International Journal of Health Policy and Management

International Journal of Health Policy and Management

Expanding the Role of Early Health Economic Modelling in Evaluation of Health Technologies; Comment on “Problems and Promises of Health Technologies: The Role of Early Health Economic Modeling”

Document Type : Commentary

Authors
Carlo Federici 1, 2
Aleksandra Torbica 1
1 Centre for Research on Health and Social Care Management (CERGAS), SDA Bocconi School of Management, Bocconi University, Milan, Italy
2 University of Warwick, School of Engineering, Coventry, UK
10.15171/ijhpm.2020.18
Abstract
In this commentary, we discuss early stage assessments of innovative medical technologies both in terms of methods applied as well as their use in healthcare decision-making. We argue that cost-effectiveness alone may be too reductive if taken as the only decision rule, and it would benefit from being used within a broader evaluation framework. We discuss innovative methods which may contribute to better estimate the potential costs and consequences of a technology in the absence of solid clinical data, as frequently the case in early assessments. Finally, we comment on the potential synergies which may take place should early economic models be used not only by technology developers alone but as a negotiating base during early dialogues with health technology assessment (HTA) bodies.
Keywords
Early Economic Modelling
Health Technology Assessment
Cost-Effectiveness
Early Dialogue
  1. 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
  2. Mauskopf J, Schulman K, Bell L, Glick H. A strategy for collecting pharmacoeconomic data during phase II/III clinical trials. Pharmacoeconomics. 1996;9(3):264-277. doi:10.2165/00019053-199609030-00007
  3. Grabowski H. The effect of pharmacoeconomics on company research and development decisions. Pharmacoeconomics. 1997;11(5):389-397. doi:10.2165/00019053-199711050-00002
  4. Terrés CR. Pharmacoeconomic analysis in new drug development: a pragmatic approach to efficiency studies. Clin Res Regul Aff. 1998;15(3-4):209-223. doi:10.3109/10601339809109196
  5. Markiewicz K, van Til JA, MJ IJ. Medical devices early assessment methods: systematic literature review. Int J Technol Assess Health Care. 2014;30(2):137-146. doi:10.1017/s0266462314000026
  6. Hartz S, John J. Contribution of economic evaluation to decision making in early phases of product development: a methodological and empirical review. Int J Technol Assess Health Care. 2008;24(4):465-472. doi:10.1017/s0266462308080616
  7. Miller P. Role of pharmacoeconomic analysis in R&D decision making: when, where, how? Pharmacoeconomics. 2005;23(1):1-12. doi:10.2165/00019053-200523010-00001
  8. IJzerman MJ, Koffijberg H, Fenwick E, Krahn M. Emerging use of early health technology assessment in medical product development: a scoping review of the literature. Pharmacoeconomics. 2017;35(7):727-740. doi:10.1007/s40273-017-0509-1
  9. Grutters JPC, Govers T, Nijboer J, Tummers M, van der Wilt GJ, Rovers MM. Problems and promises of health technologies: the role of early health economic modeling. Int J Health Policy Manag. 2019;8(10):575–582. doi:10.15171/ijhpm.2019.36
  10. Polisena J, Castaldo R, Ciani O, et al. Health technology assessment methods guidelines for medical devices: how can we address the gaps? the International Federation of Medical and Biological Engineering perspective. Int J Technol Assess Health Care. 2018;34(3):276-289. doi:10.1017/s0266462318000314
  11. Fasterholdt I, Krahn M, Kidholm K, Yderstraede KB, Pedersen KM. Review of early assessment models of innovative medical technologies. Health Policy. 2017;121(8):870-879. doi:10.1016/j.healthpol.2017.06.006
  12. Retèl VP, Joore MA, Linn SC, Rutgers EJ, van Harten WH. Scenario drafting to anticipate future developments in technology assessment. BMC Res Notes. 2012;5:442. doi:10.1186/1756-0500-5-442
  13. Cosh E, Girling A, Lilford R, McAteer H, Young T. Investing in new medical technologies: a decision framework. J Commer Biotechnol. 2007;13(4):263-271.
  14. Åstebro T, Elhedhli S. The effectiveness of simple decision heuristics: forecasting commercial success for early-stage ventures. Manage Sci. 2006;52(3):395-409. doi:10.1287/mnsc.1050.0468
  15. Holmes EA, Hughes DA, Morrison VL. Predicting adherence to medications using health psychology theories: a systematic review of 20 years of empirical research. Value Health. 2014;17(8):863-876. doi:10.1016/j.jval.2014.08.2671
  16. McGrady ME, Prosser LA, Thompson AN, Pai ALH. Application of a discrete choice experiment to assess adherence-related motivation among adolescents and young adults with cancer. J Pediatr Psychol. 2018;43(2):172-184. doi:10.1093/jpepsy/jsx104
  17. Bhattacharya P, Altai Z, Qasim M, Viceconti M. A multiscale model to predict current absolute risk of femoral fracture in a postmenopausal population. Biomech Model Mechanobiol. 2019;18(2):301-318. doi:10.1007/s10237-018-1081-0
  18. Viceconti M, Henney A, Morley-Fletcher E. In silico clinical trials: how computer simulation will transform the biomedical industry. Int J Clin Trials. 2016;3(2):37-46. doi:10.18203/2349-3259.ijct20161408
  19. Rouse R, Kruhlak N, Weaver J, Burkhart K, Patel V, Strauss DG. Translating new science into the drug review process: the US FDA's Division of Applied Regulatory Science. Ther Innov Regul Sci. 2018;52(2):244-255. doi:10.1177/2168479017720249
  20. Heath A, Manolopoulou I, Baio G. A review of methods for analysis of the expected value of information. Med Decis Making. 2017;37(7):747-758. doi:10.1177/0272989x17697692
International Journal of Health Policy and Management
Volume 10, Issue 2
February 2021
Pages 102-105

  • Received Date 10 November 2019
  • Revised Date 28 January 2020
  • Accepted Date 01 February 2020
  • First Published Date 01 February 2021
  • Published Date 01 February 2021