System Dynamics
Dr Jennifer Morgan
Taxonomy of OR methods
OR Methods
Methods to calculate
an attribute of a
system
“Soft” methods
Methods to help
structure illstructured problem
situations
Methods for more
structured problems
-parameters difficult
to quantify
Deterministic
methods
Methods to replicate
or forecast system
behaviour
Optimization
methods
Deterministic
replication methods
Optimization of
deterministic
systems
Statistical methods
Stochastic replication
methods
Optimization of
stochastic systems
Static Monte Carlo
simulation methods
Complexity
understanding
methods
Stochastic methods
Logic methods
Probabilistic methods
Williams, T (2008) Management Science in Practice, Wiley. p.101
What is System Dynamics?
“An approach to understanding the nonlinear behaviour of complex
systems over time using stocks and flows, feedback loops and delays”
Reception
Triage
Treatment
What is System Dynamics?
“An approach to understanding the nonlinear behaviour of complex
systems over time using stocks and flows, feedback loops and delays”
Reception
•
•
•
Broad system view
Seeking to explore the systems dynamic
complexity
Strategic issues
Triage
•
•
•
•
Treatment
Stocks & Flows
Feedback & Delays
Stochasticity of low importance
Continuous time
System Dynamics is great for…
• Workforce planning: modelling the long term impact of recruitment and training
•
•
•
policies on capacity and patient care.
Disease modelling: classic S-I-R modelling of disease spread to predict the spread of
disease and allow healthcare providers to investigate emergency procedures.
Technology adoption: exploring how technology is expected to be adopted
throughout an organization and its long term impact.
Bed blocking: modelling A&E within the whole hospital context to identify that the
major impact of bed shortages is felt first on elective admissions (measuring the effect using
A&E waiting times is misleading).
• Patient flow: modelling inpatient stays, outpatient clinics, A&E to identify feedback
•
and delays within the system which are impacting patient flow.
Demand modelling: exploring the many sources of demand on healthcare systems,
including re-referral and patient follow-up.
• Linking disease modelling to patient flow: using disease modelling to predict the
•
demand on A&E, and assess when emergency measures need to be implemented.
Exploring referral behaviours in response to waiting times: modelling to
examine the relationship between the size of the waiting list and referral behaviours.
An example: Waiting List Dynamics
An example: Waiting List Dynamics
An example: Waiting List Dynamics
Behaviour over time