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Journal articles on the topic 'Master surgical scheduling'

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Author: Grafiati

Published: 10 March 2023

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1

van Oostrum, Jeroen M., Tessa Parlevliet, Albert P. M. Wagelmans, and Geert Kazemier. "A Method for Clustering Surgical Cases to Allow Master Surgical Scheduling." INFOR: Information Systems and Operational Research 49, no. 4 (November 2011): 254–60. http://dx.doi.org/10.3138/infor.49.4.254.

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2

van Oostrum, Jeroen M., M. Van Houdenhoven, J. L. Hurink, E. W. Hans, G. Wullink, and G. Kazemier. "A master surgical scheduling approach for cyclic scheduling in operating room departments." OR Spectrum 30, no. 2 (September 21, 2006): 355–74. http://dx.doi.org/10.1007/s00291-006-0068-x.

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3

Britt, Justin, M. Fazle Baki, Ahmed Azab, Abderrahmane Chaouch, and Xiangyong Li. "A stochastic hierarchical approach for the master surgical scheduling problem." Computers & Industrial Engineering 158 (August 2021): 107385. http://dx.doi.org/10.1016/j.cie.2021.107385.

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4

van Oostrum, Jeroen M., Eelco Bredenhoff, and Erwin W. Hans. "Suitability and managerial implications of a Master Surgical Scheduling approach." Annals of Operations Research 178, no. 1 (August 27, 2009): 91–104. http://dx.doi.org/10.1007/s10479-009-0619-z.

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5

Patrão, Rafael L., Reinaldo C. Garcia, and João M. da Silva. "An Integrated Two-Level Integer Linear Program (ILP) Model for Elective Surgery Scheduling: A Case Study in an Italian Hospital." Mathematics 10, no. 11 (June 1, 2022): 1901. http://dx.doi.org/10.3390/math10111901.

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The urban population is increasing worldwide. This demographic shift generates great pressure over public services, especially those related to health-care. One of the most expensive health-care services is surgery, and in order to contain this growing cost of providing better services, the efficiency of surgical centers must be improved. This work proposes an integer linear programming model (ILP) considering the case-mix planning (CMP) and the master surgical scheduling (MSS) problems. The case-mix planning problem deals with the planning of the number of operating rooms to be assigned to surgical specialties. The master surgical scheduling is related to when to assign the rooms to the different specialties. The developed model uses a data set from a hospital of the city of Turin, Italy. The results are very promising, showing a reduction from 240 weeks to 144 weeks to empty the surgical waiting list (WL). Moreover, if changes to the hospital situation are implemented, including the introduction of two new surgical teams into one of the hospital’s specialties, the time to empty the surgical WL could decrease to 79 weeks.

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6

Azab, Ahmed, Mohammed Fazle Baki, Justin Britt, and Xiangyong Li. "Stochastic Goal Programming and Metaheuristics for the Master Surgical Scheduling Problem." International Journal of Operational Research 1, no. 1 (2020): 1. http://dx.doi.org/10.1504/ijor.2020.10035229.

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7

Britt, Justin, Xiangyong Li, Ahmed Azab, and Mohammed Fazle Baki. "Stochastic goal programming and metaheuristics for the master surgical scheduling problem." International Journal of Operational Research 43, no. 1/2 (2022): 5. http://dx.doi.org/10.1504/ijor.2022.121492.

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8

Banditori, C., P. Cappanera, and F. Visintin. "A combined optimization-simulation approach to the master surgical scheduling problem." IMA Journal of Management Mathematics 24, no. 2 (January 17, 2013): 155–87. http://dx.doi.org/10.1093/imaman/dps033.

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9

M'Hallah, Rym, and Filippo Visintin. "A stochastic model for scheduling elective surgeries in a cyclic Master Surgical Schedule." Computers & Industrial Engineering 129 (March 2019): 156–68. http://dx.doi.org/10.1016/j.cie.2019.01.030.

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10

Cappanera, Paola, Filippo Visintin, and Carlo Banditori. "Comparing resource balancing criteria in master surgical scheduling: A combined optimisation-simulation approach." International Journal of Production Economics 158 (December 2014): 179–96. http://dx.doi.org/10.1016/j.ijpe.2014.08.002.

