Dynamic simulation modelling of policy responses to reduce alcohol-related harms: rationale and procedure for a participatory approach.

Development of effective policy responses to address complex public health problems can be challenged by a lack of clarity about the interaction of risk factors driving the problem, differing views of stakeholders on the most appropriate and effective intervention approaches, a lack of evidence to support commonly implemented and acceptable intervention approaches, and a lack of acceptance of effective interventions. Consequently, political considerations, community advocacy and industry lobbying can contribute to a hotly contested debate about the most appropriate course of action; this can hinder consensus and give rise to policy resistance. The problem of alcohol misuse and its associated harms in New South Wales (NSW), Australia, provides a relevant example of such challenges. Dynamic simulation modelling is increasingly being valued by the health sector as a robust tool to support decision making to address complex problems. It allows policy makers to ask 'what-if' questions and test the potential impacts of different policy scenarios over time, before solutions are implemented in the real world. Participatory approaches to modelling enable researchers, policy makers, program planners, practitioners and consumer representatives to collaborate with expert modellers to ensure that models are transparent, incorporate diverse evidence and perspectives, are better aligned to the decision-support needs of policy makers, and can facilitate consensus building for action. This paper outlines a procedure for embedding stakeholder engagement and consensus building in the development of dynamic simulation models that can guide the development of effective, coordinated and acceptable policy responses to complex public health problems, such as alcohol-related harms in NSW.

[1]  Andrew Page,et al.  Applications of system dynamics modelling to support health policy. , 2015, Public health research & practice.

[2]  Jac A. M. Vennix,et al.  Group model building effectiveness: a review of assessment studies † , 2002 .

[3]  Céline Bérard,et al.  Group Model Building Using System Dynamics: An Analysis of Methodological Frameworks , 2010 .

[4]  George P. Richardson,et al.  Model-building for group decision support: Issues and alternatives in knowledge elicitation , 1992 .

[5]  Jürgen Rehm,et al.  Global burden of disease and injury and economic cost attributable to alcohol use and alcohol-use disorders , 2009, The Lancet.

[6]  Traci L Toomey,et al.  Adopting Local Alcohol Policies: A Case Study of Community Efforts to Regulate Malt Liquor Sales , 2012, American journal of health promotion : AJHP.

[7]  George P. Richardson,et al.  Scripts for group model building , 1997 .

[8]  Sally Casswell,et al.  Reducing harm from alcohol: call to action , 2009, The Lancet.

[9]  Tanya Chikritzhs,et al.  Alcohol policy and harm reduction in Australia. , 2005, Drug and alcohol review.

[10]  Amy Geller,et al.  Visit the National Academies Press Online and Register For... Frontiers in Massive Data Analysis , 2022 .

[11]  G. Royston,et al.  Using system dynamics to help develop and implement policies and programmes in health care in England , 1999 .

[12]  Mark Petticrew,et al.  Population-level interventions to reduce alcohol-related harm: an overview of systematic reviews. , 2013, Preventive medicine.

[13]  Ross A. Hammond Considerations and Best Practices in Agent-Based Modeling to Inform Policy , 2015 .

[14]  Antonio Pflüger,et al.  The costs of tobacco, alcohol and illicit drug abuse to Australian society in 2004/05: summary version , 2008 .

[15]  C. Ansell,et al.  Collaborative Governance in Theory and Practice , 2007 .

[16]  Michael Livingston,et al.  Mapping Australian public opinion on alcohol policies in the new millennium. , 2009, Drug and alcohol review.

[17]  Nathaniel D Osgood,et al.  Selecting a dynamic simulation modeling method for health care delivery research-part 2: report of the ISPOR Dynamic Simulation Modeling Emerging Good Practices Task Force. , 2015, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

[18]  Peter Miller,et al.  Alcohol‐related crime in city entertainment precincts: Public perception and experience of alcohol‐related crime and support for strategies to reduce such crime , 2015, Drug and alcohol review.

[19]  Bobby Milstein,et al.  From Model to Action , 2013, Health promotion practice.

[20]  J. Homer,et al.  System dynamics modeling for public health: background and opportunities. , 2006, American journal of public health.