Resources

Across human services, organisations struggle with the right response to quality data. Too often we spend time and resources ‘fixing’ the right thing – or addressing the right thing but not fixing it. 

Walter Shewhart, one of the pioneers of quality management, 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. Statistical process control (SPC) method seeks to distinguish between the two causes of variation to guide more effective improvement efforts.

This distinction between the ‘variations’ is crucial because the actions we should take in response are fundamentally different. Reducing common cause variation requires action to change the process; special cause variation can only be addressed if that ‘cause’ is identified. In other words, it stops us ‘jumping at shadows’, and guides the right response to the results presented. 

Using explanation of SOC theory, supported by case studies, this latest in the ‘Elements of Improving Quality and Safety in Healthcare’ series recommends that the statistical process control method is widely used in healthcare because it offers an intuitive, practical, and robust approach to supporting efforts to monitor and improve care. 

This is an essential guide to using SPC presentation and analysis for quality data, that can be adopted across all human services to support better analysis and decision-making for improvement.