Operating room scheduling for non-operating room anesthesia with emergency uncertainty

被引:10
作者
Wang, Jian-Jun [1 ]
Dai, Zongli [1 ]
Zhang, Wenxuan [1 ]
Shi, Jim Junmin [2 ]
机构
[1] Dalian Univ Technol, Sch Management & Econ, Dalian 116024, Peoples R China
[2] New Jersey Inst Technol, Martin Tuchman Sch Management, Newark, NJ 07102 USA
基金
美国农业部; 中国国家自然科学基金;
关键词
Operating room scheduling; Non-operating room anesthesia; Emergency patients; Heuristic algorithm; ELECTIVE SURGERIES; STOCHASTIC-MODEL; WAITING TIME; CHALLENGES; ASSIGNMENT;
D O I
10.1007/s10479-022-04870-6
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
How to improve the efficiency of operating rooms (ORs) has always been a challenging problem in the context of healthcare operations management. This paper focuses on the research of operating room scheduling under non-operatingroomanesthesia (NORA) mechanism, in the presence of the uncertainty of emergency arrivals. In particular, we examine the advantages of the NORA mechanism in comparison with traditional surgical anesthesia practice under different operating room settings. Operationally, the process is comprised of two stages: (1) initial scheduling and (2) rescheduling. In the first stage, the initial schedule for elective surgeries under NORA is first performed through our developed model. With experiments, it is shown that for different operating room settings, the NORA mechanism can significantly improve the operating room utilization in comparison with the traditional OR anesthesia process. In the second stage of rescheduling, our experiment results show that the rescheduling model can effectively address the disruptions caused by the random arrival of emergency patients.
引用
收藏
页码:565 / 588
页数:24
相关论文
共 50 条
[41]   A multi-objective ACO for operating room scheduling optimization [J].
Wei Xiang .
Natural Computing, 2017, 16 :607-617
[42]   Operating room and surgical team members scheduling: A comprehensive review [J].
Aktas, Esra ;
Atmaca, Hatice Ediz ;
Akbulut, Hatice Erdogan .
JOURNAL OF PROJECT MANAGEMENT, 2024, 9 (02) :149-162
[43]   A multi-objective ACO for operating room scheduling optimization [J].
Xiang, Wei .
NATURAL COMPUTING, 2017, 16 (04) :607-617
[44]   Operating Room Pooling and Parallel Surgery Processing Under Uncertainty [J].
Batun, Sakine ;
Denton, Brian T. ;
Huschka, Todd R. ;
Schaefer, Andrew J. .
INFORMS JOURNAL ON COMPUTING, 2011, 23 (02) :220-237
[45]   Efficiency and scheduling in the nonoperating room anesthesia suite: implications from patient satisfaction to increased revenue operating room: a common (Dollars and Sense) approach [J].
Navidi, Bijan ;
Kiai, Kianusch .
CURRENT OPINION IN ANESTHESIOLOGY, 2019, 32 (04) :498-503
[46]   Reformulation, linearization, and decomposition techniques for balanced distributed operating room scheduling [J].
Roshanaei, Vahid ;
Luong, Curtiss ;
Aleman, Dionne M. ;
Urbach, David R. .
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, 2020, 93
[47]   A Study of Operating Room Scheduling That Integrates Multiple Quantitative and Qualitative Objectives [J].
Chen, Chung-Kuang ;
Lin, Cecilia ;
Hou, Tung-Hsu ;
Wang, Shu-Hui ;
Lin, Hong-Mau .
JOURNAL OF NURSING RESEARCH, 2010, 18 (01) :62-74
[48]   Development and implementation of an operating room scheduling tool: an action research study [J].
Visintin, Filippo ;
Cappanera, Paola ;
Banditori, Carlo ;
Danese, Pamela .
PRODUCTION PLANNING & CONTROL, 2017, 28 (09) :758-775
[49]   A prediction-optimization approach to surgery prioritization in operating room scheduling [J].
Ahmed, Abdulaziz ;
He, Lu ;
Chou, Chun-an ;
Firouz, Mohammad ;
Hamasha, Mohammad M. .
JOURNAL OF INDUSTRIAL AND PRODUCTION ENGINEERING, 2022, 39 (05) :399-413
[50]   Effect the Number of Reservations on Implementation of Operating Room Scheduling with Genetic Algorithm [J].
Timucin, Tunahan ;
Birogul, Serdar .
ARTIFICIAL INTELLIGENCE AND APPLIED MATHEMATICS IN ENGINEERING PROBLEMS, 2020, 43 :252-265