Reducing youth suicide: systems modelling and simulation to guide targeted investments across the determinants

The current state of complex systems research on socioeconomic inequalities in health and health behavior-a systematic scoping review

BACKGROUND

Interest in applying a complex systems approach to understanding socioeconomic inequalities in health is growing, but an overview of existing research on this topic is lacking. In this systematic scoping review, we summarize the current state of the literature, identify shared drivers of multiple health and health behavior outcomes, and highlight areas ripe for future research.

METHODS

SCOPUS, Web of Science, and PubMed databases were searched in April 2023 for peer-reviewed, English-language studies in high-income OECD countries containing a conceptual systems model or simulation model of socioeconomic inequalities in health or health behavior in the adult general population. Two independent reviewers screened abstracts and full texts. Data on study aim, type of model, all model elements, and all relationships were extracted. Model elements were categorized based on the Commission on Social Determinants of Health framework, and relationships between grouped elements were visualized in a summary conceptual systems map.

RESULTS

A total of 42 publications were included; 18 only contained a simulation model, 20 only contained a conceptual model, and 4 contained both types of models. General health outcomes (e.g., health status, well-being) were modeled more often than specific outcomes like obesity. Dietary behavior and physical activity were by far the most commonly modeled health behaviors. Intermediary determinants of health (e.g., material circumstances, social cohesion) were included in nearly all models, whereas structural determinants (e.g., policies, societal values) were included in about a third of models. Using the summary conceptual systems map, we identified 15 shared drivers of socioeconomic inequalities in multiple health and health behavior outcomes.

CONCLUSIONS

The interconnectedness of socioeconomic position, multiple health and health behavior outcomes, and determinants of socioeconomic inequalities in health is clear from this review. Factors central to the complex system as it is currently understood in the literature (e.g., financial strain) may be both efficient and effective policy levers, and factors less well represented in the literature (e.g., sleep, structural determinants) may warrant more research. Our systematic, comprehensive synthesis of the literature may serve as a basis for, among other things, a complex systems framework for socioeconomic inequalities in health.

Cost-effectiveness of system-level mental health strategies for young people in the Australian Capital Territory: a dynamic simulation modelling study

BACKGROUND

Regional mental health planning is a key challenge for decision makers because mental health care is a complex, dynamic system. Economic evaluation using a system dynamics modelling approach presents an opportunity for more sophisticated planning and important evidence on the value of alternative investments. We aimed to investigate the cost-effectiveness of eight systems-based interventions targeted at improving the mental health and wellbeing of children, adolescents, and young adults in the Australian Capital Territory (ACT).

METHODS

We assessed eight interventions for children and young people (aged ≤25 years) with low, moderate, and high-to-very-high psychological distress: technology-enabled integrated care, emergency department-based suicide prevention, crisis response service, family education programme, online parenting programme, school-based suicide prevention programme, trauma service for youths, and multicultural-informed care. We developed a system dynamics model for the ACT through a participatory process and calibrated the model with historical data, including population demographics, the prevalence of psychological distress, and mental health services provision. We calculated incremental cost-effectiveness ratios compared with business as usual for cost (AU$) per: quality-adjusted life-year (QALY), suicide death avoided, self-harm related hospital admissions avoided, and mental health-related emergency department presentation, using a 10-year time horizon for health-care and societal perspectives. We investigated uncertainty through probabilistic sensitivity analysis and deterministic sensitivity analysis, including using a 30-year timeframe.

