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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Speaker: Chunhua Weng, Associate Professor of Biomedical Informatics, Columbia University
Date: Tuesday, January 30, 2018
Time: 03:00am – 04:15pm
Location: Klaus Advanced Computing Building, Room 2443
Title: Using Electronic Health Records to Support Patient Care and Clinical Research
Abstract: Electronic health records (EHR) contains rich clinical phenotype information. In this talk, I will present methods and early results from two projects to demonstrate the potential of using EHR data to facilitate precision medicine and optimize clinical research towards a learning health system. In project one, we developed a phenotype-driven diagnostic decision support system, where Human Phenotype Ontology (HPO) concepts were extracted from EHR narratives and used to prioritize disease genes based on the HPO-coded phenotypic manifestations. We tested this approach on 28 pediatric patients with confirmed diagnoses of monogenic diseases, and found that the causal genes were ranked among the top 100 genes out of > 25000 genes for 16/28 cases (P<2.2x10-16), demonstrating the promise of leveraging EHR data to automate phenotype-driven analysis of clinical exomes or genomes and implement genomic medicine on scale. In project two, we developed a metric called GIST, which stands for The Generalizability Index of Study Traits, to assess the population representativeness of clinical trials by using EHR data to profile the target populations for clinical trials and by comparing the study populations to the target populations. GIST enables us to improve the transparency of population representativeness of clinical studies and to help clinical researchers to make informed decisions to optimize patient selection.
Bio: Dr. Chunhua Weng is a tenured Associate Professor of Biomedical Informatics at Columbia University and an elected fellow of the American College of Medical Informatics (ACMI). She also co-leads the Biomedical Informatics Resource for the Columbia CTSA (The Irving Institute for Clinical and Translational Science). Dr. Weng holds a Ph.D. in Biomedical and Health Informatics from University of Washington at Seattle. Dr. Weng’s long-term research interest is to accelerate clinical and translational science using electronic data while minimizing study design biases and optimizing study results’ generalizability. She has been an active researcher and leader in the field of Clinical Research Informatics since 2000.
