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Scottish Improvement Skills

Learn the importance of measuring data over time, interpret run charts, explain improvement outcomes, and understand the system of profound knowledge. This session covers the basics of data analysis using run charts.

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Scottish Improvement Skills

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  1. Scottish Improvement Skills Data analysis: Introduction to run charts

  2. System of Profound Knowledge Deming 2000

  3. Data analysis • By the end of this session you will be able to: • Explain why it is important to measure data over time • Interpret run charts using rules to differentiate between random and non-random variation • Use run charts to explain outcomes of improvement work to others • Use and explain the importance of using a family of measures.

  4. Understanding Variation • Random variation – affects everyone and all outcomes over time • Non-random variation – does not affect everyone or not part of the system all the time; arises because of specific circumstances.

  5. Analysing data: before and after ‘When you have two data points, it is very likely that one will be different from the other.’ W Edwards Deming

  6. Data analysis: Introduction to run charts Weight (lbs)

  7. Data tells a story: New healthier me!

  8. Introduction to run charts • A ‘time series’ chart tells a story. • Baseline data helps us to see whether a change is an improvement. • Any changes made are shown on the chart.

  9. What is a run?Vanessa’s Weight

  10. How many runs (1) ?

  11. How many runs (1) ?

  12. How many runs (2) ?

  13. How many runs (2) ?

  14. How many runs (3) ?

  15. How many runs (3) ?

  16. Run charts: signals that identify non-random variation • Six or more data points in a run (all above or all below median) • Five or more consecutive data points all increasing or decreasing • Too many or too few runs • An ‘astronomical’ data point A shift A trend See table Consider

  17. Run charts: Rule 1 – a shift

  18. Run charts: Rule 2 – a trend

  19. Run charts: Rule 3 (a) Too few or too many runs

  20. Run charts: Rule 3 (b) Total useful data points Total data points

  21. Run charts: Rule 4

  22. Applying the rules Change

  23. Applying the rules (1) Change

  24. Applying the rules (2) Change

  25. Applying the rules (3) Change

  26. Applying the rules (4)

  27. Baseline data • How urgent is a change? • Is it necessary to identify whether the system has any non-random variation before introducing a change? • What is the source of historical data? • If there is existing data, make use of it. • If there is no existing data, decide whether to start collecting data before introducing the change.

  28. Project work: baseline data • Does baseline data exist somewhere? If so, how can you access it? • If you are going to collect it, how long will you collect baseline data for before introducing a change? Why?

  29. Data analysis: Introduction to run charts: summary • Data tells a story • Look for signals of non-random variation • Rules: • Shift • Trend • Too few or too many runs • Astronomical point • Baseline data

  30. References and further resources Provost Lloyd P & Murray S (2011) The Health Care Data Guide: Learning from Data for Improvement Jossey-Bass

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