Evidence intermediaries

While we at ESN-CA are admittedly biased given our own role as evidence intermediaries, we consider this community the centrepiece of the evidence-support system. It acts as the ‘interface’ between the demand side and the supply side: 1) eliciting questions; 2) prioritizing requests; 3) coordinating responses, often among multiple timely, demand-driven evidence-support units like the ESN-CA hubs; and 4) packaging the individual responses into a coherent whole that is understandable to decision-makers and available when they need it.

The McMaster Health Forum, independently or as the secretariat for the Global Commission on Evidence to Address Societal Challenges, has created a number of tools to support its work and the work of other evidence intermediaries like ESN-CA. One such tool – for finding and using research evidence – helps evidence intermediaries to map the question(s) being asked to a step in the policymaking or other decision-making process and then to the appropriate form(s) of evidence to answer the questions. Traditionally we use the heuristic of a four-step process:

  1. understanding a problem and its causes, which is where data analytics, modeling and qualitative insights are most useful
  2. selecting an option for addressing the problem, which is where evaluation, as well as modeling and qualitative insights, can be helpful, often alongside recommendations from guidelines and technology assessments
  3. identifying implementation considers, which is where behavioural and implementation research can offer important insights
  4. monitoring implementation and evaluating impacts, which is where data analytics and evaluation are again important.

For additional perspectives on the role of evidence intermediaries like ESN-CA in a strengthened evidence-support system, take a look at ESN-CA brief 4. This ESN-CA brief lists five possible next steps:

  1. build a community of practice for and coalition of evidence intermediaries, with first key steps being to collectively define the role(s), clearly distinguish them from timely, demand-driven evidence producers, and ensure they serve the full range of decision-makers (from government policymakers through to ‘everyday’ citizens)
  2. leverage the two different types of game-changing developments described in ESN-CA brief 4: a) the emergence of ultra-rapid evidence support and the ‘general contractor’ model; and b) five foundational investments being made by the Evidence Synthesis Infrastructure Collaborative
  3. formalize pilots of ‘packaged responses’ – drawing on many different forms of research evidence – using different frameworks and formats
  4. develop standards for evidence-support mechanisms, including for the integration of different forms of evidence in responses to questions, for the safe and responsible use of AI in evidence support (ideally building on insights from the living Responsible use of AI in evidence SynthEsis (RAISE) guidance), and for the use of subject-matter experts and expert advisory panels
  5. begin tracking and publicizing when evidence support goes well (or has a demonstrated impact), and learning from when it doesn’t.