World Medical & Health Policy最新文献

Post-intensive care syndrome (PICS), a condition found in survivors of critical illness, is characterized by persistent physical, cognitive, and psychological sequelae that impact the quality of life after discharge from an intensive care unit (ICU). At present, there are no International Classification of Disease (ICD) billing codes for this condition. Without financial alignment, clinicians cannot diagnose PICS, hindering tracking of its prevalence and impeding policy development for this condition. Clinicians should be screening for PICS in all survivors of critical illness, particularly those with acute respiratory distress syndrome (ARDS). Results from single-center studies suggest over 75 percent of ARDS survivors develop PICS. With nearly 5 percent of patients with COVID-19 requiring ICU admission for ARDS, it is important for clinicians to be able to diagnose PICS in survivors, and researchers to be able to track it. Member states should impress upon the World Health Organization to create ICD-10 codes for PICS.

The extent to which violent victimization may explain higher rates of suicidality for transgender and gender diverse (TGD) populations is not well-understood. We identified likely-TGD patients using 2008-2019 electronic health record data and compared them with non-TGD patients to characterize differences in suicide attempt, ideation, and violent victimization. TGD patients (n = 916) had more suicide attempts (5.2 vs. 0.4 percent), ideation (20.5 vs. 1.8 percent), and violent victimization (5.4 vs. 1.7 percent, all p < .001) than non-TGDs (n = 511,026). Violent victimization and TGD cohort were independent predictors of suicide attempt (odds ratios [ORs], 7.23 and 10.84) and ideation (ORs, 6.83 and 11.03, all p < .001). We did not observe a differential impact of violent victimization for gender minorities. TGD patients are at higher baseline risk for suicidality, which is higher still for those experiencing violent victimization. Routine screening for both outcomes, including in primary care settings, may improve treatment.

This study explored social factors that are associated with the US deaths caused by COVID-19 after the declaration of economic reopening on May 1, 2020 by President Donald Trump. We seek to understand how county-level support for Trump interacted with social distancing policies to impact COVID-19 death rates. Overall, controlling for several potential confounders, counties with higher levels of Trump support do not necessarily experience greater mortality rates due to COVID-19. The predicted weekly death counts per county tended to increase over time with the implementation of several key health policies. However, the difference in COVID-19 outcomes between counties with low and high levels of Trump support grew after several weeks of the policy implementation as counties with higher levels of Trump support suffered relatively higher death rates. Counties with higher levels of Trump support exhibited lower percentages of mobile staying at home and higher percentages of people working part time or full time than otherwise comparable counties with lower levels of Trump support. The relative negative performance of Trump-supporting counties is robust after controlling for these measures of policy compliance. Counties with high percentages of older (aged 65 and above) persons tended to have greater death rates, as did more populous counties in general. This study indicates that policymakers should consider the risks inherent in controlling public health crises due to divisions in political ideology and confirms that vulnerable communities are at particularly high risk in public health crises.