On November 4, 2022 Flatiron Health reported their attendance and presence at the ISPOR, The Professional Society for Health Economics and Outcomes Research Europe 2022 Conference, held in Vienna, Austria this year (Press release, Flatiron Health, NOV 4, 2022, View Source [SID1234623143]). A total of 7 presentations will be presented by Flatiron, including one oral podium presentation and one in-person poster being recognized as top 5% finalists for 2022 Research Presentation Awards. Research presented at this year’s ISPOR Europe represents an important milestone in Flatiron Health’s growth and leadership within real-world evidence and clinical research, as learnings from the experiences of every person with cancer in the US begin to inform and improve the lives of people living with cancer in many other parts of the world.

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"The quality of our research being presented at this year’s ISPOR Europe demonstrates our commitment to use data for good," said Javier Jimenez, Flatiron Chief Medical Officer. "Flatiron is dedicated to thoughtful and rigorous generation of EHR-derived real-world evidence, and innovating machine learning technologies to learn from every person with cancer."

Highlights include:

an oral podium presentation using machine learning to accelerate outcomes research, replicating and comparing results to health outcomes studies using a traditional abstraction approach.
a poster on real-world radiology imaging data with an assessment of the representativeness of scan-derived cohorts relative to a broader population of patients living with advanced non-small cell lung cancer and DLBCL.
a poster presentation replicating comparative-effectiveness findings with machine learning extracted variables as an alternative to expert-abstracted data in patients with metastatic non-small cell lung cancer.
a workshop featuring Flatiron Health researcher, Corey Benedum, discussing the use of real-world data at scale, specifically focusing on how machine learning extraction of information from unstructured documents can enable learnings from all patients.