The PDSA Cycle

Building on the previous episode where we explored how to use the three questions of the Model for Improvement to start a test of change, beginning with setting a SMART aim, defining measures and deciding on appropriate tests of change. This episode explores the PDSA cycle and practical steps of testing an agreed upon change idea.

The first step in the PDSA cycle is to Plan. This stage involves identifying a specific area for improvement and developing a hypothesis or change idea to address the problem. For more information on how to identify areas for improvement, you can refer to my article here: Identify Areas for Improvement. It is crucial to clearly define the objectives and desired outcomes of the test. A well-defined plan will outline what will be done, who will be responsible, where and when it will occur, and how the change will be measured. For instance, in a hospital, a team may notice that patients have long wait times before seeing a doctor. To address this issue, the team might plan to implement a new triage process aimed at reducing waiting times. The objective would be to decrease the average wait time by 20% within a month. The plan would include detailed steps for implementing the new process, identifying the staff involved, and setting up data collection methods to measure wait times before and after the change.

The second step is to Do. In this phase, the plan is implemented on a small scale. This allows the team to test the change in a real-world environment without risking widespread disruption. During this phase, it is essential to collect data and document any observations, including any unexpected challenges or outcomes that arise. This data collection should be consistent and systematic to ensure accurate analysis in the next phase. Continuing with the waiting times example, the team would implement the new triage process in one department or for a limited number of shifts. During this period, they would monitor the wait times and collect feedback from both staff and patients about the new process. Any issues encountered, such as confusion about new roles or difficulties in patient flow, would be noted. For more detailed explanation on why data is important, you can refer to my article here: Importance of Data in Healthcare Improvement.

The third step is to Study. In this phase, the collected data is analysed to determine whether the change led to the desired improvement. The team compares the results against the objectives set during the planning stage. This analysis helps to understand the impact of the change, identify any unintended consequences, and determine whether the hypothesis was correct. In our example, the team would analyse the data to see if the new triage process resulted in reduced wait times. If the average wait time decreased as planned, the change could be considered successful. However, if the wait time did not decrease or if new problems emerged, the team would need to re-evaluate the process and consider modifications. This leads us to the final phase of the PDSA cycle where we begin to bring everything together.

The final step is to Act. Based on the findings from the study phase, the team decides whether to adopt, adapt, or abandon the change. If the change is successful, it may be implemented on a broader scale. If the change did not produce the desired results, the team might decide to modify the plan and begin another PDSA cycle. The continuous nature of the PDSA cycle promotes ongoing learning and refinement of processes. In the scenario we used, if the new triage process successfully reduced wait times, the team could decide to roll it out across the entire hospital. If the process did not meet expectations, they might revise the triage steps, retrain staff, or test an entirely different approach. The PDSA methodology is an iterative process that encourages experimentation and learning. By systematically planning, implementing, studying, and acting on changes, healthcare organisations can effectively test new ideas, minimise risks, and drive continuous improvement. This methodology is particularly valuable in complex environments where changes can have significant impacts, allowing teams to make evidence-based decisions that enhance outcomes and efficiency.

In the following episodes, we will explore other improvement methodologies used by healthcare organisations, how to complete a practice test of change, drive sustainability and embrace a culture of continuous improvement.