scholarly journals The Influence of Health Insurance Stability on Racial/Ethnic Differences in Diabetes Control and Management

2021 ◽  
Vol 31 (1) ◽  
pp. 149-158
Author(s):  
Alison G. M. Brown ◽  
Nancy Kressin ◽  
Norma Terrin ◽  
Amresh Hanchate ◽  
Jillian Suzukida ◽  
...  
Keyword(s):  
Health Insurance ◽  
Ethnic Groups ◽  
Private Insurance ◽  
Insurance Coverage ◽  
Ethnically Diverse ◽  
Diabetes Control ◽  
Hispanic Patients ◽  
Control And Management ◽  
The Impact ◽  
Racial Ethnic

Objective: This study examined whether health insurance stability was associated with improved type 2 diabetes mellitus (DM) control and reduced racial/ethnic health disparities.Methods: We utilized electronic medical record data (2005-2013) from two large, urban academic health systems with a racially/ethnically diverse patient popula­tion to examine insurance coverage, and three DM outcomes (poor diabetes control, A1c ≥8.0%; very poor diabetes control A1c >9.0%; and poor BP control, ≥ 130/80 mm Hg) and one DM management outcome (A1c monitoring). We used generalized estimating equations adjusting for age, sex, comorbidities, site of care, education, and income. Additional analysis examined if insurance stability (stable public or private insurance over the six-month internal) moderates the impact of race/ethnicity on DM outcomes.Results: Nearly 50% of non-Hispanic (NH) Whites had private insurance cover­age, compared with 33.5% of NH Blacks, 31.5% of Asians, and 31.1% of Hispanics. Overall, and within most racial/ ethnic groups, insurance stability was associated with better glycemic control compared with those with insurance switches or always being uninsured, with uninsured NH Blacks having significantly worse BP control. More NH Black and Hispanic patients had poorly controlled (A1c≥8%) and very poorly controlled (A1c>9%) diabetes across all insurance stability types than NH Whites or Asians. The interaction between insurance instability and race/ethnic groups was statis­tically significant for A1c monitoring and BP control, but not for glycemic control.Conclusion: Stable insurance coverage was associated with improved DM outcomes for all racial / ethnic groups, but did not eliminate racial ethnic disparitiesEthn Dis. 2021;31(1):149-158; doi:10.18865/ed.31.1.149

scholarly journals 2193 The influence of health insurance stability on racial/ethnic differences in diabetes control and management

2018 ◽  
Vol 2 (S1) ◽  
pp. 74-75
Author(s):  
Alison G. M. Brown ◽  
Nancy R. Kressin ◽  
Norma Terrin ◽  
Amresh Hanchate ◽  
Jillian Suzukida ◽  
...  
Keyword(s):  
Health Insurance ◽  
Health Care Policy ◽  
Diabetes Management ◽  
Insurance Coverage ◽  
Ethnically Diverse ◽  
Health Insurance Coverage ◽  
Policy Debate ◽  
Race Ethnicity ◽  
The Impact ◽  
Racial Ethnic

OBJECTIVES/SPECIFIC AIMS: The aim of this study is to examine if stable health insurance coverage is associated with improved type 2 diabetes (DM) control and with reduced racial/ethnic health disparities. METHODS/STUDY POPULATION: We utilized EMR data (2005–2013) from 2 large, urban academic health centers with a racially/ethnically diverse patient population to longitudinally examine insurance coverage, and diabetes outcomes (A1C, LDL cholesterol, BP) and management measures (e.g., A1C and BP monitoring). We categorized insurance stability status during each 6-month interval as 6 separate categories based upon type (private, public, uninsured) and continuity of insurance (continuous, switches, or gaps in coverage). We will examine the association between insurance stability status and DM outcomes adjusting for time, age, sex, comorbidities, site of care, education, and income. Additional analysis will examine if insurance stability moderates the impact of race/ethnicity on DM outcomes. RESULTS/ANTICIPATED RESULTS: Overall, we anticipate that stable health insurance coverage will improve measures for DM care, particularly for racially/ethnically diverse patients. DISCUSSION/SIGNIFICANCE OF IMPACT: The finding of an interaction between insurance stability status and race/ethnicity in improved diabetes management and control would inform the national health care policy debate on the impact of stable health insurance.

