Step 9 - Understanding QI vs Audit
Having talked through the QI methodology needed to undertake a basic QI project, it is now hopefully clear how it differs from a traditional audit, and from traditional biomedical research.
In fact audit, research and QI all overlap slightly but play different yet equally important roles in modern healthcare:
Audit asks the question – How are we performing?
Research asks the question – What new knowledge can we discover?
QI projects ask – How do we best actually improve?
In many ways a QI project can be seen as the journey from how we are performing now (as identified by an audit), towards what we know is possible (as identified by research). The MFI and associated tools we have talked through give the most effective way to undertake this journey.
Figure 9.1, A Visual Depiction of the Difference Between Audit, QI and Research. Research helps us define what is possible. Audit tells us how we are currently performing. QI is the process of moving from how we are performing towards what is possible (and beyond, as demonstrated in many projects).
In TIPSQI our argument is that audit is often mistakenly used as a method for improvement. It can be done, but it is far inferior to using the tools we have covered in this guide.
The main way in which the methods differ most is that QI is a continuous process, primarily represented by continuous data collection for the run chart, and continuous testing and learning through PDSA. Compare this to how an audit cycle is often performed with a single data collection and recommendations -> intervention(s) from the recommendations -> further single data collection months later. Between data collections we have a large gap where, as we have no data, we have no idea what’s going on. We have no idea whether either data sample is truly representative of practice, or outliers that we happened to catch. Data over time will capture performance over many more time points, and therefore many more conditions – providing a more representative picture.