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Influence of peer networks on physician adoption of new drugs

Author

Listed:
  • Julie M Donohue
  • Hasan Guclu
  • Walid F Gellad
  • Chung-Chou H Chang
  • Haiden A Huskamp
  • Niteesh K Choudhry
  • Ruoxin Zhang
  • Wei-Hsuan Lo-Ciganic
  • Stefanie P Junker
  • Timothy Anderson
  • Seth Richards-Shubik

Abstract

Although physicians learn about new medical technologies from their peers, the magnitude and source of peer influence is unknown. We estimate the effect of peer adoption of three first-in-class medications (dabigatran, sitigliptin, and aliskiren) on physicians’ own adoption of those medications. We included 11,958 physicians in Pennsylvania prescribing anticoagulant, antidiabetic, and antihypertensive medications. We constructed 4 types of peer networks based on shared Medicare and Medicaid patients, medical group affiliation, hospital affiliation, and medical school/residency training. Instrumental variables analysis was used to estimate the causal effect of peer adoption (fraction of peers in each network adopting the new drug) on physician adoption (prescribing at least the median number prescriptions within 15 months of the new drug’s introduction). We illustrate how physician network position can inform targeting of interventions to physicians by computing a social multiplier. Dabigatran was adopted by 25.2%, sitagliptin by 24.5% and aliskiren by 8.3% of physicians. A 10-percentage point increase in peer adoption in the patient-sharing network led to a 5.90% (SE = 1.50%, p

Suggested Citation

  • Julie M Donohue & Hasan Guclu & Walid F Gellad & Chung-Chou H Chang & Haiden A Huskamp & Niteesh K Choudhry & Ruoxin Zhang & Wei-Hsuan Lo-Ciganic & Stefanie P Junker & Timothy Anderson & Seth Richards, 2018. "Influence of peer networks on physician adoption of new drugs," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-18, October.
    • Handle: RePEc:plo:pone00:0204826
    DOI: 10.1371/journal.pone.0204826
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    References listed on IDEAS

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    Cited by:

    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. Jie Mi & Chuanpeng Yao & Xiaoyang Zhao & Fei Li, 2024. "Research on the Diffusion Mechanism of Green Technology Innovation Based on Enterprise Perception," Computational Economics, Springer;Society for Computational Economics, vol. 63(5), pages 1981-2010, May.
    3. Leila Agha & Dan Zeltzer, 2022. "Drug Diffusion through Peer Networks: The Influence of Industry Payments," American Economic Journal: Economic Policy, American Economic Association, vol. 14(2), pages 1-33, May.
    4. 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.
    5. Yong Cai & Mohamed Abouzahra, 2023. "The influence of strong and weak ties in physician peer networks on new drug adoption," International Journal of Health Economics and Management, Springer, vol. 23(1), pages 133-147, March.
    6. Sebastian Calónico & Rafael Di Tella & Juan Cruz Lopez del Valle, 2023. "The Political Economy of a “Miracle Cure”: The Case of Nebulized Ibuprofen and its Diffusion in Argentina," NBER Working Papers 31781, National Bureau of Economic Research, Inc.

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