Measuring the missing: greater racial and ethnic disparities in COVID-19 burden after accounting for missing race/ethnicity data.
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ABSTRACT:
SUBMITTER: Labgold K
PROVIDER: S-EPMC7536882 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundBlack, Hispanic, and Indigenous persons in the United States have an increased risk of SARS-CoV-2 infection and death from COVID-19, due to persistent social inequities. However, the magnitude of the disparity is unclear because race/ethnicity information is often missing in surveillance data.MethodsWe quantified the burden of SARS-CoV-2 notification, hospitalization, and case fatality rates in an urban county by racial/ethnic group using combined race/ethnicity imputation and quantitative bias analysis for misclassification.ResultsThe ratio of the absolute racial/ethnic disparity in notification rates after bias adjustment, compared with the complete case analysis, increased 1.3-fold for persons classified Black and 1.6-fold for those classified Hispanic, in reference to classified White persons.ConclusionsThese results highlight that complete case analyses may underestimate absolute disparities in notification rates. Complete reporting of race/ethnicity information is necessary for health equity. When data are missing, quantitative bias analysis methods may improve estimates of racial/ethnic disparities in the COVID-19 burden.
| S-EPMC8641438 | biostudies-literature
Project description: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.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 chi-square 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.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.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.
| S-EPMC5342943 | biostudies-other
Project description:To assess whether black-white and Hispanic-white disparities increase or abate in the upper quantiles of total health care expenditure, conditional on covariates.Nationally representative adult population of non-Hispanic whites, African Americans, and Hispanics from the 2001-2005 Medical Expenditure Panel Surveys.We examine unadjusted racial/ethnic differences across the distribution of expenditures. We apply quantile regression to measure disparities at the median, 75th, 90th, and 95th quantiles, testing for differences over the distribution of health care expenditures and across income and education categories. We test the sensitivity of the results to comparisons based only on health status and estimate a two-part model to ensure that results are not driven by an extremely skewed distribution of expenditures with a large zero mass.Black-white and Hispanic-white disparities diminish in the upper quantiles of expenditure, but expenditures for blacks and Hispanics remain significantly lower than for whites throughout the distribution. For most education and income categories, disparities exist at the median and decline, but remain significant even with increased education and income.Blacks and Hispanics receive significantly disparate care at high expenditure levels, suggesting prioritization of improved access to quality care among minorities with critical health issues.
| S-EPMC2754550 | biostudies-literature
Project description:ObjectiveTo review methods of measuring racial/ethnic health care disparities.Study designIdentification and tracking of racial/ethnic disparities in health care will be advanced by application of a consistent definition and reliable empirical methods. We have proposed a definition of racial/ethnic health care disparities based in the Institute of Medicine's (IOM) Unequal Treatment report, which defines disparities as all differences except those due to clinical need and preferences. After briefly summarizing the strengths and critiques of this definition, we review methods that have been used to implement it. We discuss practical issues that arise during implementation and expand these methods to identify sources of disparities. We also situate the focus on methods to measure racial/ethnic health care disparities (an endeavor predominant in the United States) within a larger international literature in health outcomes and health care inequality. EMPIRICAL APPLICATION: We compare different methods of implementing the IOM definition on measurement of disparities in any use of mental health care and mental health care expenditures using the 2004-2008 Medical Expenditure Panel Survey.ConclusionDisparities analysts should be aware of multiple methods available to measure disparities and their differing assumptions. We prefer a method concordant with the IOM definition.