FINDINGS

From a societal perspective, increased investment in technology-enabled integrated care, family education, an online parenting programme, and multicultural-informed care were expected to improve health outcomes (incremental QALYs 4517 [95% UI -3135 to 14 507] for technology-enabled integrated care; 339 [91 to 661] for family education; 724 [114 to 1149] for the online parenting programme; and 137 [88 to 194] for multicultural-informed care) and reduce costs ($-91·4 million [-382·7 to 100·7]; $-12·8 million [-21·0 to -6·6]; $-3·6 million  [-6·3 to 0·2]; and $-3·1 million [-4·5 to -1·8], respectively) compared with business as usual using a 10-year time horizon. The incremental net monetary benefit for the societal perspective for these four interventions was $452 million (-351 to 1555), $40 million (14 to 74), $61 million (9 to 98), and $14 million (9 to 20), respectively, compared with business as usual, when QALYs were monetised using a willingness to pay of $79 930 per QALY. Synergistic effects are anticipated if these interventions were to be implemented concurrently. The univariate and probabilistic sensitivity analyses indicated a high level of certainty in the results. Although emergency department-based suicide prevention and school-based suicide prevention were not cost effective in the base case (41 QALYs [0 to 48], incremental cost $4·1 million [1·2 to 8·2] for emergency department-based suicide prevention; -234 QALYs [-764 to 12], incremental cost $90·3 million [72·2 to 111·0] for school-based suicide prevention) compared with business as usual, there were scenarios for which these interventions could be considered cost effective. A dedicated trauma service for young people (9 QALYs gained [4 to 16], incremental cost $8·3 million [6·8 to 10·0]) and a crisis response service (-11 QALYs gained [-12 to -10], incremental cost $7·8 million [5·1 to 11·0]) were unlikely to be cost effective in terms of QALYs.

INTERPRETATION

Synergistic effects were identified, supporting the combined implementation of technology-enabled integrated care, family education, an online parenting programme, and multicultural-informed care. Synergistic effects, emergent outcomes in the form of unintended consequences, the capability to account for service capacity constraints, and ease of use by stakeholders are unique attributes of a system dynamics modelling approach to economic evaluation.

FUNDING

BHP Foundation.

Mental health systems modelling for evidence-informed service reform in Australia

Australia's Fifth National Mental Health Plan required governments to report, not only on the progress of changes to mental health service delivery, but to also plan for services that should be provided. Future population demand for treatment and care is challenging to predict and one solution involves modelling the uncertain demands on the system. Modelling can help decision-makers understand likely future changes in mental health service demand and more intelligently choose appropriate responses. It can also support greater scrutiny, accountability and transparency of these processes. Australia has an emerging national capacity for systems modelling in mental health which can enhance the next phase of mental health reform. This paper introduces concepts useful for understanding mental health modelling and identifies where modelling approaches can support health service planners to make evidence-informed decisions regarding planning and investment for the Australian population.

Applications of Participatory System Dynamics Methods to Public Health: A Systematic Review

System dynamics, and specifically qualitative participatory applications of system dynamics, have potential to benefit public health research, scholarship, and practice. A systematic review was conducted to examine the existing applications of participatory system dynamics (PSD) to public health research. Three databases were searched using unique search terms related to PSD and methodological applications in public health research. A total of 57 unique articles met inclusion criteria and were included for review. The studies included for review were conducted globally and represent a wide breadth of public health issues. The review identified several advantages to adopting PSD methods in public health scholarship and practice. The PSD methods provide innovative frameworks for conceptualizing complex and nuanced public health problems. The participatory nature of PSD allows for increased community engagement and empowerment to address public health problems, as well as to mitigate existing power dynamics between research institutions and marginalized communities that are disproportionately impacted by social and health inequities. Finally, causal loop diagrams developed using PSD methods have unique potential to convey complex concepts to policy makers and interventionists. This systematic review reports evidence for PSD's potential to advance equity in public health research and practice.

Patterns of emergency department presentations for a youth mental health cohort: data-linkage cohort study

BACKGROUND

Primary youth mental health services in Australia have increased access to care for young people, yet the longer-term outcomes and utilisation of other health services among these populations is unclear.

AIMS

To describe the emergency department presentation patterns of a help-seeking youth mental health cohort.

METHOD

Data linkage was performed to extract Emergency Department Data Collection registry data (i.e. emergency department presentations, pattern of re-presentations) for a transdiagnostic cohort of 7024 youths (aged 12-30 years) who presented to mental health services. Outcome measures were pattern of presentations and reason for presentations (i.e. mental illness; suicidal behaviours and self-harm; alcohol and substance use; accident and injury; physical illness; and other).

