Advancing the Use of Patient Preference Information as Scientific Evidence in Medical Product Evaluation: A Summary Report of the Patient Preference Workshop

  • Heather L. BenzEmail author
  • Ting-Hsuan (Joyce) Lee
  • Jui-Hua Tsai
  • John F. P. Bridges
  • Sara Eggers
  • Megan Moncur
  • Fadia T. Shaya
  • Ira Shoulson
  • Erica S. Spatz
  • Leslie Wilson
  • Anindita Saha
Patient preference information is an assessment of the relative desirability or acceptability to patients of specified alternatives or choices among outcomes or other attributes that differ among alternative health interventions [ 4]. Put simply, PPI can tell us about what treatment attributes are important to patients, how important they are, and what trade-offs patients are willing to make between attributes [ 5, 6]. The objectives of the workshop were to:
  • present current progress on incorporating PPI into medical product benefit-risk assessments;

  • provide examples of how PPI can be collected, analyzed, and presented in a manner that matters to stakeholders;

  • explore methods for appropriate measurement, interpretation, and adoption of PPI in a regulatory context; and

  • identify future research and capacity needs to improve the use of PPI in a regulatory context.

Patient perspectives can be shared with the FDA in many ways, including Advisory Committee meetings, Patient-Focused Drug...



The authors acknowledge the extensive contributions of the workshop planning committee, including Vishal Bhatnagar, Donna Blum-Kemelor, Michelle Campbell, Meghana Chalasani, Ebony Dashiell-Aje, Liana Fraenkel, Martin Ho, Telba Irony, Ellen Janssen, Laura Lee Johnson, Paul Kluetz, Lawrence Lin, Theresa Mullin, Mimi Nguyen, Kathryn O’Callaghan, Elektra Papadopoulos, Michelle Tarver, Million Tegenge, Audrey Thomas, Pujita Vaidya, Frank F. Weichold, Rebekah Zinn, and invited speakers, including G. Caleb Alexander, R. Scott Braithwaite, Stephanie Christopher, Andrea Ferris, Juan Marcos Gonzalez, Nancy Goodman, Cynthia Grossman, Kara L. Haas, Janel Hanmer, A. Brett Hauber, RADM Denise Hinton, Frank Hurst, Catherine Kopil, Tamar Krishnamurti, Kerry Jo Lee, Bennett Levitan, Carol Linden, Deborah A. Marshall, K. Kimberly McCleary, C. Daniel Mullins, Rebecca Noel, Elisabeth (Liz) Piault-Louis, Gregory Reaman, Matt Reaney, Joseph S. Ross, Shelby D. Reed, and Melissa West.

Compliance with Ethical Standards


This work was supported by a Center of Excellence in Regulatory Science and Innovation grant to Georgetown University, Johns Hopkins University, Mayo Clinic, Stanford University, University of California San Francisco, University of Maryland, and Yale University from the US Food and Drug Administration (grant numbers UO1FD004979, U01FD005942, U01FD005946, U01FD005938, U01FD004319).

Conflict of interest

Heather L. Benz, Ting-Hsuan (Joyce) Lee, Jui-Hua Tsai, John F.P. Bridges, Sara Eggers, Megan Moncur, Fadia T. Shaya, Ira Shoulson, Erica S. Spatz, Leslie Wilson, and Anindita Saha have no conflicts of interest that are directly relevant to the content of this article.


This article reflects the views of the authors and should not be construed to represent the FDA’s views or policies.


