Find Resources
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:
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.
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:
Implementation Guide
Data Across Sectors for Health (DASH) is a national initiative funded by the Robert Wood Johnson Foundation and co-led by the Michigan Public Health Institute and the Illinois Public Health Institute. Created in 2015, DASH promotes and supports multisector data-sharing ecosystems with the goal of fostering more equitable, informed decision-making practices and ultimately improving community health outcomes. They provide financial support, technical assistance, resources, and programming to help foster community collaborations around data-sharing. Their website features information on their two active funding programs, a link to the DASH data-sharing framework and accompanying webinars, as well as information about their knowledge-sharing platform, DASH Knowledge Base, that is still in development. DASH is a great resource for organizations and community leaders seeking guidance on how to foster relationships and enhance data sharing capabilities between governments, community-based organizations, and other local players.