Prioritizing and queueing the emergency departments’ patients using a novel data-driven decision-making methodology, a real case study

作者：

Highlights：

• The Emergency department patients are classified based on their health condition.

• Four classes are considered: emergent, urgent, non-urgent, self-care.

• The patient’s queue is optimized using a mathematical model after classification.

• A real-life case study is proposed.

摘要

•The Emergency department patients are classified based on their health condition.•Four classes are considered: emergent, urgent, non-urgent, self-care.•The patient’s queue is optimized using a mathematical model after classification.•A real-life case study is proposed.

论文关键词：Data Mining,Queueing Systems,COVID-19,Classification,Grasshopper Optimization Algorithm

论文评审过程：Received 8 March 2021, Revised 9 December 2021, Accepted 17 January 2022, Available online 30 January 2022, Version of Record 1 February 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.116568