Participatory simulation modelling to inform public health policy and practice: Rethinking the evidence hierarchies

Abstract

Drawing on the long tradition of evidence-based medicine that aims to improve the efficiency and effectiveness of clinical practice, the field of public health has sought to apply 'hierarchies of evidence' to appraise and synthesise public health research. Various critiques of this approach led to the development of synthesis methods that include broader evidence typologies and more 'fit for purpose' privileging of methodological designs. While such adaptations offer great utility for evidence-informed public health policy and practice, this paper offers an alternative perspective on the synthesis of evidence that necessitates a yet more egalitarian approach. Dynamic simulation modelling is increasingly recognised as a valuable evidence synthesis tool to inform public health policy and programme planning for complex problems. The development of simulation models draws on and privileges a wide range of evidence typologies, thus challenging the traditional use of 'hierarchies of evidence' to support decisions on complex dynamic problems.

Knowledge mobilisation for policy development: implementing systems approaches through participatory dynamic simulation modelling

“…They are more practical, flexible and timely in supporting evidence-informed decision-making [ 49 ] and can also consider how the evidence fits with prevailing values, beliefs and political context [ 49 ]. However, the final product is still a static assessment that is unable to adequately account for changes over time or test the prevailing real-world hypotheses and assumptions [ 53 , 58 ].…”

Partnering to prevent chronic disease: reflections and achievements from The Australian Prevention Partnership Centre

“…We have developed six models in collaboration with policy makers to examine the impacts of prevention programs addressing alcohol harms, childhood overweight and obesity, tobacco control regulations, chronic obstructive pulmonary disorder and gestational diabetes. [8][9][10][11][12][13] We undertook the first systematic application of liveability indicators to identify which built environments optimise health and wellbeing, and produced the first baseline measure of liveability in Australia's state and territory capitals. We are currently developing a national liveability indicator platform for use by our stakeholders.…”

Impacts of licensed premises trading hour policies on alcohol‐related harms

“…However, the primary purpose of the model was to provide decision support capability by estimating the overall comparative impacts of different policy scenarios over time against the baseline rather than providing highly precise estimates of outcome indicators. A strength of the study, and a key innovation in the application of simulation models to public health settings, is the explicit engagement of key stakeholders in the design and development of the simulation modelling tool [16,[19][20][21]. The participatory approach assisted with transparent negotiation and consensus building around the most acceptable policy options in the context of previous, and sometimes contentious, empirical evidence.…”

“…Participatory approaches to the development of such models and their use are recommended to ensure transparency and accountability for model parameters, estimates, assumptions, data sources and model outputs [19,20]. Participatory model development also serves to engage stakeholders and potential end-usersimproving communication and garnering broader support for collaborative action based on model outputs [21][22][23][24][25].…”