Skip to main content
SpringerLink
Log in

Incorporation of Statistical Uncertainty in Health Economic Modelling Studies Using Second-Order Monte Carlo Simulations

  • Leading Article
  • Published:
PharmacoEconomics Aims and scope Submit manuscript

Abstract

Health economic modelling studies are of interest to many parties with different responsibilities and diverging interests. Therefore, it is obvious that recognising the relevance of statistical uncertainty and dealing with it appropriately are required to obtain unbiased results from health economic modelling studies, especially when those data are being used for reimbursement decisions.

In this manuscript we explore the relevance of the incorporation of statistical uncertainty in a health economic model and identify various types of statistical uncertainty. The concepts were applied to a hypothetical Markov model for a hypothetical antiparkinsonian (AP) product. The method was based on the incorporation of probability distributions in the input variables using a second-order Monte Carlo simulation and the definition of minimum relevant differences for clinical and economic input variables and outcomes.

Our paper shows that the outcomes of a health economic model might be severely biased when statistical uncertainty is not taken into account, which justifies the need for the incorporation of statistical uncertainty in a health economic model.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Table I
Table II
Fig. 2
Fig. 3
Fig. 4
Table III
Table IV

Similar content being viewed by others

References

  1. Nuijten MJC, Berto P, Berdeaux G, et al. Trends in decisionmaking process for pharmaceuticals in Western European countries: a focus on emerging hurdles for obtaining reimbursement and a price. HEPAC 2 2001; 4: 162–9

    Article  Google Scholar 

  2. Robinson R. Economic evaluation and health care: what does it mean? BMJ 1993; 307: 670–3

    Article  PubMed  CAS  Google Scholar 

  3. Adams ME, McCall NT, Gray DT, et al. Economic analysis in randomised controlled trials. Med Care 1992; 30 (3): 231–43

    Article  PubMed  CAS  Google Scholar 

  4. Drummond MF, Davies L. Economic analysis alongside clinical trials: revisiting the methodological issues. Int J Technol Assess Health Care 1991; 7 (4): 561–73

    Article  PubMed  CAS  Google Scholar 

  5. Drummond MF, Ludbrook A, Lowson K, et al. Studies in economic appraisal in health care. Oxford, Oxford University Press 1986; 2

    Google Scholar 

  6. Clemens K, Townsend R, Luscombe F, et al. Methodological and conduct principles for pharmacoeconomic research. Pharmacceconomics 1995; 8 (2): 169–74

    Article  CAS  Google Scholar 

  7. Drummond MF, Jefferson TO. Guidelines for authors and peer reviewers of economic submissions to the BMJ. BMJ 1996; 313: 275–83

    Article  PubMed  CAS  Google Scholar 

  8. Jefferson T, Demichelli V. Are guidelines for peer-reviewing economic evaluation necessary? A survey of current editorial practice. Health Econ 1995; 4: 383–8

    Article  PubMed  CAS  Google Scholar 

  9. Buxton MJ, Drummond MF, Van Hout BA, et al. Modelling in economic evaluation: an unavoidable fact of life. Health Econ 1997 May-Jun; 6 (3): 217–27

  10. Nuijten MJC. Measuring sensitivity in pharmacoeconomic studies: refining point sensitivity and range sensitivity by incorporating probability distributions. Pharmacceconomics 1999; 16 (1),33–41

    Article  CAS  Google Scholar 

  11. Nuijten MJC. Bridging decision analytic modelling with a cross-sectional approach: application to Parkinson’s disease. Pharmacceconomics 2000 Mar; 17 (3): 227–36

    Article  CAS  Google Scholar 

  12. Nuijten MJ, van Iperen P, Palmer C, et al. Cost-effectiveness analysis of entacapone in Parkinson’s disease: a Markov process analysis. Value Health 2001 Jul-Aug; 4 (4): 316–28

  13. Doubilet P, Begg CB, Weinstein MC, et al. Probabilistic sensitivity analysis using Monte Carlo simulation: a practical approach. Med Decis Making 1985; 5 (2): 157–77

    Article  PubMed  CAS  Google Scholar 

  14. Parmigiani G. Measuring uncertainty in complex decision analysis models. Stat Methods Med Res 2002 Dec; 11 (6): 513–37

    Article  PubMed  CAS  Google Scholar 

  15. Cooper NJ, Sutton AJ, Abrams KR. Decision analytical economic modelling within a Bayesian framework: application to prophylactic antibiotics use for caesarean section. Stat Methods Med Res 2002 Dec; 11 (6): 491–512

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgements

The author has provided no information on sources of funding or on conflicts of interest directly relevant to the content of this study.

Author information

Authors and Affiliations

  1. MEDTAP International Dorpsstraat, 75, Jisp, Amsterdam, 1526 LG, The Netherlands

    Mark J. C. Nuijten

Authors
  1. Mark J. C. Nuijten
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mark J. C. Nuijten.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Nuijten, M.J.C. Incorporation of Statistical Uncertainty in Health Economic Modelling Studies Using Second-Order Monte Carlo Simulations. PharmacoEconomics 22, 759–769 (2004). https://doi.org/10.2165/00019053-200422120-00001

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.2165/00019053-200422120-00001

Keywords

Search

Navigation