How Useful Are Early Economic Models?; Comment on “Problems and Promises of Health Technologies: The Role of Early Health Economic Modelling”

Document Type : Commentary


Centre for Health Economics, University of York, York, UK


Early economic modelling has long been recommended to aid research and development (R&D) decisions in medical innovation, although they are less frequently published and critically appraised. A review of 30 innovations by Grutters et al provides an opportunity to evaluate how early models are used in practice. The evidence of early models can be used to inform two types of decision: to continue development (“stop or go”) or to alter future R&D activities. I argue that early models have limited use in stop or go decisions, as less resource and data undermine the reliability of the models’ indicative estimates of cost-effectiveness. Whilst they are far more useful for informing future R&D directions, the best techniques available from statistical decision science, such as value of information analysis, are not regularly used. It is highly recommended that early models adopt these methods to best deal with uncertainty, quantify the potential value of further research, identify areas of study with the greatest potential benefit and generate recommendations on study design and sample size.


Main Subjects

  1. Adams CP, Brantner V V. Estimating the cost of new drug development: is it really $802 million? Health Aff (Millwood). 2006;25(2):420-428. doi:10.1377/hlthaff.25.2.420
  2. Xu K, Soucat A, Kutzin J, et al. Public Spending on Health: A Closer Look at Global Trends. Geneva: World Health Organization; 2018.
  3. Sculpher M, Drummond M, Buxton M. The Iterative Use of Economic Evaluation as Part of the Process of Health Technology Assessment. J Health Serv Res Policy. 1997;2(1):26-30. doi:10.1177/135581969700200107
  4. Brennan A, Akehurst R. Modelling in health economic evaluation. Pharmacoeconomics. 2000;17(5):445-459. doi:10.2165/00019053-200017050-00004
  5. Grutters J, Govers T, Nijboer J, Tummers M, van der Wilt GJ, Rovers M. Problems and promises of health technologies: the role of early health economic modeling. Int J Health Policy Manag. 2019;10(8):575-582. doi:10.15171/ijhpm.2019.36.
  6. Levin L. Early evaluation of new health technologies: The case for premarket studies that harmonize regulatory and coverage perspectives. Int J Technol Assess Health Care. 2015;31(4):207-209. doi:10.1017/S0266462315000422
  7. Markiewicz K, van Til JA, Steuten LMG, IJzerman MJ. Commercial viability of medical devices using Headroom and return on investment calculation. Technol Forecast Soc Change. 2016;112:338-346. doi:10.1016/j.techfore.2016.07.041
  8. Girling A, Lilford R, Cole A, Young T. Headroom approach to device development: Current and future directions. Int J Technol Assess Health Care. 2016;31(5):331-338. doi:10.1017/S0266462315000501
  9. Mathes T, Jacobs E, Morfeld J, Pieper D. Methods of international health technology assessment agencies for economic evaluations- a comparative analysis. BMC Health Serv Res. 2013;13(371):1-10. doi:10.1186/1472-6963-13-371
  10. Drummond M, Sorenson C. Nasty or nice? A perspective on the use of health technology assessment in the United Kingdom. Value Health. 2009;12:S8-S13. doi:10.1111/j.1524-4733.2009.00552.x
  11. Karnon J. Alternative decision modelling techniques for the evaluation of health care technologies: Markov processes versus discrete event simulation. Health Econ. 2003;12(10):837-848. doi:10.1002/hec.770
  12. Annemans L, Genesté B, Jolain B. Early modelling for assessing health and economic outcomes of drug therapy. Value Health. 2000;3(6):427-434. doi:10.1046/j.1524-4733.2000.36007.x
  13. IJzerman MJ, Steuten LMG. Early Assessment of Medical Technologies to Inform Product Development and Market Access: A Review of Methods and Applications. Appl Health Econ Health Policy. 2011;9(5):331-347. doi:10.2165/11593380-000000000-00000
  14. Vallejo-Torres L, Steuten LMG, Buxton MJ, Girling AJ, Lilford RJ, Young T. Integrating health economics modeling in the product development cycle of medical devices: A Bayesian approach. Int J Technol Assess Health Care. 2008;24(4):459-464. doi:10.1017/S0266462308080604
  15. Claxton K, Sculpher M, McCabe C, et al. Probabilistic sensitivity analysis for NICE technology assessment: not an optional extra. Health Econ. 2005;14(4):339-347. doi:10.1002/hec.985
  16. Wilson ECF. A Practical guide to value of information analysis. Pharmacoeconomics. 2015;33(2):105-121. doi:10.1007/s40273-014-0219-x
  17. Soares M, Sculpher M, Claxton K. Health opportunity costs: assessing the implications of uncertainty using elicitation methods with experts. York: Universities of Sheffield and York; 2018.
  18. Favato G, Baio G, Capone A, Marcellusi A, Saverio Mennini F. A novel method to value real options in health care: The case of a multicohort human papillomavirus vaccination strategy. Clin Ther. 2013;35(7):904-914. doi:10.1016/j.clinthera.2013.05.003
  19. Abel L, Shinkins B, Smith A, et al. Early economic evaluation of diagnostic technologies: experiences of the NIHR diagnostic evidence co-operatives. Med Decis Making. 2019;39(7):857-866. doi:10.1177/0272989X19866415
Volume 9, Issue 5
May 2020
Pages 215-217
  • Receive Date: 04 October 2019
  • Revise Date: 11 November 2019
  • Accept Date: 12 November 2019
  • First Publish Date: 01 May 2020