The evaluation of disease prevention and treatment using simulation models
The evaluation of disease prevention and treatment using simulation models
Health policy models provide measures of the effectiveness and costs of complex health care interventions making it possible to compare different policies. We look at the validity of models of screening, prevention and treatment, focusing on two simulation studies. In designing models, account must be taken of disease trends and changing treatment patterns. The choice of modelling technique and of system boundaries are shown to have an impact on results. Decisions have to be made about data which may be scarce or inappropriate for modelling purposes. Cost-effectiveness measures are based on the ratio of costs to benefits, such as life years saved or quality adjusted life years. These are sensitive to the time period and the discount rates chosen. Policy makers should be aware of these different sources of variability or error. For decision making purposes, the calculation of output measures must be based on the same assumptions.
health services, simulation, cost-effectiveness, modelling systems
53-66
Davies, Ruth
8111134a-4e4b-4c6c-a251-1ce8b94e648a
Roderick, Paul
e5ecc991-931d-44ae-9cb3-02f644f61e63
Raftery, James
de9dd294-3a0e-4756-8427-a4f2382495db
2003
Davies, Ruth
8111134a-4e4b-4c6c-a251-1ce8b94e648a
Roderick, Paul
e5ecc991-931d-44ae-9cb3-02f644f61e63
Raftery, James
de9dd294-3a0e-4756-8427-a4f2382495db
Davies, Ruth, Roderick, Paul and Raftery, James
(2003)
The evaluation of disease prevention and treatment using simulation models.
European Journal of Operational Research, 150 (1), .
(doi:10.1016/S0377-2217(02)00783-X).
Abstract
Health policy models provide measures of the effectiveness and costs of complex health care interventions making it possible to compare different policies. We look at the validity of models of screening, prevention and treatment, focusing on two simulation studies. In designing models, account must be taken of disease trends and changing treatment patterns. The choice of modelling technique and of system boundaries are shown to have an impact on results. Decisions have to be made about data which may be scarce or inappropriate for modelling purposes. Cost-effectiveness measures are based on the ratio of costs to benefits, such as life years saved or quality adjusted life years. These are sensitive to the time period and the discount rates chosen. Policy makers should be aware of these different sources of variability or error. For decision making purposes, the calculation of output measures must be based on the same assumptions.
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Published date: 2003
Keywords:
health services, simulation, cost-effectiveness, modelling systems
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Local EPrints ID: 35802
URI: http://eprints.soton.ac.uk/id/eprint/35802
ISSN: 0377-2217
PURE UUID: 3da9e073-6403-4b32-a618-f495d2ba1786
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Date deposited: 23 May 2006
Last modified: 15 Mar 2024 07:54
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Author:
Ruth Davies
Author:
Paul Roderick
Author:
James Raftery
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