| S-EPMC3371391 | biostudies-literature
Project description:Importance: COVID-19 racial disparities have gained significant attention yet little is known about how age distributions obscure racial-ethnic disparities in COVID-19 case fatality ratios (CFR). Objective: We filled this gap by assessing relevant data availability and quality across states, and in states with available data, investigating how racial-ethnic disparities in CFR changed after age adjustment. Design/Setting/Participants/Exposure: We conducted a landscape analysis as of July 1st, 2020 and developed a grading system to assess COVID-19 case and death data by age and race in 50 states and DC. In states where age- and race-specific data were available, we applied direct age standardization to compare CFR across race-ethnicities. We developed an online dashboard to automatically and continuously update our results. Main Outcome and Measure: Our main outcome was CFR (deaths per 100 confirmed cases). We examined CFR by age and race-ethnicities. Results: We found substantial variations in disaggregating and reporting case and death data across states. Only three states, California, Illinois and Ohio, had sufficient age- and race-ethnicity-disaggregation to allow the investigation of racial-ethnic disparities in CFR while controlling for age. In total, we analyzed 391,991confirmed cases and 17,612 confirmed deaths. The crude CFRs varied from, e.g. 7.35% among Non-Hispanic (NH) White population to 1.39% among Hispanic population in Ohio. After age standardization, racial-ethnic differences in CFR narrowed, e.g. from 5.28% among NH White population to 3.79% among NH Asian population in Ohio, or an over one-fold difference. In addition, the ranking of race-ethnic-specific CFRs changed after age standardization. NH White population had the leading crude CFRs whereas NH Black and NH Asian population had the leading and second leading age-adjusted CFRs respectively in two of the three states. Hispanic population’s age-adjusted CFR were substantially higher than the crude. Sensitivity analysis did not change these results qualitatively. Conclusions and Relevance: The availability and quality of age- and race-ethnic-specific COVID-19 case and death data varied greatly across states. Age distributions in confirmed cases obscured racial-ethnic disparities in COVID-19 CFR. Age standardization narrows racial-ethnic disparities and changes ranking. Public COVID-19 data availability, quality, and harmonization need improvement to address racial disparities in this pandemic.
| S-EPMC7536886 | biostudies-literature
Project description:ObjectiveWe aimed to address deficiencies in structured electronic health record (EHR) data for race and ethnicity by identifying black and Hispanic patients from unstructured clinical notes and assessing differences between patients with or without structured race/ethnicity data.Materials and methodsUsing EHR notes for 16 665 patients with encounters at a primary care practice, we developed rule-based natural language processing (NLP) algorithms to classify patients as black/Hispanic. We evaluated performance of the method against an annotated gold standard, compared race and ethnicity between NLP-derived and structured EHR data, and compared characteristics of patients identified as black or Hispanic using only NLP vs patients identified as such only in structured EHR data.ResultsFor the sample of 16 665 patients, NLP identified 948 additional patients as black, a 26%increase, and 665 additional patients as Hispanic, a 20% increase. Compared with the patients identified as black or Hispanic in structured EHR data, patients identified as black or Hispanic via NLP only were older, more likely to be male, less likely to have commercial insurance, and more likely to have higher comorbidity.DiscussionStructured EHR data for race and ethnicity are subject to data quality issues. Supplementing structured EHR race data with NLP-derived race and ethnicity may allow researchers to better assess the demographic makeup of populations and draw more accurate conclusions about intergroup differences in health outcomes.ConclusionsBlack or Hispanic patients who are not documented as such in structured EHR race/ethnicity fields differ significantly from those who are. Relatively simple NLP can help address this limitation.
| S-EPMC6696506 | biostudies-literature
Project description: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.
