Find Resources
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 article described a systematic analysis of various telehealth interventions designed to increase access to mental health services for ethnic minority and Indigenous peoples. The review included 58 articles of interventions culturally tailored to the following populations: Indigenous, African American, Hispanic/Latino, Chinese, and Korean populations. Some key themes included community involvement, quality service delivery, enhanced access and rapport, and multi-organizational partnerships.
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 source reviews how the COVID-19 pandemic has affected children and families, and gives recommendations on how these families and surrounding stakeholders can better support them. This includes ensuring age-appropriate information is available for parents and children, supporting childcare needs, collaborating with schools or trusted community institutions, and creating policies that support overall health, safety, and wellbeing as the pandemic continues on.
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 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.
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.
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.