Academic emergency medicine : official journal of the Society for Academic Emergency Medicine
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Artificial intelligence (AI) prediction is increasingly used for decision making in health care, but its application for adverse outcomes in emergency department (ED) patients with acute pancreatitis (AP) is not well understood. This study aimed to clarify this aspect. ⋯ The first real-time AI prediction model implemented in the HIS for predicting adverse outcomes in ED patients with AP shows favorable initial results. However, further external validation is needed to ensure its reliability and accuracy.
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Approximately 10% of emergency medical services (EMS) encounters in the United States are behavioral health related, but pediatric behavioral health EMS encounters have not been well characterized. We sought to describe demographic, clinical, and EMS system characteristics of pediatric behavioral health EMS encounters across the United States and to evaluate factors associated with sedative medication administration and physical restraint use during these encounters. ⋯ Among pediatric prehospital behavioral health EMS encounters, the use of sedative medications and physical restraint varies by demographic, clinical, and EMS system characteristics. Regional variation suggests opportunities may be available to standardize documentation and care practices during pediatric behavioral health EMS encounters.