scholarly journals A national study of the association between language use and health insurance coverage in the United States

2013 ◽  
Vol 2 (2) ◽  
pp. 115
Author(s):  
Garth Nigel Graham ◽  
Rashida Dorsey
Keyword(s):  
United States ◽  
Health Insurance ◽  
Ethnic Groups ◽  
Language Use ◽  
Insurance Coverage ◽  
Health Insurance Coverage ◽  
The United States ◽  
National Study ◽  
The Impact ◽  
The U.S

Background: A significant proportion of individuals seen in US hospitals speak a language other than English. A number of reports have shown that individuals who speak a language other than English have diminished access to care, but few have examined specifically language barriers and its relationship to health insurance coverage. Objectives: To estimate the impact of language use on prevalence of reported health insurance coverage across multiple racial and ethnic groups and among persons living in the U.S. for varying periods of time. Design and participants: Cross sectional study using data from the 2010 National Health Interview Survey. Main measures: The main outcome measure is health insurance status. Key results: Persons who spoke Spanish or a language other than English were less likely to have insurance. Among Hispanics who speak Spanish or a language other than English, only 50.6% report having health insurance coverage compared to 76.7% of Hispanics who speak only or mostly English. For non-Hispanic whites who speak Spanish or a language other than English, 71.7% report having health insurance coverage compared to 83.4% of non-Hispanic whites who speak only or mostly English, this same pattern was observed across all racial/ethnic groups. Among those speaking only or mostly English living in the U.S. <15 years had significantly lower adjusted odds of reporting health insurance coverage compared to those born in the United States. Conclusions: This was a large nationally representative study describing language differences in insurance access using a multi-ethnic population. This data suggest that individuals who speak a language other than English are less likely to have insurance across all racial and ethnic groups and nativity and years in the United States groups, underscoring the significant independent importance of language as a predictor for access to insurance.

Revisiting equity in healthcare spending through capability-approach: assessing the effectiveness of health-insurance schemes in reducing OOPE and CHE in India

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rinshu Dwivedi ◽  
Jalandhar Pradhan
Keyword(s):  
Health Care ◽  
Health Insurance ◽  
Capability Approach ◽  
Financial Burden ◽  
Private Insurance ◽  
Insurance Coverage ◽  
Health Insurance Coverage ◽  
Sample Survey ◽  
Content Type ◽  
The Impact

Purpose This paper aims to draw theoretical insight from Sen’s capability-approach and attempts to examine the effectiveness of health-insurance-schemes in reducing out-of-pocket-expenditure (OOPE) and catastrophic-health-expenditure (CHE) in India. Design/methodology/approach Data were extracted from the National-Sample-Survey-Organization, 71st round on Health-2014. Generalized-linear-regression-model was used to investigate the impact of social-protection-schemes on OOPE and CHE. Findings A notable segment of the Indian population is still not covered under any health-insurance-schemes. The majority of the insured population was covered by publicly-financed-health-insurance-schemes (PFHIs), with a trivial-share of private-insurance. Households from 16–59 age-group, urban, literate, richest, southern-regions, using private-facilities and having ear and skin ailments have reported higher insurance coverage. Reimbursement was higher among elderly, literates, middle-class, central-regions, using private-facilities/insurance and for infections. Access to PFHIs significantly reduces the risk of OOPE and CHE. Unavailability of reimbursement exposes the population to a higher risk of CHE. Research limitations/implications Being a study based on secondary data sources, its applicability may vary as per the other social indicators. Practical implications Extending insurance-coverage alone cannot answer the widespread inequalities in health care. Rather, an efficiently managed reimbursement-mechanism could condense OOPE and CHE by enhancing the capability of the population to confront the undue financial burden. Social implications Extending the health-insurance-coverage to the entire population requires a better understanding of the underlying-dynamics and health-care needs and must make health-care affordable by enhancing the overall capability. Originality/value This research brings a theoretical and conceptual analysis for improving the health-insurance coverage among the community as a public health strategy.

