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Improving Access to Rare Disease Treatments: Subsidy, Pricing, and Payment Schemes

  • Wendy Olsder
  • , Tugce Martagan*
  • , Christopher Tang
  • *Corresponding author for this work
  • Eindhoven University of Technology
  • Operations Planning Acc. & Control
  • University of California Office of the President

Research output: Contribution to journalArticleAcademicpeer-review

15 Citations (Scopus)
10 Downloads (Pure)

Abstract

There are more than 7,000 known rare diseases, but pharmaceutical manufacturers developed treatments for only 500 of them. To improve the availability and accessibility of treatments for rare diseases, governments have introduced several programs including subsidies, exogenous pricing, and outcome-based payment schemes in recent years. What kind of subsidy programs and pricing mechanisms can improve patient access? Inspired by various pilot programs, we present a multistage game theoretic model to analyze different subsidy schemes proposed for rare diseases. In addition to the traditional setting in which the manufacturer sets the price, we consider an “exogenous pricing scheme” under which an independent consortium sets the price. We also examine an outcome-based payment scheme, which offers the drug for free if it is not efficacious. We formulate a four-stage Stackelberg game to determine whether it is optimal to subsidize the pharmaceutical manufacturer, the patients, or both. Our results offer several insights. First, we find that government subsidies are crucial to entice new drug development for rare diseases. Also, we find that the pricing scheme matters: The exogenous pricing scheme can improve patient welfare, but it reduces the manufacturer’s expected profit. We find that this result is robust even when an outcome-based payment scheme is used.
Original languageEnglish
Pages (from-to)5256-5274
Number of pages19
JournalManagement Science
Volume69
Issue number9
Early online date15 Dec 2022
Publication statusPublished - Sept 2023

Bibliographical note

Funding: This work was supported by the Dutch Science Foundation [Nederlandse Organisatie voor Wetenschappelijk Onderzoek VENI Talent Scheme]

Copyright: © 2022 INFORMS

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