1. Colorado 5M WebEx Variation, Run Charts, and Control Charts Beth A. Katzenberg, EdM, MBA, CPHQ Director, Corporate Quality & Compliance Colorado Foundation for Medical Care

3. You must understand the type of variation that is occurring as this will determine how you address the problem.

6. Tools to identify variation

7. Run charts

8. Run chart Graph of data over time Track performance Display & identify variation

9. Run chart analysis: Common cause variation only Common cause variation around the median: Only common cause variation present. Output may or may not meet customer/ patient requirements

11. Expected number of runs

12. High probability of special cause variation: Too few runs Too many runs = 0.05) (

13. Run chart analysis: Run length Special cause—run length: <20 data points (not on median): A run of 7 data points on one side of the median (either above or below) 20+ data points (not on median): A run of 8 data points on one side of the median

14. Run chart analysis: Trends Special cause—trends: Consecutive points all going up or all going down. May cross the median. Ignore 2+ consecutive points that are the same. (Pyzdek, 2003) 4 5 to 8 7 101 or more 6 21 to 100 5 9 to 20 # Consecutive points all increasing or decreasing Total # data points on chart

15. Run chart analysis: Freaks Freaks: The presence of more than one or two dramatic spikes suggests the process is out of control. Run charts not as sensitive in identifying, thus may fail to detect.

16. Run chart analysis: Cycling Cycling: A zigzag or saw-tooth pattern with 14+ points in a row alternating up or down.

18. Control charts

19. Control chart Run chart with control limits Determines type of variation Is process stable? Predictable?

20. Dividing control chart into zones Each zone is 1 sigma wide UCL LCL X Zone A Zone B Zone C Zone C Zone B Zone A

23. Deciding which control chart to use

25. Control chart example 1 Common cause variation only

26. Control chart example 2 new hire snowstorm

27. Control chart example 3 Common cause variation only; can predict will stay within control limits, if no changes

28. Control chart example 4 Out of control, unpredictable

29. Just because a process is under control (common cause variation only), it does not mean that the process is meeting expectations. It just means that the process is predictable and you are getting consistent performance.

34. Beth Katzenberg, EdM, MBA, CPHQ Director, Corporate quality & compliance Colorado Foundation for Medical Care [email_address]