Maryland Smith researchers will conduct data-driven research into treating a condition associated with opioid addiction as part of a joint, UMD cross-campus initiative with the University of Maryland, Baltimore.
Interim Dean and Robert H. Smith Dean’s Chair of Information Systems Ritu Agarwal and Assistant Professor of Management Science and Statistics Margrét Bjarnadóttir will conduct a study titled “Precision Therapy for Neonatal Opioid Withdrawal Syndrome.” They will be joined in the investigation by UMB School of Medicine researchers. It’s one of multiple studies in the joint effort, which according to its announcement via UMD Right Now “seeks to solve big health care challenges through joint research that draws on the institutions’ world leading expertise in medicine and artificial intelligence.”
The Agarwal-Bjarnadóttir team will look to improve clinical decision making in the treatment of neonatal opioid withdrawal syndrome (NOWS). “The opioid epidemic has led to dramatic increases in prenatal opioid exposure,” say the researchers in the original announcement. “Our current tools do not allow us to predict which babies will develop withdrawal or how they will respond to treatment.”
The team will develop clinical and genomic biomarkers to predict withdrawal and treatment response in a unique, racially diverse cohort at the University of Maryland Medical Center and affiliated hospitals.
Agarwal, founding director of the Center for Health Information and Decision Systems (CHIDS), has published more than 100 papers in top academic journals and testified before government agencies, including the U.S. Department of Health. She has collaborated with Fortune 500 companies such as Cisco Systems, Johnson & Johnson, and Pfizer, and recently completed a six-year term as editor-in-chief of Information Systems Research, one of the world’s top academic journals in information systems.
Bjarnadóttir specializes in operations research methods using large scale data. Her research centers on data-driven decision making, combining optimization modeling with data analytics. In healthcare, she specializes in decision modeling using EMR and claims data. Her recent papers include: “Aiding the Prescriber,” which focuses on risk modeling for improved opioid prescriptions, and “Predicting Colorectal Cancer Mortality,” which utilizes EMR and Cancer Registry data to build decision support tools. Examples of other applications include drug surveillance design, practice patterns and patient targeting.