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.

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Acknowledgements

This work was funded by the National Health and Medical Research Council of Australia (NHMRC) through its partnership centre grant scheme (Grant ID: GNT9100001). NSW Health, ACT Health, The Commonwealth Department of Health, The Hospitals Contribution Fund of Australia and HCF Research Foundation contributed funds to support this work as part of the NHMRC partnership centre grant scheme. The contents of this paper are solely the responsibility of the individual authors and do not reflect the views of the NHMRC or funding partners. The authors thank Geoff McDonnell for his review and valuable comments on the penultimate draft of this paper, and Sally Redman for her contributions to discussions during the conceptualisation of this work.

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Correspondence to Eloise O’Donnell.

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O’Donnell, E., Atkinson, J., Freebairn, L. et al. Participatory simulation modelling to inform public health policy and practice: Rethinking the evidence hierarchies. J Public Health Pol 38, 203–215 (2017). https://doi.org/10.1057/s41271-016-0061-9

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Keywords

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