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11

Visintin, Filippo, Paola Cappanera, and Carlo Banditori. "Evaluating the impact of flexible practices on the master surgical scheduling process: an empirical analysis." Flexible Services and Manufacturing Journal 28, no. 1-2 (November 28, 2014): 182–205. http://dx.doi.org/10.1007/s10696-014-9208-9.

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12

Lu, Qian, Xiaomin Zhu, Dong Wei, Kaiyuan Bai, Jinsheng Gao, and Runtong Zhang. "Multi-phase and Integrated Multi-objective Cyclic Operating Room Scheduling Based on an Improved NSGA-ⅡApproach." Symmetry 11, no. 5 (April 26, 2019): 599. http://dx.doi.org/10.3390/sym11050599.

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The operating room (OR) is an important department in a hospital, and the scheduling of surgeries in ORs is a challenging combinatorial optimization problem. In this paper, we address the problem of multiple resource allocation of ORs and propose a surgery scheduling scheme for OR units. To solve this problem, a multi-phase and integrated multi-objective linear programming model is proposed. The first phase of the proposed model is a resource allocation model, which mainly focuses on the allocation of ORs for each surgical specialty (SS). Based on the results of the first phase, the second phase is the cyclic Master Surgical Schedule model, which aims to schedule the surgeries in each SS. The proposed models are solved by the Non-dominated Sorting Genetic Algorithm II (NSGA-II), which was improved. Finally, two numerical experiments based on practical data are provided to verify the effectiveness of the proposed models as well as to evaluate the performance of the improved NSGA-II. Our final results illustrate that our proposed model can provide hospital managers with a series of “optimal” solutions to effectively allocate relevant resources and ORs for surgeries, and they show that the improved NSGA-II has high computational efficiency and is more suitable in solving larger-scale problems.

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13

Atighehchian, Arezoo, and Mohammad Ebrahimi. "Design of a mathematical model and a simulation-optimization approach for master surgical scheduling considering uncertainty in length of stay, demands and duration of surgery." International Journal of Industrial and Systems Engineering 1, no. 1 (2021): 1. http://dx.doi.org/10.1504/ijise.2021.10041644.

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14

Yip, Kenneth, Louisa Leung, and Deacons Yeung. "Levelling bed occupancy: reconfiguring surgery schedules via simulation." International Journal of Health Care Quality Assurance 31, no. 7 (August 13, 2018): 864–76. http://dx.doi.org/10.1108/ijhcqa-12-2017-0237.

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Purpose The purpose of this paper is to present simulation modelling to reconfigure a 700-bed Hong Kong hospital’s master surgery schedule (MSS), aiming to improve patient flow, capacity management and resource allocation through levelling bed occupancy within the hospital. Design/methodology/approach A discrete-event simulation model was developed to understand how changes to the MSS would affect bed occupancy, thereby providing business intelligence for short- and long-term hospital planning. A decision tool was subsequently developed for hospital managers to test different scenarios. Findings Simulation modelling showed that significant bed occupancy levelling could be achieved through small and practicable changes to the MSS. Optimisation routines conducted using the simulation model then gave additional insights into how the schedule should be revamped for the long term. Practical implications The authors show how operations research methods are useful for guiding hospital operational planning. The authors show that a data-driven and evidence-based model enables hospital managers to critically explore various scheduling changes, while also providing a scientific common ground for discussion among important stakeholders. It is a crucial step forward when adopting advanced analytics for Hong Kong hospital operational planning. Originality/value The authors provide a robust method for evaluating the relationship between Hong Kong hospital’s MSS and its bed occupancy. Through simulating various changes to the surgical schedule, valuable and practicable insights were made available for hospital managers to make short- and longer-term changes that enhance the system’s overall efficiency and service quality.

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15

Shafaei, Rasoul, and Ashkan Mozdgir. "Master Surgical Scheduling Problem with Multiple Criteria and Robust Estimation." Scientia Iranica, May 1, 2018, 0. http://dx.doi.org/10.24200/sci.2018.20416.

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