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"Better Device Outcomes Through Better Data"

How timely, complete and clean data from EHRs can accelerate device research

Medical device companies face a unique challenge when attempting to study product performance post-launch – today’s real-world data (RWD) has a significant lack of detail on device use in clinical practice and related outcomes. Medical claims and registry data lack detailed information about device types and brands.

Pharma companies have used RWD derived from electronic health records (EHRs) to access clinical care and outcomes data at a growing rate over the last decade. However, the same data has not historically been useful for medical device research due to three key challenges:

• Lack of device specifics: Device data capture is not standardized and lacks brand-level and device-specific identifiers.
• EHR data is messy and hard to analyze: While rich in clinical detail, EHR data is incredibly fragmented, especially when aggregating across healthcare organizations.
• Critical information is hidden in clinician notes: A researcher is more likely to find vital details in clinical and surgical notes, but making data from unstructured free-text fields research-ready requires advanced technology.

Learn how to address each of these challenges with the most timely, complete, and clean EHR data that includes more than 150,000 unique devices and close to 13,000 device brands across 1,600 manufacturers in this whitepaper.

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