IDEAS home Printed from https://ideas.repec.org/p/tse/wpaper/124379.html
   My bibliography  Save this paper

Identifying the Effects of Scientific Information and Recommendations on Physicians’ Prescribing Behavior

Author

Listed:
  • Dubois, Pierre
  • Tuncel, Tuba

Abstract

We investigate how the prescribing behavior of physicians reacts to scientific information and recommendations released by public authorities. Taking the example of antidepressant drugs, we use French panel data on exhaustive prescriptions made by a representative sample of general practitioners to more than 110,000 depressed patients between 2000 and 2008. New results revealing an increase in suicidal thinking among children taking selective serotonin reuptake inhibitors (SSRIs) were reported in 2004 and prompted the release of new guidelines by public health authorities. We identify the effect of this unexpected warning on physicians’ drug choices while addressing that possibility that patient heterogeneity may be correlated with unobserved physician characteristics. While the warning decreased the average probability of prescribing SSRIs, we find that physicians’ responses to the warning were very heterogeneous and larger if the physician had a higher preference for prescribing SSRIs before the warning.

Suggested Citation

  • Dubois, Pierre & Tuncel, Tuba, 2020. "Identifying the Effects of Scientific Information and Recommendations on Physicians’ Prescribing Behavior," TSE Working Papers 20-1114, Toulouse School of Economics (TSE).
  • Handle: RePEc:tse:wpaper:124379
    as

    Download full text from publisher

    File URL: https://www.tse-fr.eu/sites/default/files/TSE/documents/doc/wp/2020/wp_tse_1114.pdf
    File Function: Full Text
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Janet M. Currie & W. Bentley MacLeod, 2020. "Understanding Doctor Decision Making: The Case of Depression Treatment," Econometrica, Econometric Society, vol. 88(3), pages 847-878, May.
    2. Ludwig, Jens & Marcotte, Dave E. & Norberg, Karen, 2009. "Anti-depressants and suicide," Journal of Health Economics, Elsevier, vol. 28(3), pages 659-676, May.
    3. Rodwin, V.G., 2003. "The health care system under French national health insurance: Lessons for health reform in the United States," American Journal of Public Health, American Public Health Association, vol. 93(1), pages 31-37.
    4. Stern, S. & Trajtenberg, M., 1998. "Empirical Implications of Physician Authority in Pharmaceutical Decisionmaking," Papers 24-98, Tel Aviv.
    5. David Cutler & Jonathan S. Skinner & Ariel Dora Stern & David Wennberg, 2019. "Physician Beliefs and Patient Preferences: A New Look at Regional Variation in Health Care Spending," American Economic Journal: Economic Policy, American Economic Association, vol. 11(1), pages 192-221, February.
    6. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2013. "Invited Paper ---Learning Models: An Assessment of Progress, Challenges, and New Developments," Marketing Science, INFORMS, vol. 32(6), pages 913-938, November.
    7. Janet Currie & W. Bentley MacLeod, 2017. "Diagnosing Expertise: Human Capital, Decision Making, and Performance among Physicians," Journal of Labor Economics, University of Chicago Press, vol. 35(1), pages 1-43.
    8. Andrew T. Ching, 2010. "A Dynamic Oligopoly Structural Model For The Prescription Drug Market After Patent Expiration," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 51(4), pages 1175-1207, November.
    9. Gregory S. Crawford & Matthew Shum, 2005. "Uncertainty and Learning in Pharmaceutical Demand," Econometrica, Econometric Society, vol. 73(4), pages 1137-1173, July.
    10. Maria Marta Ferreyra & Grigory Kosenok, 2011. "Learning About New Products: An Empirical Study Of Physicians' Behavior," Economic Inquiry, Western Economic Association International, vol. 49(3), pages 876-898, July.
    11. Andrew T. Ching & Hyunwoo Lim, 2020. "A Structural Model of Correlated Learning and Late-Mover Advantages: The Case of Statins," Management Science, INFORMS, vol. 66(3), pages 1095-1123, March.
    12. Michael J. Dickstein, 2018. "Efficient Provision of Experience Goods: Evidence from Antidepressant Choice," Working Papers 18-17, New York University, Leonard N. Stern School of Business, Department of Economics.
    13. Berndt, Ernst R. & Gibbons, Robert S. & Kolotilin, Anton & Taub, Anna Levine, 2015. "The heterogeneity of concentrated prescribing behavior: Theory and evidence from antipsychotics," Journal of Health Economics, Elsevier, vol. 40(C), pages 26-39.
    14. Collins, J. Michael & Simon, Kosali I. & Tennyson, Sharon, 2013. "Drug withdrawals and the utilization of therapeutic substitutes: The case of Vioxx," Journal of Economic Behavior & Organization, Elsevier, vol. 86(C), pages 148-168.
    15. Julie Berez & Guy David & David H. Howard & Mark D. Neuman, 2018. "Does Bad News Travel Faster? On the Determinants of Medical Technology Abandonment," Journal of Human Capital, University of Chicago Press, vol. 12(4), pages 569-603.
    16. David H. Howard & Guy David & Jason Hockenberry, 2017. "Selective Hearing: Physician‐Ownership and Physicians’ Response to New Evidence," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 26(1), pages 152-168, February.
    17. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2013. "Learning Models: An Assessment of Progress, Challenges and New Developments," Economics Papers 2013-W07, Economics Group, Nuffield College, University of Oxford.
    18. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    19. A. J. Culyer & J. P. Newhouse (ed.), 2000. "Handbook of Health Economics," Handbook of Health Economics, Elsevier, edition 1, volume 1, number 1.
    20. Coscelli, Andrea & Shum, Matthew, 2004. "An empirical model of learning and patient spillovers in new drug entry," Journal of Econometrics, Elsevier, vol. 122(2), pages 213-246, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mary K. Olson & Nina Yin, 2021. "New clinical information and physician prescribing: How do pediatric labeling changes affect prescribing to children?," Health Economics, John Wiley & Sons, Ltd., vol. 30(1), pages 144-164, January.

