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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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White Paper/Brief
An early report issued by the CDC identified staff members working in multiple nursing homes as a likely source of spread of COVID-19. The authors performed the first large-scale analysis of nursing home connections via shared staff and contractors. Using a large-scale analysis of smartphone location data, they found that 49 percent of COVID-19 cases among nursing home residents was attributable to staff movement between facilities. Traditional federal regulatory metrics of nursing home quality were unimportant in predicting outbreaks. The results provide evidence for a policy recommendation of compensating nursing home workers to work at only one home and limit cross-traffic across homes.
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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Data Collection Tool
This special edition data tool provides important information related to the COVID-19 pandemic, such as data regarding where populations vulnerable to the COVID-19 pandemic reside, where the cases are surging, and which communities will require greater hospital capacity for severe COVID-19. The data can be used for data collection and analysis.
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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Data Collection Tool
The Mapping Medicare Disparities (MMD) Population View provides a user-friendly way to explore and better understand disparities in chronic diseases, and allows users to: (1) visualize health outcome measures at a national, state, or county level; (2) explore health outcome measures by age, sex, race and ethnicity; (3) compare differences between two geographic locations (e.g., benchmark against the national average); and (4) compare differences between two racial and ethnic groups within the same geographic area.
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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Peer Review Study
This study explores disparities for older adults experiencing COVID-19 using Census and PULSE COVID data. The study shows that older adults are more susceptible to health disparities, especially adults from minority populations.
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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Peer Review Study
This study looks at internet usage of older adults through the California Health Interview Survey to examine how social determinants of health and socioeconomic levels can impact access to health information. Results found that minorities with lower levels of socioeconomic status are most impacted by a digital divide and access to health information via the internet.
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:
Peer Review Study
This is a retrospective cohort study that was used to inform COVID-19 infection prevention measures by identifying and assessing risk and possible vectors of infection in nursing homes (NHs) using a machine-learning approach. The strongest predictors of COVID-19 infection were identified as the county’s infection rate and the number of separate units in the NH; other predictors included the county’s population density, historical health deficiencies, and resident density. In addition, the NH’s historical percentage of non-Hispanic white residents was identified as a protective factor. The study concluded that a machine-learning model can help quantify and predict infection risk.