scholarly journals Racial Disparities in Virologic Failure and Tolerability During Firstline HIV Antiretroviral Therapy

2019 ◽  
Vol 6 (2) ◽  
Author(s):  
Priya Bhagwat ◽  
Shashi N Kapadia ◽  
Heather J Ribaudo ◽  
Roy M Gulick ◽  
Judith S Currier
Keyword(s):  
Antiretroviral Therapy ◽  
Adverse Events ◽  
Socioeconomic Factors ◽  
Ethnic Groups ◽  
Virologic Failure ◽  
Virologic Suppression ◽  
Factors Associated ◽  
Race Ethnicity ◽  
The Impact ◽  
Racial Ethnic

Abstract Background Racial/ethnic disparities in HIV outcomes have persisted despite effective antiretroviral therapy. In a study of initial regimens, we found viral suppression varied by race/ethnicity. In this exploratory analysis, we use clinical and socioeconomic data to assess factors associated with virologic failure and adverse events within racial/ethnic groups. Methods Data were from AIDS Clinical Trial Group A5257, a randomized trial of initial regimens with either atazanavir/ritonavir, darunavir/ritonavir, or raltegravir (each combined with tenofovir DF and emtricitabine). We grouped participants by race/ethnicity and then used Cox-proportional hazards regression to examine the impact of demographic, clinical, and socioeconomic factors on the time to virologic suppression and time to adverse event reporting within each racial/ethnic group. Results We analyzed data from 1762 participants: 757 self-reported as non-Hispanic black (NHB), 615 as non-Hispanic white (NHW), and 390 as Hispanic. The proportion with virologic failure was higher for NHB (22%) and Hispanic (17%) participants compared with NHWs (9%). Factors associated with virologic failure were poor adherence and higher baseline HIV RNA level. Prior clinical AIDS diagnosis was associated with virologic failure for NHBs only, and unstable housing and illicit drug use for NHWs only. Factors associated with adverse events were female sex in all groups and concurrent use of medications for comorbidities in NHB and Hispanic participants only. Conclusions Clinical and socioeconomic factors that are associated with virologic failure and tolerability of antiretroviral therapy vary between and within racial and ethnic groups. Further research may shed light into mechanisms leading to disparities and targeted strategies to eliminate those disparities.

scholarly journals Demographics associated with US healthcare disparities are exacerbated by the telemedicine surge during the COVID-19 pandemic

2021 ◽  
pp. 1357633X2110259
Author(s):  
Kristin N Gmunder ◽  
Jose W Ruiz ◽  
Dido Franceschi ◽  
Maritza M Suarez
Keyword(s):  
Income Tax ◽  
Healthcare Disparities ◽  
Descriptive Statistics ◽  
Internal Revenue Service ◽  
Patient Specific ◽  
Postal Code ◽  
The Us ◽  
Hispanic Patients ◽  
The Impact ◽  
Racial Ethnic

Introduction As coronavirus disease 2019 (COVID-19) hit the US, there was widespread and urgent implementation of telemedicine programs nationwide without much focus on the impact on patient populations with known existing healthcare disparities. To better understand which populations cannot access telemedicine during the coronavirus disease 2019 pandemic, this study aims to demographically describe and identify the most important demographic predictors of telemedicine visit completion in an urban health system. Methods Patient de-identified demographics and telemedicine visit data ( N = 362,764) between March 1, 2020 and October 31, 2020 were combined with Internal Revenue Service 2018 individual income tax data by postal code. Descriptive statistics and mixed effects logistic regression were used to determine impactful patient predictors of telemedicine completion, while adjusting for clustering at the clinical site level. Results Many patient-specific demographics were found to be significant. Descriptive statistics showed older patients had lower rates of completion ( p < 0.001). Also, Hispanic patients had statistically significant lower rates ( p < 0.001). Overall, minorities (racial, ethnic, and language) had decreased odds ratios of successful telemedicine completion compared to the reference. Discussion While telemedicine use continues to be critical during the coronavirus disease 2019 pandemic, entire populations struggle with access—possibly widening existing disparities. These results contribute large datasets with significant findings to the limited research on telemedicine access and can help guide us in improving telemedicine disparities across our health systems and on a wider scale.

