Abstract 2691: A Randomized Study of High-Fidelity Simulation Training on Actual Cardiopulmonary Resuscitation Performance
Introduction: Simulation is increasingly being incorporated into CPR training. This educational method has been shown to improve trainee performance in simulated settings but the impact on actual patient care remains unknown. We hypothesized that high-fidelity simulation training would improve CPR performance during real in-hospital cardiac arrests.
Methods: New PGY2 residents were randomized to either standard training or standard training plus participation in a 4-hour resuscitation leadership course using a high-fidelity simulator (Human Patient Simulator, Medical Education Technologies) with video debriefing prior to assuming the role of resuscitation team leaders at an academic medical center. Standard training included monthly review of Advanced Cardiac Life Support algorithms with 30 minutes of low-fidelity simulation and weekly debriefing sessions. Objective metrics of resuscitation performance were obtained from a CPR-sensing defibrillator (MRx-QCPR, Philips Medical Systems). Interns provided subjective evaluation of their residents through Likert scale questions (with a high score of 5) at the end of each month.
Results: Fourteen residents were randomized to receive high-fidelity simulation between April and July 2007, while 16 served as controls. These 30 residents then led 113 in-hospital cardiac arrest resuscitations between July 2007 and May 2008. Sixty four surveys were completed by 47 interns who served as resuscitation team members. The results are shown in the table⇓ below.
Conclusions: Actual resuscitation performance was excellent in both groups, as measured by both the defibrillator and intern evaluations, with the high-fidelity simulation experience adding no incremental benefit over the current training methods. This is likely due to a previously optimized training regimen. However, assessing the impact of a simulation-based curriculum on actual resuscitation performance is feasible using CPR-sensing technology.