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Incorporation of uncertainty in health economic modelling studies

Identifieur interne : 000425 ( PascalFrancis/Curation ); précédent : 000424; suivant : 000426

Incorporation of uncertainty in health economic modelling studies

Auteurs : Anthony O'Hagan [Royaume-Uni] ; Christopher Mccabe [Royaume-Uni] ; Ron Akehurst [Royaume-Uni] ; Alan Brennan [Royaume-Uni] ; Andrew Briggs [Royaume-Uni] ; Karl Claxton [Royaume-Uni] ; Elisabeth Fenwick [Royaume-Uni] ; Dennis Fryback [États-Unis] ; Mark Sculpher [Royaume-Uni] ; David Spiegelhalter [Royaume-Uni] ; Andrew Willan [Canada]

Source :

RBID : Pascal:05-0340420

Descripteurs français

English descriptors

Abstract

In a recent leading article in PharmacoEconomics, Nuijten described some methods for incorporating uncertainty into health economic models and for utilising the information on uncertainty regarding the cost effectiveness of a therapy in resource allocation decision-making. His proposals are found to suffer from serious flaws in statistical and health economic reasoning. Nuijten's suggestions for incorporating uncertainty: (a) wrongly interpret the p-value as the probability that the null hypothesis is true; (b) represent this probability wrongly by truncating the input distribution; and (c) in the specific example of an antiparkinsonian drug uses a completely inappropriate p-value of 0.05 when the null hypothesis would, in reality, be emphatically disproved by the data. His suggestions regarding minimum important differences in cost effectiveness: (a) introduce areas of indifference that suggest inappropriate reliance on cost minimisation while failing to recognise that decisions should be based on expected costs versus benefits; and (b) offer no guidance on how the probabilities associated with these areas could be used in decision-making. Furthermore, Nuijten's model for Parkinson's disease is over-simplified to the point of providing a bad example of modelling practice, which may mislead the readers of PharmacoEconomics. The rationale for this paper is to ensure that readers do not apply inappropriate analyses as a result of following the proposals contained in Nuijten's paper. In addition to a detailed critique of Nuijten's proposals, we provide brief summaries of the currently accepted best practice in cost-effectiveness decision-making under uncertainty.
pA  
A01 01  1    @0 1170-7690
A03   1    @0 PharmacoEconomics : (Auckl. )
A05       @2 23
A06       @2 6
A08 01  1  ENG  @1 Incorporation of uncertainty in health economic modelling studies
A11 01  1    @1 O'HAGAN (Anthony)
A11 02  1    @1 MCCABE (Christopher)
A11 03  1    @1 AKEHURST (Ron)
A11 04  1    @1 BRENNAN (Alan)
A11 05  1    @1 BRIGGS (Andrew)
A11 06  1    @1 CLAXTON (Karl)
A11 07  1    @1 FENWICK (Elisabeth)
A11 08  1    @1 FRYBACK (Dennis)
A11 09  1    @1 SCULPHER (Mark)
A11 10  1    @1 SPIEGELHALTER (David)
A11 11  1    @1 WILLAN (Andrew)
A14 01      @1 Centre for Bayesian Statistics in Health Economics, Department of Probability and Statistics, University of Sheffield @2 Sheffield @3 GBR @Z 1 aut. @Z 2 aut. @Z 3 aut. @Z 4 aut.
A14 02      @1 Department of Probability and Statistics, University of Sheffield @2 Sheffield @3 GBR @Z 1 aut.
A14 03      @1 Health Economics and Decision Science, University of Sheffield @2 Sheffield @3 GBR @Z 2 aut. @Z 3 aut. @Z 4 aut.
A14 04      @1 Health Economics Research Centre, University of Oxford @2 Oxford @3 GBR @Z 5 aut.
A14 05      @1 Centre for Health Economics, University of York @2 York @3 GBR @Z 6 aut. @Z 7 aut. @Z 9 aut.
A14 06      @1 University of Wisconsin Medical School @2 Madison, Wisconsin @3 USA @Z 8 aut.
A14 07      @1 MRC Biostatistics Unit, University of Cambridge @2 Cambridge @3 GBR @Z 10 aut.
A14 08      @1 Public Health Sciences, University of Toronto @2 Toronto, Ontario @3 CAN @Z 11 aut.
A20       @1 529-536
A21       @1 2005
A23 01      @0 ENG
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A60       @1 P
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C01 01    ENG  @0 In a recent leading article in PharmacoEconomics, Nuijten described some methods for incorporating uncertainty into health economic models and for utilising the information on uncertainty regarding the cost effectiveness of a therapy in resource allocation decision-making. His proposals are found to suffer from serious flaws in statistical and health economic reasoning. Nuijten's suggestions for incorporating uncertainty: (a) wrongly interpret the p-value as the probability that the null hypothesis is true; (b) represent this probability wrongly by truncating the input distribution; and (c) in the specific example of an antiparkinsonian drug uses a completely inappropriate p-value of 0.05 when the null hypothesis would, in reality, be emphatically disproved by the data. His suggestions regarding minimum important differences in cost effectiveness: (a) introduce areas of indifference that suggest inappropriate reliance on cost minimisation while failing to recognise that decisions should be based on expected costs versus benefits; and (b) offer no guidance on how the probabilities associated with these areas could be used in decision-making. Furthermore, Nuijten's model for Parkinson's disease is over-simplified to the point of providing a bad example of modelling practice, which may mislead the readers of PharmacoEconomics. The rationale for this paper is to ensure that readers do not apply inappropriate analyses as a result of following the proposals contained in Nuijten's paper. In addition to a detailed critique of Nuijten's proposals, we provide brief summaries of the currently accepted best practice in cost-effectiveness decision-making under uncertainty.
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C03 01  X  FRE  @0 Economie santé @5 01
C03 01  X  ENG  @0 Health economy @5 01
C03 01  X  SPA  @0 Economía salud @5 01
C03 02  X  FRE  @0 Analyse coût efficacité @5 02
C03 02  X  ENG  @0 Cost efficiency analysis @5 02
C03 02  X  SPA  @0 Análisis costo eficacia @5 02
C03 03  X  FRE  @0 Prise décision @5 03
C03 03  X  ENG  @0 Decision making @5 03
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C03 05  X  FRE  @0 Incertitude @5 05
C03 05  X  ENG  @0 Uncertainty @5 05
C03 05  X  SPA  @0 Incertidumbre @5 05
C03 06  X  FRE  @0 Parkinson maladie @5 06
C03 06  X  ENG  @0 Parkinson disease @5 06
C03 06  X  SPA  @0 Parkinson enfermedad @5 06
C03 07  X  FRE  @0 Antiparkinsonien @5 07
C03 07  X  ENG  @0 Antiparkinson agent @5 07
C03 07  X  SPA  @0 Antiparkinsoniano @5 07
C03 08  X  FRE  @0 Homme @5 08
C03 08  X  ENG  @0 Human @5 08
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C07 02  X  FRE  @0 Extrapyramidal syndrome @5 38
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C07 02  X  SPA  @0 Extrapiramidal síndrome @5 38
C07 03  X  FRE  @0 Maladie dégénérative @5 39
C07 03  X  ENG  @0 Degenerative disease @5 39
C07 03  X  SPA  @0 Enfermedad degenerativa @5 39
C07 04  X  FRE  @0 Système nerveux central pathologie @5 40
C07 04  X  ENG  @0 Central nervous system disease @5 40
C07 04  X  SPA  @0 Sistema nervosio central patología @5 40
C07 05  X  FRE  @0 Système nerveux pathologie @5 41
C07 05  X  ENG  @0 Nervous system diseases @5 41
C07 05  X  SPA  @0 Sistema nervioso patología @5 41
N21       @1 241

