Max Berger, Arlene S. Chung, Daniel J. Ackil, Ryan Clark, William E. Soares III, Jaime Jordan
{"title":"Simulation Resources in Emergency Medicine Residencies: A National Survey","authors":"Max Berger, Arlene S. Chung, Daniel J. Ackil, Ryan Clark, William E. Soares III, Jaime Jordan","doi":"10.1002/aet2.70098","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Objectives</h3>\n \n <p>The American Board of Emergency Medicine's new Certifying Exam features simulation-based assessment. The current resources available to prepare residents to pass this high-stakes exam are unknown. We sought to assess the current state of simulation resources and utilization in EM residency programs.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>This was a cross-sectional survey study of residency or simulation leadership at ACGME-accredited EM programs. We developed an online survey consisting of multiple-choice items, which was piloted before use. We collected data from August to December 2024. We calculated descriptive statistics, used chi-squared testing for categorical data comparisons, and Kruskal–Wallis for ordinal variables. Univariate logistic regression was used to examine associations between EM residency and simulation resource factors with annual simulation training hours.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>We identified contact information for 287 programs, and 194 completed the survey (67.6%). Most EM Residency programs had a simulation center (94.8%, 184/194). Fewer programs had simulation fellowship-trained physician faculty (44.3%, 86/194) or a division of simulation (40.7%, 79/194). Approximately 83% (161/194) of respondents felt that accessing simulation resources was easy or very easy. The median number of hours residents were engaged in simulation training per year was 40 (IQR 25–59). Univariate logistic regression found no association between EM program demographics and the annual number of hours of simulation training. The presence of simulation-trained faculty was associated with increased hours of simulation (OR 1.82, 95% CI 1.1–3.0, <i>p</i> = 0.05).</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>While most participating EM residency programs have access to simulation resources, variability exists in resources and implementation across programs, which may lead to inequities in preparing trainees for the new ABEM Certifying Exam.</p>\n </section>\n </div>","PeriodicalId":37032,"journal":{"name":"AEM Education and Training","volume":"9 5","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2025-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AEM Education and Training","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/aet2.70098","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"EDUCATION, SCIENTIFIC DISCIPLINES","Score":null,"Total":0}
引用次数: 0
Abstract
Objectives
The American Board of Emergency Medicine's new Certifying Exam features simulation-based assessment. The current resources available to prepare residents to pass this high-stakes exam are unknown. We sought to assess the current state of simulation resources and utilization in EM residency programs.
Methods
This was a cross-sectional survey study of residency or simulation leadership at ACGME-accredited EM programs. We developed an online survey consisting of multiple-choice items, which was piloted before use. We collected data from August to December 2024. We calculated descriptive statistics, used chi-squared testing for categorical data comparisons, and Kruskal–Wallis for ordinal variables. Univariate logistic regression was used to examine associations between EM residency and simulation resource factors with annual simulation training hours.
Results
We identified contact information for 287 programs, and 194 completed the survey (67.6%). Most EM Residency programs had a simulation center (94.8%, 184/194). Fewer programs had simulation fellowship-trained physician faculty (44.3%, 86/194) or a division of simulation (40.7%, 79/194). Approximately 83% (161/194) of respondents felt that accessing simulation resources was easy or very easy. The median number of hours residents were engaged in simulation training per year was 40 (IQR 25–59). Univariate logistic regression found no association between EM program demographics and the annual number of hours of simulation training. The presence of simulation-trained faculty was associated with increased hours of simulation (OR 1.82, 95% CI 1.1–3.0, p = 0.05).
Conclusions
While most participating EM residency programs have access to simulation resources, variability exists in resources and implementation across programs, which may lead to inequities in preparing trainees for the new ABEM Certifying Exam.
目的:美国急诊医学委员会新认证考试的特点是基于模拟的评估。目前还不知道有哪些资源可以帮助住院医生准备通过这项高风险的考试。我们试图评估EM住院医师计划中模拟资源和利用的现状。方法:这是一项关于acgme认证的EM项目住院医师或模拟领导的横断面调查研究。我们开发了一个包含多项选择题的在线调查,在使用前进行了试点。我们收集了2024年8月至12月的数据。我们计算描述性统计,使用卡方检验进行分类数据比较,使用Kruskal-Wallis检验进行有序变量比较。使用单变量逻辑回归来检验EM驻留和模拟资源因素与年度模拟培训时数之间的关系。结果:我们确定了287个项目的联系方式,其中194个(67.6%)完成了调查。大多数急诊住院医师项目都有一个模拟中心(94.8%,184/194)。较少的项目有模拟研究员培训的医师教师(44.3%,86/194)或模拟部门(40.7%,79/194)。大约83%(161/194)的受访者认为访问模拟资源很容易或非常容易。住院医师每年参与模拟培训的中位数小时数为40 (IQR 25-59)。单变量逻辑回归发现,EM计划人口统计数据与每年模拟培训小时数之间没有关联。接受过模拟训练的教员的存在与模拟时间的增加有关(OR 1.82, 95% CI 1.1-3.0, p = 0.05)。结论:虽然大多数参与的EM住院医师项目都可以访问模拟资源,但不同项目之间的资源和实施存在可变性,这可能导致学员在准备新的ABEM认证考试方面存在不平等。