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IMAGE: Medical director of high-risk populations and outcomes, UPMC Wolff Center; associate professor of surgery, University of Pittsburgh School of Medicine. view more
Credit: UPMC
PITTSBURGH, Feb. 8, 2021 - With the aid of sophisticated machine learning, researchers at UPMC and the University of Pittsburgh School of Medicine demonstrated that a tool they developed can rapidly predict mortality for patients facing transfer between hospitals in order to access higher-acuity care. This research, published today in
PLOS One, could help physicians, patients and their families avoid unnecessary hospital transfers and low-value treatments, while better focusing on the goals of care expressed by patients.