RESUMEN
Objectives. To report insurance-based discrimination rates for nonelderly adults with private, public, or no insurance between 2011 and 2019, a period marked by passage and implementation of the Affordable Care Act (ACA) and threats to it. Methods. We used 2011-2019 data from the biennial Minnesota Health Access Survey. Each year, about 4000 adults aged 18 to 64 years report experiences with insurance-based discrimination. Using logistic regressions, we examined associations between insurance-based discrimination and (1) sociodemographic factors and (2) indicators of access. Results. Insurance-based discrimination was stable over time and consistently related to insurance type: approximately 4% for adults with private insurance compared with adults with public insurance (21%) and no insurance (27%). Insurance-based discrimination persistently interfered with confidence in getting needed care and forgoing care. Conclusions. Policy changes from 2011 to 2019 affected access to health insurance, but high rates of insurance-based discrimination among adults with public insurance or no insurance were impervious to such changes. Public Health Implications. Stable rates of insurance-based discrimination during a time of increased access to health insurance via the ACA suggest deeper structural roots of health care inequities. We recommend several policy and system solutions. (Am J Public Health. 2023;113(2):213-223. https://doi.org/10.2105/AJPH.2022.307126).
Asunto(s)
Cobertura del Seguro , Patient Protection and Affordable Care Act , Estados Unidos , Adulto , Humanos , Accesibilidad a los Servicios de Salud , Seguro de Salud , MinnesotaRESUMEN
SARS-CoV-2 is primarily transmitted through person-to-person contacts. It is important to collect information on age-specific contact patterns because SARS-CoV-2 susceptibility, transmission, and morbidity vary by age. To reduce the risk of infection, social distancing measures have been implemented. Social contact data, which identify who has contact with whom especially by age and place are needed to identify high-risk groups and serve to inform the design of non-pharmaceutical interventions. We estimated and used negative binomial regression to compare the number of daily contacts during the first round (April-May 2020) of the Minnesota Social Contact Study, based on respondent's age, gender, race/ethnicity, region, and other demographic characteristics. We used information on the age and location of contacts to generate age-structured contact matrices. Finally, we compared the age-structured contact matrices during the stay-at-home order to pre-pandemic matrices. During the state-wide stay-home order, the mean daily number of contacts was 5.7. We found significant variation in contacts by age, gender, race, and region. Adults between 40 and 50 years had the highest number of contacts. The way race/ethnicity was coded influenced patterns between groups. Respondents living in Black households (which includes many White respondents living in inter-racial households with black family members) had 2.7 more contacts than respondents in White households; we did not find this same pattern when we focused on individual's reported race/ethnicity. Asian or Pacific Islander respondents or in API households had approximately the same number of contacts as respondents in White households. Respondents in Hispanic households had approximately two fewer contacts compared to White households, likewise Hispanic respondents had three fewer contacts than White respondents. Most contacts were with other individuals in the same age group. Compared to the pre-pandemic period, the biggest declines occurred in contacts between children, and contacts between those over 60 with those below 60.
Asunto(s)
COVID-19 , SARS-CoV-2 , Adulto , Niño , Humanos , COVID-19/epidemiología , COVID-19/prevención & control , Minnesota/epidemiología , Distanciamiento Físico , EtnicidadRESUMEN
OBJECTIVES: We examined reports of insurance-based discrimination and its association with insurance type and access to care in the early years of the Patient Protection and Affordable Care Act. METHODS: We used data from the 2013 Minnesota Health Access Survey to identify 4123 Minnesota adults aged 18 to 64 years who reported about their experiences of insurance-based discrimination. We modeled the association between discrimination and insurance type and predicted odds of having reduced access to care among those reporting discrimination, controlling for sociodemographic factors. Data were weighted to represent the state's population. RESULTS: Reports of insurance-based discrimination were higher among uninsured (25%) and publicly insured (21%) adults than among privately insured adults (3%), which held in the regression analysis. Those reporting discrimination had higher odds of lacking a usual source of care, lacking confidence in getting care, forgoing care because of cost, and experiencing provider-level barriers than those who did not. CONCLUSIONS: Further research and policy interventions are needed to address insurance-based discrimination in health care settings.