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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

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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