Assessing Revisit Risk in Emergency Department Patients: Machine Learning Approach.
Journal:
JMIR AI
Published Date:
Aug 7, 2025
Abstract
BACKGROUND: Overcrowded emergency rooms might degrade the quality of care and overload the clinic staff. Assessing unscheduled return visits (URVs) to the emergency department (ED) is a quality assurance procedure to identify ED-discharged patients with a high likelihood of bounce-back, to ensure patient safety, and ultimately to reduce medical costs by decreasing the frequency of URVs. The field of machine learning (ML) has evolved considerably in the past decades, and many ML applications have been deployed in various contexts.
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