Iterative cycles | To achieve an iterative approach, multiple PDSA cycles must occur. Lessons learned from one cycle link and inform cycles that follow. Depending on the knowledge gained from a PDSA cycle, the following cycle may seek to modify, expand, adopt or abandon a change that was tested |
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Were multiple cycles used? -
Were multiple cycles linked to one another (ie, does the ‘act’ stage of one cycle inform the ‘plan’ stage of the cycle that follows)? -
When isolated cycles were used were future actions postulated in the ‘act’ stage?
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Prediction-based test of change | A prediction of the outcome of a change is developed in the ‘plan’ stage of a cycle. This change is then tested and examined by comparison of results with the prediction |
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Small-scale testing | As certainty of success of a test of change is not guaranteed, PDSAs start small in scale and build in scale as confidence grows. This allows the change to be adapted according to feedback, minimises risk and facilitates rapid change and learning |
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Sample size per cycle? -
Temporal duration of cycles? -
Number of changes tested per cycle? -
Did sequential cycles increase scale of testing?
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Use of data over time | Data over time increases understanding regarding the variation inherent in a complex healthcare system. Use of data over time is necessary to understand the impact of a change on the process or outcome of interest |
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Documentation | Documentation is crucial to support local learning and transferability of learning to other settings |
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