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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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Systematic Review/Meta-Analysis
This article details an exploratory roadmap to address how artificial intelligence can assist in linking clinical and community data to enhance population health and the reduction of health disparities. The article uses a literature review to create the roadmap.
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:
Systematic Review/Meta-Analysis
This literature review examines technology companies that have created initiatives to address digital health literacy and the impact of those initiatives. The review found 38 companies with relevant initiatives, but limited data on their effectiveness.
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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Webinar
Panels of distinguished authors and experts presented their work at a virtual symposium in the February 2022 issue of Health Affairs, “Racism & Health.” They discussed the historical context, the evolving research practices and policies, and the lived experience of populations whose health has been harmed by individual and structural 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.
RELEASE DATE:
Systematic Review/Meta-Analysis
This review looks at how artificial intelligence and big data can help manage the pandemic, including monitoring, forecasting, and predicting future outbreaks and resource utilization.
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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Webinar
This national webinar series convened by the CDC Foundation discussed the future of public health in collaboration with the Association of State and Territorial Health Officials, the National Association of County and City Health Officials, Big Cities Health Coalition, and other public health partners to advance recommendations for a modernized U.S. public health system. The series includes four convenings, with recommendations from the Bipartisan Policy Center’s Public Health Forward.
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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Webinar
This webinar series focuses on the Community Information Exchange (CIE) Data Equity Framework, in which the goal is to build data systems to help institutions, and the communities they serve, approach CIE® planning and systems change work from a place of anti-racism. Part one of the series focuses on reviewing the CIE Data Equity Framework and part two focuses on examining the application of the framework across different systems including public health, social, philanthropy, and more.
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:
Systematic Review/Meta-Analysis
This article explores how health data technology tools such as Artificial Intelligence (AI) and Machine Learning (ML) tools can be implemented and adapted to assist in better responses and outcomes to the COVID-19 pandemic, as well as future epidemics. This literature review focuses on peer-reviewed articles concerning four themes: COVID-19 and the need for AI; utility of AI in COVID-19 screening, contract tracing, and diagnosis; use of AI in COVID-19 patient monitoring and drug development; AI beyond COVID-19 and opportunities for Low-Middle Income Communities (LMIC). This review contains examples of ways healthcare systems have implemented AI and ML to predict and treat outcomes of COVID-19, as well as potential capacities for AI.