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Le document en format XML

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<title level="j" type="main">PharmacoEconomics : (Auckland)</title>
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<term>Antiparkinson agent</term>
<term>Cost efficiency analysis</term>
<term>Decision making</term>
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<term>Health economy</term>
<term>Human</term>
<term>Parkinson disease</term>
<term>Public health</term>
<term>Uncertainty</term>
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<div type="abstract" xml:lang="en">In a recent leading article in PharmacoEconomics, Nuijten described some methods for incorporating uncertainty into health economic models and for utilising the information on uncertainty regarding the cost effectiveness of a therapy in resource allocation decision-making. His proposals are found to suffer from serious flaws in statistical and health economic reasoning. Nuijten's suggestions for incorporating uncertainty: (a) wrongly interpret the p-value as the probability that the null hypothesis is true; (b) represent this probability wrongly by truncating the input distribution; and (c) in the specific example of an antiparkinsonian drug uses a completely inappropriate p-value of 0.05 when the null hypothesis would, in reality, be emphatically disproved by the data. His suggestions regarding minimum important differences in cost effectiveness: (a) introduce areas of indifference that suggest inappropriate reliance on cost minimisation while failing to recognise that decisions should be based on expected costs versus benefits; and (b) offer no guidance on how the probabilities associated with these areas could be used in decision-making. Furthermore, Nuijten's model for Parkinson's disease is over-simplified to the point of providing a bad example of modelling practice, which may mislead the readers of PharmacoEconomics. The rationale for this paper is to ensure that readers do not apply inappropriate analyses as a result of following the proposals contained in Nuijten's paper. In addition to a detailed critique of Nuijten's proposals, we provide brief summaries of the currently accepted best practice in cost-effectiveness decision-making under uncertainty.</div>
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