Intensive care units (ICUs) are complex care environments at high risk for medical errors. In this retrospective study, researchers identified the occurrence of common ICU scenarios and skills during code blue events and measured trainees’ self-reported confidence in these skills. The analysis found that more than 25% of trainees reported low levels of confidence in three scenarios – familiarity with the advanced life support trolley, electrocardiogram strip interpretation, and operation of an external defibrillator. This process of integrating critical incident data with trainee self-assessment can be generalized to other clinical scenarios to create targeted education and simulation curriculum.

Simulation trainings are widely used to identify safety threats and improve processes. By analyzing video recordings of pediatric cardiac arrest simulations, researchers were able to identify 5 main areas of errors: clinical, planning and execution, communication, distraction, and knowledge/training. Investigating the root causes of these errors can result in improved trainings and, thus, improved patient outcomes.

Identifying incipient clinical deterioration is a prerequisite for rapid response and prevention of harm for hospitalized patients. This study tested a bedside pediatric early warning system, which included an illness severity score, standardized documentation, and monitoring protocols. In a cluster-randomized trial in several high-income countries, implementation of the bundle did not result in decreased in-hospital mortality compared to usual care. The overall mortality rate in the study was less than 0.2%. The authors suggest that this unexpectedly low mortality rate may have made it difficult to detect differences in intervention versus control hospitals. A related editorial suggests that artificial intelligence should be used to identify clinical deterioration and that outcomes beyond mortality should be considered in their evaluation.