Evaluating high-cost technologies – no need to throw the baby out with the bathwater

References

• Kanavos PG, Nicod E, Van den Aardweg S, et al. The impact of health technology assessments: an international comparison. Euro Observor. 2010;12:1–7.
   Google Scholar
• Kanters TA, Hakkaart L, Rutten-van Molken MP, et al. Access to orphan drugs in western Europe: can more systematic policymaking really help to avoid different decisions about the same drug? Expert Rev Pharmacoecon Outcomes Res. 2015;15(4):557–559. doi: 10.1586/14737167.2015.1045882
   PubMed Web of Science ®Google Scholar
• McKie J, Richardson J. The rule of rescue. Soc Sci Med. 2003;56(12):2407–2419. doi: 10.1016/S0277-9536(02)00244-7
   PubMed Web of Science ®Google Scholar
• Nuijten M. Pricing zolgensma – the world’s most expensive drug. J Mark Access Health Policy. 2022;10(1):2022353. doi: 10.1080/20016689.2021.2022353
   PubMedGoogle Scholar
• Heo YA. Etranacogene Dezaparvovec: first approval. Drugs. 2023;83(4):347–352. doi: 10.1007/s40265-023-01845-0
   PubMed Web of Science ®Google Scholar
• Aartsma-Rus A, Dooms M, Le Cam Y. Orphan medicine incentives: how to address the unmet needs of rare disease patients by optimizing the European orphan medicinal product landscape guiding principles and Policy proposals by the European Expert group for orphan drug incentives (OD Expert group). Front Pharmacol. 2021;12:744532. doi: 10.3389/fphar.2021.744532
   PubMed Web of Science ®Google Scholar
• Drummond M, Banta D. Health technology assessment in the United Kingdom. Int J Technol Assess Health Care. 2009;25(S1):178–181. doi: 10.1017/S0266462309090618
   PubMedGoogle Scholar
• HTAi. What is health technology assessment (HTA)? 2023. https://htai.org/about/
   Google Scholar
• Drummond MF, Wilson DA, Kanavos P, et al. Assessing the economic challenges posed by orphan drugs. Int J Technol Assess Health Care. 2007;23(1):36–42. doi: 10.1017/S0266462307051550
   PubMed Web of Science ®Google Scholar
• McNamee P, Murray E, Kelly MP, et al. Designing and undertaking a health economics study of digital health interventions. Am J Prev Med. 2016;51(5):852–860. doi: 10.1016/j.amepre.2016.05.007
   PubMed Web of Science ®Google Scholar
• Jankovic D, Bojke L, Marshall D, et al. Systematic review and critique of methods for economic evaluation of digital mental health interventions. Appl Health Econ Health Policy. 2021;19(1):17–27. doi: 10.1007/s40258-020-00607-3
   PubMed Web of Science ®Google Scholar
• Gomes M, Murray E, Raftery J. Economic evaluation of digital health interventions: methodological issues and recommendations for practice. PharmacoEconomics. 2022;40(4):367–378. doi: 10.1007/s40273-022-01130-0
   PubMed Web of Science ®Google Scholar
• Hernan MA, Robins JM. Using big data to emulate a target trial when a randomized trial is not available: table 1. Am J Epidemiol. 2016;183(8):758–764. doi: 10.1093/aje/kwv254
   PubMed Web of Science ®Google Scholar
• NICE. NICE strategy 2021 to 2026 - dynamic, collaborative. Excellent. 2021. https://www.nice.org.uk/Media/Default/Get-involved/Meetings-In-Public/Public-board-meetings/Mar-24-pbm-NICE-strategy-2021-2026.pdf
   Google Scholar
• NICE. NICE real-world evidence framework (ECD9). 2022
   Google Scholar
• Kang J, Cairns J. “Don’t think twice, it’s all right”: using additional data to reduce uncertainty regarding oncologic drugs provided through managed access agreements in England. Pharmacoecon Open. 2023;7(1):77–91. doi: 10.1007/s41669-022-00369-9
   PubMed Web of Science ®Google Scholar
• NICE. Managed access -. https://www.nice.org.uk/about/what-we-do/our-programmes/managed-access2023
   Google Scholar
• (FDA). TFaDA. Framework for FDA’s real-world evidence program. 2018. https://www.fda.gov/media/120060/download
   Google Scholar
