Background and current conceptualisation of the efficacy-effectiveness gap

A narrative review completed by GetReal examined the literature related to the concept of the efficacy-effectiveness gap. The authors used inductive analysis to identify the different ways, referred to here as ‘paradigms’, of understanding the efficacy-effectiveness gap (see definition here) that have evolved over the last few decades. These are summarised in the table below.

Paradigm  Description
1. Method used to assess the effects of a medicine
  • The efficacy-effectiveness gap is an issue of measure: different study designs (RCT vs effectiveness) give different results
  • The efficacy is the real effect whereas effectiveness is a distorted one from biased studies
  • Acknowledgement that RCTs lack external validity or generalisability
2. Impact of patient and clinician’s behaviour or real-life characteristics of the healthcare system
  • Ideal drug’s effects (efficacy) are distorted by real-life factors, such as clinician and patient behaviour, or adherence to treatment
  • Pragmatic randomised trials introduced to combine characteristics of RCTs and observational studies
3. Interaction between a medicine’s biological effect and contextual factors
  • Difference between a medicine’s effect in experimental settings and routine practice is because of an interaction of multiple real-life characteristics (or contextual factors) on the biological effect of the medicine (i.e. real-life contextual factors)
  • Current view on understanding the efficacy-effectiveness gap

Current view on the efficacy-effectiveness gap

The third and current paradigm provides the opportunity to look beyond the differences between ‘standardised’ and ‘real-life’ characteristics of the healthcare system and study designs. Many authors would rather consider a continuum between explanatory and pragmatic trials: ‘the explanatory‑pragmatic continuum’ (see the description of pragmatic trials here). Future research will determine if the identification of these contextual factors can help to design RCTs that provide better estimates of drug effectiveness.

Key contributor

Clementine Nordon, LASER