Health Insurance Differentials Among Minority Children With Chronic Conditions and the Role of Federal Agencies and Private Foundations in Improving Financial Access

PEDIATRICS ◽  
1993 ◽  
Vol 91 (5) ◽  
pp. 1040-1047
Author(s):  
Margaret A. McManus ◽  
Paul Newacheck
Keyword(s):  
Health Insurance ◽  
Race And Ethnicity ◽  
Health Care Policy ◽  
Private Insurance ◽  
Insurance Coverage ◽  
Minority Population ◽  
Hispanic Children ◽  
Health Services Use ◽  
Financial Barriers ◽  
White Children

Minorities experience a disproportionate share of the financial barriers resulting from higher rates of uninsuredness and a greater reliance on Medicaid vs private insurance. As a result, health services use and patterns of expenditures vary markedly by race and ethnicity.1,2 National survey data reveal a rapid increase in the number of uninsured black and Hispanic persons between 1977 and 1987.3 The major factors contributing to this increase are (1) overall growth in the size of the minority population, especially Hispanics; (2) reductions in private insurance coverage; and (3) the lack of significant expansions in public programs, largely Medicaid (note: several Medicaid eligibility expansions affecting poor children occurred during and after 1987). In 1987, 14% of white children younger than age 18 were uninsured compared to 22% of black children and 33% of Hispanic children (Cornelius LJ. Unpublished data). Black and Hispanic persons were more likely to rely on Medicaid as their primary financing source than were white persons.3 In 1987, 8% of white children were covered by Medicaid vs 38% of black and 28% of Hispanic children (Cornelius LJ. Unpublished data from the Agency for Health Care Policy and Research, 1992.). Despite Medicaid's importance as a financing source, low reimbursement rates have resulted in inadequate provider participation and corresponding access barriers.4,5 In comparison with white persons, minorities have less access to employer-based insurance benefits. Part of the reason lies in the types of jobs that are disproportionately held by minorities. Personal service and agricultural employers typically do not offer health insurance to their employees.

ARE HEALTH INSURANCE ITEM ALLOCATIONS IN THE AMERICAN COMMUNITY SURVEY MISSING COMPLETELY AT RANDOM?

2013 ◽  
pp. 1-7
Author(s):  
C. SIORDIA
Keyword(s):  
Health Insurance ◽  
Minority Groups ◽  
Insurance Coverage ◽  
Health Insurance Coverage ◽  
Community Survey ◽  
American Community Survey ◽  
Data Sets ◽  
Missing Responses ◽  
Missing Completely At Random ◽  
Racial Ethnic

Background:Item allocation (the assignment of plausible values to missing or illogical responses insurvey studies) is at times necessary in the production of complete data sets. In the American Community Survey(ACS), missing responses to health insurance coverage questions are allocated. Objectives:Because allocationrates may vary as a function of compositional characteristics, this project investigates how seven different healthinsurance coverage items vary in their degree of allocation along basic demographic variables. Methods: Datafrom the ACS 2010 1-year Public Use Microdata Sample file are used in a logistic regression model and tocalculate allocations rates. Results:The findings reveal that: males; people aged 65 and older; those who speakEnglish “very well” or “well”; US citizens; those out-of-poverty; and all racial/ethnic minority groups havehigher odds of experiencing a health insurance item allocation relative to their counterparts. Conclusions: Sincehealth insurance coverage allocations vary by demographic characteristics, further research is needed toinvestigate their mechanisms of missingness and how these may have implications for frailty related research.

scholarly journals The impact of welfare reform on the health insurance coverage, utilization and health of low education single mothers

