CHOP Clinical Informatics Fellows Tobias and Muthu Take Top Prize National Health Data Challenge

Washington, DC – The “Closing the Data Divide” Virtual Challenge, a nationwide search for technology-based solutions to facilitate data exchange between health care providers and public health agencies, has named a winner: “PHRASE,” or the Population Health Risk Assessment Support Engine. PHRASE was developed by Marc Tobias, MD, and Naveen Muthu, MD, both physicians and Clinical Informatics Fellows at the Children’s Hospital of Philadelphia (CHOP). The Closing the Data Divide Virtual Challenge was jointly sponsored by the de Beaumont Foundation, which seeks to transform the practice of governmental public health, and the Practical Playbook, which works to increase collaboration between public health and primary care.

PHRASE is an electronic health record (EHR)-agnostic system designed to identify at-risk populations and provide clinical decision support to health care providers at the point of care. PHRASE allows for a two-way flow of data: public health provides timely updates about evolving disease and patient risk factors through the system, while clinicians consume these recommendations in the EHR and utilize one-click reporting of disease cases back to the public health department.

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Big Data Algorithm Aids Discovery of “DNA Scrunching”s

Philadelphia, March 4, 2016 - AA bioinformatics group from CHOP collaborated with researchers from Rutgers University to uncover details of an essential process in life: how a crucial enzyme locates the site on DNA where it begins to direct the synthesis of RNA.

"The algorithms we developed enable us to tackle many questions across diverse areas of DNA and RNA biology," said Deanne Taylor, PhD, director of bioinformatics in the Department of Biomedical and Health Informatics at CHOP and research assistant professor of Pediatrics at the University of Pennsylvania. "Understanding these fundamental processes may help in developing antimicrobial treatments to fight bacterial disease."

Dr. Taylor co-authored the study, which was published online this week in the journal Science.

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New CHOP Center Harnesses "Big Data" to Help Little Patients

Philadelphia, January 26, 2016 - A new scientific center at The Children’s Hospital of Philadelphia (CHOP) aims to harness and broadly share biomedical information to more quickly benefit child patients. The Center for Data Driven Discovery in Biomedicine (D3b) has the goal of advancing precision medicine—helping to match the most appropriate treatment to individual patients.
"The genomics revolution ushered in by the first sequencing of the human genome early last decade is a watershed moment in discovery, opening up ever-growing paths to new disease treatments," said Adam Resnick, PhD, an expert in brain tumors and founding director of the new center. "However, the challenge of 'big data' lies in accessing, harnessing and sharing this flood of information, especially for pediatrics."

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Proband Pedigree Drawing iPad App from CHOP’s Center for Biomedical Informatics Debuts

Philadelphia, March 21, 2014 - Long before next-generation sequencing technology ushered in today’s data-intensive era of human genome information, clinicians have been taking family histories by jotting down pedigrees: hand-drawn diagrams recording how diseases may recur across generations, and offering clues to inheritance patterns.

CBMi, CHOP, Among Recipients of an NHGRI Four-Year Clinical Sequencing Exploratory Research Project Award

Philadelphia, Dec. 6, 2011 - The Children’s Hospital of Philadelphia is one of five U.S. centers, and the only one focusing on pediatrics, to receive a new four-year Clinical Sequencing Exploratory Research Project award. Children’s Hospital will receive $2.2 million per year for four years. The National Human Genome Research Institute (NHGRI) announced the grant today as part of an intensified focus on the medical applications of its flagship Genome Sequencing Program.

As part of the grant, CBMi's project "Sequencing, Analysis and Interpretation of Sequencing Data" aims to build a framework for systematically assessing the gene sequence data we collect, to integrate the data with medical care.

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