Hostname: page-component-78c5997874-8bhkd Total loading time: 0 Render date: 2024-11-04T21:02:59.764Z Has data issue: false hasContentIssue false

A different animal? Identifying the features of health technology assessment for developers of medical technologies

Published online by Cambridge University Press:  24 June 2020

Janet Bouttell
Affiliation:
Health Economics and Health Technology Assessment, University of Glasgow, 1 Lilybank Gardens, GlasgowG12 8RZ, UK
Andrew Briggs
Affiliation:
Department of Health Services Research & Policy, London School of Hygiene and Tropical Medicine, 15–17 Tavistock Place, LondonWC1H 9SH, UK
Neil Hawkins
Affiliation:
Health Economics and Health Technology Assessment, University of Glasgow, 1 Lilybank Gardens, GlasgowG12 8RZ, UK

Abstract

Health technology assessment (HTA) conducted to inform developers of health technologies (development-focused HTA, DF-HTA) has a number of distinct features when compared to HTA conducted to inform usage decisions (use-focused HTA). To conduct effective DF-HTA, it is important that analysts are aware of its distinct features as analyses are often not published. We set out a framework of ten features, drawn from the literature and our own experience: a target audience of developers and investors; an underlying user objective to maximize return on investment; a broad range of decisions to inform; wide decision space; reduced evidence available; earlier timing of analysis; fluid business model; constrained resources for analysis; a positive stance of analysis; and a “consumer”-specific burden of proof. This paper presents a framework of ten features of DF-HTA intended to initiate debate as well as provide an introduction for analysts unfamiliar with the field.

