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20 Best Practices
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The biopharmaceutical industry has seen an explosion in the availability of big data that can generate valuable insights for key Health Outcomes Research decisions.
However, the biopharmaceutical industry has been slower than other industries in embracing big data analytics due to the inherent costs, difficulty in measuring ROI of Big Data, uneven senior management buy-in and other challenges associated with harnessing large sets of information in varied formats.
As the industry recognizes the huge potential that big data holds for crucial HEOR decisions, rapid steps are being taken to develop greater big data capabilities.
Best Practices, LLC undertook this study to probe current & future trends, winning strategies and best practices for Big Data utilization across the HEOR function. The study investigates the most useful data types and sources for key HEOR decisions; governance policies and leadership and the most impactful data producers, dissemination channels and targets.
Post-Launch and Customer Segmentation Studies Most Common Big Data Projects: Six out of ten benchmark participants used post-launch studies around health outcomes. The second most highly rated reported data type is patient reported outcomes data.
§ Universe of Learning pp. 5-6
§ Big Data Team Overview and Key Study Insights pp. 7-8
§ Quantitative Key Findings pp. 9-12
II. Defining Big Data pp. 13-20
III. Data Types and Sources pp. 21-26
IV. Data Producers, Dissemination & Requestors pp. 27-31
V. Centralization pp. 32-34
VI. Governance and Leadership pp. 35-51
VII. About Best Practices, LLC pp. 52
List of Charts & Exhibits
Big Data Use in Medical, HEOR & Commercial Decision-Making