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G384(P) A quality improvement (qi) project to increase the number of ventilated days between unplanned extubations within paediatric intensive care – using real time statistical monitoring
  1. M Russell,
  2. J Alexander,
  3. L Hulme
  1. Paediatric Intensive Care Unit, University Hospital of North Staffordshire, Stoke-on-Trent, UK

Abstract

Aims Unplanned extubation is an important quality issue. Quality surveillance showed that we were not achieving national targets for the number of ventilated days between unplanned extubations. A QI project was launched with the primary aim of increasing the number of ventilated days between unplanned extubations.

QI literature directed at unplanned extubations have used statistical methodology that detects significance at the end of a fixed time period. This does not allow continuous quality monitoring. “G type” charts are a type of statistical quality control chart that exhibit improved sensitivity over conventional statistical approaches when dealing with rare events.

Methods A Root cause analysis showed us that most unplanned extubations were secondary to the endotracheal tube (ETT) slipping through loose tapes in lightly sedated patients. A series of interventions (Table 1) were implemented. Following intervention implementation we performed continuous monitoring using a “g-type” chart (Figure 1).

Abstract G384(P) Table 1

Intervention

Results The mean number of ventilated days between unplanned extubations increased from 1 per 40.8 days to 1 per 250 days. G-chart 1 clearly illustrates that the mean number of ventilated days between unplanned extubations increased above the upper confidence limit following intervention implementation.

Conclusion We have shown an intervention that can significantly increase the number of ventilated days between an unplanned extubation. “G type” charts can be used to monitor the real time effects of an intervention. The surveillance advantage of these charts is that they take immediate advantage of each adverse event rather than waiting until the end of a pre-defined time period to identify root causes and thus enables continuous quality improvement.

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