Type
Article Commentary
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Grutters, JP, 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;8:575.CrossRefGoogle ScholarPubMed
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;2:2630.CrossRefGoogle ScholarPubMed
Annemans, L, Genesté, B, Jolain, B. Early modelling for assessing health and economic outcomes of drug therapy. Value Health. 2000;3:427–34.CrossRefGoogle ScholarPubMed
Cosh, E, Girling, A, Lilford, R, McAteer, H, Young, T. Investing in new medical technologies: A decision framework. J Commer Biotechnol. 2007;13:263–71.CrossRefGoogle Scholar
Vallejo-Torres, L, Steuten, LM, 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;24:459–64.CrossRefGoogle ScholarPubMed
Girling, A, Young, T, Brown, C, Lilford, R. Early-stage valuation of medical devices: The role of developmental uncertainty. Value Health. 2010;13:585–91.Google ScholarPubMed
Chapman, AM. The use of early economic evaluation to inform medical device decisions: an evaluation of the Headroom method [dissertation]. Birmingham: University of Birmingham; 2013.Google Scholar
McAteer, H, Cosh, E, Freeman, G, Pandit, A, Wood, P, Lilford, R. Cost-effectiveness analysis at the development phase of a potential health technology: Examples based on tissue engineering of bladder and urethra. J Tissue Eng Regen Med. 2007;1(5):343–49.CrossRefGoogle ScholarPubMed
Craven, MP, Allsop, MJ, Morgan, SP, Martin, JL. Engaging with economic evaluation methods: Insights from small and medium enterprises in the UK medical devices industry after training workshops. Health Res Policy Syst. 2012;10:29.CrossRefGoogle ScholarPubMed
Kolominsky-Rabas, PL, Djanatliev, A, Wahlster, P, Gantner-Bär, M, Hofmann, B, German, R et al. Technology foresight for medical device development through hybrid simulation: The ProHTA project. Technol Forecast Soc Change. 2015;97:105–14.CrossRefGoogle Scholar
Steuten, LM. Multi-dimensional impact of the public–private center for translational molecular medicine (CTMM) in the Netherlands: Understanding new 21st century institutional designs to support innovation-in-society. OMICS. 2016;20:265–73.CrossRefGoogle ScholarPubMed
Ijzerman, MJ, Steuten, LM. Early assessment of medical technologies to inform product development and market access. Appl Health Econ Health Policy. 2011;9:331–47.CrossRefGoogle ScholarPubMed
Markiewicz, K, van Til, JA, IJzerman, MJ. Medical devices early assessment methods: Systematic literature review. Int J Technol Assess Health Care. 2014;30:137–46.CrossRefGoogle ScholarPubMed
de Graaf, G, Postmus, D, Westerink, J, Buskens, E. The early economic evaluation of novel biomarkers to accelerate their translation into clinical applications. Cost Eff Resour Alloc. 2018;16:23.CrossRefGoogle ScholarPubMed
Pietzsch, JB, Paté-Cornell, ME. Early technology assessment of new medical devices. Int J Technol Assess Health Care. 2008;24:3644.CrossRefGoogle ScholarPubMed
Claxton, K, Martin, S, Soares, M, Rice, N, Spackman, E, Hinde, S et al. Methods for the estimation of the national institute for health and care excellence cost-effectiveness threshold. Health Technol Assess (Winch, Eng). 2015;19:1.CrossRefGoogle ScholarPubMed
Hjelmgren, J, Ghatnekar, O, Reimer, J, Grabowski, M, Lindvall, O, Persson, U et al. Estimating the value of novel interventions for Parkinson's disease: An early decision-making model with application to dopamine cell replacement. Parkinsonism Relat Disord. 2006;12:443–52.CrossRefGoogle ScholarPubMed
van Nimwegen, KJ, Lilford, RJ, van der Wilt, GJ, Grutters, JP. Headroom beyond the quality-adjusted life-year: The case of complex pediatric neurology. Int J Technol Assess Health Care. 2017;33:510.CrossRefGoogle ScholarPubMed
Vilsbøll, AW, Mouritsen, JM, Jensen, LP, Bødker, N, Holst, AW, Pennisi, CP et al. Cell-based therapy for the treatment of female stress urinary incontinence: An early cost–effectiveness analysis. Regen Med. 2018;13:321–30.CrossRefGoogle ScholarPubMed
Latimer, N, Dixon, S, McDermott, C, McCarthy, A, Tindale, W, Heron, N et al. Modelling the cost effectiveness of a potential new neck collar for patients with motor neurone disease [Internet]. Sheffield: University of Sheffield; 2011 [cited 2020 April 17]. Available from: http://eprints.whiterose.ac.uk/43189/1/HEDS-DP_11-10.pdf.Google Scholar
Vallejo-Torres, L, Steuten, L, Parkinson, B, Girling, AJ, Buxton, MJ. Integrating health economics into the product development cycle: A case study of absorbable pins for treating hallux valgus. Med Decis Making. 2011;31:596610.CrossRefGoogle ScholarPubMed
Girling, A, Lilford, R, Cole, A, Young, T. Headroom approach to device development: Current and future directions. Int J Technol Assess Health Care. 2015;31:331–38.CrossRefGoogle ScholarPubMed
Buisman, LR, Rutten-van Mölken, MP, Postmus, D, Luime, JJ, Uyl-de Groot, CA, Redekop, WK. The early bird catches the worm: Early cost-effectiveness analysis of new medical tests. Int J Technol Assess Health Care. 2016;32:4653.CrossRefGoogle ScholarPubMed
gov.uk [Internet]. Innovate UK About Us; 2020 [cited 2020 April 17]. Available from: https://www.gov.uk/government/organisations/innovate-uk/about.Google Scholar
nice.org.uk [Internet]. Guide to the methods of technology appraisal. Guidance and guidelines. 2013 [cited 2020 April 17]. Available from: https://www.nice.org.uk/process/pmg9/chapter/the-reference-case.Google Scholar
Markiewicz, K, Van Til, J, Ijzerman, M. Early assessment of medical devices in development for company decision making: An exploration of best practices. J Commer Biotechnol. 2017;23:1531.CrossRefGoogle Scholar
Rogowski, W, John, J, Ijzerman, M. Translational health economics. In: Scheffler, RM, editor. World scientific handbook of global health economics and public policy: Volume 3: Health system characteristics and performance. Singapore: World Scientific; 2016. p. 405–40.Google Scholar
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;24:465–72.CrossRefGoogle ScholarPubMed
Abel, L, Shinkins, B, Smith, A, Sutton, AJ, Sagoo, GS, Uchegbu, I et al. Early economic evaluation of diagnostic technologies: Experiences of the NIHR diagnostic evidence co-operatives. Med Decis Making. 2019;39:857–66.CrossRefGoogle ScholarPubMed
Davey, SM, Brennan, M, Meenan, BJ, McAdam, R, Girling, A, Chapman, A et al. . A framework to manage the early value proposition of emerging healthcare technologies. Ir J Manag 2011;31:59.Google Scholar
Kluytmans, A, Tummers, M, van der Wilt, GJ, Grutters, J. Early assessment of proof-of-problem to guide health innovation. Value Health. 2019;22:601–06.CrossRefGoogle ScholarPubMed
Hummel, JM, Van Rossum, W, Verkerke, GJ, Rakhorst, G. The effects of team expert choice on group decision-making in collaborative new product development: A pilot study. J Multicriter Decis Anal. 2000;9:90.3.0.CO;2-2>CrossRefGoogle Scholar
Yock, PG, Zenios, S, Makower, J, Brinton, TJ, Kumar, UN, Watkins, FJ et al. Biodesign: The process of innovating medical technologies. Cambridge: Cambridge University Press; 2015.CrossRefGoogle Scholar
Brandes, A, Sinner, MF, Kääb, S, Rogowski, WH. Early decision-analytic modeling—a case study on vascular closure devices. BMC Health Serv Res. 2015;15:486.Google ScholarPubMed
Culyer, AJ. The dictionary of health economics. 3rd ed. Cheltenham: Edward Elgar Publishing; 2014.Google Scholar
Hummel, JM, Boomkamp, IS, Steuten, LM, Verkerke, BG, Ijzerman, MJ. Predicting the health economic performance of new non-fusion surgery in adolescent idiopathic scoliosis. J Orthop Res. 2012;30:1453–58.CrossRefGoogle ScholarPubMed
Dong, H, Buxton, M. Early assessment of the likely cost-effectiveness of a new technology: A Markov model with probabilistic sensitivity analysis of computer-assisted total knee replacement. Int J Technol Assess Health Care. 2006;22:191202.CrossRefGoogle ScholarPubMed