The impact of strengthening mental health services to prevent suicidal behaviour

Abstract

Objective: Successive suicide prevention frameworks and action plans in Australia and internationally have called for improvements to mental health services and enhancement of workforce capacity. However, there is debate regarding the priorities for resource allocation and the optimal combination of mental health services to best prevent suicidal behaviour. This study investigates the potential impacts of service capacity improvements on the incidence of suicidal behaviour in the Australian context. Methods: A system dynamics model was developed to investigate the optimal combination of (1) secondary (acute) mental health service capacity, (2) non-secondary (non-acute) mental health service capacity and (3) resources to re-engage those lost to services on the incidence of suicidal behaviour over the period 2018–2028 for the Greater Western Sydney (Australia) population catchment. The model captured population and behavioural dynamics and mental health service referral pathways and was validated using population survey and administrative data, evidence syntheses and an expert stakeholder group. Results: Findings suggest that 28% of attempted suicide and 29% of suicides could be averted over the forecast period based on a combination of increases in (1) hospital staffing (with training in trauma-informed care), (2) non-secondary health service capacity, (3) expansion of mental health assessment capacity and (4) re-engagement of at least 45% of individuals lost to services. Reduction in the number of available psychiatric beds by 15% had no substantial impact on the incidence of attempted suicide and suicide over the forecast period. Conclusion: This study suggests that more than one-quarter of suicides and attempted suicides in the Greater Western Sydney population catchment could potentially be averted with a combination of increases to hospital staffing and non-secondary (non-acute) mental health care. Reductions in tertiary care services (e.g. psychiatric hospital beds) in combination with these increases would not adversely affect subsequent incidence of suicidal behaviour.

The Science of Complex Systems Is Needed to Ameliorate the Impacts of COVID-19 on Mental Health

“…This unintended consequence arising from two "evidence-based" interventions applied in combination is explained by the imbalance they generate in the dynamics of service capacity vs. demand for services which is regionally specific. A range of similar models have been applied to inform mental health services planning, suicide prevention, and to answer long debated questions that are not able to be tested through real world experimentation (23,(29)(30)(31)(32). Most recently, early prototype systems models have been developed for the Australian context to inform national and regional policy responses to the mental health consequences of the economic and social effects of the pandemic (33-37).…”

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

“…As in other sectors, the application of systems modelling and simulation can drive better decision-making in mental health and suicide prevention by facilitating the exploration of the likely impact of alternative system design and service planning scenarios before they are implemented in the real world. Recent applications [47,56,[58][59][60][61][62][63][64][65][66][67] of these advanced decision support tools have generated new knowledge and insights that are only possible when we use systems thinking and systems modelling methods to bring together the different pieces of a complex puzzle. This puzzle has many pieces, including, for example, research into the broader social and economic determinants of mental health and suicidal behaviour, service barriers and facilitators, and assessment of local needs, evidence regarding effectiveness of mental health models of care and population-based programs, together with disparate, multi-agency data sources, expert and local knowledge, and the deep understanding and unique perspectives of those with lived experience.…”

“…For example, in 2017 a system dynamics model was developed in partnership with Western Sydney Primary Health Network and their stakeholders to inform decision making for local investment in suicide prevention programs and mental health service planning [59,63]. This model simulated cuts to psychiatric beds under different conditions related to community-based service capacity, forecasting the likely impact on suicide rates over the next 10 years [60].…”

Systems modelling and simulation to inform strategic decision making for suicide prevention in rural New South Wales (Australia)

“…Applications of systems modelling and simulation to provide decision support capability in addressing complex and persistent public health problems have demonstrated their utility (Atkinson et al, 2018(Atkinson et al, , 2019a(Atkinson et al, , 2019bLoyo et al, 2013;Page et al, 2017Page et al, , 2018bRoberts et al, 2019). These tools combine local and expert knowledge with best available data and the body of research evidence, and have the unique feature of being able to capture population and demographic dynamics, changes over time in behavioural drivers, service interactions and workforce capacity and the potentially non-additive effects of intervention combinations.…”