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How do you know that your care is improving? Part II: Using control charts to learn from your data.

Raymond G Carey1

  • 1R. G. Carey and Associates, Park Ridge, Illinois, USA.

The Journal of Ambulatory Care Management
|May 9, 2002
PubMed
Summary

Control charts offer a powerful method for analyzing data variation and documenting process improvement, surpassing traditional run charts. This tool helps identify special cause variation and measure intervention success.

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Area of Science:

  • Quality Management
  • Statistical Process Control

Background:

  • Builds upon previous work on run charts for data variation analysis.
  • Introduces control charts as a more advanced tool for process improvement.

Purpose of the Study:

  • To explain the fundamental components of control charts.
  • To detail methods for detecting special cause variation.
  • To guide the selection of appropriate control charts based on data type.

Main Methods:

  • Explanation of control chart elements.
  • Description of statistical tests for variation detection.
  • Guidance on control chart selection criteria.

Main Results:

  • Demonstrates the application of control charts in a case study.

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  • Documents a successful intervention using control chart analysis.
  • Provides recommendations for relevant computer software.

    • Conclusions:

    • Control charts are a superior tool for analyzing variation and measuring process improvement compared to run charts.
    • Effective implementation involves understanding chart elements, variation tests, and data-appropriate selection.
    • Control charts can successfully document process interventions.