Skip to main content

Health Technology Assessment and Appraisal of Therapies for Rare Diseases

  • Chapter
  • First Online:
Rare Diseases Epidemiology: Update and Overview

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 1031))

Abstract

Innovative rare disease therapies and health technology assessment (HTA) share a lot of similarities. Both represent cases of interaction of epidemiology and health economics. Both are relatively new topics in public health practice. And both pose a lot of challenges to rare disease stakeholders who are currently looking for tools to support the timely access to innovative treatments while putting budget spending in order. This is why optimisation of assessment and appraisal of new rare disease therapies is a fundamental issue in rare disease health policy. Rare disease patients and caregivers expect prolonged life expectancy and improved quality of life and they perceive innovative health technologies as a rightful way to achieve these objectives.

Multi-criteria decision analysis (MCDA) provides a structured, transparent approach to identify preferred alternatives by means of combined calculation of relative importance of different criteria and performance of the alternatives on these criteria. The labyrinth of competing interests and numerous stakeholders involved is why innovative rare disease health technologies make an excellent case study of the integration between HTA and MCDA. This kind of formalisation of decision-making is perceived as fair and legitimate, leading to a balance and agreement. MCDA provides a stage for a debate of policy priorities, health system specifics and societal attitudes, while also addressing the impact of rarity on all criteria and considerations.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

References

  1. Angelis A, Kanavos P (2016) Value-based assessment of new medical technologies: towards a robust methodological framework for the application of multiple criteria decision analysis in the context of health technology assessment. Pharmacoeconomics 34(5):435–446

    Article  PubMed  PubMed Central  Google Scholar 

  2. Baltussen R, Niessen L (2006) Priority setting of health interventions: the need for multi-criteria decision analysis. Cost Eff Resour Alloc 4:14. https://doi.org/10.1186/1478-7547-4-14

    Article  PubMed  PubMed Central  Google Scholar 

  3. Denis A, Mergaert L, Fostier C, Cleemput I, Simoens S (2010) Budget impact analysis of orphan drugs in Belgium: estimates from 2008 to 2013. J Med Econ 13(2):295–301

    Article  PubMed  Google Scholar 

  4. Eichler HG, Kong SX, Gerth WC, Mavros P, Jönsson B (2004) Use of cost-effectiveness analysis in health-care resource allocation decision-making: how are cost-effectiveness thresholds expected to emerge? Value Health 7:518–528. https://doi.org/10.1111/j.1524-4733.2004.75003.x

    Article  PubMed  Google Scholar 

  5. EUnetHTA (2016) What is health technology assessment (HTA). http://www.eunethta.eu/about-us/faq#t287n73. Accessed 13 Nov 2016

  6. Goetghebeur MM, Wagner M, Khoury H, Levitt RJ, Erickson LJ, Rindress D (2012) Bridging health technology assessment (HTA) and efficient health care decision making with multicriteria decision analysis (MCDA): applying the EVIDEM framework to medicines appraisal. Med Decis Mak 32(2):376–388. https://doi.org/10.1177/0272989X11416870

    Article  Google Scholar 

  7. Goetghebeur MM, Wagner M, Khoury H, Rindress D, Grégoire JP, Deal C (2010) Combining multicriteria decision analysis, ethics and health technology assessment: applying the EVIDEM decision-making framework to growth hormone for turner syndrome patients. Cost Eff Resour Alloc 8:4. https://doi.org/10.1186/1478-7547-8-4

    Article  PubMed  PubMed Central  Google Scholar 

  8. Iskrov G, Dermendzhiev S, Miteva-Katrandzhieva T, Stefanov R, Health (2016) Economic data in reimbursement of new medical technologies: importance of the socio-economic burden as a decision-making criterion. Front Pharmacol 7:252. https://doi.org/10.3389/fphar.2016.00252

    Article  PubMed  PubMed Central  Google Scholar 

  9. Iskrov G, Kuncheva R, Stefanov R (2016) Incorporation of multi-criteria decision analysis into health technology assessment: experiences and challenges from Bulgaria. In: Jakovljevic M (ed) Health economics and policy challenges in global emerging markets. Nova Science Publishers, New York, pp 41–58

