System Dynamics Dr Jennifer Morgan

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

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 Triage Treatment ? ? ? ? ? Broad system view Stocks & Flows Seeking to explore the systems dynamic complexity Feedback & Delays Stochasticity of low importance Strategic issues 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