Simul8: An aide to decision making Chris Yates St Helens & Knowsley Teaching Hospitals NHS Trust

What is simul8? A powerful predictive simulation analysis tool that can capture the interactions and variations that are inherent within a system. Using it enables us to understand how a service and its resources work. We can add business rules that are unique to our processes.

What can simul8 do? Make sure we get the most out of the resources we have. It enables evidence based decision making. Consider how key metrics will perform in the future, based on history and any changes we intend to make to the system. Allows you to compare and evaluate proposed initiatives/solutions/scenarios without the need for “live” trials. Is useful for predicting the impact of a wide range of what-if scenarios.

Why use Simul8 and not excel? Simul8 models real life variability and randomness. Spreadsheets use averages Simul8 can show queues building up, or a series of activities grinding to a halt. This is an effective way of communicating scenarios to staff

Who else uses simul8? Healthcare – BUPA, DoH, Johns Hospkins, Geisinger, Mount Sinai Hospital, Saint Francis Medical Centre, Northwestern Memorial Hospitals, Melbourne Health…. Motor industry – General Motors, Ford, Toyota, Jaguar, Rolls Royce.... Selected others – Unilever, Disneyland, Tesco, Bosch, MoD, Ernst & Young, Nike, McDonalds, Barclaycard, Orange, PA Consulting Group, IBM, American Express, BP, Fujitsu….

DEMO 1

Average time between arrivals = 5 mins Average length of time for activity = 5 mins Run for 8 hours (assume no breaks)

Stroke Target – 80% of stroke patients should spend 90% of their time on a dedicated Stroke Ward Question – How much do we need to reduce LOS, to ensure achievement of the target

Stroke Benchmarking analysis showed LOS was one of the best in the North West Revised question – How much do we need to increase bed capacity by to ensure achievement of the target

DEMO 2

Modelled Outputs % months achieving target Mean annual performance with 95% Confidence Intervals Utilisation of the stroke unit Outlier bed days Max number of stroke patients at any point in time

Lessons learned The service you are modelling needs to own the model The NHS collects lots of data, but not always the elements needed for modelling – Manual data collection – Best guess distribution (Triangular) Start small (high level) and only if needed model in more detail

Other potential uses for Simul8 AED staffing levels Maternity SAU - Bed Modelling Outpatient capacity Car parking Discharge process Any process where there is a flow of work

Any questions?