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Insights, ecosystems, and outcomes
Break down evidence barriers with ConvergeHEALTH Miner™
The health care ecosystem is in a period of unprecedented change, which has major implications for the way you develop and commercialize products. The combination of value-based reimbursement and precision medicine is directing treatment toward personalized care—and requiring a reorientation around insights, ecosystems and resultant outcomes.
What is evidence life cycle management?
An end-to-end approach to leveraging data, evidence, and knowledge assets of a life science organization that breaks down traditional siloes for evidence-driven decision making from discovery, development, and commercialization.
- Translational research: Integrate harmonized data into a standards-based central repository to deliver relevant information on-demand to researchers. Our flexible, collaborative analytics and visualization portal can help you ensure projects have the right priority of investment from early discovery to approval.
- Real-world evidence: Centralize your assets to empower knowledge management, collaboration management, and analytics to facilitate turning real world data into real world evidence to drive greater value in real time across the entire business and product life cycle.
- Portfolio and program management: Use evidence generated throughout the development process to understand the value of particular therapies for a metrics and data-driven drug program.
ConvergeHEALTH Miner provides you with the following benefits:
- Improved visibility into data assets: Your organization gains improved understanding of the datasets they have access to, a better grasp on the return on their data assets, and improved governance over their assets.
- Enhanced and expedited analysis: Democratize and expedite insight by allowing all users to explore relationships in the data with user-friendly tools. It further expedites analysis by bringing the power of cloud computing to big data analyses, such as genomic analyses.
- Greater Collaboration: By making cohort definitions consistent, allowing electronic spaces for collaboration, and improving governance workflows, researchers can increase their productivity and improve conclusions.
Evidence life cycle management
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