Operational modelling for the planning and management of healthcare resources
Operational modelling for the planning and management of healthcare resources
The provision of healthcare services is perhaps one of the largest and most complex industries worldwide. As one of the essential necessities to sustain life, it faces the consequences of increasing demand in times of limited financial resources and competing social needs. Providing the appropriate medical care involves decision-making in terms of planning and management of healthcare resources.
There is currently a great need to evolve a framework in which necessarily detailed, stochastic, flexible and user-friendly operational models, to aid both the planning and management of hospital resources, can be developed. Such a framework is considered and created within this research. Furthermore, detailed integrated simulation models for the planning and management of hospital beds, operating theatres, workforce needs and critical care services have been designed and built. An evolutionary development methodology has been adopted whereby the research work and model development has been guided by a number of steering groups within participating NHS Trust.
The derived framework incorporates the need for sophisticated patient classification techniques to be adopted. In order to capture the uncertainty and variability amongst the patient population, a number of classification techniques have been considered and evaluated for their relative performances and practical usefulness. Healthcare issues representing both challenges and opportunities are explored in order to provide a basis for tentative conclusions about the current state of operational modelling for healthcare. A framework for the successful design and implementation of operational models in a healthcare environment is proposed.
University of Southampton
Harper, Paul Robert
50031b94-21f0-4a9e-8e6d-613f8d10a2d1
2002
Harper, Paul Robert
50031b94-21f0-4a9e-8e6d-613f8d10a2d1
Harper, Paul Robert
(2002)
Operational modelling for the planning and management of healthcare resources.
University of Southampton, Doctoral Thesis.
Record type:
Thesis
(Doctoral)
Abstract
The provision of healthcare services is perhaps one of the largest and most complex industries worldwide. As one of the essential necessities to sustain life, it faces the consequences of increasing demand in times of limited financial resources and competing social needs. Providing the appropriate medical care involves decision-making in terms of planning and management of healthcare resources.
There is currently a great need to evolve a framework in which necessarily detailed, stochastic, flexible and user-friendly operational models, to aid both the planning and management of hospital resources, can be developed. Such a framework is considered and created within this research. Furthermore, detailed integrated simulation models for the planning and management of hospital beds, operating theatres, workforce needs and critical care services have been designed and built. An evolutionary development methodology has been adopted whereby the research work and model development has been guided by a number of steering groups within participating NHS Trust.
The derived framework incorporates the need for sophisticated patient classification techniques to be adopted. In order to capture the uncertainty and variability amongst the patient population, a number of classification techniques have been considered and evaluated for their relative performances and practical usefulness. Healthcare issues representing both challenges and opportunities are explored in order to provide a basis for tentative conclusions about the current state of operational modelling for healthcare. A framework for the successful design and implementation of operational models in a healthcare environment is proposed.
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Published date: 2002
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Local EPrints ID: 464780
URI: http://eprints.soton.ac.uk/id/eprint/464780
PURE UUID: 4f1fd805-14ab-41a4-9d35-c2aa86db7d5a
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Date deposited: 05 Jul 2022 00:01
Last modified: 16 Mar 2024 19:44
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Author:
Paul Robert Harper
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