Understanding contributors to racial and ethnic inequities in COVID-19 incidence and mortality rates

BACKGROUND: Racial inequities in Coronavirus 2019 (COVID-19) have been reported over the course of the pandemic, with Black, Hispanic/Latinx, and Native American individuals suffering higher case rates and more fatalities than their White counterparts. METHODS: We used a unique statewide dataset of confirmed COVID-19 cases across Missouri, linked with historical statewide hospital data. We examined differences by race and ethnicity in raw population-based case and mortality rates. We used patient-level regression analyses to calculate the odds of mortality based on race and ethnicity, controlling for comorbidities and other risk factors. RESULTS: As of September 10, 2020 there were 73,635 confirmed COVID-19 cases in the State of Missouri. Among the 64,526 case records (87.7% of all cases) that merged with prior demographic and health care utilization data, 12,946 (20.1%) were Non-Hispanic (NH) Black, 44,550 (69.0%) were NH White, 3,822 (5.9%) were NH Other/Unknown race, and 3,208 (5.0%) were Hispanic. Raw cumulative case rates for NH Black individuals were 1,713 per 100,000 population, compared with 2,095 for NH Other/Unknown, 903 for NH White, and 1,218 for Hispanic. Cumulative COVID-19-related death rates for NH Black individuals were 58.3 per 100,000 population, compared with 38.9 for NH Other/Unknown, 19.4 for NH White, and 14.8 for Hispanic. In a model that included insurance source, history of a social determinant billing code in the patient\u27s claims, census block travel change, population density, Area Deprivation Index, and clinical comorbidities, NH Black race (OR 1.75, 1.51-2.04, p\u3c0.001) and NH Other/Unknown race (OR 1.83, 1.36-2.46, p\u3c0.001) remained strongly associated with mortality. CONCLUSIONS: In Missouri, COVID-19 case rates and mortality rates were markedly higher among NH Black and NH Other/Unknown race than among NH White residents, even after accounting for social and clinical risk, population density, and travel patterns during COVID-19

Understanding drivers of coronavirus disease 2019 (COVID-19) racial disparities: A population-level analysis of COVID-19 testing among black and white populations

BACKGROUND: Disparities in coronavirus disease 2019 (COVID-19) testing-the pandemic\u27s most critical but limited resource-may be an important but modifiable driver of COVID-19 inequities. METHODS: We analyzed data from the Missouri State Department of Health and Senior Services on all COVID-19 tests conducted in the St Louis and Kansas City regions. We adapted a well-established tool for measuring inequity-the Lorenz curve-to compare COVID-19 testing rates per diagnosed case among Black and White populations. RESULTS: Between 14/3/2020 and 15/9/2020, 606 725 and 328 204 COVID-19 tests were conducted in the St Louis and Kansas City regions, respectively. Over time, Black individuals consistently had approximately half the rate of testing per case than White individuals. In the early period (14/3/2020 to 15/6/2020), zip codes in the lowest quartile of testing rates accounted for only 12.1% and 8.8% of all tests in the St Louis and Kansas City regions, respectively, even though they accounted for 25% of all cases in each region. These zip codes had higher proportions of residents who were Black, without insurance, and with lower median incomes. These disparities were reduced but still persisted during later phases of the pandemic (16/6/2020 to 15/9/2020). Last, even within the same zip code, Black residents had lower rates of tests per case than White residents. CONCLUSIONS: Black populations had consistently lower COVID-19 testing rates per diagnosed case than White populations in 2 Missouri regions. Public health strategies should proactively focus on addressing equity gaps in COVID-19 testing to improve equity of the overall response

The disproportionate impact of COVID-19 on black and African American communities in the St. Louis region

The novel coronavirus has had a widely varied impact on different communities in the St. Louis region. This analysis cannot fully explain the causal pathway of observed disparities in COVID-19 for communities of color in the St. Louis region. Namely, the data do not account for differences in other community risk factors such as socioeconomic status, population density, household composition, labor force composition, including the proportion of essential workers, the related ability of individuals in different areas to shelter at home versus continuing to work, presence of comorbid conditions or prevalence of testing. In truth, race is linked with many of these factors, and a deeper exploration of these relationships using patient-level data is needed to disentangle the myriad potential contributors to these findings and to help inform policy and public health solutions. As such, a mixed methods approach using a race-conscious lens and systems-oriented framework is needed to provide contextually nuanced insights on the drivers of disparities to inform thoughtful mitigation strategies among institutional leaders and policymakers

