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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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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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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.
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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Summary Report/Recommendations
Report describing Anti-Asian racism during COVID-19 in California. This research report presents the results of interviews conducted with 20 individuals from Asian American and Pacific Islander (AAPI) communities in California. These interviews discussed perceived causes of anti-Asian racism, the impact on the community, and suggested or existing mitigating strategies. These interviews highlighted the connection to the COVID-19 pandemic and the underlying and systemic causes of racism. Mitigating strategies included education about the AAPI community, improved reporting systems, and promoting policy changes to address root causes of racism.
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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Summary Report/Recommendations
In this report, the authors evaluate health equity across race and ethnicity, both within and between states, to illuminate how state health systems perform for Black, White, Latinx/Hispanic, American Indian/Alaska Native, and Asian American, Native Hawaiian, and Pacific Islander populations.
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.
RELEASE DATE:
Summary Report/Recommendations
This report uses preliminary data on COVID-19 mortality rates among Asian Minnesotans. It draws attention to the disproportionate COVID-19 mortality rates among Hmong, Karen, and Karenni residents to demonstrate the critical importance of data disaggregation.
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.
RELEASE DATE:
Summary Report/Recommendations
This report highlights how disaggregating Native Hawaiian, Pacific Islander, and Asian race data can aid in identifying racial disparities among specific subpopulations, and highlights the importance of partnering with communities to develop culturally responsive outreach teams, and tailored public health interventions, and vaccination campaigns to more effectively address health disparities.