{"id":4602,"date":"2021-07-01T19:14:23","date_gmt":"2021-07-01T19:14:23","guid":{"rendered":"https:\/\/ubc.com\/?p=2667"},"modified":"2025-05-15T19:02:30","modified_gmt":"2025-05-15T19:02:30","slug":"ubc-best-paper-in-track-pharmasug-2021","status":"publish","type":"insights","link":"https:\/\/ubc.com\/insights\/ubc-best-paper-in-track-pharmasug-2021\/","title":{"rendered":"UBC\u2019s Research Named Best Paper In Track for PharmaSug 2021"},"content":{"rendered":"

Irene Cosmatos\u2019 and Michael Bulgrien\u2019s paper \u201cStandardizing Laboratory Data from Diverse Real-World Data\u201d was recognized as the Best Paper in the Real World Evidence\/Big Data track of PharmaSUG 2021.<\/em><\/p>\n

Every year, PharmaSUG<\/a> brings together life science and health research professionals focused on the applications of technical solutions in data analytics and regulatory support. During the Real World Evidence\/Big Data track, UBC was honored to present our approach to standardizing diverse laboratory data from electronic medical record databases.\u00a0 Diversity in the naming conventions for laboratory tests and the reporting of laboratory results presents a significant challenge for generating meaningful real-world evidence to support healthcare decision-making. UBC\u2019s Irene Cosmatos, Senior RWD Epidemiologist, and Michael Bulgrien, Senior Data Analytics Project Manager, developed the manuscript and associated presentation based on their many years of experience in designing, implementing, and evaluating real world evidence studies using global real-world databases. The manuscript was named Best Paper in this track.<\/p>\n

The recorded presentation is below, and you can also access the abstract here<\/a>.<\/p>\n