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920 Reducing cardiac arrests in an acute medical unit

2017·0 Zitationen·AbstractsOpen Access
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Zitationen

3

Autoren

2017

Jahr

Abstract

<h3>Background</h3> Cardiac arrests are often preceded by a period of physiological deterioration. Preventing cardiac arrests depends on reliable recognition of, and response to, those deteriorations. Our Acute Medical Unit was identified as having the highest number of cardiac arrests in the hospital in 2013/2014. Our baseline cardiac arrest was 4.3/1000 (October 2014 – February 2016). <h3>Objectives</h3> The aim was to reduce our unit’s cardiac arrest rate by over 50%. <h3>Methods</h3> Process mapping exercises identified unreliable processes in the recognition and response to deteriorating patients. Pareto chart analysis (Figure 1) identified hypoxia as the most commonly missed cause of deterioration within the unit. The model for improvement and rapid cycle tests of change were used to develop standardise key clinical processes. Innovative multi-disciplinary learning from what went well, called ‘Save of the Month’, helped to identify good practice and develop pride in work. <h3>Results</h3> The cardiac arrest rate showed 63% reduction from the baseline period; 4.3/1000 (October 2014 to February 2016) to 1.6/1000 (March 2016 to June 2017). 11580 patients were included in this time period (Figure 2). The cardiac arrest reduction was associated with significant improvements in the following process measures when run chart rules are applied: clinical observation bundle completion, documentation of target oxygen saturations, identification of hypoxia and completion of structured response to hypoxia (Figures 3–7). <h3>Conclusions</h3> Multi-disciplinary learning from what went well can help address psychological barriers to change. This project enabled a multi-disciplinary frontline team to engage in quality improvement, identify their own local problems and test their solutions scientifically.

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Cardiac Arrest and ResuscitationHealthcare Systems and Public HealthArtificial Intelligence in Healthcare and Education
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