2. Line Charts (aka run charts, trend charts) Scott Davis QI Coordinator Tacoma Pierce County Health Department June 2012

3. Objectives Understand … Purpose of line charts When you would use them How to interpret them How to construct them

4. Line Chart Why would I use this tool? Indicates pattern of variation over time Helps avoid over-interpreting a particular result/sample Can indicate expected range of random variation (aka common cause) Can indicate patterns of unexpected and attributable variation (aka special cause)

5. Line Chart When would I use this tool? Most likely – in Evaluation to monitor performance Assessment – when selecting improvement opportunities Analysis – when trying to understand variation over time

6. Not capable 5 Here’s where we are Here’s where we need to be

7. Line Chart Elements Samples by time unit, run, etc. Count of individuals or average or % of total of the sample Calculated mean from initial series of samples … at LEAST 8

8. What am I graphing? Time (or other continuous variable): An average within a sample Defect (or other attribute variable) – Total within a sample or – % defective within a sample Mean of all averages (at least 8 data points)

9. Line Chart Indicators of Unexpected/Attributable Variation Trends (7 points in a row) Shifts (7 continuous points above/below the mean) Data Collection Problems/Manipulation (5 identical points in a row) Shift/staff variation (alternating pattern)

15. Box Plots for Control 14 A box plot used in this way will show you variation over time, but also variation within a sample. If you just know the average over time, but not the variation within a given time period, you might miss something important.

16. Control Charts Same elements as a run chart plus: Upper/lower control limits placed a certain number of standard deviations (or practical equivalent) from the mean Like the mean, limits are based on initial series of samples Typical choice is 3 (captures 98% of the variation from a normally distributed population)

17. Tampering Example So there’s this QC guy named Walter and he’s frustrated … 16 Predictable Range of Random Variation Upper spec Lower spec Part width in 1/100 th inches Operator over-interprets this expected variation as unexpected

18. Tampering Example Operator adjusts machine when it didn’t need it … Then adjusts again in reaction to a result greater than he expected Out of spec Much more variation

19. Control Chart Set the predictable range within the customer specification 18 Upper control limit Lower control limit

20. Objectives Understand … Purpose of line charts When you would use them How to interpret them How to construct them