A review of health care models for coronary heart disease interventions
A review of health care models for coronary heart disease interventions
This article reviews models for the treatment of coronary heart disease (CHD). Whereas most of the models described were developed to assess the cost effectiveness of different treatment strategies, other models have also been used to extrapolate clinical trials, for capacity and resource planning, or to predict the future population with heart disease. In this paper we investigate the use of modelling techniques in relation to different types of health intervention, and we discuss the assumptions and limitations of these approaches. Many of the models reviewed in this paper use decision tree models for acute or short term interventions, and Markov or state transition models for chronic or long term interventions. Discrete event simulation has, however, been used for more complex whole system models, and for modelling resource-constrained interventions and operational planning. Nearly all of the studies in our review used cohort-based models rather than population based models, and therefore few models could estimate the likely total costs and benefits for a population group. Most studies used de novo purpose built models consisting of only a small number of health states. Models of the whole disease system were less common. The model descriptions were often incomplete. We recommend that the reporting of model structure, assumptions and input parameters is more explicit, to reduce the risk of biased reporting and ensure greater confidence in the model results.
health care, model, decision tree, markov, discrete event simulation, economic evaluation, coronary heart disease
311-324
Cooper, K.
6b37f95e-daae-4b87-9f79-0fabd4eb8f6b
Brailsford, S.C.
634585ff-c828-46ca-b33d-7ac017dda04f
Davies, R.
b3bce148-1213-4c2e-a3bf-a79fe8360f03
Raftery, J.
f7af69fc-5be9-4d95-88e0-5b5f7aeec60b
15 November 2006
Cooper, K.
6b37f95e-daae-4b87-9f79-0fabd4eb8f6b
Brailsford, S.C.
634585ff-c828-46ca-b33d-7ac017dda04f
Davies, R.
b3bce148-1213-4c2e-a3bf-a79fe8360f03
Raftery, J.
f7af69fc-5be9-4d95-88e0-5b5f7aeec60b
Cooper, K., Brailsford, S.C., Davies, R. and Raftery, J.
(2006)
A review of health care models for coronary heart disease interventions.
Health Care Management Science, 9 (4), .
(doi:10.1007/s10729-006-9996-x).
Abstract
This article reviews models for the treatment of coronary heart disease (CHD). Whereas most of the models described were developed to assess the cost effectiveness of different treatment strategies, other models have also been used to extrapolate clinical trials, for capacity and resource planning, or to predict the future population with heart disease. In this paper we investigate the use of modelling techniques in relation to different types of health intervention, and we discuss the assumptions and limitations of these approaches. Many of the models reviewed in this paper use decision tree models for acute or short term interventions, and Markov or state transition models for chronic or long term interventions. Discrete event simulation has, however, been used for more complex whole system models, and for modelling resource-constrained interventions and operational planning. Nearly all of the studies in our review used cohort-based models rather than population based models, and therefore few models could estimate the likely total costs and benefits for a population group. Most studies used de novo purpose built models consisting of only a small number of health states. Models of the whole disease system were less common. The model descriptions were often incomplete. We recommend that the reporting of model structure, assumptions and input parameters is more explicit, to reduce the risk of biased reporting and ensure greater confidence in the model results.
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Published date: 15 November 2006
Keywords:
health care, model, decision tree, markov, discrete event simulation, economic evaluation, coronary heart disease
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Local EPrints ID: 37402
URI: http://eprints.soton.ac.uk/id/eprint/37402
ISSN: 1386-9620
PURE UUID: 5a94d9ec-3fc6-4271-b7e3-938f592bfab6
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Date deposited: 23 Apr 2007
Last modified: 12 Nov 2024 02:33
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Author:
K. Cooper
Author:
R. Davies
Author:
J. Raftery
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