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Statistical process control methodology was developed by Walter Shewhart in the 1920s as part of his work on quality control in industry. Shewhart observed that quality is about hitting target specifications with minimum variation. While every process is subject to variation, that variation can arise from 'common cause' variation, inherent in the process, or 'special cause' variation which operates from outside of that process. This distinction is crucial because the remedial actions are fundamentally different. Reducing common cause variation requires action to change the process; special cause variation can only be addressed if the external cause is identified. Statistical process control methodology seeks to distinguish between the two causes of variation to guide improvement efforts. Using case studies, this Element shows that statistical process control methodology is widely used in healthcare because it offers an intuitive, practical, and robust approach to supporting efforts to monitor and improve healthcare. This title is also available as Open Access on Cambridge Core.
Quality improvement (QI) analytic methodology is rarely encountered in the emergency medicine literature. We sought to comparatively apply QI design and analysis techniques to an existing data set, and discuss these techniques as an alternative to standard research methodology for evaluating a change in a process of care.
Methods
We used data from a previously published randomized controlled trial on triage-nurse initiated radiography using the Ottawa ankle rules (OAR). QI analytic tools were applied to the data set from this study and evaluated comparatively against the original standard research methodology.
Results
The original study concluded that triage nurse-initiated radiographs led to a statistically significant decrease in mean emergency department length of stay. Using QI analytic methodology, we applied control charts and interpreted the results using established methods that preserved the time sequence of the data. This analysis found a compelling signal of a positive treatment effect that would have been identified after the enrolment of 58% of the original study sample, and in the 6th month of this 11-month study.
Conclusions
Our comparative analysis demonstrates some of the potential benefits of QI analytic methodology. We found that had this approach been used in the original study, insights regarding the benefits of nurse-initiated radiography using the OAR would have been achieved earlier, and thus potentially at a lower cost. In situations where the overarching aim is to accelerate implementation of practice improvement to benefit future patients, we believe that increased consideration should be given to the use of QI analytic methodology.