Abstract
Cardiac arrests are often preceded by a period of physiological deterioration. Preventing potentially avoidable cardiac arrests therefore depends on reliable recognition of, and response to, those deteriorations. Our hospital's acute medical unit had one of the highest rates of cardiac arrest in our organisation at baseline. The aim was to reduce our unit's cardiac arrest rate by over 50%. Pareto chart analysis identified unreliable processes in the recognition and response to deteriorating patients. Process mapping exercises were performed, then the model for improvement and rapid cycle tests of change were used to develop standardised processes for clinical observations, recognising deteriorating patients and responding to hypoxia. Multidisciplinary learning from what went well, incorporating resilience engineering principles, helped to identify good practice and then test ways of making good practice happen more reliably. Learning from success also addressed some of the psychological barriers to change by encouraging pride in work and a positive focus within our unit. The cardiac arrest rate reduced from 4.3/1000 (October 2014 to February 2016) to 1.1/1000 (March 2016 to end of 2016), associated with improved reliability of the following process measures: reliability of clinical observations, documentation of target oxygen saturations, identification of hypoxia and completion of structured response to hypoxia. This study is an example of a multidisciplinary team engaging in quality improvement, identifying their own local problems and testing their solutions scientifically. Learning from what went well had a positive impact on the project, and the team plans to spread the successful interventions across the organisation.