A Dynamic Approach to Economic Priority Setting to Invest in Youth Mental Health and Guide Local Implementation:...

Area of Science:

• Health Economics
• System Dynamics Modeling
• Public Health Policy

Background:

• Mental illness incurs significant global economic costs, necessitating multisectoral strategies.
• Economics plays a crucial role in prioritizing mental health investments and optimizing service delivery.
• Mental health systems are complex dynamic systems requiring proactive management.

Purpose of the Study:

• To equip eight system dynamics (SD) models in Australia for priority setting and investment decisions in mental health.
• To integrate economic analysis within SD models to inform resource allocation and implementation strategies.
• To improve allocative efficiency and enhance both mental health and economic productivity.

Main Methods:

• Development of three interlinked protocols: participatory co-design, technical SD model development, and economic analysis.
• Simulation of local population dynamics, mental health drivers, service systems, and clinical outcomes using SD models.
• Economic evaluation including cost of illness, return-on-investment, cost-utility, cost-benefit, and budget impact analysis.

Main Results:

• Economic metrics will be dynamic, accounting for population changes, service capacity, and intervention interactions.
• A portfolio approach will identify optimal intervention combinations for priority setting within budget constraints.
• User-friendly dashboards will facilitate decision-making for resource allocation and funding proposals.

Conclusions:

• Equipping SD models with economic analysis capabilities supports local priority setting and optimizes investment strategies.
• The approach aims to enhance the value of mental health investments by considering timing, scale, and intervention mix.
• Improved allocative efficiency is expected to lead to better mental health and increased economic productivity.