Racial/Ethnic Disparities in Health Insurance Status Among California Women, 1998

2001 ◽  
Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 5004-5004
Author(s):  
Maria E Santaella ◽  
Michelle L Witkop ◽  
Cynthia Nichols ◽  
Rosaura Vidal ◽  
Leonard A. Valentino

Abstract Background: Community Voices in Research (CVR) is the National Hemophilia Foundation's community-powered registry designed to provide researchers with a firsthand, 360-degree view of what it means to live with an inherited bleeding disorder (IBD) by providing insight on a wide range of areas previously not evaluated or under-evaluated in this population. Since 2019, information has been collected from those with an IBD as well as their immediate family members/caregivers. Previous QOL data-collection efforts have been narrow in scope or duration and/or relied on HCP-reported data. The self-reported, confidential, de-identified aggregate CVR data are used to improve clinical outcomes and quality of life for people with IBDs and identify research questions important to the community. Methods : Participants complete an enrollment survey followed by the baseline then annual surveys. Additional surveys focused on specific areas of interest are issued periodically. Participants provide demographic data including race, ethnicity, level of education, household income, employment, and health-insurance status. External researchers of various collaborations may apply for access to the de-identified, aggregate data, launch individual surveys, or invite participants to virtual advisory panels. All research findings are communicated to its participants through a personalized CVR dashboard. Results : White/Caucasians make up 86.9% of registrants; (11.3%) include Black/African American; Asian; South Asian; Alaska Native; American Indian; Middle Eastern; and Native Hawaiian/Pacific Islander and any combination of those who identify as white/Caucasian plus another race; 1.8% indicated that their race was unknown or that they preferred not to answer. Ethnicity was reported as Hispanic/Latino(a) (51%), not Hispanic/Latino(a) (46.6%), and unknown/prefer not to answer (2.4%). Demographic data reveal significant disparities between white/Caucasian/non-Hispanic (WCNH) and other CVR participants in key social determinants of health, including education level, household income, employment, and health-insurance status. Tables 1-4 provide a detailed breakdown. Education: The majority of WCNH participants (64.2%) reported having college/graduate/professional-level education, while among others, most (59.4%) reported having a trade/vocational school-level education. Annual household income: The majority of WCNHs participants (57.5%) reported earnings between $50K-$149K. In contrast, the large majority (71.2%) of others reported earning $35K-$49K annually. For WCNHs participants, the midpoint of income range divided by number of people in the household was more than double that of other participants ($31,249 vs. $14,166). Employment: Significant differences between the groups in employment were seen. WCNH participants were more likely to be employed full-time (58.6%), disabled (30%), retired (30%), homemaker (15.7%), or a student (11.4%). Other participants were more likely to be employed part-time (32.5%) or unemployed (51.3%), or able to work but were unemployed (75.2%). Health insurance: A particularly stark disparity was noted in health-insurance type. Among WCNHs, 50.1% reported insurance through an employer or union, while only 15.8% of others fit this category. Among others, the majority (76.9%) reported enrollment in Medicaid or other public income-based insurance (vs. 13% of WCNHs). Conclusions: The demographic disparities between WCNHs and other participants in the CVR are critical and emphasize the need to focus on correlations between known social determinants of health and self-reported health outcomes and quality-of-life information. It is well known that education level and type of insurance, for example, can have a significantly negative impact on factors such as access to treatments and healthcare and medication adherence. CVR recruitment efforts must focus on enrolling racially and ethnically diverse participants to better understand their patient journey. This will enable the characterization of the links between racial/ethnic disparities and differences in access to care, quality of life, and related issues in the IBD community, and tailor education and advocacy efforts. As CVR data are extracted to answer a host of research questions, ensuring the inclusion of demographic disparities will benefit all members of the IBD community. Figure 1 Figure 1. Disclosures Witkop: Teralmmune, Inc.: Consultancy. Valentino: Spark: Ended employment in the past 24 months.


2021 ◽  
pp. 003335492199917
Author(s):  
Lindsey A. Jones ◽  
Katherine C. Brewer ◽  
Leslie R. Carnahan ◽  
Jennifer A. Parsons ◽  
Blase N. Polite ◽  
...  

