PREDICTING WORKPLACE VIOLENCE IN THE EMERGENCY DEPARTMENT BASED ON ELECTRONIC HEALTH RECORD DATA

Introduction: Emergency departments are extremely able to workplace violence, and emergency frequently exposed to workplace violence. We developed place violence prediction models using machine methods based on data from electronic health records. Methods: This study was conducted using electronic record data collected between January 1, 2016 and 31, 2021. Workplace violence cases were identified violence-related mentions in nursing records. violence was predicted using various factors emergency department visit and stay. Results: The dataset included 1215 workplace violence and 6044 nonviolence cases. Random Forest showed performance among the algorithms adopted in this place violence was predicted with higher accuracy ED visit and ED stay factors were used as predictors 95% confidence interval 0.898-0.912) than when factors were used. When both ED visit and ED stay factors were included for prediction, the strongest predictor of risk of WPV was patient dissatisfaction, followed by high average daily length of stay, high daily number of patients, and symp- toms of psychiatric disorders. Discussion: This study showed that workplace violence could be predicted with previous data regarding ED visits and stays documented in electronic health records. Timely prediction and mitigation of workplace violence could improve the safety of emergency nurses and the quality of nursing care. To prevent workplace violence, emergency nurses must recognize and continuously observe the risk factors for workplace violence from admission to discharge.