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

Incorporating Complexity and System Dynamics into Economic Modelling for Mental Health Policy and Planning

Care as usual has failed to stem the tide of mental health challenges in children and young people. Transformed models of care and prevention are required, including targeting the social determinants of mental health. Robust economic evidence is crucial to guide investment towards prioritised interventions that are effective and cost-effective to optimise health outcomes and ensure value for money. Mental healthcare and prevention exhibit the characteristics of complex dynamic systems, yet dynamic simulation modelling has to date only rarely been used to conduct economic evaluation in this area. This article proposes an integrated decision-making and planning framework for mental health that includes system dynamics modelling, cost-effectiveness analysis, and participatory model-building methods, in a circular process that is constantly reviewed and updated in a 'living model' ecosystem. We describe a case study of this approach for mental health system policy and planning that synergises the unique attributes of a system dynamics approach within the context of economic evaluation. This kind of approach can help decision makers make the most of precious, limited resources in healthcare. The application of modelling to organise and enable better responses to the youth mental health crisis offers positive benefits for individuals and their families, as well as for taxpayers.

Reducing mental health emergency visits: population-level strategies from participatory modelling

BACKGROUND

Emergency departments (EDs) are often the front door for urgent mental health care, especially when demand exceeds capacity. Long waits in EDs exert strain on hospital resources and worsen distress for individuals experiencing a mental health crisis. We used as a test case the Australian Capital Territory (ACT), with a population surge of over 27% across 2011-2021 and a lagging increase in mental health care capacity, to evaluate population-based approaches to reduce mental health-related ED presentations.

METHODS

We developed a system dynamics model for the ACT region using a participatory approach involving local stakeholders, including health planners, health providers and young people with lived experience of mental health disorders. Outcomes were projected over 2023-2032 for youth (aged 15-24) and for the general population.

RESULTS

Improving the overall mental health care system through strategies such as doubling the annual capacity growth rate of mental health services or leveraging digital technologies for triage and care coordination is projected to decrease youth mental health-related ED visits by 4.3% and 4.8% respectively. Implementation of mobile crisis response teams (consisting of a mental health nurse accompanying police or ambulance officers) is projected to reduce youth mental health-related ED visits by 10.2% by de-escalating some emergency situations and directly transferring selected individuals to community mental health centres. Other effective interventions include limiting re-presentations to ED by screening for suicide risk and following up with calls post-discharge (6.4% reduction), and limiting presentations of frequent users of ED by providing psychosocial education to families of people with schizophrenia (5.1% reduction). Finally, combining these five approaches is projected to reduce youth mental health-related ED presentations by 26.6% by the end of 2032.

CONCLUSIONS

Policies to decrease youth mental health-related ED presentations should not be limited to increasing mental health care capacity, but also include structural reforms.

Mental health impacts of COVID-19: A retrospective analysis of dynamic modelling projections for Australia

Background

In early 2020, we developed a dynamic model to support policy responses aimed at mitigating the adverse mental health effects of the COVID-19 pandemic in Australia. As the pandemic has progressed, it has become clear that our initial model forecasts overestimated the impacts of infection control measures (lockdowns, physical distancing, etc.) on suicide, intentional self-harm hospitalisation, and mental health-related emergency department (ED) presentation rates.

Methods

Potential explanations for the divergence of our model predictions from observed outcomes were assessed by comparing simulation results for a set of progressively more refined models with data on the prevalence of moderate to very high psychological distress and numbers of suicides, intentional self-harm hospitalisations, and mental health-related ED presentations published after our modelling was released in July 2020.

Results

Allowing per capita rates of spontaneous recovery and intentional self-harm to differ between people experiencing moderate to very high psychological distress prior to the pandemic and those developing comparable levels of psychological distress only as a consequence of infection control measures substantially improves the fit of our model to empirical estimates of the prevalence of psychological distress and leads to significantly lower predicted effects of COVID-19 on suicide, intentional self-harm hospitalisation, and mental health-related ED presentation rates.

Conclusion

Accommodating the influence of prior mental health on the psychological effects of population-wide social and economic disruption is likely to be critical for accurately forecasting the mental health impacts of future public health crises as they inevitably arise.

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.