    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. Jürgen Maurer & Katherine M. Harris, 2016. "Learning to Trust Flu Shots: Quasi‐Experimental Evidence from the 2009 Swine Flu Pandemic," Health Economics, John Wiley & Sons, Ltd., vol. 25(9), pages 1148-1162, September.
    2. Maurer, J. & Harris, K.M., 2015. "Learning to trust flu shots: quasi-experimental evidence on the role of learning in influenza vaccination decisions from the 2009 influenza A/H1N1 (swine flu) pandemic," Health, Econometrics and Data Group (HEDG) Working Papers 15/19, HEDG, c/o Department of Economics, University of York.
    3. Janet M. Currie & W. Bentley MacLeod, 2020. "Understanding Doctor Decision Making: The Case of Depression Treatment," Econometrica, Econometric Society, vol. 88(3), pages 847-878, May.
    4. Wu, Bingxiao & David, Guy, 2022. "Information, relative skill, and technology abandonment," Journal of Health Economics, Elsevier, vol. 83(C).
    5. Jie Bai, 2016. "Melons as Lemons: Asymmetric Information, Consumer Learning and Seller Reputation," Natural Field Experiments 00540, The Field Experiments Website.
    6. Kohei Kawaguchi, 2021. "When Will Workers Follow an Algorithm? A Field Experiment with a Retail Business," Management Science, INFORMS, vol. 67(3), pages 1670-1695, March.
    7. Hai Che & Tülin Erdem & T. Sabri Öncü, 2015. "Consumer learning and evolution of consumer brand preferences," Quantitative Marketing and Economics (QME), Springer, vol. 13(3), pages 173-202, September.
    8. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2013. "Learning Models: An Assessment of Progress, Challenges and New Developments," Economics Papers 2013-W07, Economics Group, Nuffield College, University of Oxford.
    9. S. Sriram & Pradeep K. Chintagunta & Puneet Manchanda, 2015. "Service Quality Variability and Termination Behavior," Management Science, INFORMS, vol. 61(11), pages 2739-2759, November.
    10. Matthew Grennan & Robert J. Town, 2020. "Regulating Innovation with Uncertain Quality: Information, Risk, and Access in Medical Devices," American Economic Review, American Economic Association, vol. 110(1), pages 120-161, January.
    11. Xu, Yan, 2017. "Essays on preference formation and home production," Other publications TiSEM b028fd7e-53ba-4ff6-97eb-4, Tilburg University, School of Economics and Management.
    12. Janet M. Currie & W. Bentley MacLeod, 2018. "Understanding Doctor Decision Making: The Case of Depression," NBER Working Papers 24955, National Bureau of Economic Research, Inc.
    13. Hoffman, Mitchell & Burks, Stephen V., 2017. "Worker Overconfidence: Field Evidence and Implications for Employee Turnover and Returns from Training," IZA Discussion Papers 10794, Institute of Labor Economics (IZA).
    14. Anand Acharya & Lynda Khalaf & Marcel Voia & Myra Yazbeck & David Wensley, 2021. "Severity of Illness and the Duration of Intensive Care," Working Papers 2021-003, Human Capital and Economic Opportunity Working Group.
    15. Ching, Andrew T. & Erdem, Tülin & Keane, Michael P., 2014. "A simple method to estimate the roles of learning, inventories and category consideration in consumer choice," Journal of choice modelling, Elsevier, vol. 13(C), pages 60-72.
    16. Song Lin & Juanjuan Zhang & John R. Hauser, 2015. "Learning from Experience, Simply," Marketing Science, INFORMS, vol. 34(1), pages 1-19, January.
    17. Andrew T. Ching & Hyunwoo Lim, 2020. "A Structural Model of Correlated Learning and Late-Mover Advantages: The Case of Statins," Management Science, INFORMS, vol. 66(3), pages 1095-1123, March.
    18. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2013. "Invited Paper ---Learning Models: An Assessment of Progress, Challenges, and New Developments," Marketing Science, INFORMS, vol. 32(6), pages 913-938, November.
    19. Emily Cuddy & Janet Currie, 2020. "Rules vs. Discretion: Treatment of Mental Illness in U.S. Adolescents," NBER Working Papers 27890, National Bureau of Economic Research, Inc.
    20. Ganglmair, Bernhard & Simcoe, Timothy & Tarantino, Emanuele, 2018. "Learning When to Quit: An Empirical Model of Experimentation," CEPR Discussion Papers 12733, C.E.P.R. Discussion Papers.

    More about this item

    Keywords

    Physician behavior; prescription; antidepressants; mixed logit;
    All these keywords.

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:tse:wpaper:124379. 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: . General contact details of provider: https://edirc.repec.org/data/tsetofr.html .

    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: (email available below). General contact details of provider: https://edirc.repec.org/data/tsetofr.html .

    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.