IDEAS home Printed from https://ideas.repec.org/a/spr/hecrev/v6y2016i1d10.1186_s13561-016-0113-7.html
   My bibliography  Save this article

Implementing personalized medicine with asymmetric information on prevalence rates

Author

Listed:
  • Fernando Antoñanzas

    (University of La Rioja)

  • Carmelo A. Juárez-Castelló

    (University of La Rioja)

  • Roberto Rodríguez-Ibeas

    (University of La Rioja)

Abstract

Although personalized medicine is becoming the new paradigm to manage some diseases, the economics of personalized medicine have only focused on assessing the efficiency of specific treatments, lacking a theoretical framework analyzing the interactions between pharmaceutical firms and healthcare systems leading to the implementation of personalized treatments. We model the interaction between the hospitals and the manufacturer of a new treatment as an adverse selection problem where the firm does not have perfect information on the prevalence across hospitals of the genetic characteristics of the patients making them eligible to receive a new treatment. As a result of the model, hospitals with high prevalence rates benefit from the information asymmetry only when the standard treatment is inefficient when applied to the patients eligible to receive the new treatment. Otherwise, information asymmetry has no value. Personalized medicine may be fully or partially implemented depending on the proportion of high prevalence hospitals.

Suggested Citation

  • Fernando Antoñanzas & Carmelo A. Juárez-Castelló & Roberto Rodríguez-Ibeas, 2016. "Implementing personalized medicine with asymmetric information on prevalence rates," Health Economics Review, Springer, vol. 6(1), pages 1-8, December.
    • Handle: RePEc:spr:hecrev:v:6:y:2016:i:1:d:10.1186_s13561-016-0113-7
    DOI: 10.1186/s13561-016-0113-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1186/s13561-016-0113-7
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1186/s13561-016-0113-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Bardey, David & De Donder, Philippe, 2013. "Genetic testing with primary prevention and moral hazard," Journal of Health Economics, Elsevier, vol. 32(5), pages 768-779.
    2. Meckley, Lisa M. & Neumann, Peter J., 2010. "Personalized medicine: Factors influencing reimbursement," Health Policy, Elsevier, vol. 94(2), pages 91-100, February.
    Full references (including those not matched with items on IDEAS)

    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. Simeon Schudy & Verena Utikal, 2015. "Does imperfect data privacy stop people from collecting personal health data?," TWI Research Paper Series 98, Thurgauer Wirtschaftsinstitut, Universität Konstanz.
    2. Leopold, C. & Vogler, S. & Habl, C. & Mantel-Teeuwisse, A.K. & Espin, J., 2013. "Personalised medicine as a challenge for public pricing and reimbursement authorities – A survey among 27 European countries on the example of trastuzumab," Health Policy, Elsevier, vol. 113(3), pages 313-322.
    3. Bardey, David & De Donder, Philippe, 2019. "A Welfare Analysis of Genetic Testing in Health Insurance Markets with Adverse Selection and Prevention," TSE Working Papers 19-1035, Toulouse School of Economics (TSE), revised 22 Jan 2024.
    4. Bardey, David & De Donder, Philippe & Mantilla, César, 2019. "How is the trade-off between adverse selection and discrimination risk affected by genetic testing? Theory and experiment," Journal of Health Economics, Elsevier, vol. 68(C).
    5. Stefan Felder, 2022. "Decision thresholds with genetic testing," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(6), pages 1071-1078, August.
    6. Simeon Schudy & Verena Utikal, 2012. "The Influence of (Im)perfect Data Privacy on the Acquisition of Personal Health Data," Working Paper Series of the Department of Economics, University of Konstanz 2012-12, Department of Economics, University of Konstanz.
    7. Veronika Kalouguina & Joël Wagner, 2020. "Challenges and Solutions for Integrating and Financing Personalized Medicine in Healthcare Systems: A Systematic Literature Review," JRFM, MDPI, vol. 13(11), pages 1-22, November.
    8. Goulão Catarina & Thibault Emmanuel, 2013. "Physical Activity and Policy Recommendations: A Social Multiplier Approach," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 14(2), pages 577-612, November.
    9. Tan, Kar Man & Gründl, Helmut, 2023. "Testing frequency and severity risk under various information regimes and implications in insurance," ICIR Working Paper Series 49/23, Goethe University Frankfurt, International Center for Insurance Regulation (ICIR).
    10. Filipova-Neumann, Lilia & Hoy, Michael, 2014. "Managing genetic tests, surveillance, and preventive medicine under a public health insurance system," Journal of Health Economics, Elsevier, vol. 34(C), pages 31-41.
    11. Lagerlof, Johan & Schottmüller, Christoph, 2013. "Monopoly Insurance with Endogenous Information," CEPR Discussion Papers 9774, C.E.P.R. Discussion Papers.
    12. Diego C. Nocetti, 2018. "Ambiguity and the value of information revisited," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 43(1), pages 25-38, May.
    13. Christine Arentz, 2012. "Auswirkungen von Gentests in der Krankenversicherung," Otto-Wolff-Institut Discussion Paper Series 04/2012, Otto-Wolff-Institut für Wirtschaftsordnung, Köln, Deutschland.
    14. Simeon Schudy & Verena Utikal, 2018. "Does Imperfect Data Privacy Stop People from Collecting Personal Data?," Games, MDPI, vol. 9(1), pages 1-23, March.
    15. F. Antoñanzas & C. Juárez-Castelló & R. Rodríguez-Ibeas, 2015. "Some economics on personalized and predictive medicine," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(9), pages 985-994, December.
    16. Jisang Yu & Nathan P. Hendricks, 2020. "Input Use Decisions with Greater Information on Crop Conditions: Implications for Insurance Moral Hazard and the Environment," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(3), pages 826-845, May.
    17. David Crainich, 2017. "Self-Insurance With Genetic Testing Tools," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(1), pages 73-94, March.
    18. Tracy Merlin & Claude Farah & Camille Schubert & Andrew Mitchell & Janet E. Hiller & Philip Ryan, 2013. "Assessing Personalized Medicines in Australia," Medical Decision Making, , vol. 33(3), pages 333-342, April.
    19. Shooshan Danagoulian, 2018. "Policy of prevention: Medical utilization under a wellness plan," Health Economics, John Wiley & Sons, Ltd., vol. 27(11), pages 1843-1858, November.
    20. Felix C.H. Gottschalk, 2019. "Why prevent when it does not pay? Prevention when health services are credence goods," Health Economics, John Wiley & Sons, Ltd., vol. 28(5), pages 693-709, May.

    More about this item

    Keywords

    Endogenous reference price; Exogenous reference price; Off-patent drug; Generic drug; Pharmaceutical expenditures;
    All these keywords.

    JEL classification:

    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets
    • L51 - Industrial Organization - - Regulation and Industrial Policy - - - Economics of Regulation

    Statistics

    Access and download statistics

    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:6:y:2016:i:1:d:10.1186_s13561-016-0113-7. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    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 (email available below). General contact details of provider: http://www.springer.com/economics/journal/13561 .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.