    Google Scholar 

  10. Iskrov G, Miteva-Katrandzhieva T, Stefanov R (2016) Multi-criteria decision analysis for assessment and appraisal of orphan drugs. Front Public Health 4:214

    Article  PubMed  PubMed Central  Google Scholar 

  11. Iskrov G, Stefanov R (2016) Criteria for drug reimbursement decision-making: an emerging public health challenge in Bulgaria. Balkan Med J 33(1):27–35. https://doi.org/10.5152/balkanmedj.2015.15185

    Article  PubMed  PubMed Central  Google Scholar 

  12. Iskrov G, Stefanov R (2014) Post-marketing access to orphan drugs: a critical analysis of health technology assessment and reimbursement decision-making considerations. Orphan drugs. Res Rev 4:1–9. https://doi.org/10.2147/ODRR.S43409

    Google Scholar 

  13. Kolasa K, Zwolinski KM, Kalo Z, Hermanowski T (2016) Potential impact of the implementation of multiple-criteria decision analysis (MCDA) on the Polish pricing and reimbursement process of orphan drugs. Orphanet J Rare Dis 11:23. https://doi.org/10.1186/s13023-016-0388-0

    Article  PubMed  PubMed Central  Google Scholar 

  14. Leider JP, Resnick B, Kass N, Sellers K, Young J, Bernet P, Jarris P (2014) Budget- and priority-setting criteria at state health agencies in times of austerity: a mixed-methods study. Am J Public Health 104(6):1092–1099. https://doi.org/10.2105/AJPH.2013.301732

    Article  PubMed  PubMed Central  Google Scholar 

  15. Logviss K, Krievins D, Purvina S (2016) Impact of orphan drugs on Latvian budget. Orphanet J Rare Dis 11(1):59. https://doi.org/10.1186/s13023-016-0434-y

    Article  PubMed  PubMed Central  Google Scholar 

  16. Mauskopf J, Chirila C, Birt J, Boye KS, Bowman L (2013) Drug reimbursement recommendations by the National Institute for health and clinical excellence: have they impacted the National Health Service budget? Health Policy 110(1):49–59

    Article  PubMed  Google Scholar 

  17. McCabe C, Claxton K, Culyer AJ (2008) The NICE cost-effectiveness threshold. Pharmacoeconomics 26(9):733–744

    Article  PubMed  Google Scholar 

  18. Nicod E, Kanavos P (2012) Commonalities and differences in HTA outcomes: a comparative analysis of five countries and implications for coverage decisions. Health Policy 108(2–3):167–177. https://doi.org/10.1016/j.healthpol.2012.09.012

    Article  PubMed  Google Scholar 

  19. Nicod E, Kanavos P (2016) Scientific and social value judgments for orphan drugs in health technology assessment. Int J Technol Assess Health Care 14:1–15

    Google Scholar 

  20. Nicod E. (2016). Why do health technology assessment coverage recommendations for the same drugs differ across settings? Applying a mixed methods framework to systematically compare orphan drug decisions in four European countries. Eur J Health Econ. Aug 18. [Epub ahead of print]

    Google Scholar 

  21. Niezen MG, de Bont A, Busschbach JJ, Cohen JP, Stolk EA (2009) Finding legitimacy for the role of budget impact in drug reimbursement decisions. Int J Technol Assess Health Care 25(01):49–55

    Article  PubMed  Google Scholar 

  22. Rocchi A, Menon D, Verma S, Miller E (2008) The role of economic evidence in Canadian oncology reimbursement decision-making: to lambda and beyond. Value Health 11(4):771–783. https://doi.org/10.1111/j.1524-4733.2007.00298.x

    Article  PubMed  Google Scholar 

  23. Rosenberg-Yunger ZR, Daar AS, Thorsteinsdóttir H, Martin DK (2011) Priority setting for orphan drugs: an international comparison. Health Policy 100(1):25–34. https://doi.org/10.1016/j.healthpol.2010.09.008

