Birth Certificates in the Context of U.S. Demographic Change
Health Services Research, 2013
Objective. To compare infant race/ethnicity based on birth certificates with parent report of infant race/ethnicity in a survey. Data Sources. The 2007 Oklahoma birth certificates and SEED for Oklahoma Kids baseline survey. Study Design. Using sensitivity scores and positive predictive values, we examined consistency of infant race/ethnicity across two data sources (N = 2,663). Data Collection/Extraction Methods. We compared conventional measures of infant race/ethnicity from birth certificate and survey data. We also tested alternative measures that allow biracial classification, determined from parental information on the infant's birth certificate or parental survey report. Principal Findings. Sensitivity of conventional measures is highest for whites and African Americans and lowest for Hispanics; positive predictive value is highest for Hispanics and African Americans and lowest for American Indians. Alternative measures improve values among whites but yield mostly low values among minority and biracial groups. Conclusions. Health disparities research should consider the source and validity of infant race/ethnicity data when creating sampling frames or designing studies that target infants by race/ethnicity. The common practice of assigning the maternal race/ ethnicity as infant race/ethnicity should continue to be challenged. Key Words. Vital statistics, racial/ethnic differences in health and health care, infant health, survey research and questionnaire design Birth certificates provide a valuable sampling frame for infant health and disparity studies, as they include information on almost everyone in the target population and on birth parents (e.g., race, ethnicity, and education), and allow researchers to construct subsamples of underrepresented groups (Schoendorf and Branum 2006). Since 1989, the National Center for Health Statistics (NCHS) has tabulated infant vital statistics primarily by assigning
Subjectively-Assigned versus self-reported race and ethnicity in US healthcare
Social Medicine, 2014
Documenting patient "race" descriptors in clinical medicine, epidemiology, and public health data and analysis has been routine in the US. However, patient race has historically been and is still most often subjectively-assigned rather than selfidentified. Even when self-identification is allowed, persons must often self-deny parts of their ancestry by adhering to restrictive race categories. In contrast, most other countries ignore so-called race and may use other ancestral background information including family and geographical histories, language(s) and/or ethnic group(s) membership. We performed two studies involving 160 patients to investigate subjectively-assigned versus selfreported race using a verbal questionnaire in a New Orleans medical clinic. Results revealed that the subjectively-assigned race recorded by the hospital administration/physician was incomplete and therefore inaccurate. Clinicians and researchers must make more accurate and respectful ancestral inquiries in order to derive useful information about individual and population health risks and disease conditions, while also being mindful of potentially erroneous race data previously gathered and conclusions inferred in healthcare literature.