Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

Keynote webinar | Spotlight on medication adherence

LIVE: Thursday 27th June 2024, 18:00-19:30 (CEST)
Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.
ADVANCED SEARCH
Log in
Top
PharmacoEconomics
Published in: PharmacoEconomics 6/2005

01-06-2005 | Leading Article

Incorporation of uncertainty in health economic modelling studies

Authors: Professor Anthony O’Hagan, Christopher McCabe, Ron Akehurst, Alan Brennan, Andrew Briggs, Karl Claxton, Elisabeth Fenwick, Dennis Fryback, Mark Sculpher, David Spiegelhalter, Andrew Willan

Published in: PharmacoEconomics | Issue 6/2005

Login to get access

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.
Appendix
Available only for authorised users
Literature
1.
Nuijten MJC. Incorporation of statistical uncertainty in health economic modelling studies using second order Monte Carlo simulations. Pharmacoeconomics 2004; 22 (12): 759–69PubMedCrossRef
2.
Briggs A. Handling uncertainty in economic evaluation and presenting the results. In: Drummond M, McGuire A, editors. Economic evaluation in health care: merging theory with practice. Oxford: OHE/Oxford University Press, 2001: 172–214
3.
Weinstein MC, O’Brien B, Homberger J, et al. Principles of good practice in decision analytic modelling in health care evaluation: report of the ISPOR Task Force on good research practices: modelling studies. Value Health 2003; 6 (1): 9–17PubMedCrossRef
4.
Kuntz K, Weinstein M. Modelling in economic evaluation. In: Drummond M, McGuire A, editors. Economic evaluation in health care: merging theory with practice. Oxford: OHE/Oxford University Press, 2001
5.
Manning WG, Fryback DG, Weinstein MC. Reflecting uncertainty in cost effectiveness analysis. In: Gold MR, Siegal JE, Russell LB, et al., editors. Cost effectiveness in health and medicine. New York: Oxford University Press, 1996: 247–75
6.
Drummond MG, O’Brien B, Stoddart GL, Torrance GW. Methods for the economic evaluation of health care programmes. 2nd ed. Oxford: Oxford University Press, 1997: 232–64
7.
Manning WG, Fryback DG, Weinstein MC. Reflecting uncertainty in cost effectiveness analysis. In: Gold MR, Siegal JE, Russell LB, et al., editors. Cost effectiveness in health and medicine. New York: Oxford University Press, 1996: 247–75
8.
National Institute for Clinical Excellence. Guide to the methods of health technology appraisal. London: NICE, 2004 Apr
9.
Van Hout BA, Al MJ, Gordon GS, et al. Costs, effects, and CIE ratios alongside a clinical trial. Health Econ 1994; 3 (5): 30919
10.
Luce B, O’Hagan A. A primer on Bayesian statistics in health economics and outcomes research. London: MEDTAP International, 2003
11.
Claxton K, Sculpher M, Drummond M. A rational framework for decision making by the National Institute for Clinical Excellence (NICE). Lancet 2002; 360: 711–5PubMedCrossRef
12.
Akehurst RL, Anderson P, Brazier JE, et al. Decision analytic modelling in economic evaluation of health technologies. Pharmacoeconomics 2000; 17 (5): 443–4CrossRef
13.
Sculpher M, Fenwick E, Claxton K. Assessing quality in decision analytic cost effectiveness models: a suggested framework and example of application. Pharmacoeconomics 2000; 17 (5): 461–77PubMedCrossRef
14.
Briggs A. Handling uncertainty in cost effectiveness models. Pharmacoeconomics 2000; 17 (5): 479–500PubMedCrossRef
15.
McCabe C, Dixon S. Testing the validity of cost effectiveness models. Pharmacoeconomics 2000; 17 (5): 501–13PubMedCrossRef
16.
Parmigiani G. Modeling in medical decision making: a Bayesian approach. Chichester: John Wiley and Sons, 2002