RESULTS

During the follow-up period, 5372 (76.5%) had at least one emergency department presentation. The presentation rate was lower for males (IRR = 0.87, 95% CI 0.86-0.89) and highest among those aged 18 to 24 (IRR = 1.117, 95% CI 1.086-1.148). Almost one-third (31.12%) had an emergency department presentation that was directly associated with mental illness or substance use, and the most common reasons for presentation were for physical illness and accident or injury. Index visits for mental illness or substance use were associated with a higher rate of re-presentation.

CONCLUSIONS

Most young people presenting to primary mental health services also utilised emergency services. The preventable and repeated nature of many presentations suggests that reducing the ongoing secondary risks of mental disorders (i.e. substance misuse, suicidality, physical illness) could substantially improve the mental and physical health outcomes of young people.

Which programmes and policies across health and community settings will generate the most significant impacts for youth suicide prevention in Australia and the UK? Protocol for a systems modelling and simulation study

INTRODUCTION

Suicide is a leading cause of mortality among young people aged 15-24 globally. Despite the deployment of comprehensive suicide prevention strategies, we still do not know which interventions, for which groups of young people, for how long and with what intensity could generate the most significant reductions in suicide rates. System dynamics modelling has the potential to address these gaps. SEYMOUR (System Dynamics Modelling for Suicide Prevention) will develop and evaluate a system dynamics model that will indicate which suicide prevention interventions could generate the most significant reductions in rates of suicide and attempted suicide among young people aged 12-25 in Australia and the UK.

METHODS AND ANALYSIS

A comparative case study design, applying participatory system dynamics modelling in North-West Melbourne (Australia) and Birmingham (UK). A computer simulation model of mental health service pathways and suicidal behaviour among young people in North-West Melbourne will be developed through three workshops with expert stakeholder groups (young people with lived experience, carers, clinicians, policy makers, commissioners). The model will be calibrated and validated using national, state and local datasets (inputs). The simulation model will test a series of interventions identified in the workshops for inclusion. Primary model outputs include suicide deaths, self-harm hospitalisations and self-harm presentations to emergency departments. An implementation strategy for the sustainable embedding of promising suicide prevention interventions will be developed. This will be followed by model customisation, re-parameterisation, and validation in Birmingham and adaptation of the implementation strategy.

ETHICS AND DISSEMINATION

The project has received approval from the University of Melbourne Human Research Ethics Committee (2022-22885-25971-4), the University of Birmingham Science, Technology, Engineering and Mathematics Ethics Review Committee (ERN_21-02385) and the UK HRA (22/HRA/3826). SEYMOUR's dissemination strategy includes open-access academic publications, conference presentations, accessible findings coproduced with young people, e-briefs to policy makers, webinars for service providers and commissioners.

Unemployment and underemployment are causes of suicide

Epidemiological studies indicate that labor underutilization and suicide are associated, yet it remains unclear whether this association is causal. We applied convergent cross mapping to test for causal effects of unemployment and underemployment on suicidal behavior, using monthly data on labor underutilization and suicide rates in Australia for the period 2004-2016. Our analyses provide evidence that rates of unemployment and underemployment were significant drivers of suicide mortality in Australia over the 13-year study period. Predictive modeling indicates that 9.5% of the ~32,000 suicides reported between 2004 and 2016 resulted directly from labor underutilization, including 1575 suicides attributable to unemployment and 1496 suicides attributable to underemployment. We conclude that economic policies prioritizing full employment should be considered integral to any comprehensive national suicide prevention strategy.

