BACKGROUND: Unplanned extubation (UE) is a common adverse event and is an important measure of quality and patient safety in the neonatal ICU. It is well recognized that UEs occur more frequently in neonates than in any other group of ventilated patients. The objective of this study was to evaluate the effectiveness of the quality improvement interventions in reducing the rates of UE in a tertiary neonatal ICU. METHODS: A retrospective audit performed on ventilated infants showed a rate of 7.2 unplanned extubations per 100 ventilation days in a 12-month period (April 2016 to March 2017). We evaluated the common factors associated with UEs, with the primary reasons being loose fixation and providing care without assistance. We introduced sequential interventions focusing on better practices. Standardizing endotracheal tube fixation, continuous scrutiny of fixation through checks, 2-person technique for providing care, and adverse event reporting were a few of the important interventions. Rates of UE for each month were collected and analyzed. RESULTS: With interventions, UE rates reduced by 80% (from 7.2 per 100 ventilated days in the pre-implementation period to 1.4 per 100 ventilated days in the post-implementation period) in 12-18 months. CONCLUSIONS: Significant reductions in UE rates were achieved by implementing quality improvement interventions. It is important to analyze critical event rates continuously and for longer periods of time to determine the true change.

Background Major surgery accounts for a substantial proportion of health service activity and resource consumption, due not only to the primary procedure, but also the short and long-term implications of perioperative complications. It is likely that both compliance with best practice processes and outcomes from major surgery vary substantially between hospitals and therefore could be targets for quality improvement. Methods The Perioperative Quality Improvement Programme (PQIP) patient study is a multi-centre prospective cohort study which recruits participants undergoing major inpatient non-cardiac surgery with three main aims: to measure and improve processes of care and outcome from major surgery; to implement and evaluate a complex intervention aiming to enhance the use of data for improvement by clinical teams; and to create a national database to support collaborative research and efficient study design. The prospective dataset combines variables for risk adjustment, process measures and both objective and patient reported outcome data. Longer-term outcomes are collected through linkage to national administrative datasets (mortality and readmissions). PQIP deploys a theoretically underpinned improvement methodology to support the use of data for improvement by perioperative clinicians, incorporating action research principles to enable changes to be made in response to user feedback. Dissemination of interim findings (non-inferential) form a part of the improvement methodology and are provided to participating centres at regular intervals, including near-real-time feedback of key process measures. Inferential analyses will be published in the peer-reviewed literature, supported by a multi-modal communications strategy to patients, public, policy makers and academic audiences as well as clinicians. Discussion PQIP is the first national effort in the UK to measure and report risk-adjusted complications, patient-reported outcome and mortality rates for patients undergoing major surgery across multiple surgical specialties in the UK. Its main limitation is the risk of sampling bias due to the requirement for patient consent, and because local resource constraints may lead hospitals to recruit a convenience sample, rather than a truly random sample. We will evaluate this risk by using Hospital Episode Statistics (HES) to identify all patients undergoing PQIP eligible procedures, and undertaking sensitivity analyses comparing common data points in the PQIP sample and the HES population. As the purpose of PQIP is to support quality improvement and research as opposed to quality assurance or institutional comparisons, even if they exist, such sampling biases are unlikely to materially affect the ability of the programme to achieve its aims.

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