When are we there?
The science of quality improvement (improvement science) is developing. It sits at the interface between improving practice in a practical real world way and collecting evidence of improvement. Quality improvement is said to include and build on from the elements of audit and evidence based medicine by adding in a regular review over time to assess the impact of interventions. There is an evolving “Plan Do Study Act” cycle which is preceded by three specific questions.
What are we trying to accomplish?
How will we know that a change is an improvement?
What are the changes we can make to deliver improvement?
Key principles are to involve all relevant parties, to keep things focused, and to start with a small number of people and a realistic change
This aim statment should be clear and relatively brief. It should include “how good” and “by when”. To ensure all doctors in training have an educational supervisor within 3 months. The aim should be SMART – Specific Measurable Achievable Realistic and Timed
When are we there?
Measures of change can be outcome, process or balanced. An outcome measure might include the opinion of the customer, patient or staff. It may be satisfaction or it could be a result. A process measure looks at the working of the system. A Balancing measure looks at unintended consequences.
It is best not to presuppose the changes required but considering them can help design the measures to show change. There are classifications of change that can be used as an aide memoire or to help planning. These are outlined in the implementation guide of the London Deanery. Examples of categories include reducing waste, improving workflow, customer interface and mistake proofing. Each category has specific subheading of between 3 and 15 appoaches.
A run chart gives an overview of the procress and is a method which introduces some rigor in the process. The measure is plotted against time and the pattern determines the impact of the changes. Four rules help to confirm the test is reliable. The relationship of serial results and the median of the previous results gives evidence of change.
Rule 1 A point outside the control limits set by the data. 3 standard deviations is 99% of the data
Rule 2 Sevenpoints are above or below the previous mean line
Rule 3 Any unusual pattern or trend
Rule 4 Middle third differs from out third