Simulation Models for Suicide Prevention: A Survey of the State-of-the-Art

Suicide is a leading cause of death and a global public health problem, representing more than one in every 100 deaths in 2019. Modeling and Simulation (M&S) is widely used to address public health problems, and numerous simulation models have investigated the complex, dependent, and dynamic risk factors contributing to suicide. However, no review has been dedicated to these models, which prevents modelers from effectively learning from each other and raises the risk of redundant efforts. To guide the development of future models, in this paper we perform the first scoping review of simulation models for suicide prevention. Examining ten articles, we focus on three practical questions. First, which interventions are supported by previous models? We found that four groups of models collectively support 53 interventions. We examined these interventions through the lens of global recommendations for suicide prevention, highlighting future areas for model development. Second, what are the obstacles preventing model application? We noted the absence of cost effectiveness in all models reviewed, meaning that certain simulated interventions may be infeasible. Moreover, we found that most models do not account for different effects of suicide prevention interventions across demographic groups. Third, how much confidence can we place in the models? We evaluated models according to four best practices for simulation, leading to nuanced findings that, despite their current limitations, the current simulation models are powerful tools for understanding the complexity of suicide and evaluating suicide prevention interventions.

Bi-stability and critical transitions in mental health care systems: a model-based analysis

BACKGROUND

Delayed initiation and early discontinuation of treatment due to limited availability and accessibility of services may often result in people with mild or moderate mental disorders developing more severe disorders, leading to an increase in demand for specialised care that would be expected to further restrict service availability and accessibility (due to increased waiting times, higher out-of-pocket costs, etc.).

METHODS

We developed a simple system dynamics model of the interaction of specialised services capacity and disease progression to examine the impact of service availability and accessibility on the effectiveness and efficiency of mental health care systems.

RESULTS

Model analysis indicates that, under certain conditions, increasing services capacity can precipitate an abrupt, step-like transition from a state of persistently high unmet need for specialised services to an alternative, stable state in which people presenting for care receive immediate and effective treatment. This qualitative shift in services system functioning results from a 'virtuous cycle' in which increasing treatment-dependent recovery among patients with mild to moderate disorders reduces the number of severely ill patients requiring intensive and/or prolonged treatment, effectively 'releasing' services capacity that can be used to further reduce the disease progression rate. We present an empirical case study of tertiary-level child and adolescent mental health services in the Australian state of South Australia demonstrating that the conditions under which such critical transitions can occur apply in real-world services systems.

CONCLUSIONS

Policy and planning decisions aimed at increasing specialised services capacity have the potential to dramatically increase the effectiveness and efficiency of mental health care systems, promoting long-term sustainability and resilience in the face of future threats to population mental health (e.g., economic crises, natural disasters, global pandemics).

Trajectories of resilience and mental distress to global major disruptions

The COVID-19 pandemic has resulted in a major societal disruption, raising the question of how people can maintain or quickly regain their mental health (i.e., be resilient) during such times. Researchers have used the pandemic as a use case for studying resilience in response to a global, synchronously starting, and chronic set of stressors on the individual and societal level. Our review of this recent literature reveals that mental distress trajectories during the pandemic largely resemble mental distress responses to individual-level macro-stressors, except for a lower prevalence of recovery trajectories. Results suggest more resilient responses in older adults, but trajectories are less consistent for younger and older ages compared with middle-aged adults. We call for more research integrating state-of-the-art operationalizations of resilience and using these to study resilience over the lifespan.

Measuring, Modeling, and Forecasting the Mental Wealth of Nations

The COVID-19 pandemic has exposed the deep links and fragility of economic, health and social systems. Discussions of reconstruction include renewed interest in moving beyond GDP and recognizing "human capital", "brain capital", "mental capital", and "wellbeing" as assets fundamental to economic reimagining, productivity, and prosperity. This paper describes how the conceptualization of Mental Wealth provides an important framing for measuring and shaping social and economic renewal to underpin healthy, productive, resilient, and thriving communities. We propose a transdisciplinary application of systems modeling to forecast a nation's Mental Wealth and understand the extent to which policy-mediated changes in economic, social, and health sectors could enhance collective mental health and wellbeing, social cohesion, and national prosperity. Specifically, simulation will allow comparison of the projected impacts of a range of cross-sector strategies (education sector, mental health system, labor market, and macroeconomic reforms) on GDP and national Mental Wealth, and provide decision support capability for future investments and actions to foster Mental Wealth. Finally, this paper introduces the Mental Wealth Initiative that is harnessing complex systems science to examine the interrelationships between social, commercial, and structural determinants of mental health and wellbeing, and working to empirically challenge the notion that fostering universal social prosperity is at odds with economic and commercial interests.

