A Human Factors Approach to Building High-Performance Multi- Professional Cardiac Arrest Teams

Abstract

Background: The American Heart Association (AHA) estimates that annually there are approximately 200,000 in-hospital cardiac arrests (IHCA). Hospitals have implemented multidisciplinary teams trained in advanced cardiac life support (ACLS) to provide care during these events. Outcome measures of these team’s effectiveness are typically mortality rates at discharge and reduction of unplanned cardiac arrest occurring outside of the ICU. Neither is a sensitive measure of team effectiveness. Methods: Using a retrospective analysis of 10 simulated code blue events we developed a metric of team effectiveness for code blue teams that also identifies specific teamwork weaknesses. Results: The new ASU-Mayo metric was highly correlated with Mayo high performance team scale (MHPTS) (r (6) = .71), team emergency assessment measure (TEAM) (r (6) = .84), and the observational skill-based assessment tool for resuscitation (OSCAR) (r (6) = .89) metrics as well as the ratings of the subject matter experts (r (6) = .88). Conclusions: We developed a team performance metric that allows for the identification of performance gaps therefore, can allow for targeted intervention with the intention of providing trainees richer feedback on performance. Also, it will generate quantitative assessments of the value of mock code exercises and can be used to evaluate interventions. Our understanding of teamwork during a simulated code blue event was also enhanced.