| S-EPMC2653886 | biostudies-other
Project description:ImportanceRacial and ethnic disparities in postpartum care access have been well identified in the United States. Such disparities could be exacerbated by the COVID-19 pandemic because of amplified economic distress and compromised social capital among pregnant women who belong to racial or ethnic minority groups.ObjectiveTo examine whether the COVID-19 pandemic is associated with an increase in the existing racial and ethnic disparity in postpartum care access.Design, setting, and participantsThis was a retrospective cohort study using electronic health records data. Multinomial logistic regressions in an interrupted time series approach were used to assess monthly changes in postpartum care access across Asian, Hispanic, non-Hispanic Black (hereafter, Black), non-Hispanic White (hereafter, White) women, and women of other racial groups, controlling for maternal demographic and clinical characteristics. Eligible participants were women who gave live birth at 8 hospitals in the greater Boston, Massachusetts, area from January 1, 2019, to November 30, 2021, allowing for tracking 90-day postpartum access until March 1, 2022.ExposuresDelivery period: prepandemic (January to December 2019), early pandemic (January to March 2020), and late pandemic (April 2020 to November 2021).Main outcomes and measuresPostpartum care within 90 days after childbirth was categorized into 3 groups: attended, canceled, and nonscheduled.ResultsA total of 45 588 women were included. Participants were racially and ethnically diverse (4735 [10.4%] Asian women, 3399 [7.5%] Black women, 6950 [15.2%] Hispanic women, 28 529 [62.6%] White women, and 1269 [2.8%] women of other race or ethnicity). The majority were between 25 and 34 years of age and married and had a full-term pregnancy, vaginal delivery, and no clinical conditions. In the prepandemic period, the overall postpartum care attendance rate was 75.2%, dropping to 41.7% during the early pandemic period, and rebounding back to 60.9% in the late pandemic period. During the months in the late pandemic, the probability of not scheduling postpartum care among Black (average marginal effect [AME], 1.1; 95% CI, 0.6-1.6) and Hispanic women (AME, 1.3; 95% CI, 0.9-1.6) increased more than among their White counterparts.Conclusions and relevanceIn this cohort study of postpartum care access before and during the COVID-19 pandemic, racial and ethnic disparities in postpartum care were exacerbated following the onset of the COVID-19 pandemic, when postpartum care access recovered more slowly among Black and Hispanic women than White women. These disparities require swift attention and amelioration to address barriers for these women to obtain much needed postpartum care during this pandemic.
| S-EPMC9226999 | biostudies-literature
Project description:The disproportionate burden of prevalent, persistent pathogens among disadvantaged groups may contribute to socioeconomic and racial/ethnic disparities in long-term health. We assessed if the social patterning of pathogen burden changed over 16 years in a U.S.-representative sample. Data came from 17 660 National Health and Nutrition Examination Survey participants. Pathogen burden was quantified by summing the number of positive serologies for cytomegalovirus, herpes simplex virus-1, HSV-2, human papillomavirus and Toxoplasma gondii and dividing by the number of pathogens tested, giving a percent-seropositive for each participant. We examined sex- and age-adjusted mean pathogen burdens from 1999-2014, stratified by race/ethnicity and SES (poverty-to-income ratio (PIR); educational attainment). Those with a PIR < 1.3 had a mean pathogen burden 1.4-1.8 times those with a PIR > 3.5, with no change over time. Educational disparities were even greater and showed some evidence of increasing over time, with the mean pathogen burden among those with less than a high school education approximately twice that of those who completed more than high school. Non-Hispanic Black, Mexican American and other Hispanic participants had a mean pathogen burden 1.3-1.9 times non-Hispanic Whites. We demonstrate that socioeconomic and racial/ethnic disparities in pathogen burden have persisted across 16 years, with little evidence that the gap is closing.
| S-EPMC6873154 | biostudies-literature
Project description:Though wide disparities in wealth have been documented across racial/ethnic groups, it is largely unknown whether differences in wealth are associated with health disparities within racial/ethnic groups.Data from the Survey of Consumer Finances (2004, ages 25-64) and the Health and Retirement Survey (2004, ages 50+), containing a wide range of assets and debts variables, were used to calculate net worth (a standard measure of wealth). Among non-Hispanic black, Hispanic and non-Hispanic white populations, we tested whether wealth was associated with self-reported poor/fair health status after accounting for income and education.Except among the younger Hispanic population, net worth was significantly associated with poor/fair health status within each racial/ethnic group in both data sets. Adding net worth attenuated the association between education and poor/fair health (in all racial/ethnic groups) and between income and poor/fair health (except among older Hispanics).The results add to the literature indicating the importance of including measures of wealth in health research for what they may reveal about disparities not only between but also within different racial/ethnic groups.
| S-EPMC3686361 | biostudies-literature