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Promising Practices that show evidence of effectiveness in improving public health outcomes in a specific real-life setting, as indicated by achievement of aims consistent with the objectives of the activities, and are suitable for adaptation by other communities.
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Other
This episode from the podcast 99 Percent Invisible reflects on how the COVID-19 pandemic exposed the American public to a long-standing problem: the disjointed nature of the U.S. health system. Because state and local health departments largely operate independently and use their own data collection and analysis tools, health systems across the country lack standardized data definitions and systems. These inconsistencies made it nearly impossible to collect and analyze comprehensive, standardized data on COVID-19 cases, deaths, and vaccines administered amid the pandemic. Health experts featured on this episode believe that the pandemic made the need for an overhaul of America’s informatics system very apparent. When rebuilding this system, it’s important to focus on remedying existing inequalities in data collection and classification that in some cases render the health status of certain populations – think Native American communities and other communities of color – completely invisible in the data. By virtue of being small populations, it can be difficult for health departments to collect sufficient and/or statistically significant data on minority communities. Another issue discussed in this episode is the use of broad racial categories like “other,” “multiple races,” or even “Asian American,” which, if not disaggregated, obscures the health status of diverse populations who are grouped under the same category. Without comprehensive and inclusive health data, it’s difficult to identify disparities and implement policies and programming that promote social mobility and health equity.
Best Practices that show evidence of effectiveness in improving public health outcomes when implemented in multiple real-life settings, as indicated by achievement of aims consistent with the objectives of the activities.
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Systematic Review/Meta-Analysis
This review of state data collection and reporting practices during the COVID-19 pandemic found inconsistencies and gaps in data collected by race and ethnicity. Improved standardization across the U.S.–which may come in the form of a federally-operated centralized database–would address some of the concerns in data representation of all Americans.
Promising Practices that show evidence of effectiveness in improving public health outcomes in a specific real-life setting, as indicated by achievement of aims consistent with the objectives of the activities, and are suitable for adaptation by other communities.
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Peer Review Study
This analysis identifies risk factors and socio-economic impacts of long COVID with a public health lens. It notes that more analysis is needed, but encourages the impacts of long COVID to be seen within a larger social, and not just medical, context. Workplace and family structure implications are substantial. Long COVID should be tracked as distinct condition using person-centered research techniques that include traditionally underrepresented populations such as children.
Promising Practices that show evidence of effectiveness in improving public health outcomes in a specific real-life setting, as indicated by achievement of aims consistent with the objectives of the activities, and are suitable for adaptation by other communities.
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White Paper/Brief
This brief lists interventions to support state public health efforts to address rural disparities and racial discrimination. It emphasizes the importance of localized data on social determinants of health and improving systemic and structural underpinnings of racial disparities. Suggested interventions address data collection and workforce issues, including representativeness and paid family leave.
Promising Practices that show evidence of effectiveness in improving public health outcomes in a specific real-life setting, as indicated by achievement of aims consistent with the objectives of the activities, and are suitable for adaptation by other communities.
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Peer Review Study
This article examines a cohort study of children in England to determine a possible association between COVID-19 testing rates, COVID-19 mortality rates, and race. Results found that Asian and Black children experienced race-specific disparities when compared to white children, with white children receiving more COVID-19 testing, but Black and Asian children experiencing worse outcomes, including hospitalization, ICU admission, and death.
Emerging Practices that show potential to achieve desirable public health outcomes in a specific real-life setting and produce early results that are consistent with the objectives of the activities and thus indicate effectiveness.
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Peer Review Study
This article describes the survey results of 33 Black adolescents (ages 12-17) living in Southeastern United States during the COVID-19 pandemic. The survey illustrates stressors and barriers for these teenagers, citing financial issues, access to health care, and increased mental health strain as key issues during the pandemic. These answers could provide context for addressing issues within this population.
Best Practices that show evidence of effectiveness in improving public health outcomes when implemented in multiple real-life settings, as indicated by achievement of aims consistent with the objectives of the activities.
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Peer Review Study
This is an assessment of the association between hospitalization for illness from COVID-19 infection and chronic conditions among Medicare beneficiaries (MBs) with fee-for-service (FFS) claims by race and ethnicity for January 1–September 30, 2020. Racial/ethnic disparities in hospitalization rates persist among MBs with COVID-19, and associations of COVID-19 hospitalization with chronic conditions differ among racial/ethnic groups in the U.S.
Emerging Practices that show potential to achieve desirable public health outcomes in a specific real-life setting and produce early results that are consistent with the objectives of the activities and thus indicate effectiveness.
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Commentary
This story is part of a series, “Race Matters.” It highlights the problems with inconsistent data collection and reporting for Native Hawaiians and Pacific Islanders. Native Hawaiians and Pacific Islanders are often grouped with Asians or not tracked at all.
Best Practices that show evidence of effectiveness in improving public health outcomes when implemented in multiple real-life settings, as indicated by achievement of aims consistent with the objectives of the activities.
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Summary Report/Recommendations
This study uses data from the COVID Tracking Project’s Racial Data Tracker, which aggregates state-level COVID-19 reporting and tracking databases to determine racial/ethnic trends of COVID-19 incidence and evaluate the racial/ethnic distribution of COVID-19 related mortality in the US. Results found that disparities are more apparent at the county and city level, and discusses the importance of transparent, local data in order to allow for greater precision in resource allocation and effective policy changes aimed at reducing disparities. The study includes choropleth maps of the results by state.
Novel Practices that show potential to achieve desirable public health outcomes in a specific real-life setting and are in the process of generating evidence of effectiveness or may not yet be tested.
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Peer Review Study
A retrospective registry-based chart review examined the various demographic and clinical risk factors associated with COVID-19 severity among patients aged 18-29. The study was done within a metropolitan health care system in Houston, TX. In the cohort of 1,853 young adult patients diagnosed with COVID-19 infection at a hospital encounter, including 226 pregnant women, 1,438 (78%) scored 0 on the Charlson Comorbidity Index, and 833 (45%) were obese (≥30 kg/m2). Within 30 days of their diagnostic encounter, 316 (17%) patients were diagnosed with pneumonia, 148 (8%) received other severe disease diagnoses, and 268 (14%) returned to the hospital after being discharged home. In multivariate logistic regression analyses, increasing age, male gender, Hispanic ethnicity, obesity, asthma history, congestive heart failure, cerebrovascular disease, and diabetes were predictive of severe disease diagnoses within 30 days. Non-Hispanic Black race, obesity, asthma history, myocardial infarction history, and household exposure were predictive of 30-day readmission.