Trends in Missing Race and Ethnicity Information After Imputation in HealthCare.gov Marketplace Enrollment Data, 2015-2021

Branham, Douglas Keith; Finegold, Kenneth; Chen, Lucy; Sorbero, Melony E.; Euller, Roald; Elliott, Marc N.; Sommers, Benjamin D.

doi:10.1001/jamanetworkopen.2022.16715

Cited by 25 publications

(21 citation statements)

References 8 publications

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“…To address the nearly 20% of Medicaid and 30% of marketplace enrollees who do not report their race or ethnicity, as well as misclassification of some Medicare beneficiaries based on previous Social Security categories of White, Black, and other, the HHS is currently using imputation and other methods. The results are already helping the HHS evaluate the effects of enrollment outreach campaigns and map health care disparities to social factors . Other efforts to enhance data include supporting community-level data sharing; expanding a comprehensive database on social determinants created by the Agency for Healthcare Research and Quality; adding information on food insecurity, housing, financial strain, and transportation to the data the HHS collects from community health centers and as part of national health surveillance efforts; and expanding the Office of the National Coordinator for Health Information Technology,…”

Section: Better Datamentioning

confidence: 99%

Addressing Social Determinants of Health in Federal Programs

Lew

Sommers

2022

JAMA Health Forum

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Although high-quality, affordable health care is essential to addressing medical conditions when they arise, the strongest predictor of health outcomes in the US is not medical care but rather the broader social context in which people live and work. These social determinants of health, such as economic conditions, housing, nutrition, the environment, transportation, and education, are estimated to account for half of the county-level variation in health outcomes and are a major driver of health disparities. 1 Advancing racial equity and supporting underserved communities is a central priority of the Biden-Harris administration. To improve the health of the US population and dismantle long-standing inequities, a comprehensive federal approach addressing social determinants is now underway.Many federal health care and public health programs reside within the US Department of Health and Human Services (HHS), including Medicare, Medicaid,

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Section: Better Datamentioning

confidence: 99%

Addressing Social Determinants of Health in Federal Programs

Lew

Sommers

2022

JAMA Health Forum

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“…Given the significant implicit and explicit bias many patients of colour face in the healthcare system, it is important to maintain this option in demographic surveys, while also providing information on how answers to this question will be used (e.g., to understand inequities in care, promote patient–provider concordance). This limitation is similar to other healthcare data sources: for example, 30% of enrollees in the https://Healthcare.gov Marketplace plans have missing race data, with rates as high as 63% in some states 5 . Better understanding disparities in maternal and digital health relies on the ability to accurately ascertain demographic data.…”

Section: Discussionmentioning

confidence: 83%

“…This limitation is similar to other healthcare data sources: for example, 30% of enrollees in the Healthcare.gov Marketplace plans have missing race data, with rates as high as 63% in some states. 5 Better understanding disparities in maternal and digital health relies on the ability to accurately ascertain demographic data. Second, Maven is only available to pregnant people who have the tools to access digital care.…”

Section: Discussionmentioning

confidence: 99%

Differences in digital prenatal service utilization by self‐reported race

Peahl,

Jahnke,

Rubin‐Miller

et al. 2023

Repro Female Child Health

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ObjectiveThe objective of this study was to understand the use of supplemental digital prenatal services by race and ethnicity among pregnant people utilizing a comprehensive, employer‐sponsored digital health platform.Materials and MethodsWe conducted a retrospective cohort study of pregnant people enrolled in a comprehensive, employer‐sponsored digital health platform, assessing utilization of app‐based supplemental digital prenatal services by race and ethnicity. Care utilization included three categories: asynchronous utilization (e.g., article reads, videos); interactions with a care advocate, a trained care navigator; and provider interactions (e.g., messages and visits with a medical provider). Differences in service utilization by race and ethnicity were assessed using basic descriptive statistics with between‐group comparisons.ResultsOf 5662 users, 2362 (41.7%) were White, 266 (4.7%) were Black, and 1411 (24.9%) reported ‘prefer not to say’ for their race. More Black and Asian users sent messages to a provider and had provider appointments than White and Hispanic users (messages: White: 33.7%, Hispanic: 33.6%, Asian: 44.9%, Black: 45.1%, p < 0.001; provider appointments: White: 49.8%, Hispanic: 43.3%, Asian: 52.4%, Black: 46.2%, p < 0.001). More Black users accessed doula and mental health appointments than other racial groups.ConclusionsOur study demonstrates that pregnant people of historically marginalized groups use digital supplemental prenatal services as much or more than White patients. Digital prenatal services may be a promising avenue for improving care access and experience for patient groups that face the biggest barriers to care and worst maternity care outcomes.

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“…In large surveys, it has been demonstrated that underrepresented minorities such as African Americans, Latinx, and Asian/Pacific Islanders are less likely to report their race than White survey respondents. 11,12 An important example of this in public health research was the finding that missing race data in COVID cases reported in Massachusetts did not occur randomly among all races and was most notable among minority races. 13 These findings of inequities in the time to treatment of syphilis along racial lines demands further investigation into contributory factors.…”

Section: Discussionmentioning

confidence: 99%

The Tenacious Treponema: A Retrospective Examination of Syphilis Treatment Disparities in Washington, DC

Liroff,

Kassaye,

Spence

et al. 2023

Sexual Trans Dis

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Background Since 2000 there have been rising rates of syphilis infections nationally with higher incidence among minorities and persons living with HIV (PLWH). The purpose of this study was to determine syphilis treatment adequacy and factors associated with treatment delay. Methods This was a retrospective academic-public health collaboration with the District of Columbia Department of Public Health reviewing surveillance data of all primary, secondary, and early latent syphilis cases diagnosed between 1/1/2015 and 12/31/2019. Data were analyzed using multivariable logistic regression to identify factors associated with delayed treatment >14 days from diagnosis. Results Among 1852 individuals diagnosed with early syphilis, 93% (1730/1852) were male; 48% (893/1852) were co-infected with HIV; 43% (n = 796/1852) were African American/Black, 27% (n = 492/1852) were White, and race/ethnicity was unknown for 17% (n = 318/1852) of cases. Among 679 PLWH for whom viral load (VL) was known, 41% (278/679) had a viral load (VL) < 20 copies/mL, and 18% (123/679) had VL >10,000 copies/mL. Treatment adequacy overall was 96.5%. Median time to syphilis treatment was 6 days [IQR = 4,7]. Factors associated with delay of treatment included refused/unknown race (aOR = 1.95; CI = 1.00, 3.79), reporting provider veterans/military (aOR = 5.26; (CI = 1.51-18.28),and HIV VL > 10,000 copies/mL (aOR = 1.97; CI = 1.08-3.58). Conclusions The factors we identified associated with delayed treatment may reflect systemic factors contributing to the increased rates of infection among key populations. This highlights the importance of targeted public health efforts with the goal of reducing transmission of both HIV and syphilis.

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Trends in Missing Race and Ethnicity Information After Imputation in HealthCare.gov Marketplace Enrollment Data, 2015-2021

Abstract: This cross-sectional study examines patterns of missing information on race and ethnicity after an imputation of HealthCare.gov enrollment data between 2015 and 2021.

Cited by 25 publications

References 8 publications

Addressing Social Determinants of Health in Federal Programs

Addressing Social Determinants of Health in Federal Programs

Differences in digital prenatal service utilization by self‐reported race

The Tenacious Treponema: A Retrospective Examination of Syphilis Treatment Disparities in Washington, DC

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