The value of quantitative patient preferences in regulatory benefit-risk assessment

Journal of Market Access and Health Policy

Volumn 2, Issue 1, 2014, Pages

  Egbrink, Mart oude ^a   IJzerman, Maarten ^a  

^a UNIVERSITY OF TWENTE   (Netherlands)

Author keywords

benefit risk assessment; European Medicines Agency; patient involvement; preferences

Indexed keywords

EID: 84930618901     PISSN: None     EISSN: 20016689     Source Type: Journal    
DOI: 10.3402/jmahp.v2.22761     Document Type: Article

References (27)

1. Health Equality Europe.Understanding Health Technology Assessment (HTA). 2008. [cited 2013 June 20]. Available from: http://img.eurordis.org/newsletter/pdf/nov-2010/58-1%20HEE%20Guide%20To%20HTA%20for%20Patients%20English.pdf.
2. FaceyK, BoivinA, GraciaJ, HansenHP, ScalzoAL, Ann SingleJM.Patients’ perspectives in health technology assessment: A route to robust evidence and fair deliberation. Int J Technol Assess Health Care. 2010; 26(3):334–40.
3. GagnonMP, DesmartisM, Lepage-SavaryD, GagnonJ, RhaindsM, LemieuxM et al. Introducing patients’ and the public's perspectives to health technology assessment: A systematic review of international experiences. Int J Technol Assess Health Care. 2011; 27(1):31–42.
4. MussenF, SalekS, WalkerS. Benefit-risk appraisal of medicines–A systematic approach to decision-making. 2009; Oxford, UK: Wiley-Blackwell.
5. WhittyJA.An international survey of the public engagement practices of health technology assessment organizations. Value Health. 2013; 16(1):155–63.
6. BridgesJFP, JonesC.Patient-based health technology assessment: A vision of the future. Int J Technol Assess Health Care. 2007; 23(1):30–5.
7. RoweG, FrewerL.A typology of public engagement mechanisms. Sci Tech Hum Val. 2005; 30(2):251–90.
8. GauvinFP. Public involvement in health technology assessment agencies: A comparative analysis of Canada, Denmark, and the United Kingdom. 2008; Hamilton, ON: McMaster University.
9. BreckenridgeA.Patient opinions and preferences in drug development and regulatory decision making. Drug Discov Today Technol. 2011; 8(1):e11–4.
10. EMA.Report of the CHMP working group on benefit-risk assessment models and methods. 2007; London: EMA.
11. EMA.Road map to 2015–The European Medicines Agency's contribution to science, medicines and health. 2010; London: EMA.
12. EMA.Fifth report on the interaction with patients’ and consumers’ organisations (2011). 2012; London: EMA.
13. JohnsonFR, LancsarE, MarshallD, KilambiV, MuhlbacherAC, RegierDA et al. Constructing experimental designs for discrete-choice experiments: Report of the ISPOR conjoint analysis experimental design good research practices task force. Value Health. 2013; 16(2013):3–13.
14. MarshallD, BridgesJFP, HauberAB, CameronR, DonnalleyL, FyieK et al. Conjoint Analysis Applications in Health—How are Studies being Designed and Reported?. Patient. 2010; 3(4):249–56.
15. BridgesJFP, HauberAB, MarshallD, LloydD, ProsserLA, RegierDA et al. Conjoint analysis applications in health—A checklist: A report of the ISPOR good research practices for conjoint analysis task force. Value Health. 2011; 14(2011):403–13.
16. SullivanT. Using MCDA (Multi-Criteria Decision Analysis) to prioritise publicly-funded health care. 2012; Dunedin, New Zealand: University of Otago.
17. BridgesJFP.Stated preference methods in health care evaluation: An emerging methodological paradigm in health economics. Appl Health Econ Health Policy. 2003; 2(4):213–24. [PubMed Abstract].
18. BridgesJFP, OnukwughaE, JohnsonFR, HauberAB. Patient preference methods–A patient centered evaluation paradigm. ISPOR Connections 2007;13(6):4–7.
19. EMA.Benefit-risk methodology project–Work package 2 report: Applicability of current tools and processes for regulatory benefit-risk assessment. 2010; London: EMA.
20. JohnsonFR, OzdemirS, HauberB, KaufTL.Women's willingness to accept perceived risks for vasomotor symptom relief. J Women's Health. 2007; 16(7):1028–40.
21. HummelMJ, VolzF, Van ManenJG, DannerM, DintsiosC, Charalabos-Markos et al. Using the analytic hierarchy process to elicit patient preferences: Prioritizing multiple outcome measures of antidepressant drug treatment. Patient. 2012; 5(4):225–37. [PubMed Abstract].
22. DannerM, HummelMJ, VolzF, Van ManenJG, WiegardB, DintsiosC et al. Integrating patients’ views into health technology assessment: Analytic hierarchy process (AHP) as a method to elicit patient preferences. Int J Technol Assess Health Care. 2011; 27(4):369–75.
23. IJzermanMJ, van TilJA, BridgesJFP. A comparison of analytic hierarchy process and conjoint analysis methods in assessing treatment alternatives for stroke rehabilitation. Patient. 2012; 5(1):45–56. [PubMed Abstract].
24. Bowman-BusatoJ.Patient engagement in health technology assessment. Pharmaceuticals Policy and Law. 2011; 13(2011):193–201.
25. HauberAB, FairchildAO, Reed JohnsonF.Quantifying benefit-risk preferences for medical interventions: An overview of a growing empirical literature. Appl Health Econ Health Policy. 2013; 11(4):319–29.
26. BroekhuizenH, Groothuis-OudshoornCGM, HauberAB, JansenJP, IJzermanMJ. Integrating elicited patient preferences and clinical trial data in a quantitative model for benefit-risk assessment. DIA 2013: The 25th Annual EuroMeeting of the Drug Information Association. 2013; March.3–5
27. JohnsonFR.Between Regulatory Rocks and Hard Places: Quantifying Tolerance for Pharmaceutical Risks. Ispor Connections. 2008; 14(6):6–8.