Young People’s Workforce Reform Programme : evaluation report

"The Children's Workforce Development Council (CWDC) commissioned Ecorys and H.J. Giller & Associates to independently evaluate the 2008–2011 Young People's Workforce Reform Programme (YPWRP). The YPWRP was introduced in 2008 as part of a ten year government strategy to help develop help develop a more skilled, confident workforce able to work in an effective and integrated way to deliver the best possible outcomes for young people. The main evaluation methodology used was semi-structured interviews with stakeholders, supplemented by telephone surveys and a small number of focus groups and event observations. Desk review of programme information was also undertaken. This summary assesses the main YPWRP strands and workstreams along with its cross cutting themes of communications and data collation in light of intended outcomes. It concludes by assessing the outcomes of the programme overall." - page iv

Decision makers\u27 experience of participatory dynamic simulation modelling: Methods for public health policy

Background: Systems science methods such as dynamic simulation modelling are well suited to address questions about public health policy as they consider the complexity, context and dynamic nature of system-wide behaviours. Advances in technology have led to increased accessibility and interest in systems methods to address complex health policy issues. However, the involvement of policy decision makers in health-related simulation model development has been lacking. Where end-users have been included, there has been limited examination of their experience of the participatory modelling process and their views about the utility of the findings. This paper reports the experience of end-user decision makers, including senior public health policy makers and health service providers, who participated in three participatory simulation modelling for health policy case studies (alcohol related harm, childhood obesity prevention, diabetes in pregnancy), and their perceptions of the value and efficacy of this method in an applied health sector context. Methods: Semi-structured interviews were conducted with end-user participants from three participatory simulation modelling case studies in Australian real-world policy settings. Interviewees were employees of government agencies with jurisdiction over policy and program decisions and were purposively selected to include perspectives at different stages of model development. Results: The ‘co-production’ aspect of the participatory approach was highly valued. It was reported as an essential component of building understanding of the modelling process, and thus trust in the model and its outputs as a decision-support tool. The unique benefits of simulation modelling included its capacity to explore interactions of risk factors and combined interventions, and the impact of scaling up interventions. Participants also valued simulating new interventions prior to implementation in the real world, and the comprehensive mapping of evidence and its gaps to prioritise future research. The participatory aspect of simulation modelling was time and resource intensive and therefore most suited to high priority complex topics with contested options for intervening. Conclusion: These findings highlight the value of a participatory approach to dynamic simulation modelling to support its utility in applied health policy settings

Simulation modelling as a tool for knowledge mobilisation in health policy settings: a case study protocol

Background: Evidence-informed decision-making is essential to ensure that health programs and services are effective and offer value for money; however, barriers to the use of evidence persist. Emerging systems science approaches and advances in technology are providing new methods and tools to facilitate evidence-based decision-making. Simulation modelling offers a unique tool for synthesising and leveraging existing evidence, data and expert local knowledge to examine, in a robust, low risk and low cost way, the likely impact of alternative policy and service provision scenarios. This case study will evaluate participatory simulation modelling to inform the prevention and management of gestational diabetes mellitus (GDM). The risks associated with GDM are well recognised; however, debate remains regarding diagnostic thresholds and whether screening and treatment to reduce maternal glucose levels reduce the associated risks. A diagnosis of GDM may provide a leverage point for multidisciplinary lifestyle modification interventions. This research will apply and evaluate a simulation modelling approach to understand the complex interrelation of factors that drive GDM rates, test options for screening and interventions, and optimise the use of evidence to inform policy and program decision-making. Methods/Design: The study design will use mixed methods to achieve the objectives. Policy, clinical practice and research experts will work collaboratively to develop, test and validate a simulation model of GDM in the Australian Capital Territory (ACT). The model will be applied to support evidence-informed policy dialogues with diverse stakeholders for the management of GDM in the ACT. Qualitative methods will be used to evaluate simulation modelling as an evidence synthesis tool to support evidence-based decision-making. Interviews and analysis of workshop recordings will focus on the participants’ engagement in the modelling process; perceived value of the participatory process, perceived commitment, influence and confidence of stakeholders in implementing policy and program decisions identified in the modelling process; and the impact of the process in terms of policy and program change. Discussion: The study will generate empirical evidence on the feasibility and potential value of simulation modelling to support knowledge mobilisation and consensus building in health settings

Whole-of-system approaches to physical activity;

Background: The literature on whole of system approaches (WSAs) has been largely theoretical in focus. The Australian Systems Approaches to Physical Activity is a national project designed to contribute a practical implementation focus to such approaches at the population level. Methods: National meetings were convened with federal and state government sector stakeholders to identify physical activity (PA) related policies and programs. Policies and programs were audited to develop an understanding of the existing PA system. A WSA conceptual map for PA was developed using feedback from system stakeholders, existing WSAs, and related work in obesity. Results: Completion of the policy audit has revealed key areas of need regarding policy governance, coordination, financing, and evaluation. An initial WSA conceptual map for Australia has been developed incorporating governance, translation, and advocacy. Stakeholder co-production of an integrated framework for PA and design plans for a community of practice knowledge hub has commenced. Conclusions: In Australia, Australian Systems Approaches to Physical Activity project partners have developed a conceptual whole of systems map that is guiding progress beyond the theoretical to application in the real world: A national PA policy audit, co-production of an integrated PA policy framework, and planning for a PA community of practice knowledge hub.</p

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

My patient is short of breath: is there pleural fluid, and will PoCUS help drain it safely?

