Use of Large Real-World Datasets to Improve Practice Guidelines and Clinical Study Designs in Metabolic Diseases, Upcoming Webinar Hosted by Xtalks
In this free webinar, attendees will gain insights into the depth and breadth of the Labcorp database and its potential uses and understand how real-world data can support and improve clinical guideline development and adherence. The featured speakers will discuss how large clinical datasets can improve efficiency of patient enrollment in metabolic disease research and how partnerships within healthcare can increase adoption of standards of care and drive medical innovation.
TORONTO, Aug. 16, 2021 /PRNewswire-PRWeb/ -- Over the last decade, the collection and analysis of personal medical data has expanded and has been applied to understand population health parameters, trends and individual preferences. Practically speaking, these data can provide insights to help drive improvements in healthcare delivery. In this webinar, we will highlight the Labcorp clinical data set—a massive resource containing more than 30 billion clinical laboratory test results—and how it might provide such insights and validation. Importantly, we will also discuss how these datasets can provide actionable implementation, in particular how organizations such as AMGA are providing solutions to improve health and healthcare by serving as a catalyst and collaborator within health systems, addressing concerns of population health, resource needs and standards of care.
Join expert speakers from Labcorp Drug Development, Dara Schuster, MD., Senior Medical Director, Global Clinical Development and Barry J. Goldstein, MD, PhD, Vice President and Therapeutic Area Head, Cardiovascular, Metabolic, Endocrine and Renal, as well as John W. Kennedy, MD, President, AMGA Foundation, Chief Medical Officer, AMGA in a live webinar on Thursday, September 2, 2021 at 11am EDT (4pm BST/UK).
For more information, or to register for this event, visit Use of Large Real-World Datasets to Improve Practice Guidelines and Clinical Study Designs in Metabolic Diseases.
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