Predicting emergency department orders with multilabel machine learning techniques and simulating effects on length of stay.
Journal:
Journal of the American Medical Informatics Association : JAMIA
Published Date:
Dec 1, 2019
Abstract
OBJECTIVE: Emergency departments (EDs) continue to pursue optimal patient flow without sacrificing quality of care. The speed with which a healthcare provider receives pertinent information, such as results from clinical orders, can impact flow. We seek to determine if clinical ordering behavior can be predicted at triage during an ED visit.