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QI toolkit: measuring improvement

Collecting data will be an important element of your project, and here are some tools that will help you analysis the data.

Using data for improvement

To demonstrate the effectiveness of your project, data should be collected to show whether the changes being tested are resulting in improvements.

Small amounts of data can be collected regularly and complied into ‘run charts’, or ‘control charts’ to look at review the impact of a change over a period of time. For example:

Run Chart – Infection rate vs Target

run chart

Run charts or control charts focus on variation. There is an important distinction between the two:

  • A run chart acts a bit like a camcorder, showing you every up and down.
  • Snapshot audits are more like a camera, taking a picture of what things look like at just one point
    in time.

To show that things have improved you need to show the things that have changed, and that the change is not a one off. You must consider whether the change has been sustained. Run or control charts allow you to see if this has happened.

Statistical Process Control (SPC)

This approach helps you to understand the scale of a problem, gathering information and identifying possible causes. It examines the difference between:

  • Natural variation – also known as common cause variation
  • Controlled variation – also known as special cause variation.

Control charts are used that display boundaries for acceptable variation in a process. The data collected over time shows whether a process is within control limits in order to detect poor or deteriorating performance and target where improvements are needed.

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