Statistical Process Control

Explores the role of statistical process control in offering an intuitive, practical, and robust approach to supporting efforts to improve healthcare. This title is also available as Open Access on Cambridge Core.

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.