Heart Failure Identification Algorithms Developed Using EHR Data

October 13, 2016 Share this content: “Problem lists” identified only half of the patients hospitalized with heart failure. Machine-learning algorithms can be successfully used to identify heart failure (HF) in real-time in hospitalized patients, according to research published in JAMA Cardiology. Researchers from the New York University School (NYU) of Medicine in New York City conducted a retrospective study of hospitalizations at NYU’s Langone Medical Center, with the purpose of developing algorithms that could be used to identify hospitalized patients with HF. They noted that one of the main methods of improving quality of care—“problem lists”—can be useful for case identification but are often inaccurate or incomplete.2-6 Continue Reading Below Data were collected through electronic health records (EHR), and included hospitalizations of adult patients between January 1, 2013 and February…


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