  1. 1.
    Hunter NL, O’Callaghan KM, Califf RM. Engaging patients across the spectrum of medical product development: view from the US Food and Drug Administration. JAMA. 2015;314(23):2499–500.CrossRefGoogle Scholar
  2. 2.
    Hoos A, Anderson J, Boutin M, et al. Partnering with patients in the development and lifecycle of medicines: a call for action. Ther Innov Regul Sci. 2015;49(6):929–39.PubMedPubMedCentralGoogle Scholar
  3. 3.
    UCSF. Patient Preference Workshop. Advancing use of patient preference information as scientific evidence in medical product evaluation. 2018. Accessed 15 Nov 2018.
  4. 4.
    US FDA. Patient preference information: voluntary submission, review in premarket approval applications, humanitarian device exemption applications, and de novo requests, and inclusion in decision summaries and device labeling. 2016. Accessed 15 Nov 2018.
  5. 5.
    Craig BM, Lancsar E, Mühlbacher AC, Brown DS, Ostermann J. Health preference research: an overview. Patient. 2017;10(4):507–10.CrossRefGoogle Scholar
  6. 6.
    Ho M, Saha A, McCleary KK, et al. A framework for incorporating patient preferences regarding benefits and risks into regulatory assessment of medical technologies. Value Health. 2016;19(6):746–50.CrossRefGoogle Scholar
  7. 7.
    Dirksen CD, Utens CM, Joore MA, et al. Integrating evidence on patient preferences in healthcare policy decisions: protocol of the patient-VIP study. Implement Sci. 2013;8(1):64.CrossRefGoogle Scholar
  8. 8.
    Purks JL, Wilhelm EE, Shoulson I, Creveling J, Dorsey ER, Irony T, et al. Inaugural conference on incorporating patient-reported outcomes and patient preference information into clinical research, clinical care, and risk-benefit assessments for neurodegenerative diseases. Patient. 2017;10(5):541–4.CrossRefGoogle Scholar
  9. 9.
    Johnson FR, Beusterien K, Özdemir S, Wilson L. Giving patients a meaningful voice in United States regulatory decision making: the role for health preference research. Patient. 2017;10(4):523–6.CrossRefGoogle Scholar
  10. 10.
    Ho MP, Gonzalez JM, Lerner HP, et al. Incorporating patient-preference evidence into regulatory decision making. Surg Endosc. 2015;29(10):2984–93.CrossRefGoogle Scholar
  11. 11.
    US FDA. Public Workshop. The patient preference initiative: incorporating patient preference information into the medical device regulatory processes, September 18–19, 2013. 2019. Accessed 24 Sep 2019.
  12. 12.
    Medical Device Innovation Consortium. A framework for incorporating information on patient preferences regarding benefit and risk into regulatory assessments of new medical technology. 2015. Accessed 15 Nov 2018.
  13. 13.
    Soekhai V, Whichello C, Levitan B, et al. Methods for exploring and eliciting patient preferences in the medical product lifecycle: a literature review. Drug Discov Today. 2019;24(7):1324–31.CrossRefGoogle Scholar
  14. 14.
    Bridges J, Hauber AB, Marshall D, et al. A checklist for conjoint analysis applications in health: report of the ISPOR Conjoint Analysis Good Research Practices Taskforce. Value Health. 2011;14(4):403–13.CrossRefGoogle Scholar
  15. 15.
    Johnson FR, Lancsar E, Marshall D, 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;16:3–13.CrossRefGoogle Scholar
  16. 16.
    Hauber A, Gonzalez J, Groothuis-Oudshoorn C, et al. Statistical methods for the analysis of discrete choice experiments: a report of the ISPOR Conjoint Analysis Good Research Practices Task Force. Value Health. 2016;19:300–15.CrossRefGoogle Scholar
  17. 17.
    Rydén A, Chen S, Flood E, Romero B, Grandy S. Discrete choice experiment attribute selection using a multinational interview study: treatment features important to patients with type 2 diabetes mellitus. Patient. 2017;10(4):475–87.CrossRefGoogle Scholar
  18. 18.
    Vass CM, Payne K. Using discrete choice experiments to inform the benefit-risk assessment of medicines: are we ready yet? Pharmacoeconomics. 2017;35(9):859–66.CrossRefGoogle Scholar
  19. 19.
    Arentze T, Borgers A, Timmermans H, DelMistro R. Transport stated choice responses: effects of task complexity, presentation format and literacy. Transp Res E Log. 2003;39(3):229–44.CrossRefGoogle Scholar
  20. 20.
    Levitan B, Hauber AB, Damiano MG, et al. The ball is in your court: agenda for research to advance the science of patient preferences in the regulatory review of medical devices in the United States. Patient. 2017;10(5):531–6.CrossRefGoogle Scholar
  21. 21.
    Mühlbacher A, Johnson FR. Choice experiments to quantify preferences for health and healthcare: state of the practice. Appl Health Econ Health Policy. 2016;14(3):253–66.CrossRefGoogle Scholar
  22. 22.
    Johnson FR, Zhou M. Patient preferences in regulatory benefit-risk assessments: a US perspective. Value Health. 2016;19(6):741–5.CrossRefGoogle Scholar
  23. 23.
    de Bekker-Grob EW, Berlin C, Levitan B, et al. Giving patients’ preferences a voice in medical treatment life cycle: the PREFER public-private project. Patient. 2017;10(3):263–6.CrossRefGoogle Scholar
  24. 24.
    US FDA. CDER patient-focused drug development. 2018. Accessed 15 Nov 2018.
  25. 25.
    US FDA. Patient preference information (PPI) in medical device decision-making. 2019. Accessed 27 Sep 2019.
  26. 26.
    Patient focused drug development and patient engagement at CBER. 2018. Accessed 15 Nov 2018.

Copyright information

© This is a U.S. government work and its text is not subject to copyright protection in the United States; however, its text may be subject to foreign copyright protection  2019

Authors and Affiliations

  • Heather L. Benz
    • 1
    • 4
    Email author
  • Ting-Hsuan (Joyce) Lee
    • 1
  • Jui-Hua Tsai
    • 2
    • 9
    • 10
  • John F. P. Bridges
    • 2
    • 9
    • 11
  • Sara Eggers
    • 3
  • Megan Moncur
    • 3
    • 12
  • Fadia T. Shaya
    • 5
  • Ira Shoulson
    • 6
  • Erica S. Spatz
    • 7
  • Leslie Wilson
    • 8
  • Anindita Saha
    • 1
  1. 1.FDA Center for Devices and Radiological HealthSilver SpringUSA
  2. 2.Johns Hopkins University Center of Excellence in Regulatory Science and InnovationBaltimoreUSA
  3. 3.FDA Center for Drug Evaluation and ResearchSilver SpringUSA
  4. 4.FDA Center for Biologics Evaluation and ResearchSilver SpringUSA
  5. 5.University of Maryland Center of Excellence in Regulatory Science and InnovationBaltimoreUSA
  6. 6.Georgetown University Center of Excellence in Regulatory Science and InnovationWashingtonUSA
  7. 7.Yale University-Mayo Clinic Center of Excellence in Regulatory Science and InnovationNew HavenUSA
  8. 8.UCSF-Stanford Center of Excellence in Regulatory Science and InnovationSan FranciscoUSA
  9. 9.Johns Hopkins Bloomberg School of Public HealthBaltimoreUSA
  10. 10.Pharmerit International, LPBerlinGermany
  11. 11.Ohio State UniversityColumbusGermany
  12. 12.FDA Center for Biologics Evaluation and ResearchSilver SpringUSA

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