Journal of Public Health Policy

, Volume 38, Issue 2, pp 203–215 | Cite as

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

  • Eloise O’Donnell
  • Jo-An Atkinson
  • Louise Freebairn
  • Lucie Rychetnik
Original Article

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.

Keywords

dynamic simulation modelling participatory modelling evidence hierarchy evidence synthesis systems science health policy 

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Copyright information

© Macmillan Publishers Ltd 2017

Authors and Affiliations

  • Eloise O’Donnell
    • 1
  • Jo-An Atkinson
    • 2
  • Louise Freebairn
    • 4
  • Lucie Rychetnik
    • 3
  1. 1.The Australian Prevention Partnership CentreSax InstituteSydneyAustralia
  2. 2.The Australian Prevention Partnership Centre, School of MedicineThe University of SydneySydneyAustralia
  3. 3.The Australian Prevention Partnership Centre, School of MedicineThe University of Notre DameNotre DameUSA
  4. 4.The Australian Prevention Partnership Centre, Knowledge Translation and Health Outcomes, Epidemiology Section, ACT HealthCanberra CityAustralia

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