Emergency Department Online Patient-Caregiver Scheduling

H. Rosmarin, A. Rosenfeld, S. Kraus

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Emergency Departments (EDs) provide an imperative source of medical care. Central to the ED workflow is the patient-caregiver scheduling, directed at getting the right patient to the right caregiver at the right time. Unfortunately, common ED scheduling practices are based on ad-hoc heuristics which may not be aligned with the complex and partially conflicting ED's objectives. In this paper, we propose a novel online deep-learning scheduling approach for the automatic assignment and scheduling of medical personnel to arriving patients. Our approach allows for the optimization of explicit, hospital-specific multi-variate objectives and takes advantage of available data, without altering the existing workflow of the ED. In an extensive empirical evaluation, using real-world data, we show that our approach can significantly improve an ED's performance metrics.
Original languageAmerican English
Title of host publicationAAAI Conference on Artificial Intelligence
StatePublished - 2019

Bibliographical note

Place of conference:Honolulu, Hawaii, USA


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