Racial and ethnic disparities in H1N1 vaccine uptake in Medicaid: Lessons learned for a COVID-19 vaccine rollout.

BACKGROUND: Racial and ethnic minorities in the US have been disproportionately affected by the COVID-19 pandemic and are at risk for disparities in COVID-19 vaccinations. The H1N1 flu vaccine experience provides lessons learned to address and prevent racial and ethnic disparities in COVID-19 vaccinations. We aim to identify racial/ethnic and geographic disparities in H1N1 vaccinations among Medicaid enrollees to inform equitable COVID-19 vaccination policies and strategies. METHODS: The study population included people under 65 who were continuously enrolled in Medicaid in 2009 and 2010 from 28 states and the District of Columbia. H1N1 vaccinations were identified from Medicaid outpatient claims. Vaccination rates were calculated for the overall sample and subpopulations by race/ethnicity and state. RESULTS: 3,708,894 (12.3%) Medicaid enrollees in the sample were vaccinated for H1N1 in 2009-2010. Race-specific vaccination rates ranged from 8.1% in American Indian/Alaska Native (AI/AN) to 19.8% in Asian/Pacific Islander Medicaid enrollees. NHB enrollees had lower vaccination rates than non-Hispanic White (NHW) enrollees in all states, with the exceptions of Maryland, Missouri, Ohio, and Washington. The largest disparity between NHB and NHW was in Pennsylvania (1.0% vs. 7.0%), while the largest absolute difference between NHB and NHW enrollees was in Georgia (17.4% vs. 30.7%). CONCLUSIONS: Our study found huge variation in H1N1 vaccinations across states and racial/ethnic disparities in H1N1 vaccinations within states. In most states, NHB and AI/AN Medicaid enrollees had lower vaccination rates than Whites. Hispanic and Asian/Pacific Islander Medicaid enrollees in most states had higher vaccination rates than Whites.

Population-Level Disparities in COVID-19: Measuring the Independent Association of the Proportion of Black Population on COVID-19 Cases and Deaths in US Counties.

CONTEXT: There is a need to understand population race and ethnicity disparities in the context of sociodemographic risk factors in the US experience of the COVID-19 pandemic. OBJECTIVE: Determine the association between county-level proportion of non-Hispanic Black (NHB) on county COVID-19 case and death rates and observe how this association was influenced by county sociodemographic and health care infrastructure characteristics. DESIGN AND SETTING: This was an ecologic analysis of US counties as of September 20, 2020, that employed stepwise construction of linear and negative binomial regression models. The primary independent variable was the proportion of NHB population in the county. Covariates included county demographic composition, proportion uninsured, proportion living in crowded households, proportion living in poverty, population density, state testing rate, Primary Care Health Professional Shortage Area status, and hospital beds per 1000 population. MAIN OUTCOME MEASURES: Outcomes were exponentiated COVID-19 cases per 100 000 population and COVID-19 deaths per 100 000 population. We produced county-level maps of the measures of interest. RESULTS: In total, 3044 of 3142 US counties were included. Bivariate relationships between the proportion of NHB in a county and county COVID-19 case (Exp ß = 1.026; 95% confidence interval [CI], 1.024-1.028; P < .001) and death rates (rate ratio [RR] = 1.032; 95% CI, 1.029-1.035; P < .001) were not attenuated in fully adjusted models. The adjusted association between the proportion of NHB population in a county and county COVID-19 case was Exp ß = 1.025 (95% CI, 1.023-1.027; P < .001) and the association with county death rates was RR = 1.034 (95% CI, 1.031-1.038; P < .001). CONCLUSIONS: The proportion of NHB people in a county was positively associated with county COVID-19 case and death rates and did not change in models that accounted for other socioecologic and health care infrastructure characteristics that have been hypothesized to account for the disproportionate impact of COVID-19 on racial and ethnic minority populations. Results can inform efforts to mitigate the impact of structural racism of COVID-19.

Does adoption of an evidence-based practice lead to job turnover? Results from a randomized trial.

It is important to understand the impact of implementation of evidence-based practices (EBPs) on the workforce. EBP implementation can increase job demands, stress, and burnout, and may thereby exacerbate turnover. This study examined the effects of implementation of an EBP on turnover among staff at nine child welfare agencies. A total of 102 providers were randomized to either adopt an EBP, SafeCare© , or continue providing services as usual. Participants completed a baseline survey assessing demographics, attitudes toward EBPs, and organizational functioning, and provider turnover was recorded for up to 18 months following implementation. The overall turnover rate was 35%, but did not differ by EBP assignment (odds ratio [OR] = 1.27; 95% confidence interval [0.66, 2.45]). Variables associated with turnover included age (OR = 0.92), years since degree completion (OR = 0.94), prior exposure to EBP (OR = 3.91), believing that adopting an EBP was burdensome (OR = 0.52), and motivation for change (OR = 0.89). EBP assignment moderated two aspects of negative attitudes toward EBP (divergence and monitoring) to predict turnover; those attitudes were only positively related to turnover for individuals assigned to the EBP (OR = 1.46, 1.16). Implications of the findings for implementation are discussed.