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Testing a Computational Model of Interruptions Between Clinicians in a Hospital Ward
DescriptionInterruptions in healthcare are associated with increases in errors, which can be detrimental for patient safety. However, attempts to reduce interruptions have generally not been successful. Interruptions can be problematic for the interruptee but may be necessary for the interrupter to maintain patient safety. We developed a computational model representing the role that interruptions play for clinicians within a hospital ward. In a series of simulations we found that urgent interruptions can improve team efficiency when post-interruption consequences are mild, but worsen team efficiency when consequences are severe. When consequences are mild, nurses are most efficient when working on tasks with similar levels of importance and cost, but when consequences are severe, they are most efficient when working on tasks with contrasting importance and cost. These predictions can be tested experimentally, and the model can guide future interventions so that they best support the nursing team and maintain patient safety.