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PBM Competition in Pharmaceutical Supply Chain: Formulary Design and Drug Pricing

Author

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  • Panos Kouvelis

    (Olin Business School, Washington University in St. Louis, St. Louis, Missouri 63130)

  • Yixuan Xiao

    (Department of Management Sciences, College of Business, City University of Hong Kong, Hong Kong)

  • Nan Yang

    (Olin Business School, Washington University in St. Louis, St. Louis, Missouri 63130)

Abstract

We model the competition among multiple pharmacy benefit managers (PBMs) for the patronage of a client organization. Each PBM selects a list of prices to be charged to the client organization for each of the branded and generic drugs within a therapeutic class (price decision) and a formulary list that assigns branded drugs to preferred or nonpreferred tiers (formulary decision). Drug manufacturers offer rebates to PBMs for drugs on preferred tier of formularies. The individuals participating in the client’s pharmacy benefit plan are the ones consuming the drugs and making purchasing decisions, whereas the client organization is paying the majority of drug cost. The choices of the individuals and the client organization are governed by different utility measures. For this complex drug distribution setting and for competing PBMs, we show the existence and uniqueness of a pure Nash equilibrium on aggregate formulary and price decisions, which represent the welfare-adjusted cost and welfare-adjusted price of each PBM’s plan, respectively. We characterize each PBM’s optimal formulary and equilibrium price decisions and discuss the impact of various model primitives. We apply our model to gain insights on the impact of mergers in the PBM industry.

Suggested Citation

  • Panos Kouvelis & Yixuan Xiao & Nan Yang, 2015. "PBM Competition in Pharmaceutical Supply Chain: Formulary Design and Drug Pricing," Manufacturing & Service Operations Management, INFORMS, vol. 17(4), pages 511-526, October.
    • Handle: RePEc:inm:ormsom:v:17:y:2015:i:4:p:511-526
    DOI: 10.1287/msom.2015.0542
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    References listed on IDEAS

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    Cited by:

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    4. Faghih-Roohi, Shahrzad & Akcay, Alp & Zhang, Yingqian & Shekarian, Ehsan & de Jong, Eelco, 2020. "A group risk assessment approach for the selection of pharmaceutical product shipping lanes," International Journal of Production Economics, Elsevier, vol. 229(C).
    5. Lin, Xiaogang & Chen, Danna & Zhou, Yong-Wu & Lin, Qiang, 2022. "Horizontal mergers in low carbon manufacturing," European Journal of Operational Research, Elsevier, vol. 297(1), pages 359-368.
    6. Hongmin Li & Scott Webster & Nicholas Mason & Karl Kempf, 2019. "Product-Line Pricing Under Discrete Mixed Multinomial Logit Demand," Service Science, INFORMS, vol. 21(1), pages 14-28, January.
    7. Tinglong Dai & Sridhar Tayur, 2020. "OM Forum—Healthcare Operations Management: A Snapshot of Emerging Research," Manufacturing & Service Operations Management, INFORMS, vol. 22(5), pages 869-887, September.
    8. Hongmin Li & Scott Webster, 2017. "Optimal Pricing of Correlated Product Options Under the Paired Combinatorial Logit Model," Operations Research, INFORMS, vol. 65(5), pages 1215-1230, October.
    9. Woonghee T. Huh & Hongmin Li, 2023. "Product‐line pricing with dual objective of profit and consumer surplus," Production and Operations Management, Production and Operations Management Society, vol. 32(4), pages 1223-1242, April.
    10. Yanbo Ma & Zheng Li & Kaiyue Liu & Zhengmin Liu, 2022. "Price Decision-Making in Dual-Channel Healthcare Services Supply Chain Considering the Channel Acceptance, Price Ceiling, and Public Welfare," IJERPH, MDPI, vol. 19(20), pages 1-23, October.
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    12. Pinar Keskinocak & Nicos Savva, 2020. "A Review of the Healthcare-Management (Modeling) Literature Published in Manufacturing & Service Operations Management," Manufacturing & Service Operations Management, INFORMS, vol. 22(1), pages 59-72, January.

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