Proactively identifying patients who are showing signs of deterioration is critical to preventing morbidity and mortality for acute care patients. Predictive models, which use statistical analysis to find patterns, can take in a vast amount of data and quickly turn it into actionable information about individual patient risk for clinicians. Studies show that by considering more data points than traditional methods, on top of learning from patient and population data, models can offer more personalized and accurate predictions.
Novant Health New Hanover Regional Medical Center deployed and operationalized Epic’s Deterioration Index, a predictive algorithm that uses data like demographic information and lab results in its score calculation to proactively identify patients at risk of deterioration.
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