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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.
RELEASE DATE:
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.
RELEASE DATE:
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.
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 summarizes the factors contributing to COVID-19 inequities among immigrant communities. The review concludes with the overarching recommendation of engaging and empowering immigrant communities. Facilitating factors to address health inequities in this population include providing linguistically appropriate services, addressing poverty, and ensuring undocumented immigrants have access to public benefits.
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.
RELEASE DATE:
Systematic Review/Meta-Analysis
This article summarizes the factors that place incarcerated people at high risk for COVID-19 infection and the effective strategies to reduce transmission and complications due to COVID-19, informed by other infectious disease outbreaks. The authors highlight the role of interagency collaboration, health communication, screening for contagious diseases, restriction, isolation and quarantine, contact tracing, immunisation programmes, epidemiological surveillance, and prison-specific guidelines in managing any outbreaks.
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.