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Describing, measuring and defining process capability in health modelling and simulation studies

   School of Management

   Applications accepted all year round  Competition Funded PhD Project (Students Worldwide)

About the Project

All successful applicants may elect to apply for a range of competitive PhD studentships we offer, guidance for which can be found here:

Self funded applications will also be considered.

The project: Why is the organisation and delivery of health and care services so difficult to plan for and manage? Difficulties and delays in accessing care services, cancellations and increasing costs have a negative impact on all of us: patients, carers and health and care professionals. Despite the attention and resources invested in addressing these problems, many countries and health and care systems face increasing pressure to improve both the effectiveness and the efficiency of their operations. Part of the problem is the complexity inherent in the organisation of health and care services and our limited understanding of how changes will affect their delivery. Another problem is the uncertainty and variability that is associated with many aspects of care service delivery. 

One method of assessing the likely impact of changes in the organisation of a care process on patients and costs is systems modelling and computer simulation. Often this entails the development of a model of the flow of patients through a clinic and its population with input parameters values derived from empirical or hypothetical settings. The likely impact of changes on patient waiting times of adding one additional activity in the care process or increasing the number of care professionals available in the clinic can be studied through computer simulation.

Many aspects of the development of models and the running of computer simulation studies in health care are well studied. For example, several frameworks have been suggested in the literature on working through the conceptual modelling part (the process of abstracting a model from a real or proposed system) of a health simulation study. A number of statistical methods has been suggested for obtaining accurate and robust simulation results.

However, many modellers still face significant challenges in their effort to describe, measure and define the processing capability of care activities. For example, a rapid diagnostic cancer clinic may have access to a CT scanner, but this is shared among the cancer clinic, the Emergency Department and another hospital unit. The number of appointment slots available in an outpatient clinic or general practice, which ultimately determines the capacity to see patients, is a function of the number of care professionals available, but there are many additional factors that contribute to the actual number of available slots over time to fluctuate.

The overarching aim of this research is to propose new methods for describing, measuring and defining capacity (process capability) in health care modelling and simulation studies. The aim will be achieved through systematic work across three key phases/papers. First, a systematic review of the literature will be carried out to help identify relevant current approaches and practices, and to propose a possible state-of-the-art solution to the problem. Two empirical modelling and simulation studies will then be conducted to help validate, refine, and finalise the suggested approach. The specific settings of the empirical case studies will be chosen with the help of the doctoral student and will be sourced from the many active collaborations with health and care organisations of the host research centre.

Preferred start date: October 2023

Application criteria: You should have at least a 2:1 at undergraduate level (or its international equivalent). Your background can be in any subject, not just management. Applicants should also have a good understanding of stochastic simulation methods such Monte Carlo and discrete event. Knowledge or willingness to learn how to programme in R and/or Python.

How to apply

Funding Notes

All successful applicants may elect to apply for a range of competitive PhD studentships we offer, guidance for which can be found here: View Website
Self funded applications will also be considered.

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