IDEAS home Printed from https://ideas.repec.org/a/spr/hecrev/v10y2020i1d10.1186_s13561-020-00267-y.html
   My bibliography  Save this article

The impact of reimbursement negotiations on cost and availability of new pharmaceuticals: evidence from an online experiment

Author

Listed:
  • Dominik J. Wettstein

    () (University of Lucerne)

  • Stefan Boes

    (University of Lucerne)

Abstract

Background The necessity to measure and reward “value for money” of new pharmaceuticals has become central in health policy debates, as much as the requirement to assess the “willingness to pay” for an additional, quality-adjusted life year (QALY). There is a clear need to understand the capacity of “value-based” pricing policies to impact societal goals, like timely access to new treatments, sustainable health budgets, or incentivizing research to improve patient outcomes. Not only the pricing mechanics, but also the process of value assessment and price negotiation are subject to reform demands. This study assesses the impact of a negotiation situation for life-extending pharmaceuticals on societal outcomes. Of interest were general effects of the bargaining behaviour, as well as differences caused by the assigned role and the magnitude of prices. Methods We ran an online experiment (n = 404) on Amazon Mechanical Turk (MTurk). Participants were randomly assigned into four treatment groups for a reimbursement negotiation between two roles (health minister, pharma representative) in two price framings. Payoff to players consisted of a fixed salary and a potential bonus, depending on their preferences, their price offer and the counter offer of a randomly paired negotiation partner. Success had real social consequences on other MTurk users (premium payers, investors) and via donations to a patient association. Results Margins between reservation prices and price offers increased throughout the game. Yet, 47% of players reduced at least once and 15% always their bonus probability to zero in favour of an agreement. 61% of simulated negotiation pairs could have reached an agreement, based on their preferences. 63% of these were successful, leaving 61% of patients with no access to the new treatment. The group with “real world” prices had lower prices and less agreements than the unconverted payoff group. The successful markets redistributed 20% of total assets from premium payers to investors over five innovation cycles. Conclusions The negotiation situation for pharmaceutical reimbursement has notable impact on societal outcomes. Further research should evaluate policies that align preferences and increase negotiation success.

Suggested Citation

  • Dominik J. Wettstein & Stefan Boes, 2020. "The impact of reimbursement negotiations on cost and availability of new pharmaceuticals: evidence from an online experiment," Health Economics Review, Springer, vol. 10(1), pages 1-15, December.
  • Handle: RePEc:spr:hecrev:v:10:y:2020:i:1:d:10.1186_s13561-020-00267-y
    DOI: 10.1186/s13561-020-00267-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1186/s13561-020-00267-y
    File Function: Abstract
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Heiner Schumacher & Iris Kesternich & Michael Kosfeld & Joachim Winter, 2014. "Us and Them: Distributional Preferences in Small and Large Groups," CESifo Working Paper Series 4657, CESifo.
    2. John H. Kagel & Alvin E. Roth, 2016. "The Handbook of Experimental Economics, Volume 2," Economics Books, Princeton University Press, edition 1, volume 2, number 10874, October.
    3. Vogler, Sabine & Zimmermann, Nina & de Joncheere, Kees, 2016. "Policy interventions related to medicines: Survey of measures taken in European countries during 2010–2015," Health Policy, Elsevier, vol. 120(12), pages 1363-1377.
    4. Lei Feng & Mark Seasholes, 2005. "Do Investor Sophistication and Trading Experience Eliminate Behavioral Biases in Financial Markets?," Review of Finance, Springer, vol. 9(3), pages 305-351, September.
    5. Oliver,Adam, 2017. "The Origins of Behavioural Public Policy," Cambridge Books, Cambridge University Press, number 9781316510261, December.
    6. Oliver,Adam, 2017. "The Origins of Behavioural Public Policy," Cambridge Books, Cambridge University Press, number 9781316649664, December.
    7. Nathaniel J. S. Ashby & Stephan Dickert & Andreas Glockner, 2012. "Focusing on what you own: Biased information uptake due to ownership," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 7(3), pages 254-267, May.
    8. David Johnson & John Barry Ryan, 2020. "Amazon Mechanical Turk workers can provide consistent and economically meaningful data," Southern Economic Journal, John Wiley & Sons, vol. 87(1), pages 369-385, July.
    9. Lei Feng & Mark S. Seasholes, 2005. "Do Investor Sophistication and Trading Experience Eliminate Behavioral Biases in Financial Markets?," Review of Finance, European Finance Association, vol. 9(3), pages 305-351.
    10. Dirk Engelmann & Martin Strobel, 2004. "Inequality Aversion, Efficiency, and Maximin Preferences in Simple Distribution Experiments," American Economic Review, American Economic Association, vol. 94(4), pages 857-869, September.
    11. Yao-Min Chiang & David Hirshleifer & Yiming Qian & Ann E. Sherman, 2011. "Do Investors Learn from Experience? Evidence from Frequent IPO Investors," Review of Financial Studies, Society for Financial Studies, vol. 24(5), pages 1560-1589.
    12. Wang, Jian & Iversen, Tor & Hennig-Schmidt, Heike & Godager, Geir, 2020. "Are patient-regarding preferences stable? Evidence from a laboratory experiment with physicians and medical students from different countries," European Economic Review, Elsevier, vol. 125(C).
    13. Jason Shogren, 2012. "Behavioural Economics and Environmental Incentives," OECD Environment Working Papers 49, OECD Publishing.
    14. Valérie Paris & Annalisa Belloni, 2013. "Value in Pharmaceutical Pricing," OECD Health Working Papers 63, OECD Publishing.
    Full references (including those not matched with items on IDEAS)

