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Big Data encompasses everything from real world data such as patient records and payer information to data from clinical trials and product utilization. Harnessing relevant data can generate valuable insights for key medical, commercial and HEOR decisions.
However, the inherent costs, uneven senior management buy-in, difficulty in measuring ROI of Big Data and other challenges that come with harnessing large sets of information in varied formats have caused the pharmaceutical sector to embrace Big Data analytics slower than other industries.
As the pharmaceutical industry strives to develop big data capabilities, they are wrestling with questions such as:
Which big data projects are valuable?
What data capabilities do we need?
Should analytics be centralized or decentralized?
What is the appropriate staffing and budget levels?
What governance system or policies should be in place?
And what type of organizations are best to partner with on projects?
Best Practices, LLC undertook this study to probe these questions and current and future trends for big data utilization across medical, commercial and HEOR functions.
Most Have Centralized or Dedicated Big Data Team or Function: Half of the study participants for both the medical and HEOR segments said they have a centralized/dedicated group (Big Data team or function) to support Big Data projects. For the commercial segment, 40% said they have a centralized/dedicated Big Data group.
Majority of Each Segment Rate Internal Groups as Most Impactful Targets for Data Analysis: Internal Commercial, Medical and Development functions were rated by a majority of medical, commercial and HEOR respondents as the most impactful targets for data analysis presentations. A majority of each segment also said these internal groups were also the most frequent requestors of presentations.