Affiliation:
1. Clemson University, SC
Abstract
Hospitals are plagued with a multitude of logistical challenges amplified by a time-sensitive and high intensity environment. These conditions have resulted in burnout among both doctors and nurses as they work tirelessly to provide critical care to patients in need. We propose a new machine-learning-powered matching mechanism that manages the surgeon-nurse-patient assignment process in an efficient way that saves time and energy for hospitals, enabling them to focus almost entirely on delivering effective care. Through this design, we show how incorporating artificial intelligence into management systems enables teams of all sizes to meaningfully coordinate in highly chaotic and complex environments.
Subject
General Medicine,General Chemistry
Cited by
3 articles.
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