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Responses of Staff Nurses to an EMR-Based Clinical Decision Support Service for Predicting Inpatient Fall Risk
1Department of Nursing, Inca University, Incheon, Republic of Korea.
Abstract:
Wide spread of electronic medical records provide an opportunity to use time-variant longuitudinal data near real time. Hospital nurses would benefit greatly from the ability to use such data to predict adverse event risks of individual patient. We have developed an clinical decision support service to predict inpatient falling using machine learning and clinical big data approach. This study reports the initial responses of nurses to the service in an acute care setting.
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