ConvergeHEALTH Miner™ Evidence

Real-world data and analytics at scale in the life sciences industry

ConvergeHEALTH Miner™ Evidence is an award-winning platform transforming how real-world data and digital health data is managed, analyzed, and shared across the product life cycle. Learn how this end-to-end approach is accelerating medical innovations.

Why ConvergeHEALTH Miner™ Evidence?

Transform how digital health data is managed, analyzed, and shared

Using analytics to generate evidence-based insights from real-world data and other digital health data is transforming how pharma companies approach drug development. At the same time, the volume of health care data is growing at a staggering rate. To keep pace, life sciences organizations need an end-to-end capability that can help address these fundamental challenges:

How do we effectively manage the growing number of digital health data sources?
How can we rapidly generate insights from this data?
How can we act on these insights?
How can we empower more stakeholders to leverage this data and apply evidence-based insights across the drug life cycle?

ConvergeHEALTH Miner Evidence is a market-proven, cloud-based platform designed to help transform how patient-level data (e.g., real-world data (RWD), patient registry, clinical trials, omics/biomarker data etc.) is managed, analyzed, and shared across the product life cycle. This enables organizations to dramatically decrease the cycle time for insight and evidence generation, foster collaboration, and amplify the impact of these insights and evidence.

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Download the overview

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The benefits

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Breaks down traditional silos and creates efficiencies by providing a marketplace experience across the enterprise, customizable workflows govern data access and streamline analytics processes

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Decreases time to generate insights and evidence with a comprehensive set of intuitive, self-service analytical applications

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Drives innovation using an open architecture, microservices, and APIs that accelerate custom application development and allow integration of third-party tools

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04

Fosters collaboration and knowledge-sharing via a user-centric design tailored to multiple personas, from business users to researchers to data scientists

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Data at scale

Enables the exploration of available data (e.g., RWD, randomized controlled trails molecular, etc.) and studies evidence/results with the controls and governance for access across the enterprise

Analytics at scale

Enables a broader set of users to analyze data with a comprehensive set of statistical tools and self-service applications

Collaboration at scale

Accelerates development of new applications to meet the rapidly evolving needs of the business

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Podcasts

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Podcast: The Past, Present, and Future of Real World Data in the Pharma Industry With Karla Feghali of Deloitte

Podcast: Learning How Combining RCTs and RWD Helps With Patient Outcomes Featuring Seshamalini Srinivasan, Laura Fernandes, and Karla Feghali

Podcast: Identifying fit-for-purpose databases within clinical oncology research

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