    Article  PubMed  Google Scholar 

  24. Rosenberg-Yunger ZR, Thorsteinsdóttir H, Daar AS, Martin DK (2012) Stakeholder involvement in expensive drug recommendation decisions: an international perspective. Health Policy 105(2–3):226–235. https://doi.org/10.1016/j.healthpol.2011.12.002

    Article  PubMed  Google Scholar 

  25. Schnipper LE, Davidson NE, Wollins DS, Tyne C, Blayney DW, Blum D, Dicker AP, Ganz PA, Hoverman JR, Langdon R, Lyman GH, Meropol NJ, Mulvey T, Newcomer L, Peppercorn J, Polite B, Raghavan D, Rossi G, Saltz L, Schrag D, Smith TJ, Yu PP, Hudis CA, Schilsky RL (2015) American society of clinical oncology statement: a conceptual framework to assess the value of cancer treatment options. J Clin Oncol 33(23):2563–2577. https://doi.org/10.1200/JCO.2015.61.6706. Epub 2015 Jun 22

    Article  PubMed  PubMed Central  Google Scholar 

  26. Sussex J, Rollet P, Garau M, Schmitt C, Kent A, Hutchings A (2013) A pilot study of multicriteria decision analysis for valuing orphan medicines. Value Health 16(8):1163–1169. https://doi.org/10.1016/j.jval.2013.10.002

    Article  PubMed  Google Scholar 

  27. Tanios N, Wagner M, Tony M, Baltussen R, van Til J, Rindress D, Kind P, Goetghebeur MM (2013) International task force on decision criteria. Which criteria are considered in healthcare decisions? Insights from an international survey of policy and clinical decision makers. Int J Technol Assess Health Care 29(4):456–465. https://doi.org/10.1017/S0266462313000573

    Article  PubMed  Google Scholar 

  28. Thokala P, Duenas A (2012) Multiple criteria decision analysis for health technology assessment. Value Health 15(8):1172–1181. https://doi.org/10.1016/j.jval.2012.06.015

    Article  PubMed  Google Scholar 

  29. Wagner M, Khoury H, Willet J, Rindress D, Goetghebeur M (2016) Can the EVIDEM framework tackle issues raised by evaluating treatments for rare diseases: analysis of issues and policies, and context-specific adaptation. Pharmacoeconomics 34(3):285–301. https://doi.org/10.1007/s40273-015-0340-5

    Article  PubMed  Google Scholar 

  30. Wahlster P, Goetghebeur M, Kriza C, Niederländer C, Kolominsky-Rabas P (2015) National leading-edge cluster medical technologies ‘Medical valley EMN’. Balancing costs and benefits at different stages of medical innovation: a systematic review of multi-criteria decision analysis (MCDA). BMC Health Serv Res 15:262. https://doi.org/10.1186/s12913-015-0930-0

    Article  PubMed  PubMed Central  Google Scholar 

  31. Wahlster P, Goetghebeur M, Schaller S, Kriza C, Kolominsky-Rabas P (2015) National leading-edge cluster medical technologies ‘Medical valley EMN’. Exploring the perspectives and preferences for HTA across German healthcare stakeholders using a multi-criteria assessment of a pulmonary heart sensor as a case study. Health Res Policy Syst 13:24. https://doi.org/10.1186/s12961-015-0011-1

    Article  PubMed  PubMed Central  Google Scholar 

  32. Zelei T, Molnár MJ, Szegedi M, Kaló Z (2016) Systematic review on the evaluation criteria of orphan medicines in central and eastern European countries. Orphanet J Rare Dis 11(1):72. https://doi.org/10.1186/s13023-016-0455-6

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Georgi Iskrov .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Iskrov, G., Miteva-Katrandzhieva, T., Stefanov, R. (2017). Health Technology Assessment and Appraisal of Therapies for Rare Diseases. In: Posada de la Paz, M., Taruscio, D., Groft, S. (eds) Rare Diseases Epidemiology: Update and Overview. Advances in Experimental Medicine and Biology, vol 1031. Springer, Cham. https://doi.org/10.1007/978-3-319-67144-4_13

Download citation

Publish with us

Policies and ethics