17.
Stevenson MD, Oakley J, Chilcott JB. Gaussian process modelling in conjunction with individual patient simulation modelling: a case study describing the calculation of cost-effective ness ratios for the treatment of osteoporosis. Med Decis Making 2004; 24 (1): 89–100PubMedCrossRef
18.
Chilcott J, McCabe C, Tappenden P, et al. Modelling the cost effectiveness of interferon beta and glatiramer acetate in the management of multiple sclerosis. BMJ 2003; 326: 522–6PubMedCrossRef
19.
Cooper NJ, Sutton AJ, Mugford M, et al. Use of Bayesian Markov Chain Monte Carlo methods to model cost data. Med Decis Making 2003; 23: 38–53PubMedCrossRef
20.
Briggs AH, Goeree R, Blackhouse G, et al. Probabilistic analysis of cost-effectiveness models: choosing between treatment strategies for gastroesophageal reflux disease. Med Decis Making 2002; 22 (4): 290–308PubMed
21.
Spiegelhalter DJ, Abrams KR, Miles JP. Bayesian approaches to clinical trials and health-care evaluation. Chichester: John Wiley & Sons, 2003CrossRef
22.
Stinnett A, Paltiel A. Estimating CE ratios under second order uncertainty: the mean ratio versus the ratio of means. Med Decis Making 1997; 17: 483–9PubMedCrossRef
23.
Tappenden P, Chilcott JB, Eggington S, et al. Methods for expected value of information analysis in complex health economic models: developments on the health economics of beta-interferon and glatiramer acetate for multiple sclerosis. Health Technol Assess 2004; 8 (27): 1–78
24.
Doubilet P, Begg CB, Weinstein MC, et al. Probabilistic sensitivity analysis using Monte Carlo simulation: a practical approach. Med Decis Making 1985; 5 (2): 157–77PubMedCrossRef
25.
Briggs AH, Fenn P. Confidence intervals or surfaces? Uncertainty on the cost-effectiveness plane. Health Econ 1998; 7 (8): 723–40PubMedCrossRef
26.
Fenwick E, Claxton K, Sculpher M. Representing uncertainty: the role of cost-effectiveness acceptability curves. Health Econ 2001; 10: 779–89PubMedCrossRef
27.
Ades AE, Lu G, Claxton K. Expected value of sample information in medical decision modelling. Med Decis Making 2004; 24 (2): 702–28CrossRef
28.
Tarn TYH, Smith MD. Pharmacoeconomic guidelines around the world. ISPOR Connections 2004; 10 (4): 5–15
29.
Stinnett AA, Mullahy J. Net Health Benefits: a new framework for the analysis of uncertainty in cost effectiveness analysis. Med Decis Making 1998; 18 (2): S65–80CrossRef
30.
31.
32.
33.
Metadata
Title
Incorporation of uncertainty in health economic modelling studies
Authors
Professor Anthony O’Hagan
Christopher McCabe
Ron Akehurst
Alan Brennan
Andrew Briggs
Karl Claxton
Elisabeth Fenwick
Dennis Fryback
Mark Sculpher
David Spiegelhalter
Andrew Willan
Publication date
01-06-2005
Publisher
Springer International Publishing
Published in
PharmacoEconomics / Issue 6/2005
Print ISSN: 1170-7690
Electronic ISSN: 1179-2027
DOI
https://doi.org/10.2165/00019053-200523060-00001

Other articles of this Issue 6/2005

PharmacoEconomics 6/2005 Go to the issue

Review Article

Pharmacoeconomic evaluation of antidepressants

Review Article

The economics of topical immunomodulators for the treatment of atopic dermatitis

Original Research Article

Development of an economic model to assess the cost effectiveness of treatment interventions for chronic obstructive pulmonary disease

Commentary

Health utilities in Alzheimer’s disease and implications for cost-effectiveness analysis

Review Article

Bipolar disorder and health-related quality of life

Review Article

Remission from depression