军事重症空运队伍战备部署经验与临床实践特征的相关性:模拟构建效度研究。

Daniel J Brown, Lane Frasier, F Eric Robinson, Mark Cheney, William T Davis, Ann Salvator, Mark Andresen, Melissa Proctor, Ryan Earnest, Timothy Pritts, Richard Strilka
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引用次数: 0

摘要

重症监护航空运输小组(CCATT)高级课程利用完全沉浸式高保真模拟来培训CCATT人员并评估他们的部署准备情况。本研究旨在(1)确定这些模拟是否正确区分有部署经验的学生(“有经验的”)和没有部署经验的学生(“新手”);(2)检验学生临床实践环境对他们在训练模拟中的表现的影响。材料与方法分析2006年3月至2020年4月重症监护航空运输小组高级学生调查数据和课程状况(合格/不合格)。数据包括学生的专业、以前接触CCATT高级课程、以前的CCATT部署经验、临床实践年数(15年)、危重病护理的日常实践(是/否),以及学生所在医院的描述,包括医院总数(400)和重症监护病房(0、1-10、11-20和bbb20)床位。通过描述性分析和比较检验,采用多变量回归来确定通过CCATT高级课程的预测因素。结果共分析2723份问卷:内科医生841名(31%)、注册护士1035名(38%)、呼吸治疗师847名(31%);641名(24%)学生正在重复维持训练课程,664名(24%)学生有以前的部署经验。按学生专业分类,医学博士合格率为92.7%,注册护士合格率为90.6%,注册护士合格率为85.6%。多变量回归结果表明,部署经验是通过的稳健预测因子。此外,与5到15年的练习组相比,练习15年的小组通过的几率降低了47%。最后,使用MDs作为参考,RTs的通过几率降低了61%。重症监护的日常实践提供了一个边缘但不显著的通过优势,而以前的CCATT课程暴露没有影响。结论本研究的主要结果是,CCATT高级模拟在评估学生是否做好任务准备方面成功地区分了“新手”和“老手”;这与有效的模拟构造是一致的。最后,CCATT的新学员在强制的进修培训期间不能保持他们的准备技能。
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Relevance of Deployment Experience and Clinical Practice Characteristics on Military Critical Care Air Transport Team Readiness: A Study of Simulation Construct Validity.

Introduction: The Critical Care Air Transport Team (CCATT) Advanced course utilizes fully immersive high-fidelity simulations to train CCATT personnel and assess their readiness for deployment. This study aims to (1) determine whether these simulations correctly discriminate between students with previous deployment experience ("experienced") and no deployment experience ("novices") and (2) examine the effects of students' clinical practice environment on their performance during training simulations.

Materials and methods: Critical Care Air Transport Team Advanced student survey data and course status (pass/no pass) between March 2006 and April 2020 were analyzed. The data included students' specialty, previous exposure to the CCATT Advanced course, previous CCATT deployment experience, years in clinical practice (<5, 5-15, and >15 years), and daily practice of critical care (yes/no), as well as a description of the students' hospital to include the total number of hospital (<100, 100-200, 201-400, and >400) and intensive care unit (0, 1-10, 11-20, and >20) beds. Following descriptive analysis and comparative tests, multivariable regression was used to identify the predictors of passing the CCATT Advanced course.

Results: A total of 2,723 surveys were analyzed: 841 (31%) were physicians (MDs), 1,035 (38%) were registered nurses, and 847 (31%) were respiratory therapists (RTs); 641 (24%) of the students were repeating the course for sustainment training and 664 (24%) had previous deployment experience. Grouped by student specialty, the MDs', registered nurses', and RTs' pass rates were 92.7%, 90.6%, and 85.6%, respectively. Multivariable regression results demonstrated that deployment experience was a robust predictor of passing. In addition, the >15 years in practice group had a 47% decrease in the odds of passing as compared to the 5 to 15 years in practice group. Finally, using MDs as the reference, the RTs had a 61% decrease in their odds of passing. The daily practice of critical care provided a borderline but nonsignificant passing advantage, whereas previous CCATT course exposure had no effect.

Conclusion: Our primary result was that the CCATT Advanced simulations that are used to evaluate whether the students are mission ready successfully differentiated "novice" from "experienced" students; this is consistent with valid simulation constructs. Finally, novice CCATT students do not sustain their readiness skills during the period between mandated refresher training.

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