Data for Quality Improvement
Why is data important for Quality Improvement?
Use of data is integral to Quality Improvement (QI). Without data, we wouldn’t know our baseline, we wouldn’t know whether the changes we have made are an improvement, and we wouldn’t know whether we have achieved our aim.
Baseline data
Our baseline data is our starting point. Having a baseline allows comparisons to be made later down the line. Ideally, the baseline data should be captured over multiple points in time to show the natural variation in your process. For instance, data on the number of phone calls to a GP practice is likely to be higher on a Monday than any other day of the week. If you were to capture your baseline data from a Monday and attempt to compare this with data 3-months down the line taken from a Wednesday, the likelihood is that you will see an apparent reduction. Capturing baseline data over the course of the whole week will provide far more valuable information and a greater understanding of the current system.
Data for tests of change
Once a baseline is established, data can be used to inform whether changes are having the desired impact. Consider the phone call example from above, if the practice wanted to look at the data to decide where to focus their efforts, they could produce a pareto chart. Read more about Pareto charts here.
If the practice aims to reduce the number of phone calls coming in, they may want to try out a few different change ideas. The number of phone calls to the practice would be the outcome measure, but the impact of the change ideas would be the process measures. Read more about the family of measures here.
By measuring the data over time, they will be able to see the impact of the changes and can plot this in a run chart. Read more about run charts here.
Two points are marked on the graph above. In week 5, there is a decrease in calls to the practice. If this was when a change idea was introduced, the result is promising. If not, the team may need to investigate what else changed in week 5.
In week 18-19, this number shot up. Perhaps a core team member went on annual leave, maybe the practice’s website was down. Either would provide valuable information about the practice’s system.
The bar graph on the right shows the same data if it had been captured at only 2 points in time. While it does show the improvement, it does not show the same story as the run chart does.
Sustainability
Capturing data after the initial project period will also provide information on the sustainability of the changes.
In the case of the graph on the left, the number of calls to the practice started creeping back up after week 30, potentially indicating the need for further interventions to ensure sustainability.
More information
Have a read of this article from the British Medical Journal - Using data for improvement (elft.nhs.uk)