Table 3 Key themes derived from the expert group

1. Capitalise on the unique and contrasting lens on patient safety offered by different groups

Patients and clinicians/healthcare professionals may have complementary and differing perspectives on safety

2. Existing frameworks should already enable the identification of high-level signals to inform decisions about where to prioritise resources for further analysis or investigation

Current coding frameworks can capture relevant learning. Be clear on how to generate those signals, e.g., by reviewing the most frequent incident types and severity combinations

3. Consider the objectives and purpose of the inquiry when using the framework, with a process to enable a timely and insightful analysis

Study objectives are key to interpreting the data. The need for granular coding approaches depends on the purpose of the question being asked of the different data sources

4. Be aware of factors that might always have been present but have not been previously captured

Avoid overlooking new learning from less-cited contributing factors that have been brought to the fore in reports in specific contexts like COVID-19

5. Consider the temporal relationship between the period of data collection and substantive events/system constraints

The timeframe in which data have been collected sometimes makes it unique and may offer explanations for new findings. The time periods of major systemic constraints can also be used to contextualise findings rather than generating bespoke labels or new classes (e.g. COVID-19 related) in a classification system