Participatory Systems Modelling for Youth Mental Health: An Evaluation Study Applying a Comprehensive Multi-Scale Framework

The youth mental health sector is persistently challenged by issues such as service fragmentation and inefficient resource allocation. Systems modelling and simulation, particularly utilizing participatory approaches, is offering promise in supporting evidence-informed decision making with limited resources by testing alternative strategies in safe virtual environments before implementing them in the real world. However, improved evaluation efforts are needed to understand the critical elements involved in and to improve methods for implementing participatory modelling for youth mental health system and service delivery. An evaluation protocol is described to evaluate the feasibility, value, impact, and sustainability of participatory systems modelling in delivering advanced decision support capabilities for youth mental health. This study applies a comprehensive multi-scale evaluation framework, drawing on participatory action research principles as well as formative, summative, process, and outcome evaluation techniques. Novel data collection procedures are presented, including online surveys that incorporate gamification to enable social network analysis and patient journey mapping. The evaluation approach also explores the experiences of diverse stakeholders, including young people with lived (or living) experience of mental illness. Social and technical opportunities will be uncovered, as well as challenges implementing these interdisciplinary methods in complex settings to improve youth mental health policy, planning, and outcomes. This study protocol can also be adapted for broader international applications, disciplines, and contexts.

Informing the Future of Integrated Digital and Clinical Mental Health Care: Synthesis of the Outcomes From Project Synergy

BACKGROUND

Globally, there are fundamental shortcomings in mental health care systems, including restricted access, siloed services, interventions that are poorly matched to service users' needs, underuse of personal outcome monitoring to track progress, exclusion of family and carers, and suboptimal experiences of care. Health information technologies (HITs) hold great potential to improve these aspects that underpin the enhanced quality of mental health care.

OBJECTIVE

Project Synergy aimed to co-design, implement, and evaluate novel HITs, as exemplified by the InnoWell Platform, to work with standard health care organizations. The goals were to deliver improved outcomes for specific populations under focus and support organizations to enact significant system-level reforms.

METHODS

Participating health care organizations included the following: Open Arms-Veterans & Families Counselling (in Sydney and Lismore, New South Wales [NSW]); NSW North Coast headspace centers for youth (Port Macquarie, Coffs Harbour, Grafton, Lismore, and Tweed Heads); the Butterfly Foundation's National Helpline for eating disorders; Kildare Road Medical Centre for enhanced primary care; and Connect to Wellbeing North Coast NSW (administered by Neami National), for population-based intake and assessment. Service users, families and carers, health professionals, and administrators of services across Australia were actively engaged in the configuration of the InnoWell Platform to meet service needs, identify barriers to and facilitators of quality mental health care, and highlight potentially the best points in the service pathway to integrate the InnoWell Platform. The locally configured InnoWell Platform was then implemented within the respective services. A mixed methods approach, including surveys, semistructured interviews, and workshops, was used to evaluate the impact of the InnoWell Platform. A participatory systems modeling approach involving co-design with local stakeholders was also undertaken to simulate the likely impact of the platform in combination with other services being considered for implementation within the North Coast Primary Health Network to explore resulting impacts on mental health outcomes, including suicide prevention.

RESULTS

Despite overwhelming support for integrating digital health solutions into mental health service settings and promising impacts of the platform simulated under idealized implementation conditions, our results emphasized that successful implementation is dependent on health professional and service readiness for change, leadership at the local service level, the appropriateness and responsiveness of the technology for the target end users, and, critically, funding models being available to support implementation. The key places of interoperability of digital solutions and a willingness to use technology to coordinate health care system use were also highlighted.

