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Measuring and improving the quality of postoperative epidural analgesia for major abdominal surgery using statistical process control charts
Author(s) -
Duncan Fiona,
Haigh Carol
Publication year - 2013
Publication title -
journal of clinical nursing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.94
H-Index - 102
eISSN - 1365-2702
pISSN - 0962-1067
DOI - 10.1111/jocn.12116
Subject(s) - medicine , quality management , statistical process control , psychological intervention , audit , physical therapy , process (computing) , operations management , nursing , computer science , management system , management , economics , operating system
Aims and objectives To explore and improve the quality of continuous epidural analgesia for pain relief using Statistical Process Control tools. Background Measuring the quality of pain management interventions is complex. Intermittent audits do not accurately capture the results of quality improvement initiatives. The failure rate for one intervention, epidural analgesia, is approximately 30% in everyday practice, so it is an important area for improvement. Continuous measurement and analysis are required to understand the multiple factors involved in providing effective pain relief. Design Process control and quality improvement Methods Routine prospectively acquired data collection started in 2006. Patients were asked about their pain and side effects of treatment. Statistical Process Control methods were applied for continuous data analysis. A multidisciplinary group worked together to identify reasons for variation in the data and instigated ideas for improvement. The key measure for improvement was a reduction in the percentage of patients with an epidural in severe pain. Results The baseline control charts illustrated the recorded variation in the rate of several processes and outcomes for 293 surgical patients. The mean visual analogue pain score (VNRS) was four. There was no special cause variation when data were stratified by surgeons, clinical area or patients who had experienced pain before surgery. Fifty‐seven per cent of patients were hypotensive on the first day after surgery. We were able to demonstrate a significant improvement in the failure rate of epidurals as the project continued with quality improvement interventions. Conclusion Statistical Process Control is a useful tool for measuring and improving the quality of pain management. Implications for nursing management The applications of Statistical Process Control methods offer the potential to learn more about the process of change and outcomes in an Acute Pain Service both locally and nationally. We have been able to develop measures for improvement and benchmarking in routine care that has led to the establishment of a national pain registry.