Dataset Information

A new method for estimating race/ethnicity and associated disparities where administrative records lack self-reported race/ethnicity.

ABSTRACT: To efficiently estimate race/ethnicity using administrative records to facilitate health care organizations' efforts to address disparities when self-reported race/ethnicity data are unavailable.Surname, geocoded residential address, and self-reported race/ethnicity from 1,973,362 enrollees of a national health plan.We compare the accuracy of a Bayesian approach to combining surname and geocoded information to estimate race/ethnicity to two other indirect methods: a non-Bayesian method that combines surname and geocoded information and geocoded information alone. We assess accuracy with respect to estimating (1) individual race/ethnicity and (2) overall racial/ethnic prevalence in a population.The Bayesian approach was 74 percent more efficient than geocoding alone in estimating individual race/ethnicity and 56 percent more efficient in estimating the prevalence of racial/ethnic groups, outperforming the non-Bayesian hybrid on both measures. The non-Bayesian hybrid was more efficient than geocoding alone in estimating individual race/ethnicity but less efficient with respect to prevalence (p<.05 for all differences).The Bayesian Surname and Geocoding (BSG) method presented here efficiently integrates administrative data, substantially improving upon what is possible with a single source or from other hybrid methods; it offers a powerful tool that can help health care organizations address disparities until self-reported race/ethnicity data are available.

SUBMITTER: Elliott MN

PROVIDER: S-EPMC2653886 | biostudies-other | 2008 Oct

REPOSITORIES: biostudies-other

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A new method for estimating race/ethnicity and associated disparities where administrative records lack self-reported race/ethnicity.

Elliott Marc N MN Fremont Allen A Morrison Peter A PA Pantoja Philip P Lurie Nicole N

Health services research 20080512 5 Pt 1

<h4>Objective</h4>To efficiently estimate race/ethnicity using administrative records to facilitate health care organizations' efforts to address disparities when self-reported race/ethnicity data are unavailable.<h4>Data source</h4>Surname, geocoded residential address, and self-reported race/ethnicity from 1,973,362 enrollees of a national health plan.<h4>Study design</h4>We compare the accuracy of a Bayesian approach to combining surname and geocoded information to estimate race/ethnicity to ...[more]

PMID: 18479410

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Project description:Background:Administrative data are commonly used to study clinical outcomes in renal disease. Race is an important determinant of renal health delivery and outcomes in Canada but is not validated in most administrative data, and the correlation with census-based definitions of race is unknown. Objectives:Validation of self-reported race (SRR) in a Canadian provincial renal administrative database (Patient Records and Outcome Management Information System [PROMIS]) and comparison with the Canadian census categories of race. Design:Prospective patient survey study to validate SRR in PROMIS. Setting:British Columbia, Canada. Patients:Adult patients registered in PROMIS. Measurements:Survey SRR was used as gold standard to validate SRR in PROMIS. Self-reported race in PROMIS was compared with census race categories. Methods:This is a cross-sectional telephone survey of a random sample of all adults in PROMIS conducted between February 2016 and November 2016. Responders selected a race category from PROMIS and from the Canadian census. Sensitivity (Sn) and specificity (Sp) were calculated with 95% confidence intervals (CIs). Results:A total of 21?039 patients met inclusion criteria, 1677 were selected for the survey and 637 participated (38% response rate). There were no differences between the PROMIS, sampled, and responder populations. PROMIS SRR had an accuracy of 95.3% (95% CI: 94.2%-97.0%) when validated against the survey SRR with Sn and Sp ?90% in all race groups except in Aboriginals (Sn 87.5%). The positive and negative predictive values were ?95%, except in very low and high-prevalence groups, respectively. The Canadian census had an accuracy of 95.7% (95% CI: 94.4%-97.6%) when validated against PROMIS SRR with Sn and Sp ?90%. The results did not differ in subgroups based on age, sex, birth outside Canada, or renal group (glomerulonephritis, chronic kidney disease, hemodialysis, peritoneal dialysis, transplant recipients, or live donors). Limitations:Analysis of minority groups and lower prevalence groups is limited by sample size. Results may not be generalizable to other administrative databases. Conclusions:We have shown high accuracy of PROMIS SRR that validates its use in the secondary analysis of administrative data for research. There is high correlation between PROMIS and census race categories which allows linkage with other data sources that use census-based definitions of race.