• Group OITRW. The evolving role of real-world evidence in Australia. 2020. https://www.medicinesaustralia.com.au/wp-content/uploads/sites/65/2020/11/OIT-RWE-Report-Oct-2020-FINAL-MA-VERSION.pdf
   Google Scholar
• Grigore B, Ciani O, Dams F, et al. Surrogate endpoints in health technology assessment: an international review of methodological guidelines. PharmacoEconomics. 2020;38(10):1055–1070. doi: 10.1007/s40273-020-00935-1
   PubMed Web of Science ®Google Scholar
• Ciani O, Grigore B, Taylor RS. Development of a framework and decision tool for the evaluation of health technologies based on surrogate endpoint evidence. Health Econ. 2022;Suppl 31(S1):44–72. doi: 10.1002/hec.4524
   Google Scholar
• Wilson ECF. Methodological note: reporting deterministic versus probabilistic results of Markov, partitioned survival and other non-linear models. Appl Health Econ Health Policy. 2021;19(6):789–795. doi: 10.1007/s40258-021-00664-2
   PubMed Web of Science ®Google Scholar
• Wilson EC. A practical guide to value of information analysis. PharmacoEconomics. 2015;33(2):105–121. doi: 10.1007/s40273-014-0219-x
   PubMed Web of Science ®Google Scholar
• Jackson CH, Baio G, Heath A, et al. Value of information analysis in models to inform health Policy. Annu Rev Stat Appl. 2022;9(1):95–118. doi: 10.1146/annurev-statistics-040120-010730
   PubMedGoogle Scholar
• Rothery C, Strong M, Koffijberg HE, et al. Value of information analytical methods: report 2 of the ISPOR value of information analysis emerging good practices task force. Value Health. 2020;23(3):277–286. doi: 10.1016/j.jval.2020.01.004
   PubMed Web of Science ®Google Scholar
• Fenwick E, Steuten L, Knies S, et al. Value of information analysis for research decisions—an Introduction: report 1 of the ISPOR value of information analysis emerging good practices task force. Value In Health. 2020;23(2):139–150. doi: 10.1016/j.jval.2020.01.001
   PubMed Web of Science ®Google Scholar
• Sagoo GS, Mohammed S, Barton G, et al. Cost effectiveness of using array-CGH for diagnosing learning disability. Appl Health Econ Health Policy. 2015;13(4):421–432. doi: 10.1007/s40258-015-0172-7
   PubMed Web of Science ®Google Scholar
• Mauskopf JA, Sullivan SD, Annemans L, et al. Principles of good practice for budget impact analysis: report of the ISPOR task force on good research Practices—budget impact analysis. Value In Health. 2007;10(5):336–347. doi: 10.1111/j.1524-4733.2007.00187.x
   PubMed Web of Science ®Google Scholar
• NICE. Atidarsagene autotemcel for treating metachromatic leukodystrophy - highly specialised technologies guidance (HST18). 2022
   Google Scholar
• Kirwin E, Round J, Bond K, et al. A conceptual framework for life-cycle health technology assessment. Value Health. 2022;25(7):1116–1123. doi: 10.1016/j.jval.2021.11.1373
   PubMed Web of Science ®Google Scholar
• NICE. Early value assessment interim statement [PMG39]. 2022. https://www.nice.org.uk/process/pmg39/chapter/introduction
   Google Scholar
• Bryan S, Mitton C, Donaldson C. Breaking the addiction to technology adoption. Health Econ. 2014;23(4):379–383. doi: 10.1002/hec.3034
   PubMed Web of Science ®Google Scholar
• Aggarwal A, Fojo T, Chamberlain C, et al. Do patient access schemes for high-cost cancer drugs deliver value to society?—lessons from the NHS cancer drugs fund. Ann Oncol. 2017;28(8):1738–1750. doi: 10.1093/annonc/mdx110
   PubMed Web of Science ®Google Scholar
• Abel L, Shinkins B, Smith A, et al. Early economic evaluation of diagnostic technologies: experiences of the NIHR diagnostic evidence co-operatives. Med Decis Mak. 2019;39(7):857–866. doi: 10.1177/0272989X19866415
   PubMed Web of Science ®Google Scholar
• Hofmann B. Biases and imperatives in handling medical technology. Health Policy Technol. 2019;8(4):377–385. doi: 10.1016/j.hlpt.2019.10.005
   Web of Science ®Google Scholar