Objective For colon cancer patients, one goal of health insurance is to improve access to screening that leads to early detection, early-stage diagnosis, and polyp removal, all of which results in easier treatment and better outcomes. We examined associations among health insurance status, mode of detection (screen detection vs symptomatic presentation), and stage at diagnosis (early vs late) in a diverse sample of patients recently diagnosed with colon cancer from the Chicago metropolitan area. Methods Data came from the Colon Cancer Patterns of Care in Chicago study of racial and socioeconomic disparities in colon cancer screening, diagnosis, and care. We collected data from the medical records of non-Hispanic Black and non-Hispanic White patients aged ≥50 and diagnosed with colon cancer from October 2010 through January 2014 (N = 348). We used logistic regression with marginal standardization to model associations between health insurance status and study outcomes. Results After adjusting for age, race, sex, and socioeconomic status, being continuously insured 5 years before diagnosis and through diagnosis was associated with a 20 (95% CI, 8-33) percentage-point increase in prevalence of screen detection. Screen detection in turn was associated with a 15 (95% CI, 3-27) percentage-point increase in early-stage diagnosis; however, nearly half (47%; n = 54) of the 114 screen-detected patients were still diagnosed at late stage (stage 3 or 4). Health insurance status was not associated with earlier stage at diagnosis. Conclusions For health insurance to effectively shift stage at diagnosis, stronger associations are needed between health insurance and screening-related detection; between screening-related detection and early stage at diagnosis; or both. Findings also highlight the need to better understand factors contributing to late-stage colon cancer diagnosis despite screen detection.


Sci ◽  
2021 ◽  
Vol 3 (2) ◽  
pp. 25
Author(s):  
Jesse Patrick ◽  
Philip Q. Yang

The Affordable Care Act (ACA) is at the crossroads. It is important to evaluate the effectiveness of the ACA in order to make rational decisions about the ongoing healthcare reform, but existing research into its effect on health insurance status in the United States is insufficient and descriptive. Using data from the National Health Interview Surveys from 2009 to 2015, this study examines changes in health insurance status and its determinants before the ACA in 2009, during its partial implementation in 2010–2013, and after its full implementation in 2014 and 2015. The results of trend analysis indicate a significant increase in national health insurance rate from 82.2% in 2009 to 89.4% in 2015. Logistic regression analyses confirm the similar impact of age, gender, race, marital status, nativity, citizenship, education, and poverty on health insurance status before and after the ACA. Despite similar effects across years, controlling for other variables, youth aged 26 or below, the foreign-born, Asians, and other races had a greater probability of gaining health insurance after the ACA than before the ACA; however, the odds of obtaining health insurance for Hispanics and the impoverished rose slightly during the partial implementation of the ACA, but somewhat declined after the full implementation of the ACA starting in 2014. These findings should be taken into account by the U.S. Government in deciding the fate of the ACA.


Author(s):  
Gaon-Sorae Wang ◽  
Kyoung-Min You ◽  
You-Hwan Jo ◽  
Hui-Jai Lee ◽  
Jong-Hwan Shin ◽  
...  

(1) Background: Sepsis is a life-threatening disease, and various demographic and socioeconomic factors affect outcomes in sepsis. However, little is known regarding the potential association between health insurance status and outcomes of sepsis in Korea. We evaluated the association of health insurance and clinical outcomes in patients with sepsis. (2) Methods: Prospective cohort data of adult patients with sepsis and septic shock from March 2016 to December 2018 in three hospitals were retrospectively analyzed. We categorized patients into two groups according to their health insurance status: National Health Insurance (NHI) and Medical Aid (MA). The primary end point was in-hospital mortality. The multivariate logistic regression model and propensity score matching were used. (3) Results: Of a total of 2526 eligible patients, 2329 (92.2%) were covered by NHI, and 197 (7.8%) were covered by MA. The MA group had fewer males, more chronic kidney disease, more multiple sources of infection, and more patients with initial lactate > 2 mmol/L. In-hospital, 28-day, and 90-day mortality were not significantly different between the two groups and in-hospital mortality was not different in the subgroup analysis. Furthermore, health insurance status was not independently associated with in-hospital mortality in multivariate analysis and was not associated with survival outcomes in the propensity score-matched cohort. (4) Conclusion: Our propensity score-matched cohort analysis demonstrated that there was no significant difference in in-hospital mortality by health insurance status in patients with sepsis.


2013 ◽  
Vol 173 (22) ◽  
pp. 2047 ◽  
Author(s):  
Keith S. Goldfeld ◽  
David C. Grabowski ◽  
Daryl J. Caudry ◽  
Susan L. Mitchell

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