Using SPC charts during the lifecycle of a QI project

Picture of Suzie Creighton

Published on 28 March 2023 at 17:15

by Suzie Creighton


In this series of articles, we’ve taken a look at the benefits of using SPC within Quality Improvement (QI) projects. We’ve also had a closer look at how to use SPC charts and what SPC charts can be used for. Now we’re going to drill down into how using SPC charts during the lifecycle of a QI project can help you to discover issues in processes and check in on your ongoing project success.


Using SPC charts to discover issues in current processes

Using SPC charts or control charts can play a really important part in your QI journey. And they can be extremely beneficial to your project.


We have explored the complexities of setting up SPC charts. But how do they ultimately provide huge benefits for those trying to roll out quality improvement?


Let’s have a quick recap on SPC charts, which are ‘a popular tool which will help you to record your QI project and evaluate data – either at a small scale or across your organisation.’ They are statistical tools that help you measure causes – both special and common. They are decision-making tools vital as they help you to identify if there are any variations or trends. ‘Essentially, a control chart uses data plotted in time order to demonstrate how a process changes over time.’


NHS England and NHS Improvement recommend that Statistical Process Control should be used throughout the whole QI project in order to ‘help you identify a project, get a baseline and evaluate how you are currently operating. SPC will also help you to assess whether your project has made a sustainable difference.’


A key factor in what SPC can be used for, is to use your SPC chart to start monitoring before you start your project. This means that you can use SPC charts to discover issues in your current processes, and use the analysis of these charts in order to improve processes for the future.


It’s particularly easy to discover issues in current processes if you are using QI software, such as Life QI. Software solutions such as Life QI will automatically detect and visualise any special cause variation (SCV) in your SPC chart. It means you don't need to implement or remember SCV rules, the software will automatically flag them up for you.


This means that you can quite easily monitor which changes in your QI project are having the most impact. As well as using the SPC chart you can flag up any issues in your current processes.


This is what you can do with SPC charts:


  • ‘Measure the impact of your changes
  • Predict the expected outcomes of improvements
  • Monitor the processes to see if they are under control
  • Analyse the cause of the variations’


Essentially, using SPC charts can give you statistical proof of your improvement!



Use SPC charts to prove the results of a PDSA cycle

Statistical Process Control (SPC) charts are ideally placed to help you in the measurement phase of your improvement journey, as they are designed to measure how a process or system changes over time.


SPC charts can also help you plot and evaluate the results of a Plan Do Study Act (PDSA) cycle. They work by identifying the difference between positive or negative variation just like normal and unusual variation in the data. If you are using a software solution such as Life QI, this can be done really simply. The software enables you to gain rich insights to inform your improvement projects.


You can use Statistical Process Control (SPC) charts to plot and evaluate the results of a PDSA cycle. If you are using Life QI, you simply need to add and link a PDSA cycle to your SPC chart. It will enable you to plot a PDSA cycle on a chart. Once you’ve got into your SPC chart, you can drill down into real detail and simply highlight the data point against which you wish to plot the PDSA cycle. This would normally be the data point that marks to the point in time you starting running the PDSA cycle.


You can read more about how to use SPC charts to measure your QI projects here and here.



Use SPC charts to measure the long-term results of an improvement initiative

As you can use an SPC chart to show whether an intervention has any impact, they can give such valuable insight into ongoing improvement initiatives, while also providing statistical proof as to whether your ongoing efforts are still successful.


SPC charts provide an easy visual demonstration of your ongoing QI programme. They allow you to easily monitor where your changes are causing significant variations to the process.


This is particularly the case when you are using QI software, which significantly simplifies statistical analysis and enables you to keep adding to your SPC chart, while checking if you maintain the improvement.


You can quickly check in on your SPC charts to measure the long-term results of an improvement initiative and whether there is any variation. This means you can quickly ascertain if any changes you have made have had an impact. And if so, whether it is statistically significant or not.


If you are using Life QI for your SPC charts, it will automatically calculate the control limits for your data. This functionality allows you to see quickly and easily how stable the process is, and where the problem areas are.


So just to reiterate, SPC charts can tell you:


  • Whether the introduction of a new change has had an impact on the system and, if so, whether that impact has been positive or negative.
  • Whether variation is common and therefore normal, or whether it is unusual and warrants further investigation
  • When the change has become stable and is therefore safe to implement permanently.
  • Predictions of what you can expect to happen in the future.’


All of which is really helpful for checking if your improvement is maintained.


NHS England's Making Data Count has some useful pointers when you are coming back to look at your SPC chart, to find out if your improvement is maintained:


‘Another useful thing to do is to annotate your SPC charts with a visual cue indicating when a change was introduced. You then won’t waste time discussing what might have caused a new pattern in a dataset. Everyone will be able to see immediately if a change has had the desired effect or if something else needs to be tried. Doing this also retains a ‘memory of changes’ made over time so that interventions that were ineffective are not repeated.’


The authors conclude by saying that 'Plotting data on a SPC chart is a starting point rather than an end in itself. To gain the real value of SPC – better decisions – you will need to change mindsets’. They highlight that you can use the SPC chart to present key messages which will in turn prompt more meaningful conversations and actions. A point well worth bearing in mind when using SPC charts in your QI projects.





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