Objectives: To know the opinion of medical residents in hospitals in Catalonia about the need for and usefulness of the training they receive in the emergency department.
Material And Methods: We sent an electronic questionnaire to all residents in Catalonia, through their cooperating supervisors. The questionnaire contained items to collect information on sociodemographic variables and attitudes toward emergency medicine. Items related to training covered the residents' assessment of the need for a rotation in the emergency department and the knowledge and skills acquired during the rotation (case history writing, relations with patients' relatives, teamwork, decision-making, identifying and managing critical patients, acquisition of diagnostic and therapeutic techniques). We compiled descriptive statistics and compared the results for residents from different specialties.
Results: Questionnaires were sent to 1431 residents in 21 hospitals and other training facilities. Responses were received from 427 (29.8%). Mean (SD) scores expressed on a scale of 1 to 10 were high for both the need for training in emergency medicine (8.9 [1.7]) and knowledge acquired during the rotation (8.2 [1.9]). The residents reported that they had acquired more knowledge in the areas of decision-making and management of critical patients. Family medicine residents expressed greater interest in choosing the specialty of emergency medicine (33.7% vs 6.1% for other residents, P<.001), and their opinion of the need for training in emergency medicine was also higher than other residents' (9.2 [1.5] vs 8.7 [1.8], P=.006).
Conclusion: Medical residents in Catalonia believe that a rotation in the emergency department provides necessary and useful training. Family medicine residents are the ones who value emergency training most highly.
Download full-text PDF |
Source |
---|
Am J Emerg Med
January 2025
Department of Emergency Medicine, Yale University School of Medicine, New Haven, CT, USA; Center for Outcomes Research and Evaluation, Yale University, New Haven, CT, USA.
Background: This study aimed to examine how physician performance metrics are affected by the speed of other attendings (co-attendings) concurrently staffing the ED.
Methods: A retrospective study was conducted using patient data from two EDs between January-2018 and February-2020. Machine learning was used to predict patient length of stay (LOS) conditional on being assigned a physician of average speed, using patient- and departmental-level variables.
Am J Emerg Med
January 2025
Faculty of Medicine, Universidad de Valladolid, Valladolid, Spain; Emergency Department, Hospital Clínico Universitario, Gerencia Regional de Salud de Castilla y León, Valladolid, Spain.
Background: The study of the inclusion of new variables in already existing early warning scores is a growing field. The aim of this work was to determine how capnometry measurements, in the form of end-tidal CO2 (ETCO2) and the perfusion index (PI), could improve the National Early Warning Score (NEWS2).
Methods: A secondary, prospective, multicenter, cohort study was undertaken in adult patients with unselected acute diseases who needed continuous monitoring in the emergency department (ED), involving two tertiary hospitals in Spain from October 1, 2022, to June 30, 2023.
J Med Internet Res
January 2025
Institute of Medical Teaching and Medical Education Research, University Hospital Würzburg, Würzburg, Germany.
Background: Objective structured clinical examinations (OSCEs) are a widely recognized and accepted method to assess clinical competencies but are often resource-intensive.
Objective: This study aimed to evaluate the feasibility and effectiveness of a virtual reality (VR)-based station (VRS) compared with a traditional physical station (PHS) in an already established curricular OSCE.
Methods: Fifth-year medical students participated in an OSCE consisting of 10 stations.
JMIR AI
January 2025
Department of Radiology, Children's National Hospital, Washington, DC, United States.
Clin Infect Dis
January 2025
Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Infectious Diseases, Respiratory Medicine and Critical Care, Berlin, Germany.
Background: Existing risk evaluation tools underperform in predicting intensive care unit (ICU) admission for patients with the Coronavirus Disease 2019 (COVID-19). This study aimed to develop and evaluate an accurate and calculator-free clinical tool for predicting ICU admission at emergency room (ER) presentation.
Methods: Data from patients with COVID-19 in a nationwide German cohort (March 2020-January 2023) were analyzed.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!