Development and validation of clinical performance assessment in simulated medical emergencies: an observational study

模拟医疗紧急情况下临床表现评估的开发与验证:一项观察性研究

阅读:1

Abstract

BACKGROUND: Critical illness is a time-sensitive process which requires practitioners to process vast quantities of data and make decisions rapidly. We have developed a tool, the Checklist for Early Recognition and Treatment of Acute Illness (CERTAIN), aimed at enhancing care delivery in such situations. To determine the efficacy of CERTAIN and similar cognitive aids, we developed rubric for evaluating provider performance in a simulated medical resuscitation environments. METHODS: We recruited 18 clinicians with current valid ACLS certification for evaluation in three simulated medical scenarios designed to mimic typical medical decompensation events routinely experienced in clinical care. Subjects were stratified as experienced or novice based on prior critical care training. A checklist of critical actions was designed using face validity for each scenario to evaluate task completion and performance. Simulation sessions were video recorded and scored by two independent raters. Construct validity was assessed under the assumption that experienced clinicians should perform better than novice clinicians on each task. Reliability was assessed as percentage agreement, kappa statistics and Bland-Altman plots as appropriate. RESULTS: Eleven experts and seven novices completed evaluation. The overall agreement on common checklist item completion was 84.8 %. The overall model achieved face validity and was consistent with our construct, with experienced clinicians trending towards better performance compared to novices for accuracy and speed of task completion. CONCLUSIONS: A standardized video assessment tool has potential to provide a valid and reliable method to assess 12 performances of clinicians facing simulated medical emergencies.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。