Shorten Cohort Definition Times for RWE/HEOR Projects with Iterative Web-speed Creation and Visual Comparison of Patient Populations


Using traditional methods, defining, analyzing, comparing, and finalizing a cohort of patients for HEOR and RWE analysis can often take months, impacting the ability to answer questions. Today, advanced technology, including AI and machine learning, enables a user to define and instantly generate a cohort including descriptive statistics such as age/gender distributions, patient counts, record counts, test, diagnosis, and Rx volumes, geographic distributions, and more. The ability to quickly adjust cohort definitions in a user-friendly format can also reduce the time it takes to understand results and their impact on the given analysis.

In this webinar, you’ll understand how advanced platform technologies can shorten the time it takes to create cohort definitions and iterate on cohort variables with output formats that meet unique business needs — such as charts, graphs, box plots, Sankey plots, and more. We’ll also look at:

  • Patient journey discovery
  • Real time cohort comparison
  • Provider relationship graphs


  • Jason Bhan, MD, Co-founder and Chief Medical Officer, Prognos Health
  • Kristian Kaufmann, PhD, Principal Data Scientist, Prognos Health

Sponsored by:

Prognos Health

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