Association of Stratification by Dual Enrollment Status With Financial Penalties in the Hospital Readmissions Reduction Program

Importance: Beginning in fiscal year 2019, Medicare\u27s Hospital Readmissions Reduction Program (HRRP) stratifies hospitals into 5 peer groups based on the proportion of each hospital\u27s patient population that is dually enrolled in Medicare and Medicaid. The effect of this policy change is largely unknown. Objective: To identify hospital and state characteristics associated with changes in HRRP-related performance and penalties after stratification. Design, Setting, and Participants: A cross-sectional analysis was performed of all 3049 hospitals participating in the HRRP in fiscal years 2018 and 2019, using publicly available data on hospital penalties, merged with information on hospital characteristics and state Medicaid eligibility cutoffs. Exposures: The HRRP, under the 2018 traditional method and the 2019 stratification method. Main Outcomes and Measures: Performance on readmissions, as measured by the excess readmissions ratio, and penalties under the HRRP both in relative percentage change and in absolute dollars. Results: The study sample included 3049 hospitals. The mean proportion of dually enrolled beneficiaries ranged from 9.5% in the lowest quintile to 44.7% in the highest quintile. At the hospital level, changes in penalties ranged from an increase of $225 000 to a decrease of more than$436 000 after stratification. In total, hospitals in the lowest quintile of dual enrollment saw an increase of $12 330 157 in penalties, while those in the highest quintile of dual enrollment saw a decrease of$22 445 644. Teaching hospitals (odds ratio [OR], 2.13; 95% CI, 1.76-2.57; P \u3c .001) and large hospitals (OR, 1.51; 95% CI, 1.22-1.86; P \u3c .001) had higher odds of receiving a reduced penalty. Not-for-profit hospitals (OR, 0.64; 95% CI, 0.52-0.80; P \u3c .001) were less likely to have a penalty reduction than for-profit hospitals, and hospitals in the Midwest (OR, 0.44; 95% CI, 0.34-0.57; P \u3c .001) and South (OR, 0.42; 95% CI, 0.30-0.57; P \u3c .001) were less likely to do so than hospitals in the Northeast. Hospitals with patients from the most disadvantaged neighborhoods (OR, 2.62; 95% CI, 2.03-3.38; P \u3c .001) and those with the highest proportion of beneficiaries with disabilities (OR, 3.12; 95% CI, 2.50-3.90; P \u3c .001) were markedly more likely to see a reduction in penalties, as were hospitals in states with the highest Medicaid eligibility cutoffs (OR, 1.79; 95% CI, 1.50-2.14; P \u3c .001). Conclusions and Relevance: Stratification of the hospitals under the HRRP was associated with a significant shift in penalties for excess readmissions. Policymakers should monitor the association of this change with readmission rates as well as hospital financial performance as the policy is fully implemented

Adjusting for social risk factors impacts performance and penalties in the hospital readmissions reduction program

OBJECTIVE: Medicare\u27s Hospital Readmissions Reduction Program (HRRP) does not account for social risk factors in risk adjustment, and this may lead the program to unfairly penalize safety-net hospitals. Our objective was to determine the impact of adjusting for social risk factors on HRRP penalties. STUDY DESIGN: Retrospective cohort study. DATA SOURCES/STUDY SETTING: Claims data for 2 952 605 fee-for-service Medicare beneficiaries with acute myocardial infarction (AMI), congestive heart failure (CHF) or pneumonia from December 2012 to November 2015. PRINCIPAL FINDINGS: Poverty, disability, housing instability, residence in a disadvantaged neighborhood, and hospital population from a disadvantaged neighborhood were associated with higher readmission rates. Under current program specifications, safety-net hospitals had higher readmission ratios (AMI, 1.020 vs 0.986 for the most affluent hospitals; pneumonia, 1.031 vs 0.984; and CHF, 1.037 vs 0.977). Adding social factors to risk adjustment cut these differences in half. Over half the safety-net hospitals saw their penalty decline; 4-7.5 percent went from having a penalty to having no penalty. These changes translated into a $17 million reduction in penalties to safety-net hospitals. CONCLUSIONS: Accounting for social risk can have a major financial impact on safety-net hospitals. Adjustment for these factors could reduce negative unintended consequences of the HRRP