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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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Summary Report/Recommendations
This article describes policy, regulatory, and payment reforms implemented in Massachusetts in response to people with serious mental illnesses that are at disproportionate risk of COVID-19 morbidity and mortality. The reforms include: (1) ensuring continuity of care for individuals with serious mental illness during the COVID-19 pandemic and (2) supporting community-based behavioral health organizations.
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 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.