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We evaluated the AAM performance variation across medical centers and the effect of data quality errors on the AAM score using the Validation data set and the Training cutoff. We then calculated the PPV, NPV, sensitivity, specificity and c-statistic of this modified data. These scores or systems aim to identify and care for patients who present with or develop acute illness in the hospital.

Using a very large patient database, we have developed, validated and implemented an automated EWS that can be used to alert hospitalists outside the ICU as to when a patient is likely to deteriorate in the next 12 h.

The score is among the first open-source EWSs based on routinely-collected EMR data elements (including vital signs and laboratory data) to be successfully implemented in practice.