Pathological pleural fluid is common in patients presenting to the emergency department, occurring in as many as 17% of patients presenting with shortness of breath, and as many as 20% of patients with blunt thoracic trauma. A typical chest X-ray may fail to identify as much as 175 mL of pleural fluid in the erect position, and as much as 500 mL in the supine position. Point-of-care ultrasound (PoCUS) on the other hand can detect as little as 20 mL of pleural fluid, and has consistently been shown to have sensitivities and specificities for the detection of pleural fluid close to 100% in both the trauma and critically ill populations. In addition, ultrasound identifies pleural fluid more rapidly than chest X-ray. PoCUS can be used to guide thoracentesis, resulting in improved success rates with decreased complications. Here we describe the evidence supporting the use of PoCUS in the management of pleural fluid collections

Connections: the contribution of social capital to regional development

This article explores perceptions of social capital and sustainability of farming and its contribution to regional development. A review of the literature highlights challenges in the operationalization of social capital as a development tool and the limits of research that gauges community perceptions of the role of social capital in their region's development. The current study investigated stakeholder attitudes regarding regional development within a target region in North Queensland, Australia. Focus groups were conducted at regional, state and national levels. Findings suggest stakeholders perceived social capital to be important for farming sustainability and regional development, but thought it could variously help or hinder effective development. Future research should embrace social capital as a multi-dimensional construct with positive and negative implications for regional development depending on stage and context

A decision-support tool to inform Australian strategies for preventing suicide and suicidal behaviour

Dynamic simulation modelling is increasingly being recognised as a valuable decision-support tool to help guide investments and actions to address complex public health issues such as suicide. In particular, participatory system dynamics (SD) modelling provides a useful tool for asking high-level 'what if' questions, and testing the likely impacts of different combinations of policies and interventions at an aggregate level before they are implemented in the real world. We developed an SD model for suicide prevention in Australia, and investigated the hypothesised impacts over the next 10 years (2015-2025) of a combination of current intervention strategies proposed for population interventions in Australia: 1) general practitioner (GP) training, 2) coordinated aftercare in those who have attempted suicide, 3) school-based mental health literacy programs, 4) brief-contact interventions in hospital settings, and 5) psychosocial treatment approaches. Findings suggest that the largest reductions in suicide were associated with GP training (6%) and coordinated aftercare approaches (4%), with total reductions of 12% for all interventions combined. This paper highlights the value of dynamic modelling methods for managing complexity and uncertainty, and demonstrates their potential use as a decision-support tool for policy makers and program planners for community suicide prevention actions

Bringing new tools, a regional focus, resource-sensitivity, local engagement and necessary discipline to mental health policy and planning

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

Turning conceptual systems maps into dynamic simulation models: An Australian case study for diabetes in pregnancy

Background: System science approaches are increasingly used to explore complex public health problems. Quantitative methods, such as participatory dynamic simulation modelling, can mobilise knowledge to inform health policy decisions. However, the analytic and practical steps required to turn collaboratively developed, qualitative system maps into rigorous and policy relevant quantified dynamic simulation models are not well described. This paper reports on the processes, interactions and decisions that occurred at the interface between modellers and end-user participants in an applied health sector case study focusing on diabetes in pregnancy. Methods: An analysis was conducted using qualitative data from a participatory dynamic simulation modelling case study in an Australian health policy setting. Recordings of participatory model development workshops and subsequent meetings were analysed and triangulated with field notes and other written records of discussions and decisions. Case study vignettes were collated to illustrate the deliberations and decisions made throughout the model development process. Results: The key analytic objectives and decision-making processes included: defining the model scope; analysing and refining the model structure to maximise local relevance and utility; reviewing and incorporating evidence to inform model parameters and assumptions; focusing the model on priority policy questions; communicating results and applying the models to policy processes. These stages did not occur sequentially; the model development was cyclical and iterative with decisions being re-visited and refined throughout the process. Storytelling was an effective strategy to both communicate and resolve concerns about the model logic and structure, and to communicate the outputs of the model to a broader audience. Conclusion: The in-depth analysis reported here examined the application of participatory modelling methods to move beyond qualitative conceptual mapping to the development of a rigorously quantified and policy relevant, complex dynamic simulation model. The analytic objectives and decision-making themes identified provide guidance for interpreting, understanding and reporting future participatory modelling projects and methods