How to attribute causality in quality improvement: lessons from epidemiology

Background

Quality improvement and implementation (QI&I) initiatives face critical challenges in an era of evidence-based, value-driven patient care. Whether front-line staff, large organisations or government bodies design and run QI&I, there is increasing need to demonstrate impact to justify investment of time and resources in implementing and scaling up an intervention.

Decisions about sustaining, scaling up and spreading an initiative can be informed by evidence of causation and the estimated attributable effect of an intervention on observed outcomes. Achieving this in healthcare can be challenging, where interventions often are multimodal and applied in complex systems.1 Where there is weak evidence of causation, credibility in the effectiveness of the intervention is reduced with a resultant reduced desire to replicate. The greater confidence of a causal relationship between QI&I interventions and observed results, the greater our confidence that improvement will result when the intervention occurs in different settings.

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