Insurance patterns and instability from 2006 to 2016

Autor: Yunwei Gai, Kent Jones
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: BMC Health Services Research, Vol 20, Iss 1, Pp 1-12 (2020)
Druh dokumentu: article
ISSN: 1472-6963
DOI: 10.1186/s12913-020-05226-1
Popis: Abstract Background There is a rich literature on insurance coverage and its impacts on health care. Many recent studies have examined the impacts of the Affordable Care Act (ACA) and found that it had positive effects on health insurance coverage and health care usage. Most of the literature, however, has focused on insurance coverage at a single point in time, while research on insurance instability is underrepresented, even though it could significantly impact health outcomes. The aim of this study is to examine changes and implications of insurance instability among nonelderly adults from 2006 to 2016, covering the Great Recession and post-ACA periods. Methods Using 2006-to-2016 Medical Expenditure Panel Survey data, we identify seven insurance patterns and analyze them by race/ethnicity, age, geography, income, and medical conditions. We then use multivariable linear models to analyze the relationship between insurance instability and health care status, access, and utilization. Logistic, Poisson and nonlinear models test the robustness of our results. Results The post-ACA period 2015–2016 saw the lowest ever-uninsured rate (25.68% or 67.91 million). The largest decrease in insurance instability was among adults aged 19–25, low-income families, Hispanics, the western population, and the healthy population. Like the always-uninsured, those with other insurance gaps experienced a lack of access to care and decreased preventive care and other services. Conclusions Despite the post-ACA instability reduction, over 25% of the U.S. population continued to have insurance gaps over a two-year period. Disparities continued to exist between income groups, race/ethnicities, and regions. Repealing ACA could exacerbate insurance instability and disparities between different groups, which in turn could lead to adverse health outcomes.
Databáze: Directory of Open Access Journals
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