Funnel Plots

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A funnel plot is a chart that helps to understand variation within a system.

What is it?

A funnel plot is a chart that shows the measure of interest on the vertical (y) axis and sample size on the horizontal (x) axis.  A line showing the overall average of the measure, and ‘funnel limit’ lines are also shown.

Points above or below the funnel limits differ from the others by more than would be expected by chance.

(Note for people familiar with SPC:  The funnel limits are based on the same calculations as the control limits in SPC charts.  In SPC charts, when the sample size at each data point varies, the control limits vary.   When you sort these in order of sample size then you get a ‘funnel’ shape.)

What does this tool look like?
Image of Funnel Plots tool
Why use this tool?

A funnel plot is a useful way to show comparisons between different units to identify where there may be special cause variation.

It is helpful if you have data relating to different teams, hospitals, schools, NHS boards, Local Authorities for example, which are of different sizes and you want to avoid misleading ranking that doesn’t account for this.  The measure you plot would have a denominator (e.g. rate, proportion or average).

You might want to use it to identify which units you might need to focus improvement work on, and also which ones might have something to learn from.

Where does this tool fit in the improvement journey?

 

This tool is relevant at this stage of the Quality Improvement Journey.

How to use it.

How to interpret it

Where a point is outside the funnel limits this indicates a difference that would be very unlikely if only common cause variation was present.  This helps to focus inquiry.  You may wish to look first into whether there are any reasons why the data might be different (e.g. are they using the same definitions?), and then whether there is something else going on.

If a unit has better results than others, then there may be something to be learned from them that can lead to improvement across the system.  If one is worse, then it could be a good place to focus on improvement.

How to create it

ISD have created a handy excel tool for this, which you can download here: http://www.isdscotland.org/Health-Topics/Quality-Indicators/Statistical-Process-Control/ (you will need to save as a macro enabled excel file).

You can also create funnel plots in excel using most QI software or by doing the calculations yourself and using a scatter plot, but ask your local data expert if you’re not sure. 

If you use QI charts software, you can sort your data by sample size and create an SPC chart appropriate to your data.