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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 review offers to provide context for the indirect health effects of the COVID-19 pandemic thus far, including its impact on health service delivery and utilization. Results found an overall decrease in utilization of health services for non-COVID-19 related care, which could lead to an increase in chronic diseases in the future as patients are not receiving timely checkups.
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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Systematic Review/Meta-Analysis
In an effort to help build the evidence base around social determinants of health (SDOH), the Assistant Secretary for Planning and Evaluation (ASPE) engaged RAND in a project to evaluate the current evidence from programs and policies targeting SDOH and identify research questions, data sources, and data gaps. RAND used a multi-methods approach that included an environmental scan of the published and gray literature of SDOH interventions; key informant interviews with subject matter experts; and a convening of U.S. Department of Health and Human Services agencies and operating divisions to review the results of the environmental scan and offer insights on findings.
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 systematic review examines COVID-19 literature on infections, hospitalizations, or deaths by race and ethnicity in the United States. Results found that Black and Hispanic populations experience higher rates of COVID-19 infection and COVID-19 related mortality, but similar rates of case fatality.
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.