Matzen Jain (footbull48)

This article explores high-fidelity simulation in anesthesiology education and provides strategies for its use to improve management of critical events. Educational theories that underlie the use of simulation are described. High-fidelity simulation is useful in teaching technical (diagnostic and procedural) and nontechnical (communication and professionalism) skills, including crisis resource management (CRM) skills. The practice of CRM is fundamental to ensuring patient safety during critical events and to the safe practice of anesthesiology, and its critical elements are presented. A discussion of the use of high-fidelity simulation to learn to combine highly complex procedural skills and CRM is also provided.Many factors come together probabilistically to affect clinician response to critical events in the operating room; no 2 critical events are alike. These factors involve 4 primary domains (1) the event itself, (2) the individual anesthetist(s), (3) the operating room team, and (4) the resources available and environments in which the event occurs. Appreciating these factors, anticipating how they create vulnerabilities for error and poor response, and actively addressing those vulnerabilities (before events occur as well as during) will help clinicians manage critical event response more effectively and avoid errors. This study reviews optimization models for human immunodeficiency virus (HIV) and acquired immunodeficiency syndrome (AIDS) resource allocation. We searched 2 databases for peer-reviewed articles published from January 1985 through August 2019 that describe optimization models for resource allocation in HIV/AIDS. We included models that consider 2 or more competing HIV/AIDS interventions. We extracted data on selected characteristics and identified similarities and differences across models. We also assessed the quality of mathematical disease transmission models based on the best practices identified by a 2010 task force. The final qualitative synthesis included 23 articles that used 14 unique optimization models. LY3023414 in vivo The articles shared several characteristics, including the use of dynamic transmission modeling to estimate health benefits and the inclusion of specific high-risk groups in the study population. The models explored similar HIV/AIDS interventions that span primary and secondary prevention andcross optimization models, but they did not align with global HIV/AIDS goals or targets. Future work should be applied in countries facing the largest declines in HIV/AIDS funding. Large secondary databases, such as those containing insurance claims data, are increasingly being used to compare the effects and costs of treatments in routine clinical practice. Despite their appeal, however, caution must be exercised when using these data. In this study, we aimed to identify and assess the methodological quality of studies that used claims data to compare the effectiveness, costs, or cost-effectiveness of systemic therapies for breast cancer. We searched Embase, the Cochrane Library, Medline, Web of Science, and Google Scholar for English-language publications and assessed the methodological quality using the Good Research for Comparative Effectiveness principles. This study was registered with the International Prospective Register of Systematic Reviews (PROSPERO) under number CRD42018103992. We identified 1251 articles, of which 106 met the inclusion criteria. Most studies were conducted in the United States (74%) and Taiwan (9%) and were based on claims data sets (35%) or claims dhodological issues persist and are often inappropriately addressed or reported. There are several issues of concern for the composite time trade-off (c-TTO) used to estimate EQ-5D-5L value sets. The "nonstopping" TTO (n-TTO) differs from the c-TTO mainly in 2 aspects (1) n-TTO uses a standardized top-down or bottom-up routing; and (2) n-TTO conti