Cardiac Arrest Management in Pregnancy: Review of Team Performance in High-Fidelity Simulations

OBSTETRICS AND GYNECOLOGY(2022)

引用 0|浏览3
暂无评分
摘要
INTRODUCTION: Management of cardiac arrest during pregnancy has several unique components when compared to resuscitation of non-pregnant patients. These interventions are not emphasized in current national training courses but are critical to optimizing outcomes for the mother and fetus. The objective of the current study was to evaluate team performance during high-fidelity maternal cardiac arrest simulations to identify areas of focus for future training. METHODS: At a national course, multidisciplinary teams participated in high-fidelity simulation cases of obstetric emergencies to include maternal cardiac arrest. Critical actions were determined by review of evidence-based recommendations for care. Trained facilitators completed standardized checklist assessments for each team’s performance, with each action documented as “not done”, “poorly done”, or “well done”. Descriptive statistics for all elements of performance were evaluated. The study was reviewed and determined to be exempt by the hospital institutional review board. RESULTS: One hundred thirty multidisciplinary teams with complete data participated in simulations from 2014-2019. Less than two-thirds of teams were rated “well done” for standard resuscitation skills such as airway management, defibrillation, and chest compressions. Pregnancy specific modifications, such as left uterine displacement, was rated as “poorly done” or “not done” by 23.8% of teams. CONCLUSION: Overall resuscitation skills by teams during high-fidelity simulations were suboptimal for both routine and pregnancy-specific interventions. This cohort of providers routinely care for pregnant women, so we expect that other providers may be even less familiar with these interventions and suggest there is a gap in education and training that needs to be addressed.
更多
查看译文
关键词
pregnancy,team performance,high-fidelity
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要