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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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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.
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.
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
The authors discuss the need for a formal evaluation of the health equity impact of a new intervention, as these evaluations are hardly ever performed as part of a health technology assessment to understand its value. An evidence-based quantitative assessment of the health equity impact can help decision makers develop coverage policies, program designs, and quality initiatives focused on optimizing both total health and health equity, given the treatment options available. The authors outline the conceptual basis of how a new intervention can impact health equity and adopt distributional cost-effectiveness analysis based on decision-analytic models to assess this quantitatively, using a newly FDA-approved drug for Alzheimer’s disease (aducanumab) as an example.
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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Commentary
This article provides an overview of the link between racism and COVID-19 disparities, missing race and ethnicity data, and literature on demographic data gaps. The authors also provide recommendations on how health departments and healthcare systems can engage communities of color to co-develop race and ethnicity data collection processes.
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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Commentary
This article outlines a framework for partnering with Indigenous nations in research and data collection and calls for the need for equitable data use agreements. The framework guidelines include (1) incorporating respect and collaboration early in negotiations; (2) recognition that specificity of terms is key to trust-building; (3) remembering that good data stewardship entails safeguarding; and (4) building sustainable relationships.