Advisory & decision-making processes

‘Engaged requesters’ within advisory and decision-making processes are the ‘make or break’ part of evidence-support system. If no one is asking for and using the available research evidence in decision-making, then all of the other components of the system are for naught. Ideally these requesters are supported by structures and processes to:

  1. enable the incorporation of evidence into advisory and decision-making processes, as well as into learning and improvement platforms, which are the focus of the next section
  2. build and sustain an evidence culture
  3. strengthen capacity for evidence use.

Such enablers, culture and capacity can move us beyond individual champions and towards the routinized use of evidence in decision-making.

The McMaster Health Forum, which acts as the secretariat for ESN-CA, has created a number of tools to help ‘engaged requesters’ in their work, including a set of prompts to assist in executing five strategies to be more efficient, systematic and transparent in using evidence in policy work. These requesters are also ideally supported by (and contribute to) efforts to counter misinformation and to safely and responsibly use artificial intelligence in their work (which we call ‘AI for policy’).

For more insights into how we can better support ‘engaged requesters’ within advisory and decision-making processes, check out ESN-CA brief 1. Six of nine possible ‘next steps’ listed in the brief relate to enablers of evidence use:

  1. develop tools that accompany briefing documents and funding requests to document what evidence was used, how it was identified, and whether and how AI was safely and responsibly used in compiling it
  2. engage evidence-methods experts and citizen partners alongside subject-matter experts in advisory and decision-making processes
  3. develop principles (or standards) that underpin the use of evidence, and embed them in funding agreements with organizations (e.g., pan-Canadian health organizations) and in contracts with consultants and external experts
  4. develop and contribute to an optimal infrastructure for addressing misinformation and more generally better empowers ‘everyday’ citizens to make informed decisions
  5. create a ‘front door’ in each government department or organization through which evidence-support providers can learn about evidence needs and ‘windows of opportunity’ to meet these needs
  6. evaluate whether and how different forms of evidence are being used to inform decisions, and develop a plan for improving consistency and efficiency across advisory and decision-making bodies.

The remaining three next steps relate to capacity:

  1. define the capacities required for evidence use, coordination and support and embed them in hiring criteria, professional-development plans, and performance frameworks (particularly as public-service reform reshapes roles and expectations in government)
  2. providing learning opportunities to help staff keep pace with the rapid changes happening in the evidence-support system and broader global evidence architecture (e.g., ultra-rapid evidence support and AI-enabled, policy-scale living evidence syntheses)
  3. build capacity among staff in ‘interfacing’ teams – including those comprised of evaluators, behavioural scientists, and policy analysts – to work with timely, demand-driven evidence-support units.