Webinar: Top 5 key NLP application areas for Payers and Health Plans

April 2, 2020
Venue: Online Webinar

When: Thursday 2nd April 2020

Time: 11:00am EDT; 8:00am PDT; 4:00pm BST; 5:00pm CEST.

Duration: 60 minutes.

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New sources of unstructured data about members are opening up for payers and health plans. Significant insights can be gained from medical records in PDF format, call center notes and EHR exports, but many of these insights are trapped in text. Enterprise Natural Language Processing (NLP) technologies extract value from these data sets, freeing the insights and features trapped in medical records to improve business processes and efficiency. 

In this webinar you will learn how NLP enables you to:

  • Power predictive and risk stratification models with disease severity and Social Determinants of Health features
  • Improve the efficiency of HEDIS quality measure extraction
  • Automate Clinical Review to reduce the manual burden of reviewing medical records
  • Support call center analytics to route, classify and track tends in calls
  • Assess the disease comorbidities associated with each member to support risk adjustment

Presenter:

Simon Beaulah, Director Healthcare, Linguamatics

Simon is responsible for Linguamatics’ healthcare products and solutions including applications in the areas of clinical risk models, population health, and medical research. Previously, Simon was Marketing Director, Translational Medicine at IDBS/InforSense where he was responsible for the company’s market analysis, product marketing and Go To Market strategy in healthcare analytics and translational medicine. Prior to IDBS, he was Director of Product Management at BioWisdom, where he was responsible for delivery of customer projects using the company’s ontology products. He also worked as a senior product manager at LION Bioscience and Synomics, and as a software developer at the UK’s Biotechnology and Biological Sciences Research Council. Simon has degrees from Aston University and Cranfield Institute of Technology.