Assessment of Emergency Medicine Resident Performance in an Adult Simulation Using a Multisource Feedback Approach.

Introduction: The Accreditation Council for Graduate Medical Education (ACGME) specifically notes multisource feedback (MSF) as a recommended means of resident assessment in the emergency medicine (EM) Milestones. High-fidelity simulation is an environment wherein residents can receive MSF from various types of healthcare professionals. Previously, the Queen\u27s Simulation Assessment Tool (QSAT) has been validated for faculty to assess residents in five categories: assessment; diagnostic actions; therapeutic actions; interpersonal communication, and overall assessment. We sought to determine whether the QSAT could be used to provide MSF using a standardized simulation case. Methods: Prospectively after institutional review board approval, residents from a dual ACGME/osteopathic-approved postgraduate years (PGY) 1-4 EM residency were consented for participation. We developed a standardized resuscitation after overdose case with specific 1-5 Likert anchors used by the QSAT. A PGY 2-4 resident participated in the role of team leader, who completed a QSAT as self-assessment. The team consisted of a PGY-1 peer, an emergency medical services (EMS) provider, and a nurse. Two core faculty were present to administer the simulation case and assess. Demographics were gathered from all participants completing QSATs. We analyzed QSATs by each category and on cumulative score. Hypothesis testing was performed using intraclass correlation coefficients (ICC), with 95% confidence intervals. Interpretation of ICC results was based on previously published definitions. Results: We enrolled 34 team leader residents along with 34 nurses. A single PGY-1, a single EMS provider and two faculty were also enrolled. Faculty provided higher cumulative QSAT scores than the other sources of MSF. QSAT scores did not increase with team leader PGY level. ICC for inter-rater reliability for all sources of MSF was 0.754 (0.572-0.867). Removing the self-evaluation scores increased inter-rater reliability to 0.838 (0.733-0.910). There was lesser agreement between faculty and nurse evaluations than from the EMS or peer evaluation. Conclusion: In this single-site cohort using an internally developed simulation case, the QSAT provided MSF with excellent reliability. Self-assessment decreases the reliability of the MSF, and our data suggest self-assessment should not be a component of MSF. Use of the QSAT for MSF may be considered as a source of data for clinical competency committees

Injury Due to Mechanical Falls: Future Directions in Gender-specific Surveillance, Screening, and Interventions in Emergency Department Patients.

The Centers for Disease Control and Prevention report that among older adults (≥65 years), falls are the leading cause of injury-related death. Fall-related fractures among older women are more than twice as frequent as those for men. Gender-specific evidence-based fall prevention strategy and intervention studies show that improved patient-centered outcomes are elusive. There is a paucity of emergency medicine literature on the topic. As part of the 2014 Academic Emergency Medicine (AEM) consensus conference on Gender-Specific Research in Emergency Care: Investigate, Understand, and Translate How Gender Affects Patient Outcomes, a breakout group convened to generate a research agenda on priority questions to be answered on this topic. The consensus-based priority research agenda is presented in this article

Health-state utilities in a prisoner population : a cross-sectional survey

Background: Health-state utilities for prisoners have not been described. Methods: We used data from a 1996 cross-sectional survey of Australian prisoners (n = 734). Respondent-level SF-36 data was transformed into utility scores by both the SF-6D and Nichol's method. Socio-demographic and clinical predictors of SF-6D utility were assessed in univariate analyses and a multivariate general linear model. Results: The overall mean SF-6D utility was 0.725 (SD 0.119). When subdivided by various medical conditions, prisoner SF-6D utilities ranged from 0.620 for angina to 0.764 for those with none/mild depressive symptoms. Utilities derived by the Nichol's method were higher than SF-6D scores, often by more than 0.1. In multivariate analysis, significant independent predictors of worse utility included female gender, increasing age, increasing number of comorbidities and more severe depressive symptoms. Conclusion: The utilities presented may prove useful for future economic and decision models evaluating prison-based health programs

Effects of countdown displays in public transport route choice under severe overcrowding

The paper presents a route choice model for dynamic assignment in congested, i.e. overcrowded, transit networks where it is assumed that passengers are supported with real-time information on carrier arrivals at stops. If the stop layout is such that passenger congestion results in First-In-First-Out (FIFO) queues, a new formulation is devised for calculating waiting times, total travel times and route splits. Numerical results for a simple example network show the effect of information on route choice when heavy congestion is observed. While the provision of information does not lead to a remarkable decrease in total travel time, with the exception of some particular instances, it changes the travel behaviour of passengers that seem to be more averse to queuing at later stages of their journey and, thus, prefer to interchange at less congested stations

Robotic Wireless Sensor Networks

In this chapter, we present a literature survey of an emerging, cutting-edge, and multi-disciplinary field of research at the intersection of Robotics and Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system that aims to achieve certain sensing goals while meeting and maintaining certain communication performance requirements, through cooperative control, learning and adaptation. While both of the component areas, i.e., Robotics and WSN, are very well-known and well-explored, there exist a whole set of new opportunities and research directions at the intersection of these two fields which are relatively or even completely unexplored. One such example would be the use of a set of robotic routers to set up a temporary communication path between a sender and a receiver that uses the controlled mobility to the advantage of packet routing. We find that there exist only a limited number of articles to be directly categorized as RWSN related works whereas there exist a range of articles in the robotics and the WSN literature that are also relevant to this new field of research. To connect the dots, we first identify the core problems and research trends related to RWSN such as connectivity, localization, routing, and robust flow of information. Next, we classify the existing research on RWSN as well as the relevant state-of-the-arts from robotics and WSN community according to the problems and trends identified in the first step. Lastly, we analyze what is missing in the existing literature, and identify topics that require more research attention in the future

GPS-ARM: Computational Analysis of the APC/C Recognition Motif by Predicting D-Boxes and KEN-Boxes

Anaphase-promoting complex/cyclosome (APC/C), an E3 ubiquitin ligase incorporated with Cdh1 and/or Cdc20 recognizes and interacts with specific substrates, and faithfully orchestrates the proper cell cycle events by targeting proteins for proteasomal degradation. Experimental identification of APC/C substrates is largely dependent on the discovery of APC/C recognition motifs, e.g., the D-box and KEN-box. Although a number of either stringent or loosely defined motifs proposed, these motif patterns are only of limited use due to their insufficient powers of prediction. We report the development of a novel GPS-ARM software package which is useful for the prediction of D-boxes and KEN-boxes in proteins. Using experimentally identified D-boxes and KEN-boxes as the training data sets, a previously developed GPS (Group-based Prediction System) algorithm was adopted. By extensive evaluation and comparison, the GPS-ARM performance was found to be much better than the one using simple motifs. With this powerful tool, we predicted 4,841 potential D-boxes in 3,832 proteins and 1,632 potential KEN-boxes in 1,403 proteins from H. sapiens, while further statistical analysis suggested that both the D-box and KEN-box proteins are involved in a broad spectrum of biological processes beyond the cell cycle. In addition, with the co-localization information, we predicted hundreds of mitosis-specific APC/C substrates with high confidence. As the first computational tool for the prediction of APC/C-mediated degradation, GPS-ARM is a useful tool for information to be used in further experimental investigations. The GPS-ARM is freely accessible for academic researchers at: http://arm.biocuckoo.org