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Parambir Dulai, MD, on Drug Specific Prediction Models for IBD Care Decision Support
Dr Dulai discusses his presentation from Digestive Disease Week on decision support tools for inflammatory bowel disease care that he and colleagues at Northwestern University developed for clinical trials to overcome issues of interpretation and actionability.
Parambir Dulai, MD, is director of GI precision medicine and clinical trials at Northwestern University in Chicago, Illinois.
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Hi, I'm Parambir Dulai, Director of GI Clinical Trials and Precision Medicine at Northwestern University here in Chicago. Welcome to DDW.
Today I'll be talking about the presentation that we gave related to prediction tools and decision support tools for ulcerative colitis and Crohn's disease in inflammatory bowel disease. One of the biggest things that we deal with, with current guidelines and decision support tools is they're often difficult to interpret, they are not necessarily actionable in the moment, and they often fail to provide opportunities to provoke future thought or future research.
So what we showed today in our presentation and at our plenary poster presentation later in the day was that we've built decision support tools from the clinical trial programs for vedolizumab, ustekinumab, and anti-TNF therapy. We validated those in routine practice and showed that they're able to predict clinical and endoscopic outcomes of importance. And then, we further defined that these tools actually allow for personalized decisions, and these prediction tools are drug-specific, allowing for an ability to understand comparative effectiveness at an individual level. Most importantly, these tools have been launched as online decision support tools through an educational initiative at www.cdstforibd.com.
And through that educational initiative, what we showed was significant uptake by providers, significant improvement in provider knowledge and comprehension, and significant changes in providers' willingness and confidence to use these therapies, and a sense that these therapies would improve outcomes for their patients. So, we hope you try the tool. We hope you try the webpage. And we appreciate the opportunity here today.
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