CONCLUSIONS

Although the COVID-19 pandemic has resulted in the widespread acceptance of very basic digital health solutions, Project Synergy highlights the critical need to support equity of access to HITs, provide funding for digital infrastructure and digital mental health care, and actively promote the use of technology-enabled, coordinated systems of care.

Participatory Methods for Systems Modeling of Youth Mental Health: Implementation Protocol

Background

Despite significant investment, mental health issues remain a leading cause of death among young people globally. Sophisticated decision analysis methods are needed to better understand the dynamic and multisector drivers of youth mental health. System modeling can help explore complex issues such as youth mental health and inform strategies to effectively respond to local needs and achieve lasting improvements. The advantages of engaging stakeholders in model development processes have long been recognized; however, the methods for doing so are often not well-described.

Objective

This paper aims to describe the participatory procedures that will be used to support systems modeling for national multisite implementation. The Right Care, First Time, Where You Live research program will focus on regional youth mental health applications of systems modeling in 8 different sites across Australia.

Methods

The participatory model development approach involves an iterative process of engaging with a range of participants, including people with lived experience of mental health issues. Their knowledge of the local systems, pathways, and drivers is combined with the academic literature and data to populate the models and validate their structure. The process centers around 3 workshops where participants interact and actively engage in group model-building activities to define, refine, and validate the systems models. This paper provides a detailed blueprint for the implementation of this process for mental health applications.

Results

The participatory modeling methods described in this paper will be implemented at 2 sites per year from 2022 to 2025. The 8 selected sites have been chosen to capture variations in important factors, including determinants of mental health issues and access to services. Site engagement commenced in August 2021, and the first modeling workshops are scheduled to commence in February 2022.

Conclusions

Mental health system decision makers require tools to help navigate complex environments and leverage interdisciplinary problem-solving. Systems modeling can mobilize data from diverse sources to explore a range of scenarios, including the impact of interventions in different combinations and contexts. Involving stakeholders in the model development process ensures that the model findings are context-relevant and fit-for-purpose to inform decision-making.

International Registered Report Identifier (IRRID)

PRR1-10.2196/32988

Sound Decision Making in Uncertain Times: Can Systems Modelling Be Useful for Informing Policy and Planning for Suicide Prevention?

The COVID-19 pandemic demonstrated the significant value of systems modelling in supporting proactive and effective public health decision making despite the complexities and uncertainties that characterise an evolving crisis. The same approach is possible in the field of mental health. However, a commonly levelled (but misguided) criticism prevents systems modelling from being more routinely adopted, namely, that the presence of uncertainty around key model input parameters renders a model useless. This study explored whether radically different simulated trajectories of suicide would result in different advice to decision makers regarding the optimal strategy to mitigate the impacts of the pandemic on mental health. Using an existing system dynamics model developed in August 2020 for a regional catchment of Western Australia, four scenarios were simulated to model the possible effect of the COVID-19 pandemic on levels of psychological distress. The scenarios produced a range of projected impacts on suicide deaths, ranging from a relatively small to a dramatic increase. Discordance in the sets of best-performing intervention scenarios across the divergent COVID-mental health trajectories was assessed by comparing differences in projected numbers of suicides between the baseline scenario and each of 286 possible intervention scenarios calculated for two time horizons; 2026 and 2041. The best performing intervention combinations over the period 2021–2041 (i.e., post-suicide attempt assertive aftercare, community support programs to increase community connectedness, and technology enabled care coordination) were highly consistent across all four COVID-19 mental health trajectories, reducing suicide deaths by between 23.9–24.6% against the baseline. However, the ranking of best performing intervention combinations does alter depending on the time horizon under consideration due to non-linear intervention impacts. These findings suggest that systems models can retain value in informing robust decision making despite uncertainty in the trajectories of population mental health outcomes. It is recommended that the time horizon under consideration be sufficiently long to capture the full effects of interventions, and efforts should be made to achieve more timely tracking and access to key population mental health indicators to inform model refinements over time and reduce uncertainty in mental health policy and planning decisions.

Mental Health in Australia: Psychological Distress Reported in Six Consecutive Cross-Sectional National Surveys From 2001 to 2018

PURPOSE

To examine Australian psychological distress trends from 2001 to 2017/18, including analysis by age, sex, location, and household income.

METHODS

Secondary analysis of the working age population (18-64 years) in six successive representative national health surveys. Measures were prevalence of psychological distress at very-high symptom level (defined by a Kessler Psychological Distress Scale (K10) score of 30 or more) and combined high/very-high level (K10 score of 22 or more). Very-high K10 scores are associated with mental health problems meeting diagnostic thresholds in past year.

RESULTS

From 2001 to 2017/18 Australian rates of K10 very-high distress rose significantly from 3.8 to 5.1% and combined high/very-high from 13.2 to 14.8%. In women aged 55-64, very-high distress rose significantly and substantially from 3.5 to 7.2% and high/very-high distress from 12.4 to 18.7%. In men aged 25-34, very-high distress increased from 2.1 to 4.0% and high/very-high from 10.6 to 11.5%. Income was strongly and inversely associated with distress (lowest vs. highest quintile adjusted OR 11.4). An apparent association of increased distress with regional location disappeared with adjustment for income.

CONCLUSION

Australia's population level of psychological distress increased significantly from 2001-2017/18, with levels highest in women and with rates inversely associated with income. This is likely to be indicative of increased community rates of mental disorders. Given that this has occurred whilst mental healthcare expenditure has increased, there is an urgent need to reconsider how best to respond to mental illness, including targeting the most vulnerable based on social determinants such as age, gender, and lower incomes.

A Dynamic Approach to Economic Priority Setting to Invest in Youth Mental Health and Guide Local Implementation: Economic Protocol for Eight System Dynamics Policy Models

BACKGROUND

Mental illness costs the world economy over US2.5 Bn each year, including premature mortality, morbidity, and productivity losses. Multisector approaches are required to address the systemic drivers of mental health and ensure adequate service provision. There is an important role for economics to support priority setting, identify best value investments and inform optimal implementation. Mental health can be defined as a complex dynamic system where decision makers are challenged to prospectively manage the system over time. This protocol describes the approach to equip eight system dynamics (SD) models across Australia to support priority setting and guide portfolio investment decisions, tailored to local implementation context.

METHODS

As part of a multidisciplinary team, three interlinked protocols are developed; (i) the participatory process to codesign the models with local stakeholders and identify interventions for implementation, (ii) the technical protocol to develop the SD models to simulate the dynamics of the local population, drivers of mental health, the service system and clinical outcomes, and (iii) the economic protocol to detail how the SD models will be equipped to undertake a suite of economic analysis, incorporating health and societal perspectives. Models will estimate the cost of mental illness, inclusive of service costs (health and other sectors, where necessary), quality-adjusted life years (QALYs) lost, productivity costs and carer costs. To assess the value of investing (disinvesting) in interventions, economic analysis will include return-on-investment, cost-utility, cost benefit, and budget impact to inform affordability. Economic metrics are expected to be dynamic, conditional upon changing population demographics, service system capacities and the mix of interventions when synergetic or antagonistic interactions. To support priority setting, a portfolio approach will identify best value combinations of interventions, relative to a defined budget(s). User friendly dashboards will guide decision makers to use the SD models to inform resource allocation and generate business cases for funding.

DISCUSSION

Equipping SD models to undertake economic analysis is intended to support local priority setting and help optimise implementation regarding the best value mix of investments, timing and scale. The objectives are to improve allocative efficiency, increase mental health and economic productivity.

The Impact of Technology-Enabled Care Coordination in a Complex Mental Health System: A Local System Dynamics Model

Background

Prior to the COVID-19 pandemic, major shortcomings in the way mental health care systems were organized were impairing the delivery of effective care. The mental health impacts of the pandemic, the recession, and the resulting social dislocation will depend on the extent to which care systems will become overwhelmed and on the strategic investments made across the system to effectively respond.

