<p>The Bayer Data Generation and Observational Studies (DGOS) team has partnered longitudinally with a consistent advisor group (DGOS Council). The DGOS Council operates as an extension of the DGOS team, providing external strategic perspectives. Here, we describe Bayer’s engagement with the DGOS Council and how it contributes throughout a product’s lifecycle. We present the composition and organization of the DGOS Council, share case studies describing its relation to and impact across Bayer’s portfolio of products, and discuss bi-directional benefits to Bayer and DGOS Council members. We conclude with recommendations for best practices for an HEOR Peer Review Council model. Teaser. Bayer has partnered longitudinally with a group of strategic advisors. The relationship between Bayer and the advisors is described here as a consideration for best practice for evidence generation teams.&#xa0;</p>

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Transforming Traditional Industry Advisory Boards Into Mutually Beneficial Strategic Think Tanks: A Peer Review Council Case Series and Best Practices

  • Todd Williamson,
  • John Fox,
  • Scott Ramsey,
  • Maria Martins-Lopes,
  • Kevin M. Pantalone,
  • C. Daniel Mullins,
  • Kenneth Schaecher,
  • Sean D. Sullivan

摘要

The Bayer Data Generation and Observational Studies (DGOS) team has partnered longitudinally with a consistent advisor group (DGOS Council). The DGOS Council operates as an extension of the DGOS team, providing external strategic perspectives. Here, we describe Bayer’s engagement with the DGOS Council and how it contributes throughout a product’s lifecycle. We present the composition and organization of the DGOS Council, share case studies describing its relation to and impact across Bayer’s portfolio of products, and discuss bi-directional benefits to Bayer and DGOS Council members. We conclude with recommendations for best practices for an HEOR Peer Review Council model. Teaser. Bayer has partnered longitudinally with a group of strategic advisors. The relationship between Bayer and the advisors is described here as a consideration for best practice for evidence generation teams.