Preface

This book is about the practical application of Statistical Process Control (SPC) methodology in healthcare.

At its core, SPC is founded on a powerful, intuitive insight: processes are subject to two sources of variation – common cause and special cause. This distinction enables us to understand, monitor, and improve a wide range of processes. With this insight comes a suite of visual tools – run charts and control charts – that help differentiate between common and special cause variation with ease.

However, while SPC tools are conceptually simple to use, applying them correctly can be a challenge. As noted in a systematic review of SPC in healthcare:

… although SPC charts may be easy to use even for patients, clinicians, or managers without extensive SPC training, they may not be equally simple to construct correctly. To apply SPC is, paradoxically, both simple and difficult at the same time.

– Thor et al. (2007)

This book seeks to address this paradox by providing a straightforward, practical guide to the correct construction of SPC charts in healthcare using modern software.

What Sets This Book Apart?

This book is a step-by-step guide to easily and correctly producing SPC charts. Since this involves statistics, computing, and visualization, our software of choice is R – often referred to as the lingua franca of statistical computing and visualization.

What makes this book unique is its specialized, practical, and modern approach, specifically tailored for data scientists and practitioners in the healthcare sector. Here’s what you can expect:

  1. Target audience
    This book is for anyone looking to produce SPC charts using modern tools. While it is specifically geared toward data scientists, we recognize that our readers may include analysts, practitioners, managers, educators, students, researchers, clinicians, or even patients. Regardless of your role, if you work with healthcare data and want to master SPC, then this book is for you.

  2. Why R?
    We’ve chosen R as our primary tool because it is popular, free, and open-source. While we are pro-R, we are not anti-other software; readers can adapt the concepts in this book to their preferred tools.
    R has several key advantages:

    • Transparency and reproducibility: R’s programming capabilities ensure every step of data analysis and SPC chart construction is documented, making your work both readable and reproducible – something rarely achieved with “point-and-click” software.
    • Automation: R allows for automating repetitive tasks such as generating monthly reports, slide decks, and SPC dashboards with customizable, high-quality graphics.

  3. Healthcare-focused
    Unlike general SPC books, this one focuses on healthcare-specific applications, addressing challenges like patient safety, clinical outcomes, and operational efficiency. It complements the foundational concepts in our companion book, Statistical Process Control: Elements of Improving Quality and Safety in Healthcare (Mohammed 2024).

  4. Practical and hands-on
    The book takes a hands-on approach, providing real-world examples and case studies to help readers produce and use SPC charts confidently. This practical emphasis bridges the gap between theory and application.

  5. Comprehensive coverage
    From foundational principles to advanced SPC techniques, this book covers it all. It’s designed to cater to both beginners and experienced data scientists, ensuring everyone finds value.

  6. Additional resources
    Readers will gain access to supplemental materials, including:

    • R scripts
    • Datasets
    • A dedicated GitHub repository for continued learning and collaboration.

Prerequisites

No prior knowledge of SPC is assumed. However, basic familiarity with R is necessary to follow the steps and algorithms for constructing SPC charts. For those new to R, we recommend excellent (and free) resources such as the NHS-R Community.

How to Use This Book

  • New to SPC?: Start with Chapter 1 to learn about variation.

  • Eager to start plotting?: Jump straight to Chapters 5 and 6.

  • Want to go deeper?: Advanced chart types and topics are covered in later chapters for both beginners and experts.

  • Need more resources?: Visit our GitHub repository for datasets, code, and updates.

We hope this book proves valuable, and we welcome your feedback for ongoing improvement.

About the Authors

  • Jacob Anhøj: Medical doctor with over 30 years of experience and a diploma in Information Technology. With 45+ published papers, two books, and extensive teaching expertise, he is deeply passionate about patient safety and quality improvement in healthcare. Jacob is an experienced R user and the creator of several R packages, including qicharts2, widely used for SPC chart construction and analysis.
    Contact:

  • Mohammed Amin Mohammed: Emeritus Professor of Healthcare Quality and Effectiveness at the University of Bradford, Mohammed has over 100 peer-reviewed publications. His landmark paper introducing SPC to healthcare (Mohammed, Cheng, and Marshall 2001) and his book Statistical Process Control: Elements of Improving Quality and Safety in Healthcare (Mohammed 2024) are seminal works in the field. He is also the founder of the NHS-R Community, promoting the use of R in healthcare.
    Contact: ;

References

Mohammed, M A. 2024. Statistical Process Control. Elements of Improving Quality and Safety in Healthcare. Cambridge University Press. https://www.cambridge.org/core/elements/statistical-process-control/60B6025BF62017A9A203960A9E223C10.
Mohammed, M A, Rouse Cheng KK, and T Marshall. 2001. “Bristol, Shipman, and Clinical Governance: Shewhart’s Forgotten Lessons.” Lancet 357. https://doi.org/10.1016/s0140-6736(00)04019-8.
Thor, Johan, Jonas Lundberg, Jakob Ask, Jesper Olsson, Cheryl Carli, Karin Pukk Härenstam, and Mats Brommels. 2007. “Application of Statistical Process Control in Healthcare Improvement: Systematic Review.” BMJ Qual Saf 16: 387–99. https://doi.org/10.1136/qshc.2006.022194.