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

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.

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The impact of health insurance coverage on pediatric diabetes management

Diabetes Research and Clinical Practice ◽

10.1016/j.diabres.2010.06.013 ◽

2010 ◽

Vol 90 (1) ◽

pp. 40-44 ◽

Cited By ~ 10

Author(s):

Kupper A. Wintergerst ◽

Krystal M. Hinkle ◽

Christopher N. Barnes ◽

Adetokunbo O. Omoruyi ◽

Michael B. Foster

Keyword(s):

Health Insurance ◽

Diabetes Management ◽

Insurance Coverage ◽

Health Insurance Coverage ◽

Pediatric Diabetes ◽

The Impact

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Health insurance coverage among foreign-born US residents: the impact of race, ethnicity, and length of residence.

American Journal of Public Health ◽

10.2105/ajph.87.1.96 ◽

1997 ◽

Vol 87 (1) ◽

pp. 96-102 ◽

Cited By ~ 104

Author(s):

M Thamer ◽

C Richard ◽

A W Casebeer ◽

N F Ray

Keyword(s):

Health Insurance ◽

Insurance Coverage ◽

Health Insurance Coverage ◽

Foreign Born ◽

Length Of Residence ◽

Race Ethnicity ◽

The Impact

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

Ethnicity & Disease ◽

10.18865/ed.31.1.149 ◽

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

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The Impact of the ACA Medicaid Expansions on Health Insurance Coverage through 2015 and Coverage Disparities by Age, Race/Ethnicity, and Gender

Health Services Research ◽

10.1111/1475-6773.12711 ◽

2017 ◽

Vol 53 (2) ◽

pp. 1248-1271 ◽

Cited By ~ 39

Author(s):

George L. Wehby ◽

Wei Lyu

Keyword(s):

Health Insurance ◽

Insurance Coverage ◽

Health Insurance Coverage ◽

Race Ethnicity ◽

And Gender ◽

Ethnicity And Gender ◽

The Impact ◽

Medicaid Expansions

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The convergence of racial and income disparities in health insurance coverage in the United States

International Journal for Equity in Health ◽

10.1186/s12939-021-01436-z ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

De-Chih Lee ◽

Hailun Liang ◽

Leiyu Shi

Keyword(s):

Health Insurance ◽

Low Income ◽

Insurance Coverage ◽

Health Insurance Coverage ◽

The United States ◽

Combined Effect ◽

Medical Expenditure ◽

The Us ◽

Race Ethnicity ◽

Vulnerability Measure

Abstract Objective This study applied the vulnerability framework and examined the combined effect of race and income on health insurance coverage in the US. Data source The household component of the US Medical Expenditure Panel Survey (MEPS-HC) of 2017 was used for the study. Study design Logistic regression models were used to estimate the associations between insurance coverage status and vulnerability measure, comparing insured with uninsured or insured for part of the year, insured for part of the year only, and uninsured only, respectively. Data collection/extraction methods We constructed a vulnerability measure that reflects the convergence of predisposing (race/ethnicity), enabling (income), and need (self-perceived health status) attributes of risk. Principal findings While income was a significant predictor of health insurance coverage (a difference of 6.1–7.2% between high- and low-income Americans), race/ethnicity was independently associated with lack of insurance. The combined effect of income and race on insurance coverage was devastating as low-income minorities with bad health had 68% less odds of being insured than high-income Whites with good health. Conclusion Results of the study could assist policymakers in targeting limited resources on subpopulations likely most in need of assistance for insurance coverage. Policymakers should target insurance coverage for the most vulnerable subpopulation, i.e., those who have low income and poor health as well as are racial/ethnic minorities.

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

Journal of Frailty & Aging ◽

10.14283/jfa.2013.29 ◽

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.

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