Data is needed at all stages of the improvement journey. You will probably need data in order to:

1. Understand your system and what needs to be improved  
2. Make the case for change 
3. Develop your aim and change ideas  
4. Test changes – pdsa measures help you understand whether a test has the predictedeffect  
5. Monitor progress -  see if  your changes are resulting in improvement over time
6. Communicate the story of your improvement journey – especially if you want to spread the improvement
7. Ensure the changes and improved outcomes are maintained, and are part of everyday practice. 

• Get just enough data to learn
• Collect data often and plot over time
• The improvement team owns the measurement

You should develop a small set of project measures that you will track over time, as often as makes sense. See developing your measures.   

Each time you test a change, you might also need measures that are specific to that test. These might be qualitative measures – particularly in the early stages of testing.  They don’t necessarily need to be tracked over time, just give you enough information to learn from your test. See pdsa.

Data is commonly gathered so that managers and quality assurance and scrutiny organisations can assess the performance of those services against agreed targets.  This is measurement for accountability, or judgement. Data is also commonly collected by research projects that seek to develop knowledge of better ways of caring for patients. 

There are differences between measurement for improvement and these other two types of measurement, which are summarised in the table below.  

Qualitative data is data that involves words, and quantitative data is numbers.

Stories and feedback give rich qualitative data.  They are a very powerful way of finding out where opportunities for improvement lie, and of understanding and describing the impact of improvements.  Qualitative data can also describe a characteristic that is observed, for example a person has blue eyes.

Quantitative data represent something that is measured as a number, including the numbers with a qualitative characteristic – for example number of people with blue eyes.

It is possible to convert stories and feedback to quantitative data (numbers) by either:

1. Asking people to express an opinion on a statement using a rating scale. Measures of attitudes, satisfaction and experience are commonly collected this way.
2. Organising qualitative feedback into themes and counting the number in each (for example number of positive stories, or number of stories relating to poor communication).