Jo-An Atkinson1,2,3,4, Adam Skinner5,6, Kenny Lawson7,8, Sebastian Rosenberg5,9, Ian B Hickie5. 1. Brain and Mind Centre, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia. Jo-An.Atkinson@sydney.edu.au. 2. Computer Simulation and Advanced Research Technologies, Sydney, Australia. Jo-An.Atkinson@sydney.edu.au. 3. Menzies Centre for Health Policy, The University of Sydney, Sydney, Australia. Jo-An.Atkinson@sydney.edu.au. 4. Translational Health Research Institute, Western Sydney University, Penrith, Australia. Jo-An.Atkinson@sydney.edu.au. 5. Brain and Mind Centre, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia. 6. Menzies Centre for Health Policy, The University of Sydney, Sydney, Australia. 7. Translational Health Research Institute, Western Sydney University, Penrith, Australia. 8. Hunter Medical Research Institute, Newcastle, Australia. 9. Research School of Population Health, The Australian National University, Canberra, Australia.
Abstract
BACKGROUND: While reducing the burden of mental and substance use disorders is a global challenge, it is played out locally. Mental disorders have early ages of onset, syndromal complexity and high individual variability in course and response to treatment. As most locally-delivered health systems do not account for this complexity in their design, implementation, scale or evaluation they often result in disappointing impacts. DISCUSSION: In this viewpoint, we contend that the absence of an appropriate predictive planning framework is one critical reason that countries fail to make substantial progress in mental health outcomes. Addressing this missing infrastructure is vital to guide and coordinate national and regional (local) investments, to ensure limited mental health resources are put to best use, and to strengthen health systems to achieve the mental health targets of the 2015 Sustainable Development Goals. Most broad national policies over-emphasize provision of single elements of care (e.g. medicines, individual psychological therapies) and assess their population-level impact through static, linear and program logic-based evaluation. More sophisticated decision analytic approaches that can account for complexity have long been successfully used in non-health sectors and are now emerging in mental health research and practice. We argue that utilization of advanced decision support tools such as systems modelling and simulation, is now required to bring a necessary discipline to new national and local investments in transforming mental health systems. CONCLUSION: Systems modelling and simulation delivers an interactive decision analytic tool to test mental health reform and service planning scenarios in a safe environment before implementing them in the real world. The approach drives better decision-making and can inform the scale up of effective and contextually relevant strategies to reduce the burden of mental disorder and enhance the mental wealth of nations.
BACKGROUND: While reducing the burden of mental and substance use disorders is a global challenge, it is played out locally. Mental disorders have early ages of onset, syndromal complexity and high individual variability in course and response to treatment. As most locally-delivered health systems do not account for this complexity in their design, implementation, scale or evaluation they often result in disappointing impacts. DISCUSSION: In this viewpoint, we contend that the absence of an appropriate predictive planning framework is one critical reason that countries fail to make substantial progress in mental health outcomes. Addressing this missing infrastructure is vital to guide and coordinate national and regional (local) investments, to ensure limited mental health resources are put to best use, and to strengthen health systems to achieve the mental health targets of the 2015 Sustainable Development Goals. Most broad national policies over-emphasize provision of single elements of care (e.g. medicines, individual psychological therapies) and assess their population-level impact through static, linear and program logic-based evaluation. More sophisticated decision analytic approaches that can account for complexity have long been successfully used in non-health sectors and are now emerging in mental health research and practice. We argue that utilization of advanced decision support tools such as systems modelling and simulation, is now required to bring a necessary discipline to new national and local investments in transforming mental health systems. CONCLUSION: Systems modelling and simulation delivers an interactive decision analytic tool to test mental health reform and service planning scenarios in a safe environment before implementing them in the real world. The approach drives better decision-making and can inform the scale up of effective and contextually relevant strategies to reduce the burden of mental disorder and enhance the mental wealth of nations.
Entities:
Keywords:
Mental health services planning; Suicide prevention; System reform
Authors: Grace Yeeun Lee; Ian Bernard Hickie; Jo-An Occhipinti; Yun Ju Christine Song; Adam Skinner; Salvador Camacho; Kenny Lawson; Adriane Martin Hilber; Louise Freebairn Journal: PLoS One Date: 2022-04-22 Impact factor: 3.752
Authors: Catherine Vacher; Nicholas Ho; Adam Skinner; Jo Robinson; Louise Freebairn; Grace Yeeun Lee; Frank Iorfino; Ante Prodan; Yun Ju C Song; Jo-An Occhipinti; Ian B Hickie Journal: Int J Environ Res Public Health Date: 2022-05-26 Impact factor: 4.614
Authors: Sebastian Rosenberg; Luis Salvador-Carulla; Graham Meadows; Ian Hickie Journal: Int J Environ Res Public Health Date: 2022-04-15 Impact factor: 4.614
Authors: Grace Yeeun Lee; Ian Bernard Hickie; Jo-An Occhipinti; Yun Ju Christine Song; Salvador Camacho; Adam Skinner; Kenny Lawson; Samuel J Hockey; Adriane Martin Hilber; Louise Freebairn Journal: Int J Environ Res Public Health Date: 2022-03-28 Impact factor: 3.390
Authors: Jo-An Occhipinti; Danya Rose; Adam Skinner; Daniel Rock; Yun Ju C Song; Ante Prodan; Sebastian Rosenberg; Louise Freebairn; Catherine Vacher; Ian B Hickie Journal: Int J Environ Res Public Health Date: 2022-01-27 Impact factor: 3.390
Authors: Louise Freebairn; Jo-An Occhipinti; Yun Ju C Song; Adam Skinner; Kenny Lawson; Grace Yeeun Lee; Samuel J Hockey; Samantha Huntley; Ian B Hickie Journal: JMIR Res Protoc Date: 2022-02-07