    Citations

    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Chris Sampson’s journal round-up for 8th June 2020
      by Chris Sampson in The Academic Health Economists' Blog on 2020-06-08 11:00:08

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gregor Dorfleitner & Lars Hornuf & Martina Weber, 2018. "Paralyzed by Shock: The Portfolio Formation Behavior of Peer-to-Business Lending Investors," CESifo Working Paper Series 7092, CESifo.
    2. Peiran Jiao, 2015. "The Double-Channeled Effects of Experience on Individual Investment Decisions: Experimental Evidence," Economics Series Working Papers 766, University of Oxford, Department of Economics.
    3. Utpal Bhattacharya & Wei-Yu Kuo & Tse-Chun Lin & Jing Zhao, 2018. "Do Superstitious Traders Lose Money?," Management Science, INFORMS, vol. 64(8), pages 3772-3791, August.
    4. Heinrich H. Nax, 2016. "When is Market the Benchmark? Reinforcement Evidence from Repurchase Decisions," Economics Series Working Papers 781, University of Oxford, Department of Economics.
    5. Hayley, Simon & Marsh, Ian W., 2016. "What do retail FX traders learn?," Journal of International Money and Finance, Elsevier, vol. 64(C), pages 16-38.
    6. Jürgen Huber & Michael Kirchler & Thomas Stöckl, 2016. "The influence of investment experience on market prices: laboratory evidence," Experimental Economics, Springer;Economic Science Association, vol. 19(2), pages 394-411, June.
    7. John Gathergood & David Hirshleifer & David Leake & Hiroaki Sakaguchi & Neil Stewart, 2019. "Naïve *Buying* Diversification and Narrow Framing by Individual Investors," NBER Working Papers 25567, National Bureau of Economic Research, Inc.
    8. Chan, Kalok & Wang, Baolian & Yang, Zhishu, 2019. "Why investors do not buy cheaper securities: Evidence from a natural experiment," Journal of Banking & Finance, Elsevier, vol. 101(C), pages 59-76.
    9. Kristjan Liivamägi, 2015. "Investor Education and Portfolio Diversification on the Stock Market," Research in Economics and Business: Central and Eastern Europe, Tallinn School of Economics and Business Administration, Tallinn University of Technology, vol. 7(1).
    10. Moeeni , Shahram & Tayebi , Komeil, 2018. "Is It Necessary to Restrict Forex Financial Trading? A Modified Model," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 13(1), pages 63-80, January.
    11. James Choi & David Laibson & Brigitte Madrain & Andrew Metrick, 2007. "Reinforcement Learning in Investment Behavior," Levine's Bibliography 122247000000001737, UCLA Department of Economics.
    12. Markus Glaser & Thomas Langer & Martin Weber, 2007. "On the Trend Recognition and Forecasting Ability of Professional Traders," Decision Analysis, INFORMS, vol. 4(4), pages 176-193, December.
    13. Cary Frydman & Nicholas Barberis & Colin Camerer & Peter Bossaerts & Antonio Rangel, 2012. "Using Neural Data to Test a Theory of Investor Behavior: An Application to Realization Utility," NBER Working Papers 18562, National Bureau of Economic Research, Inc.
    14. Fei, Tianlun & Liu, Xiaoquan & Wen, Conghua, 2019. "Cross-sectional return dispersion and volatility prediction," Pacific-Basin Finance Journal, Elsevier, vol. 58(C).
    15. Sabine Vogler & Valérie Paris & Alessandra Ferrario & Veronika J. Wirtz & Kees Joncheere & Peter Schneider & Hanne Bak Pedersen & Guillaume Dedet & Zaheer-Ud-Din Babar, 2017. "How Can Pricing and Reimbursement Policies Improve Affordable Access to Medicines? Lessons Learned from European Countries," Applied Health Economics and Health Policy, Springer, vol. 15(3), pages 307-321, June.
    16. Choi, Darwin, 2019. "Disposition sales and stock market liquidity," Journal of Financial Markets, Elsevier, vol. 45(C), pages 19-36.
    17. Tao, Qizhi & Chen, Carl & Lu, Rui & Zhang, Ting, 2017. "Underfunding or distress? An analysis of corporate pension underfunding and the cross-section of expected stock returns," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 116-133.
    18. Berk, Ales S. & Cummins, Mark & Dowling, Michael & Lucey, Brian M., 2017. "Psychological price barriers in frontier equities," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 49(C), pages 1-14.
    19. Tanjim Hossain & John A. List, 2012. "The Behavioralist Visits the Factory: Increasing Productivity Using Simple Framing Manipulations," Management Science, INFORMS, vol. 58(12), pages 2151-2167, December.
    20. Oliver Gloede & Lukas Menkhoff, 2014. "Financial Professionals' Overconfidence: Is It Experience, Function, or Attitude?," European Financial Management, European Financial Management Association, vol. 20(2), pages 236-269, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:hecrev:v:10:y:2020:i:1:d:10.1186_s13561-020-00267-y. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla) or (Springer Nature Abstracting and Indexing). General contact details of provider: http://www.springer.com/economics/journal/13561 .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.