Big Data in Pharma: Structure and Governance for Big Data Utilization across Health Outcomes Research Functions

STUDY OVERVIEW

The availability of a wealth of data across varied sources - the foundation of Big Data - has provided an opportunity for the biopharmaceutical industry to generate valuable insights for HEOR functions. However, the inherent costs and other challenges have caused the biopharmaceutical sector to embrace Big Data analytics slower than other industries.

Best Practices, LLC undertook this study to better understand the structure and governance approaches the biopharmaceutical sector is taking for Big Data utilization across Health Outcomes Research functions. In addition, the study investigates the types of Big Data studies, the most valued partnerships and the policies that companies are using as they move to a more analytically based approach to medical decisions.

KEY TOPICS

• Types of Big Data Projects Used to Support Medical, Commercial and HEOR Decisions
• Big Data Capabilities and Governance
• Value Rating of Partnerships on Big Data Projects
• Policies and Procedures Governing Big Data Activities

• Do you have a centralized/dedicated group to support Big Data projects?
• When do you expect to establish a Big Data team?
• Functions in North America that utilize and/or lead Big Data projects
• Who has responsibility for these 8 Big Data capabilities at your company?
• Will your company increase its expertise for these 9 Big Data capabilities?
• Will your company internally increase its expertise for these 9 Big Data capabilities
• Which partners are the most valuable for Big Data projects?
• Indicate the policies that are in place to govern Big Data activities
• Indicate the maturity level of 9 Big Data capabilities.
• Types of Big Data projects used to support medical decisions
• Rank these Big Data applications by the amount of use within your organization

• A majority of participants said that partnerships with payers and data aggregators were highly impactful. Health systems were also seen as valuable partners by each of the three segments.
• Six out of ten benchmark participants use post-launch studies around health outcomes. The second most highly rated reported data type is patient reported outcomes data.
  

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