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Title: A theoretical framework for hybrid simulation in modelling complex patient pathways
Author: Zulkepli, Jafri
ISNI:       0000 0004 2724 7986
Awarding Body: Brunel University
Current Institution: Brunel University
Date of Award: 2012
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Providing care services across several departments and care givers creates the complexity of the patient pathways, as it deals with different departments, policies, professionals, regulations and many more. One example of complex patient pathways (CPP) is one that exists in integrated care, which most literature relates to health and social care integration. The world population and demand for care services have increased. Therefore, necessary actions need to be taken in order to improve the services given to patients in maintaining their quality of life. As the complexity arises due to different needs of stakeholders, it creates many problems especially when it involves complex patient pathways (CPP). To reduce the problems, many researchers tried using several decision tools such as Discrete Event Simulation (DES), System Dynamic (SD), Markov Model and Tree Diagram. This also includes Direct Experimentation, one of techniques in Lean Thinking/Techniques, in their efforts to help simplify the system complexity and provide decision support tools. However, the CPP models were developed using a single tools which makes the models have some limitations and not capable in covering the entire needs and features of the CPP system. For example, lack of individual analysis, feedback loop as well as lack of experimentation prior to the real implementation. As a result, ineffective and inefficient decision making was made. The researcher also argues that by combining the DES and SD techniques, named the hybrid simulation, the CPP model would be enhanced and in turn will help to provide decision support tools and consequently, will reduce the problems in CPP to the minimum level. As there is no standard framework, a framework of a hybrid simulation for modelling the CPP system is proposed in this research. The researcher is much concerned with the framework development rather than the CPP model itself, as there is no standard model that can represent any type of CPP since it is different in term of its regulations, policies, governance and many more. The framework is developed based on several literatures, selected among developed framework/models that have used combinations of DES and SD techniques simultaneously, applied in a large system or in healthcare sectors. This is due to the condition of the CPP system which is a large healthcare system. The proposed framework is divided into three phases, which are Conceptual, Modelling and Models Communication Phase, and each phase is decomposed into several steps. To validate the suitability of the proposed framework that provides guidance in developing CPP models using hybrid simulation, the inductive research methodology will be used with the help of case studies as a research strategy. Two approaches are used to test the suitability of the framework – practical and theoretical. The practical approach involves developing a CPP model (within health and social care settings) assisted by the SD and DES simulation software which was based on several case studies in health and social care systems that used single modelling techniques. The theoretical approach involves applying several case studies within different care settings without developing the model. Four case studies with different areas and care settings have been selected and applied towards the framework. Based on suitability tests, the framework will be modified accordingly. As this framework provides guidance on how to develop CPP models using hybrid simulation, it is argued that it will be a benchmark to researchers and academicians, as well as decision and policy makers to develop a CPP model using hybrid simulation.
Supervisor: Eldabi, T. ; Ali, M. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Integration model ; Social care ; Health care ; System dynamics model ; Discrete simulation model ; Hybrid simulation