Project description:BackgroundFamily history and African-American race are important risk factors for both prostate cancer (CaP) incidence and aggressiveness. When studying complex diseases such as CaP that have a heritable component, chances of finding true disease susceptibility alleles can be increased by accounting for genetic ancestry within the population investigated. Race, ethnicity and ancestry were studied in a geographically diverse cohort of men with newly diagnosed CaP.MethodsIndividual ancestry (IA) was estimated in the population-based North Carolina and Louisiana Prostate Cancer Project (PCaP), a cohort of 2,106 incident CaP cases (2063 with complete ethnicity information) comprising roughly equal numbers of research subjects reporting as Black/African American (AA) or European American/Caucasian/Caucasian American/White (EA) from North Carolina or Louisiana. Mean genome wide individual ancestry estimates of percent African, European and Asian were obtained and tested for differences by state and ethnicity (Cajun and/or Creole and Hispanic/Latino) using multivariate analysis of variance models. Principal components (PC) were compared to assess differences in genetic composition by self-reported race and ethnicity between and within states.ResultsMean individual ancestries differed by state for self-reporting AA (p = 0.03) and EA (p = 0.001). This geographic difference attenuated for AAs who answered "no" to all ethnicity membership questions (non-ethnic research subjects; p = 0.78) but not EA research subjects, p = 0.002. Mean ancestry estimates of self-identified AA Louisiana research subjects for each ethnic group; Cajun only, Creole only and both Cajun and Creole differed significantly from self-identified non-ethnic AA Louisiana research subjects. These ethnicity differences were not seen in those who self-identified as EA.ConclusionsMean IA differed by race between states, elucidating a potential contributing factor to these differences in AA research participants: self-reported ethnicity. Accurately accounting for genetic admixture in this cohort is essential for future analyses of the genetic and environmental contributions to CaP.

Project description:ImportanceDespite recent advances in therapies for heart failure (HF), deaths from HF are increasing, with persistent disparities between Black and White adults. Recent national trends in the prevalence of HF need to be clarified to appropriately allocate resources and develop effective preventive interventions.ObjectivesTo examine the prevalence of ambulatory HF overall and by race/ethnicity and age and the temporal changes in HF prevalence between 2001 and 2016.Design, setting, and participantsThis cross-sectional study of nationally representative data collected biennially through the National Health and Nutrition Examination Survey (NHANES) from January 1, 2001, to December 31, 2016, assessed nonpregnant adults 35 years and older who self-identified as non-Hispanic Black, non-Hispanic White, or Mexican American. Data analysis was performed from November 16, 2019, to April 12, 2020.ExposuresSurvey period, race/ethnicity, and age group.Main outcomes and measuresAge-standardized prevalence was calculated within 4-year survey periods (2001-2004, 2005-2008, 2009-2012, and 2013-2016) based on self-report of ambulatory HF overall and by race/ethnicity and age group (35-64 and ≥65 years). Weighted multivariable logistic regression was used to examine trends in ambulatory HF prevalence over time by race/ethnicity and age group.ResultsA total of 26 097 participants (mean [SD] age, 55.9 [10.7] years; 13 192 [52%] female; 6519 [12%] non-Hispanic Black; and 4906 [7%] Mexican American) were studied. Overall age-standardized prevalence (per 100 000 population) of ambulatory HF was 3184 (95% CI, 2641-3728) from 2001 to 2005 and 3045 (95% CI, 2651-3438) from 2013 to 2016. The prevalence of ambulatory HF was highest among non-Hispanic Black adults: from 2013 to 2016, HF prevalence (per 100 000 population) was 5017 (95% CI, 3755-6279) among non-Hispanic Black adults, 2746 (95% CI, 2313-3179) among non-Hispanic White adults, and 2508 (95% CI, 1154-3862) among Mexican American adults. Differences between White and Black adults in HF prevalence were also present in younger and middle-aged adults (eg, 35-64 years of age in 2013-2016: 3864 [95% CI, 2369-5359] for non-Hispanic Black adults vs 1297 [95% CI, 878-1716] for non-Hispanic White adults).Conclusions and relevanceThis study found that a high burden of ambulatory HF persisted between 2001 and 2016 in the US. Disparities were most prominent by age group. Alongside prevention and aggressive management of risk factors, targeted efforts aimed at mitigating racial disparities are needed.

Dataset Information

A new method for estimating race/ethnicity and associated disparities where administrative records lack self-reported race/ethnicity.

Publications

A new method for estimating race/ethnicity and associated disparities where administrative records lack self-reported race/ethnicity.

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