What is Statistical Process Control?

This is the online version of Mastering Statistical Process Control Charts in Healthcare, a book currently under early development.

The ultimate purpose of collecting and analysing data is to support better decision-making and actions that will lead to improvement. Statistical Process Control (SPC) is a proven methodology for doing just that.

SPC methodology provides a philosophy and framework for continually learning about the behaviour of processes for analytical purposes – where the aim is to act on the underlying causes of variation to maintain or improve the performance of a process.

SPC was initially developed by Walter A. Shewhart in the 1920s to improve the quality of manufactured products and has since been successfully used in many settings including healthcare.

At is core, SPC methodology involves the plotting of data over time to detect unusual patterns or variations that might indicate a change or problem with a process. This simple graphical device is underpinned by an intuitive theory of variation, the hypothesis-generating testing-cycle of the scientific method, and statistical theory.

To master SPC, it is essential to first understand the underlying theory of variation, which we explore in Part 1 of this book. Next, proficiency in using software to construct SPC charts is key, and this is covered in Part 2. In the later sections, we delve into specialized topics for more advanced SPC practitioners, offering deeper insights and expertise.