For the risks and Maslach Burnout Inventory scores, emotional exhaustion and depersonalization were correlated with age, gender, occupation, marital status, years of practice, and education level. Reduced personal accomplishment was correlated with marital status. The variables of age (< 29 years old), occupation (nurses), marital status (unmarried), years of practice (< 5 years), and educational level (≤ Undergraduate) were associated with high levels of burnout.
 
  Healthcare professionals who care for patients with disorders of consciousness experienced high levels of burnout. Especially those who were younger, nurse, unmarried, less practice experience or lower educational levels were more likely to experience high burnout.
 Healthcare professionals who care for patients with disorders of consciousness experienced high levels of burnout. Especially those who were younger, nurse, unmarried, less practice experience or lower educational levels were more likely to experience high burnout.
  Although values underpin the goals pursued in health systems, including how health systems benefit the population, it is often not clear how values are incorporated into policy decision-making about health systems. The challenge is to encompass social/citizen values, health system goals, and financial realities and to incorporate them into the policy-making process. This is a challenge for all health systems and of particular importance for Latin American (LA) countries. Our objective was to understand how and under what conditions societal values inform decisions about health system financing in LA countries.
 
  A critical interpretive synthesis approach was utilised for this work. We searched 17 databases in December 2016 to identify articles written in English, Spanish or Portuguese that focus on values that inform the policy process for health system financing in LA countries at the macro and meso levels. Two reviewers independently screened records and assessed them for inclusion. One researcher conceptrying according to the four factors).
 
  It is an effort to consolidate and explain how different social values are considered and how they support policy decision-making about health system financing. This can help policy-makers to explicitly incorporate values into the policy process and understand how values are supporting the achievement of policy goals in health system financing.
 
  The protocol was registered with PROSPERO, ID=CRD42017057049 .
 The protocol was registered with PROSPERO, ID=CRD42017057049 .
  Unintended pregnancy has dire consequences on the health and socioeconomic wellbeing of adolescent girls and young women (AGYW) (aged 15-24 years). While most studies tend to focus on lack of access to contraceptive information and services, and poverty as the main contributing factor to early-unintended pregnancies, the influence of sexual violence has received limited attention. Understanding the link between sexual violence and unintended pregnancy is critical towards developing a multifaceted intervention to reduce unintended pregnancies among AGYW in South Africa, a country with high teenage pregnancy rate. Thus, we estimated the magnitude of unintended pregnancy among AGYW and also examined the effect of sexual violence on unintended pregnancy.
 
  Our study adopted a cross-sectional design, and data were obtained from AGYW in a South African university between June and November 2018. A final sample of 451 girls aged 17-24 years, selected using stratified sampling, were included in the analysis. We usedW. Sexual violence is an important predictor of unintended pregnancy in this age cohort. Thus, addressing unintended pregnancies among AGYW in South Africa requires interventions that not only increase access to contraceptive information and services but also reduce sexual violence and cater for survivors.
  An established body of literature has shown evidence of implicit bias in the health care system on the basis of patient race and ethnicity that contributes to well documented disparities in outcomes. However, little is known about the influence of patient race and ethnicity on the decision to order diagnostic radiology exams in the acute care setting. This study examines the role of patient race and ethnicity on the likelihood of diagnostic imaging exams being ordered during United States emergency department encounters.
 
  Publicly available data from the National Hospital Ambulatory Medical Care Survey Emergency Department sample for the years 2006-2016 was compiled. The proportion of patient encounters where diagnostic imaging was ordered was tabulated by race/ethnicity, sub-divided by imaging modality. A multivariable logistic regression model was used to evaluate the influence of patient race/ethnicity on the ordering of diagnostic imaging controlling for other patient and hospital characteristics.  https://www.selleckchem.com/products/gdc-0994.html  Survnt race and ethnicity even when controlling for other patient and hospital characteristics. Further work must be done to understand and mitigate what may represent systematic bias and ensure equitable use of health care resources.
 The likelihood that a diagnostic imaging exam will be ordered during United States emergency department encounters differs significantly by patient race and ethnicity even when controlling for other patient and hospital characteristics. Further work must be done to understand and mitigate what may represent systematic bias and ensure equitable use of health care resources.
  Automated systems that use machine learning to estimate a patient's risk of death are being developed to influence care. There remains sparse transparent reporting of model generalizability in different subpopulations especially for implemented systems.
 
  A prognostic study included adult admissions at a multi-site, academic medical center between 2015 and 2017. A predictive model for all-cause mortality (including initiation of hospice care) within 60 days of admission was developed. Model generalizability is assessed in temporal validation in the context of potential demographic bias. A subsequent prospective cohort study was conducted at the same sites between October 2018 and June 2019. Model performance during prospective validation was quantified with areas under the receiver operating characteristic and precision recall curves stratified by site. Prospective results include timeliness, positive predictive value, and the number of actionable predictions.
 
  Three years of development data included 128,941 inpatient admissions (94,733 unique patients) across sites where patients are mostly white (61%) and female (60%) and 4.