HAR672: Advanced Simulation Methods

The Advanced Simulation Methods module is led by Hazel Squires. It runs in the Spring semester and is worth 15 credits.


The Advanced Simulation Methods module is led by Hazel Squires. It runs in the Spring semester and is worth 15 credits.

It is one of the modules on:

This module is available as a CPD option

This module is available as a DDP module

When studying part-time this module is taken in year 2.


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.


This module aims to produce students who will be able to undertake simulation projects to a professional level.

The module will be both theoretically-based and practically-based with the use of the Simul8 software package.

Key themes, both in learning and application within a model will include modelling complex systems, verification of the model, interpreting the output and approaches for minimising model run time.

Learning outcomes

By the end of the module , participants will be able to:

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

Further details

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 turn-around 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.

Teaching methods

The module will be delivered predominantly through a series of 9 x 2 hours taught lectures. Lectures will introduce students to the key theory and methods, covering learning outcomes 1-4.

These will be supported by the use of tutorials (7 x 1 hour) 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 10 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.


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.

    The content of our courses is reviewed annually to make sure it is up-to-date and relevant. Individual modules are occasionally updated or withdrawn. This is in response to discoveries through our world-leading research, funding changes, professional accreditation requirements, student or employer feedback, outcomes of reviews, and variations in staff or student numbers. In the event of any change we'll consult and inform students in good time and take reasonable steps to minimise disruption.

    Information last updated: 15 June 2022

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