The economic costs of alcohol-related harms at the local level in New South Wales

INTRODUCTION

Alcohol is a harmful, toxic and addictive substance that causes many diseases and injuries. Alcohol use also incurs a financial cost to the health care system and wider economy. This project aimed to undertake a cost impact analysis of alcohol-related harms at the local level in New South Wales (NSW). The alcohol-related harms costing model is an interactive tool designed for use by local health districts, stakeholders such as Liquor and Gaming NSW, NSW Independent Liquor and Gaming Authority and community stakeholders.

METHODS

Costs included in the analysis were alcohol-related hospitalisations, deaths, crimes, emergency department attendances, outpatient presentations and their impacts on productivity. Two local government areas (LGA) were used as case studies to demonstrate local impacts.

RESULTS

In 2019-2020, the total cost of alcohol-related harms for NSW was estimated at $9 billion, at a rate of $120.3 million per 100,000 population. The total costs were comprised of alcohol-attributable premature mortality ($8.3 billion), non-fatal health care costs ($275 million) and crime costs ($457 million). A comparative analysis of two case study LGAs estimated that alcohol-related harms cost $195 million for the Northern Beaches LGA and $351 million for the Central Coast LGA.

DISCUSSION AND CONCLUSIONS

This research has developed a 'proof-of-concept' model to estimate the cost of alcohol-related harms at the local level in Australia, empowering health agencies and local community stakeholders to use economic evidence in their submissions in response to new liquor licence applications and other policies that impact their local community. This economic evidence can be used to improve the quality of decisions on alcohol regulation and policies. There are a number of future research opportunities that would enhance the economic evidence available to liquor licensing decision-makers.

Can participatory processes lead to changes in the configuration of local mental health networks? A social network analysis

Systems modeling offers a valuable tool to support strategic decision-making for complex problems because it considers the causal inter-relationships that drive population health outcomes. This tool can be used to simulate policies and initiatives to determine which combinations are likely to deliver the greatest impacts and returns on investment. Systems modeling benefits from participatory approaches where a multidisciplinary stakeholder group actively engages in mapping and contextualizing causal mechanisms driving complex system behaviors. Such approaches can have significant advantages, including that they may improve connection and coordination of the network of stakeholders operating across the system; however, these are often observed in practice as colloquial anecdotes and seldom formally assessed. We used a basic social network analysis to explore the impact on the configuration of the network of mental health providers, decision-makers, and other stakeholders in Bogota, Colombia active in a series of three workshops throughout 2021 and 2022. Overall, our analysis suggests that the participatory process of the systems dynamics exercise impacts the social network's structure, relationships, and dynamics.

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.

Applying systems approaches to stakeholder and community engagement and knowledge mobilisation in youth mental health system modelling

Background

There is a significant push to change the trajectory of youth mental ill-health and suicide globally. Ensuring that young people have access to services that meet their individual needs and are easily accessible is a priority. Genuine stakeholder engagement in mental health system design is critical to ensure that system strengthening is likely to be successful within these complex environments. There is limited literature describing engagement processes undertaken by research teams in mental health program implementation and planning. This protocol describes the methods that will be used to engage local communities using systems science methods to mobilize knowledge and action to strengthen youth mental health services.

Methods

Using participatory action research principles, the research team will actively engage with local communities to ensure genuine user-led participatory systems modelling processes and enhance knowledge mobilisation within research sites. Ensuring that culturally diverse and Aboriginal and Torres Strait Islander community voices are included will support this process. A rigorous site selection process will be undertaken to ensure that the community is committed and has capacity to actively engage in the research activities. Stakeholder engagement commences from the site selection process with the aim to build trust between researchers and key stakeholders. The research team will establish a variety of engagement resources and make opportunities available to each site depending on their local context, needs and audiences they wish to target during the process.

Discussion

This protocol describes the inclusive community engagement and knowledge mobilization process for the Right care, first time, where you live research Program. This Program will use an iterative and adaptive approach that considers the social, economic, and political context of each community and attempts to maximise research engagement. A theoretical framework for applying systems approaches to knowledge mobilization that is flexible will enable the implementation of a participatory action research approach. This protocol commits to a rigorous and genuine stakeholder engagement process that can be applied in mental health research implementation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13033-022-00530-1.

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.

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

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.