1. System Dynamics
Dr Jennifer Morgan

2. Taxonomy of OR methods
OR Methods
“Soft” methods
Methods to help structure ill-structured problem situations
Methods for more structured problems -parameters difficult to quantify
Methods to calculate an attribute of a system
Deterministic methods
Stochastic methods
Statistical methods
Static Monte Carlo simulation methods
Probabilistic methods
Logic methods
Methods to replicate or forecast system behaviour
Deterministic replication methods
Stochastic replication methods
Complexity understanding methods
Optimization methods
Optimization of deterministic systems
Optimization of stochastic systems
Williams, T (2008) Management Science in Practice, Wiley. p.101

3. 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

4. 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 ? ? ? ? ?
Broad system view
Stocks & Flows
Seeking to explore the systems dynamic complexity
Feedback & Delays
Stochasticity of low importance
Strategic issues
Continuous time

5. 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.

6. An example: Waiting List Dynamics

7. An example: Waiting List Dynamics

8. An example: Waiting List Dynamics

9. Behaviour over time