Admission predicting system using pre-arrival information in emergency departments

Abstract

In emergency departments in Japan, physicians prepare for patients using information from emergency medical technicians before their arrival. But those information were not recorded on previous electronical health record system. We constructed a database to record prearrival information and developed experimental prediction models to assess whether the patients need hospital admission or not. The prediction accuracy of the models was superior to that of human predictions. We focused on the cases which physicians correctly predicted the outcome, and the models had almost perfect concordance. Our database and prediction model may support clinical decision making in emergency department.