Suchergebnisse

To inform current national discussions about the deaths of black men due to the police, we present novel data on long-term trends (1960-2010) in deaths due to legal intervention (i.e., deaths due to law enforcement actions) among US black and white men, by county income level. Among the three health studies investigating trends in this outcome, one focused on the total US population for 1962-1993, one documented a marked excess for young adult black as compared to white men for 1979-1997, and the third reported on systematic underreporting of such deaths, overall and by race/ethnicity and age, for 1976-1998; none included socioeconomic data.

Valid measures of the integration of patient care could provide rapid and accurate feedback on the successfulness of current efforts to improve health care delivery systems. This article describes the development and pilot testing of a new survey, based on a novel conceptual model, which measures the integration of patient care as experienced by patients. We administered the survey to 1,289 patients with multiple chronic conditions from one health system and received responses from 527 patients (43%). Psychometric analysis of responses supported a six-dimension model of integration with satisfactory internal consistency, discriminant validity, and goodness of fit. The Patient Perceptions of Integrated Care survey can be used to measure the integration of care received by chronically ill patients for two main purposes: as a research tool to compare interventions intended to improve the integration of care and as a quality improvement tool intended to guide the refinement of delivery system innovations.

Objectives: To illustrate the intersections of, and intercounty variation in, individual, household and community factors that influence the impact of COVID-19 on US counties and their ability to respond. Design: We identified key individual, household and community characteristics influencing COVID-19 risks of infection and survival, guided by international experiences and consideration of epidemiological parameters of importance. Using publicly available data, we developed an open-access online tool that allows county-specific querying and mapping of risk factors. As an illustrative example, we assess the pairwise intersections of age (individual level), poverty (household level) and prevalence of group homes (community-level) in US counties. We also examine how these factors intersect with the proportion of the population that is people of colour (ie, not non-Hispanic white), a metric that reflects histories of US race relations. We defined 'high' risk counties as those above the 75th percentile. This threshold can be changed using the online tool. Setting: US counties. Participants: Analyses are based on publicly available county-level data from the Area Health Resources Files, American Community Survey, Centers for Disease Control and Prevention Atlas file, National Center for Health Statistic and RWJF Community Health Rankings. Results: Our findings demonstrate significant intercounty variation in the distribution of individual, household and community characteristics that affect risks of infection, severe disease or mortality from COVID-19. About 9% of counties, affecting 10 million residents, are in higher risk categories for both age and group quarters. About 14% of counties, affecting 31 million residents, have both high levels of poverty and a high proportion of people of colour. Conclusion: Federal and state governments will benefit from recognising high intrastate, intercounty variation in population risks and response capacity. Equitable responses to the pandemic require strategies to protect those in counties at highest risk of adverse COVID-19 outcomes and their social and economic impacts.

Objectives: To illustrate the intersections of, and intercounty variation in, individual, household and community factors that influence the impact of COVID-19 on US counties and their ability to respond. Design: We identified key individual, household and community characteristics influencing COVID-19 risks of infection and survival, guided by international experiences and consideration of epidemiological parameters of importance. Using publicly available data, we developed an open-access online tool that allows county-specific querying and mapping of risk factors. As an illustrative example, we assess the pairwise intersections of age (individual level), poverty (household level) and prevalence of group homes (community-level) in US counties. We also examine how these factors intersect with the proportion of the population that is people of colour (ie, not non-Hispanic white), a metric that reflects histories of US race relations. We defined 'high' risk counties as those above the 75th percentile. This threshold can be changed using the online tool. Setting: US counties. Participants: Analyses are based on publicly available county-level data from the Area Health Resources Files, American Community Survey, Centers for Disease Control and Prevention Atlas file, National Center for Health Statistic and RWJF Community Health Rankings. Results: Our findings demonstrate significant intercounty variation in the distribution of individual, household and community characteristics that affect risks of infection, severe disease or mortality from COVID-19. About 9% of counties, affecting 10 million residents, are in higher risk categories for both age and group quarters. About 14% of counties, affecting 31 million residents, have both high levels of poverty and a high proportion of people of colour. Conclusion: Federal and state governments will benefit from recognising high intrastate, intercounty variation in population risks and response capacity. Equitable responses to the pandemic require strategies to protect those in counties at highest risk of adverse COVID-19 outcomes and their social and economic impacts.

We assessed surgical team member perceptions of multiple dimensions of safe surgical practice in 38 South Carolina hospitals participating in a statewide initiative to implement surgical safety checklists. Primary data were collected using a novel 35-item survey. We calculated the percentage of 1,852 respondents with strongly positive, positive, and neutral/negative responses about the safety of surgical practice, compared results by hospital and professional discipline, and examined how readiness, teamwork, and adherence related to staff perception of care quality. Overall, 78% of responses were positive about surgical safety at respondent's hospitals, but in each survey dimension, from 16% to 40% of responses were neutral/negative, suggesting significant opportunity to improve surgical safety. Respondents not reporting they would feel safe being treated in their operating rooms varied from 0% to 57% among hospitals. Surgeons responded more positively than nonsurgeons. Readiness, teamwork, and practice adherence related directly to staff perceptions of patient safety ( p < .001).

Abstract
Excess mortality has exceeded reported deaths from Covid-19 during the pandemic. This gap may be attributable to deaths that occurred among individuals with undiagnosed Covid-19 infections or indirect consequences of the pandemic response such as interruptions in medical care; distinguishing these possibilities has implications for public health responses. In the present study, we examined patterns of excess mortality over time and by setting (in-hospital or out-of-hospital) and cause of death using death certificate data from California. The estimated number of excess natural-cause deaths from 2020 March 1 to 2021 February 28 (69,182) exceeded the number of Covid-19 diagnosed deaths (53,667) by 29%. Nearly half, 47.4% (32,775), of excess natural-cause deaths occurred out of the hospital, where only 28.6% (9,366) of excess mortality was attributed to Covid-19. Over time, increases or decreases in excess natural non-Covid-19 mortality closely mirrored increases or decreases in Covid-19 mortality. The time series were positively correlated in out-of-hospital settings, particularly at time lags when excess natural-cause deaths preceded reported Covid-19 deaths; for example, when comparing Covid-19 deaths to excess natural-cause deaths in the week prior, the correlation was 0.73. The strong temporal association of reported Covid-19 deaths with excess out-of-hospital deaths from other reported natural-cause causes suggests Covid-19 deaths were undercounted during the first year of the pandemic.