2017 ◽  
Vol 180 ◽  
pp. 28-35 ◽  
Author(s):  
Kimberly Narain ◽  
Marianne Bitler ◽  
Ninez Ponce ◽  
Gerald Kominski ◽  
Susan Ettner
Keyword(s):  
Health Insurance ◽  
Welfare Reform ◽  
Single Mothers ◽  
Insurance Coverage ◽  
Health Insurance Coverage ◽  
Low Education ◽  
The Impact

Autism and Families' Financial Burden: The Association With Health Insurance Coverage

2015 ◽  
Vol 120 (2) ◽  
pp. 166-175 ◽  
Author(s):  
Susan L. Parish ◽  
Kathleen C. Thomas ◽  
Christianna S. Williams ◽  
Morgan K. Crossman
Keyword(s):  
Health Insurance ◽  
Medical Expenditure Panel Survey ◽  
Financial Burden ◽  
Private Insurance ◽  
Insurance Coverage ◽  
Health Insurance Coverage ◽  
Autism Spectrum ◽  
Medical Expenditure ◽  
Outpatient Services ◽  
Raising Children

Abstract We examined the relationship between family financial burden and children's health insurance coverage in families (n  =  316) raising children with autism spectrum disorders (ASD), using pooled 2000–2009 Medical Expenditure Panel Survey data. Measures of family financial burden included any out-of-pocket spending in the previous year, and spending as a percentage of families' income. Families spent an average of $9.70 per $1,000 of income on their child's health care costs. Families raising children with private insurance were more than 5 times as likely to have any out-of-pocket spending compared to publicly insured children. The most common out-of-pocket expenditure types were medications, outpatient services, and dental care. This study provides evidence of the relative inadequacy of private insurance in meeting the needs of children with ASD.

scholarly journals Racial/ethnic differences in inpatient mortality and use of institutional postacute care following subarachnoid hemorrhage

2013 ◽  
Vol 119 (6) ◽  
pp. 1627-1632 ◽  
Author(s):  
Blessing N. R. Jaja ◽  
Gustavo Saposnik ◽  
Rosane Nisenbaum ◽  
Benjamin W. Y. Lo ◽  
Tom A. Schweizer ◽  
...  
Keyword(s):  
Subarachnoid Hemorrhage ◽  
Ethnic Groups ◽  
Ethnic Differences ◽  
Institutional Care ◽  
Inpatient Mortality ◽  
Risk Of Death ◽  
The Us ◽  
Hispanic Patients ◽  
Racial Ethnic ◽  
White Patients

Object The goal of this study was to determine racial/ethnic differences in inpatient mortality rates and the use of institutional postacute care following subarachnoid hemorrhage (SAH) in the US. Methods A cross-sectional study of hospital discharges for SAH was conducted using the Nationwide Inpatient Sample for the years 2005–2010. Discharges with a principal diagnosis of SAH were identified and abstracted using the appropriate ICD-9-CM diagnostic code. Racial/ethnic groups were defined as white, black, Hispanic, Asian/Pacific Islander (API), and American Indian. Multinomial logistic regression analyses were performed comparing racial/ethnic groups with respect to the primary outcome of risk of in-hospital mortality and the secondary outcome of likelihood of discharge to institutional care. Results During the study period, 31,631 discharges were related to SAH. Race/ethnicity was a significant predictor of death (p = 0.003) and discharge to institutional care (p ≤ 0.001). In the adjusted analysis, compared with white patients, API patients were at higher risk of death (OR 1.34, 95% CI 1.13–1.59) and Hispanic patients were at lower risk of death (OR 0.84, 95% CI 0.72–0.97). The likelihood of discharge to institutional care was statistically similar between white, Hispanic, API, and Native American patients. Black patients were more likely to be discharged to institutional care compared with white patients (OR 1.27, 95% CI 1.14–1.40), but were similar to white patients in the risk of death. Conclusions Significant racial/ethnic differences are present in the risk of inpatient mortality and discharge to institutional care among patients with SAH in the US. Outcome is likely to be poor among API patients and best among Hispanic patients compared with other groups.

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