title: A modelling tool for policy analysis to support the design of efficient and effective policy responses for complex public health problems.
abstract: BACKGROUND
  In the design of public health policy, a broader understanding of risk factors for disease across the life course, and an increasing awareness of the social determinants of health, has led to the development of more comprehensive, cross-sectoral strategies to tackle complex problems. However, comprehensive strategies may not represent the most efficient or effective approach to reducing disease burden at the population level. Rather, they may act to spread finite resources less intensively over a greater number of programs and initiatives, diluting the potential impact of the investment. While analytic tools are available that use research evidence to help identify and prioritise disease risk factors for public health action, they are inadequate to support more targeted and effective policy responses for complex public health problems.
  
  
  CONCLUSIONS
  This paper discusses the limitations of analytic tools that are commonly used to support evidence-informed policy decisions for complex problems. It proposes an alternative policy analysis tool which can integrate diverse evidence sources and provide a platform for virtual testing of policy alternatives in order to design solutions that are efficient, effective, and equitable. The case of suicide prevention in Australia is presented to demonstrate the limitations of current tools to adequately inform prevention policy and discusses the utility of the new policy analysis tool. In contrast to popular belief, a systems approach takes a step beyond comprehensive thinking and seeks to identify where best to target public health action and resources for optimal impact. It is concerned primarily with what can be reasonably left out of strategies for prevention and can be used to explore where disinvestment may occur without adversely affecting population health (or equity). Simulation modelling used for policy analysis offers promise in being able to better operationalise research evidence to support decision making for complex problems, improve targeting of public health policy, and offers a foundation for strengthening relationships between policy makers, stakeholders, and researchers.
authors.affiliation: Research Fellow, The Australian Prevention Partnership Centre, Sax Institute, PO Box K617, Haymarket, Sydney, NSW 1240, Australia. jo-an.atkinson@saxinstitute.org.au.
authors.forename: Jo-An
authors.initials: JA
authors.lastname: Atkinson
authors.affiliation: Professor of Public Health, School of Science and Health, University of Western Sydney, Campbelltown Campus, Penrith, NSW 2571, Australia. a.page@uws.edu.au.
authors.forename: Andrew
authors.initials: A
authors.lastname: Page
authors.affiliation: Deputy CEO, Sax Institute, PO Box K617, Haymarket, Sydney, NSW 1240, Australia. robert.wells@saxinstitute.org.au.
authors.forename: Robert
authors.initials: R
authors.lastname: Wells
authors.affiliation: School of Public Health, University of Sydney, Edward Ford Building (A27), Camperdown, NSW 2059, Australia. amila@doh.health.nsw.gov.au.
authors.forename: Andrew
authors.initials: A
authors.lastname: Milat
authors.affiliation: Director, The Australian Prevention Partnership Centre, Sax Institute, PO Box K617, Haymarket, Sydney, NSW 1240, Australia. andrew.wilson@saxinstitute.org.au.
authors.forename: Andrew
authors.initials: A
authors.lastname: Wilson
mesh_terms: D000328:Adult; D001315:Australia / Q000453:epidemiology; D019317:Evidence-Based Medicine; D005260:Female; D006291:Health Policy; D006801:Humans; D008297:Male; D008962:Models, Theoretical; D011050:Policy Making; D011635:Public Health Administration / Q000379:methods*; D013405:Suicide / Q000706:statistics & numerical data; D057170:Translational Research, Biomedical / Q000379:methods; D000092864:Suicide Prevention