Understanding Statistical Process Control charts

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Understanding Statistical Process Controlcharts

• Amanda McGough
• Clinical Effectiveness Lead
• Hambleton and Richmondshire PCT

Acknowledgements to Tony Roberts and Clinical
Indicators Support Team, Scotland
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Traditional approach in NHS

• League tables
• Confidence intervals

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Diabetes QOF data
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Ranking performance
Which practices are outliers?
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Ranking performance
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Statistical Process Control

• Simple graphical way to display data and outcomes
• Relatively easy to construct
• Easy to interpret
• Designed to identify any unusual variation in a
  process

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Background

• Originated in engineering industry
• Used to identify special cause variation
• SPC charts increasingly used in healthcare
• Hospital-acquired infections
• National blood service
• Consultant appraisal

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How good is your handwriting?

• Write a line of as
• Now write a line of as but write one of them
  with your opposite hand
• Ask your neighbour to spot the odd a

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Types of variation

• Consider health care systems as processes
• All processes have inherent random variability
  known as common cause variability
• Unexpected events / unplanned situations can
  result in special cause variation

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Anatomy of an SPC funnel chart
Special cause
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South Tees Hospitals Trust
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Coronary Heart Disease data

• Prevalence across Tees and North Yorkshire PCTs
• Prevalence across GP practices
• Individual Quality and Outcome indicators across
  GP practices

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Are SPC charts useful?

• Enables comparison across
• Organisations
• Networks
• Clinical services and GP practices
• Identifies outliers (high or low)
• Spread good practice
• Understand poor performance
• Demonstrate improvement
• For individual practices
• For PCT as a whole

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The way ahead

• SPC charts can be produced for all clinical and
  quality indicators eg QOF
• National diabetes data can be produced in SPC
  format
• Likely that CHD and QOF data will be published in
  SPC format in 2006