Multi-objective operating room scheduling considering desiderata of the surgical team

Meskens, Nadine; Duvivier, David; Hanset, Arnauld

doi:10.1016/j.dss.2012.10.019

Cited by 120 publications

(60 citation statements)

References 31 publications

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“…In their study, they focus on patients and staff as the most important stakeholders and re-organise an existing schedule which is necessary due to the arrival of an emergency patient. In contrast to the paper by van Essen et al (2012b), Meskens et al (2013) formulate a multiple-objective approach. However, both papers deal with a daily planning horizon and take into account the sequence of surgeries.…”

Section: Literature Reviewmentioning

confidence: 95%

A fuzzy multi-criteria approach for robust operating room schedules

Rachuba

Werners

2015

Ann Oper Res

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Operating room schedules are regularly influenced by uncertain demands such as unknown surgery durations or randomly arriving emergency patients. The performance of these schedules depends on the information available about these uncertainties when designing the schedules. We focus on an offline operational planning level which assigns patients to days and rooms without focusing on the intra-day sequence. A sufficient amount of time per day is to be reserved for elective and emergency surgeries. At the same time we observe that the performance of a particular schedule influences several stakeholders' interests. We therefore combine the aspects of uncertain planning parameters and multiple stakeholders' interests and investigate the performance of schedules for operating rooms using a dedicated robust multi-criteria optimisation approach. We compute a robust compromise schedule focusing on stochastic surgery times and different objectives and simultaneously reserve time windows dedicated to randomly arriving emergency demand. In order to evaluate the schedule's quality, we perform an extensive simulation study and demonstrate to what extent each robust schedule achieves the mentioned goals. In a second step, we perform a sensitivity analysis in order to investigate how significant changes in assumptions about the stochastic model parameters affect the level of achievement of the different objectives.

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Section: Literature Reviewmentioning

confidence: 95%

A fuzzy multi-criteria approach for robust operating room schedules

Rachuba

Werners

2015

Ann Oper Res

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“…Most recently, Meskens et al proposed the constraint programming paradigm to solve a complicated scheduling problem considering perhaps the most complete multiple resource constraints including ORs, surgeons, nurses, anesthetists, material, pre-operative holding units (PHU) and the post anesthesia care unit (PACU) beds. Multiple real-life resource constraints cover availability, staff preferences, and affinities among staff members [30]. Their work also indicates the importance and the efficiency of short-term surgery scheduling which integrates real-life resource constraints.…”

Section: Literature Reviewmentioning

confidence: 99%

A short-term operating room surgery scheduling problem integrating multiple nurses roster constraints

Xiang

Yin

Lim

2015

Artificial Intelligence in Medicine

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“…Multiobjective OR scheduling achieved by minimizing the makespan, minimizing overtime hours, and maximizing affinities among members of the surgical team is considered. The results achieved when using this model in a real-life situation are presented [16].…”

Section: Introductionmentioning

confidence: 98%

Clinical Pathways Scheduling Using Hybrid Genetic Algorithm

Jiang

Yang

et al. 2013

J Med Syst

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In order to improve the standard of management in hospitals and effectively control the cost of clinical treatments, this research primarily focuses on optimizing the scheduling of clinical pathways (CPs). A mathematical model for CP scheduling is constructed, and the hybrid genetic algorithm (HGA, combining a genetic algorithm with particle swarm optimization) is proposed for solving this problem so as to distribute medical resources and schedule the treatments of patients reasonably and effectively. The optimal search space can be further enlarged by introducing a new mutation mechanism, which allows a more satisfactory solution to be found. In particular, the relative patient waiting time and relative time efficiency are used as measure indexes, which are more scientific and effective than the usual indexes of absolute time and absolute time efficiency. After comparing absolute waiting time, relative waiting time, utilization of absolute waiting time, and utilization of relative waiting time waiting respectively, the conclusion can confidently be drawn that task scheduling obviously enhances patients' time efficiency, reduces time wastage and therefore promotes patient satisfaction with medical processes. Moreover, the patients can to a certain degree move away from their usual passive role in medical processes by using this scheduling system. In order to further validate the rationality and validity of the proposed method, the heuristic rules for CP scheduling are also tested using the same case. The results demonstrate that the proposed HGA achieves superior performance, in terms of precision, over those heuristic rules for CP scheduling. Therefore, we utilize HGA to optimize CP scheduling, thus providing a decision-making mechanism for medical staff and enhancing the efficiency of medical processes. This research has both theoretical and practical significance for electronic CP management, in particular.

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Multi-objective operating room scheduling considering desiderata of the surgical team

Cited by 120 publications

References 31 publications

A fuzzy multi-criteria approach for robust operating room schedules

A fuzzy multi-criteria approach for robust operating room schedules

A short-term operating room surgery scheduling problem integrating multiple nurses roster constraints

Clinical Pathways Scheduling Using Hybrid Genetic Algorithm

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