Synopsis

Introduction

  1. What is SPC?
  2. Preface
  3. Synopsis

Part 1: Understanding Variation

  1. Understanding Variation
  2. Understanding SPC Charts
  3. Looking for Signals
  4. Using SPC in Healthcare

Part 2: Constructing SPC Charts with R

  1. Your First SPC Charts with Base R
  2. Calculating Control Limits
  3. Highlighting Freaks, Shifts, and Trends
  4. Core R Functions to Construct SPC Charts
  5. SPC Charts with ggplot2
  6. Introducing qicharts2

Part 3: Advanced SPC Techniques

  1. Screened I Chart (eliminating freak moving ranges before calculating limits)
  2. SPC Charts for Rare Events
    • T Chart for Time Between Events
    • G Chart for Opportunities Between Cases
    • Bernoulli CUSUM chart for binary data
  3. Prime Charts for Count Data with Very Large Subgroups
  4. I Prime Chart for Measurement Data With Variable Subgroup Sizes
  5. Funnel Plots for Categorical Subgroups
  6. Pareto Charts for Ranking Problems

Part 4: Best Practices, Controversies, and Tips

  1. Tips for Effective SPC Implementation
    • Engaging stakeholders
    • Automating production of SPC charts
    • Continuous monitoring and improvement.
  2. Common Pitfalls to Avoid
    • Data issues, misinterpretation of charts
    • Signal fatigue
    • Automating rephasing
    • The control chart vs run chart debate
    • One-to-one relation between PDSA cycles and dots on the plot
  3. The forgotten Art of Rational Subgrouping

Part 5: Conclusion and Final Thoughts

  1. Conclusion and Final Thoughts
    • Summary of Key Points
    • Emerging trends in SPC and healthcare analytics
    • Encouragement for Continuous Learning and Application
    • Final Thoughts

Appendices

  1. Included Data Sets
  2. Basic Statistical Concepts
  3. Two Types of Errors When Using SPC
  4. R Notes
  5. Table of Critical Values for Longest Runs and Number of Crossings
  • Ideas for chapters / topics
    • Case Studies and Worked Examples
    • Dual Charting
    • High Volume Data
    • Scaling Up Charts (technical issues, tabular charts, grids)
    • When to Transform Data Before Plotting
    • Resources and Further Readings (books, websites, communities, R packages)
    • Glossary of Terms
    • Improved Runs Analysis Using the Bestbox and Cutbox approaches
    • Multivariate charts
  • Ideas for papers:
    • Improved I chart (in process)
    • The problem with SPC
    • RAGs to RICHes (two voices)
    • Big data issues – CUSUM vs 3000 SPC charts