91Ö±²¥

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Module description

This module provides an in-depth review of simulation rationale, techniques and methodologies with a particular focus on discrete event simulation and their practical application to inform healthcare decision-making.

From the fundamentals of a basic model, the course will progress to modelling complex systems, verification, interpreting output and approaches for minimising model run time.

The methods outlined in this module will be transferable to decision problems in settings other than healthcare. Lectures will be augmented by practical modelling sessions.

Discrete event simulation (DES)

The prior 'Cost-Effectiveness for HTA' module in the Autumn semester teaches Markov modelling and decision-tree modelling methods.

The Advanced Simulation Methods module teaches a different technique, Discrete event simulation (DES), which can be used for modelling where there is a service design aim, such as modelling patient flows through clinical pathways or capacity planning in a hospital.

In such cases, the pattern of arrival times and capacity constraints are important factors when evaluating alternative options for change.

The first part of the module focuses on developing such a resource-constrained simulation model, including a first introduction of how to use the simulation package Simul8.

An example project includes an assessment of a 7-day turnaround for the reporting of cervical screening results using discrete event simulation.

The second part of the module focuses on the approaches for, and benefits of, using Simul8 to develop health economic models as an alternative to other approaches such as cohort Markov modelling.

Students will develop an individual-level cost-effectiveness model in Simul8, including the incorporation of discounting and probabilistic sensitivity analysis (PSA).

Students will be taught the different types and uses of uncertainty analyses.

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Objectives

• Define, formulate, construct and resolve simulation models of complex systems within Simul8
• Describe the limitations of simulation analyses
• Interpret outputs from a simulation model
• Disseminate results, defend the choices of model structure and data inputs by means of an interactive oral examination

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Teaching 

This module can also be taken as part of the following courses:

The module will be delivered predominantly through a series of nine lectures, each lasting two hours. These will be supported by the use of seven hour-long tutorials to consolidate concepts and skills learned within the lectures. Students will be expected to undertake reading and/or exercises prior to each lecture and tutorial.

Independent study will primarily be self-directed. Small assignments for formative assessment are set throughout the module and feedback will be given during tutorials; the feedback will not be documented.

Tutorial sessions and interaction within the lectures will allow the candidate to discuss the modelling techniques used, the selection of input parameters, the results and the ultimate conclusions that can be drawn from the modelled results.

These learning and teaching methods will reinforce learning outcomes and provide practical experience of applying some concepts.

Study expectations

Students will also be expected to undertake approximately 120 hours of independent study, including preparation for tutorials, preparation for the assignment and oral examination, and further recommended reading.

Students will be expected to undertake reading and/or exercises prior to each lecture and tutorial. Independent study will primarily be self-directed.

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Fees and funding

You can find out more about fees and funding for CPD modules in the School of Medicine and Population Health at the link below. We accept sponsored as well as self-funding students.

Fees and funding information

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How to apply

Find out what you need to do to apply for a CPD module in the School of Medicine and Population Health.

Apply for this module

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Contact

For more information on this module, speak to the lead academic: