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Health System Simulation
The health system is large and complex. The structural components forming the health system span across multiple levels of the health system hierarchy, from within the patient, health professionals and communities to the organisations, institutions and resources whose primary purpose is to improve people’s health (WHO, 2005).
Fig 1 Conceptual drawing of a 4 level health care system p20 (Reid et al 2005)
However, it is the arrangement of these structural components and the interactions between them, such as decisions made and actions taken, that drives the health system’s behaviour and determines its ability to achieve the overall goals of promoting, restoring and maintaining health or achieving this in a more efficient or equitable manner.
Health Systems Simulation is the application of modelling and computer simulation methods to explore, understand and improve the interaction between structure and action in health care and policy (Heffernan, McDonnell, 2005). Simulation provides dynamic analysis of the health system that is, observing how the system behaves over time. Also, simulation can replace or extend studies such as random controlled trials that are impossible, too long, too late or too expensive in the real world (Heffernan, McDonnell, 2005).
Since the health system is a multi-scale system, combinations of modelling methods are applied to depict both the aggregate and disaggregate view of the system. System dynamics models outline the context of the problem. It makes explicit the boundaries of the health system, its structure and relationships. Using this approach we can identify reinforcing and balancing feedback effects, circular causation, delayed responses and the leverage points where decisions and actions bring about changes to the systems performance. Combining this with agent based modelling we can capture emergent and non-linear behaviour arising from the interactions at the individual level and how the system learns, adapts and self-organises itself to maintain order.
Using these modelling and simulation methods, we are able to develop a hypothesis about the structure (components and their interactions), from the detail level to the overall context, that is both necessary and sufficient to account for the specific focussed behaviour of interest or health system problem. The simulation tests this hypothesis by enabling comparisons with data and observed behaviour with the derived behaviour. Behaviour modes of interest include overshoot and collapse or damped oscillation with a certain period (for example, health workforce over- and under-supply cycles). This is valuable whenever decision makers misperceive the system and draw wrong conclusions about behaviour and therefore about the choice of policies.
References
- What is a health system? World Health Organisation 2005 http://www.who.int/healthsystems/en/
- Heffernan M, McDonnell G, 'In Silico' Intervention Experiments for the Health System2005 (Internal paper, please contact for more information)
- Reid, Proctor P. Compton, W. Dale Jerome H. Grossman, and Gary Fanjiang, Editors, Committee on Engineering and the Health Care System, National Academy of Engineering, Institute of Medicine Building a Better Delivery System: A New Engineering/Health Care Partnership. National Academies Press 2005 http://www.nap.edu/catalog/11378.html
Key messages about Health Systems Simulation
- We represent the world as a system of connected decisions (informing, deciding, acting, communicating)
- We use multiscale methods to model system constraints interacting with individual behaviours
- We provide a logical consistent dynamic systems framework
- In silico experiments are being used to integrate theory data and intuition as a new way of doing science (combining abduction, deduction, induction)
- Things take time
"Hard work and best efforts, put forth without the guidance of profound knowledge may well be at the route of our ruination. There is no substitute for knowledge."
W.Edwards Deming
Current Simulation Workplan
Health Systems Simulation as a Method
- Systems Approaches & System Dynamics (SD)
- Multiscale Modelling using Multiple Simulation Methods (SD plus Agent based modelling (emergent system dynamics)
- “In silico” experiments and Decision Learning Environments
Health System Performance and Design
- Safe systems design (esp. Medications & ICT)
- Analysing and improving complex interventions
- Analysing & designing Health facilities & services
Understanding Interactions among Health Policy, Practice, Workforce expertise & Technology
What We Try To Do In Systems Simulation
- To demonstrate the disadvantages of non-systemic solutions to complex issues
- To formulate and test systemic solutions
- A mix of qualitative and quantitative methods
- To tell complex stories clearly and accurately
- To change the way we think about problems
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