Mining Unstructured EHR Data: Generate more effective real-world evidence by accessing the language of clinicians

Although a growing number of studies incorporate real-world data (RWD), pharma companies have only scratched the surface of its potential.

That’s because most healthcare data is unstructured and difficult to analyze and use.

What if we could bring structure to the unstructured?

With sophisticated natural language processing (NLP) techniques, pharma can gain access to unstructured clinicians’ notes, clinical outcome assessments and other freeform text. That information unlocks a virtual treasure chest of information that can be used to improve and enhance drug development and commercial activities.

Download the white paper to discover:

• The treatment-related insights you can find in unstructured textual data

• How pharma can benefit from more contextual patient information  

• Why clinician and data scientist oversight is critical for precise RWD output

• How Veradigm uses proprietary NLP models to extract clinical insights from unstructured EHR data