Plan-Do-Study-Act (PDSA) Model

The PDSA method follows a four stage cyclic learning approach to adapt changes aimed at improvement. In the "plan" stage a change aimed at improvement is identified, the "do" stage sees this change tested, the "study" stage examines the success of the change and the "act" stage identifies adaptations and next steps to inform a new cycle. [Table 1]

The principle of cycles is to promote the use of a small-scale, iterative approach to test changes, as this:

• provides users with freedom to act and learn
• minimizes risk to patients
• minimizes resources required
• enables rapid assessment and provides flexibility to adapt the change according to feedback to ensure fit-for-purpose solutions are developed.
• provides the opportunity to build evidence for the change being tested
• increases stakeholders participation confidence in the intervention increases

Key metrics indicating successful use of the PDSA method: [Table 2]

1. initial small-scale testing
2. prediction-based testing of change
3. use of iterative cycles
4. short duration of cycles (less than a month)
5. detailed documentation
6. use of data over time (run charts, CUSUM control charts)

The PDSA cycle promotes prediction of the outcome of a test of change and subsequent measurement over time (quantitative or qualitative) to assess the impact of that intervention on the process or outcomes of interest. Thus, learning is the primary goal (not improvement). In complex settings with inherent variability, measurement of data over time helps understand natural variation in the system, and increases awareness of other factors influencing processes or outcomes.

 

Lecture, textbooks and review articles that teach about PDSA typically depict the cycles as a smooth progression, with each cycle seamlessly and iteratively building on the previous. The commonly shown schematic is of perfect circles rolling up the hill of change. [Figure 1] As the number of cycles increases, their effectiveness and their overall cumulative effect strengthens.

Figure 1. Ramp model of PDSA improvement.

However, this pristine view of PDSA does not capture reality, which involves frequent ‘false starts, miss firings, plateaus, regroupings, backsliding, feedback, and overlapping scenarios within the process.’ [Figure 2] depicts a complex network which is a tangle of the numerous starts, stops, backtracking and, often incomplete, cycles of change that occur in practice. Even so, the changes continue to move upwards, to better performance (Thick black line ① in Figure 2).

One of the challenges with PDSA cycles is the substantial variability with which they are designed, executed and reported in the healthcare literature. Fewer than 20% of papers documented a sequence of iterative cycles, and only about 15% of articles reported the use of quantitative data at monthly or more frequent intervals to inform the progression of cycles [3]. Collecting data less frequently than monthly is not considered rapid cycle improvement.