Objective

This study aimed to explore the impact of strengthening the mental health system through technology-enabled care coordination on mental health and suicide outcomes.

Methods

A system dynamics model for the regional population catchment of North Coast New South Wales, Australia, was developed that incorporated defined pathways from social determinants of mental health to psychological distress, mental health care, and suicidal behavior. The model reproduced historic time series data across a range of outcomes and was used to evaluate the relative impact of a set of scenarios on attempted suicide (ie, self-harm hospitalizations), suicide deaths, mental health–related emergency department (ED) presentations, and psychological distress over the period from 2021 to 2030. These scenarios include (1) business as usual, (2) increase in service capacity growth rate by 20%, (3) standard telehealth, and (4) technology-enabled care coordination. Each scenario was tested using both pre– and post–COVID-19 social and economic conditions.

Results

Technology-enabled care coordination was forecast to deliver a reduction in self-harm hospitalizations and suicide deaths by 6.71% (95% interval 5.63%-7.87%), mental health–related ED presentations by 10.33% (95% interval 8.58%-12.19%), and the prevalence of high psychological distress by 1.76 percentage points (95% interval 1.35-2.32 percentage points). Scenario testing demonstrated that increasing service capacity growth rate by 20% or standard telehealth had substantially lower impacts. This pattern of results was replicated under post–COVID-19 conditions with technology-enabled care coordination being the only tested scenario, which was forecast to reduce the negative impact of the pandemic on mental health and suicide.

Conclusions

The use of technology-enabled care coordination is likely to improve mental health and suicide outcomes. The substantially lower effectiveness of targeting individual components of the mental health system (ie, increasing service capacity growth rate by 20% or standard telehealth) reiterates that strengthening the whole system has the greatest impact on patient outcomes. Investments into more of the same types of programs and services alone will not be enough to improve outcomes; instead, new models of care and the digital infrastructure to support them and their integration are needed.

Which Social, Economic, and Health Sector Strategies Will Deliver the Greatest Impacts for Youth Mental Health and Suicide Prevention? Protocol for an Advanced, Systems Modelling Approach

Background: Current global challenges are generating extensive social disruption and uncertainty that have the potential to undermine the mental health, wellbeing, and futures of young people. The scale and complexity of challenges call for engagement with systems science-based decision analytic tools that can capture the dynamics and interrelationships between physical, social, economic, and health systems, and support effective national and regional responses. At the outset of the pandemic mental health-related systems models were developed for the Australian context, however, the extent to which findings are generalisable across diverse regions remains unknown. This study aims to explore the context dependency of systems modelling insights. Methods: This study will employ a comparative case study design, applying participatory system dynamics modelling across eight diverse regions of Australia to answer three primary research questions: (i) Will current regional differences in key youth mental health outcomes be exacerbated in forward projections due to the social and economic impacts of COVID-19?; (ii) What combination of social policies and health system strengthening initiatives will deliver the greatest impacts within each region?; (iii) To what extent are optimal strategic responses consistent across the diverse regions? We provide a detailed technical blueprint as a potential springboard for more timely construction and deployment of systems models in international contexts to facilitate a broader examination of the question of generalisability and inform investments in the mental health and wellbeing of young people in the post COVID-19 recovery. Discussion: Computer simulation is known as the third pillar of science (after theory and experiment). Simulation allows researchers and decision makers to move beyond what can be manipulated within the scale, time, and ethical limits of the experimental approach. Such learning when achieved collectively, has the potential to enhance regional self-determination, help move beyond incremental adjustments to the status quo, and catalyze transformational change. This research seeks to advance efforts to establish regional decision support infrastructure and empower communities to effectively respond. In addition, this research seeks to move towards an understanding of the extent to which systems modelling insights may be relevant to the global mental health response by encouraging researchers to use, challenge, and advance the existing work for scientific and societal progress.