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

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

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)

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

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

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

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)

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)

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.

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)

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

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

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

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