A stochastic hierarchical approach for the master surgical scheduling problem

Britt, Justin; Baki, Mohammed Fazle; Azab, Ahmed; Chaouch, A.B.; Li, Xiangyong

doi:10.1016/j.cie.2021.107385

Cited by 16 publications

(23 citation statements)

References 61 publications

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“…Require human intervention for solution. [50,65,66,73]. Two papers have a horizon length of more than 365 days [49,63].…”

Section: Author Contribution Applicability Of the Findings/resultsmentioning

confidence: 99%

“…We identified that the most common type of surgery group is the medical specialities associated with the surgeries used in 19 papers [14,25,[49][50][51][52][53][55][56][57][58][59][60][61][62][63][64]. In contrast, other researchers assigned surgeons, which enabled them to consider surgeons' availability and preferences [50,[65][66][67][68][69][70][71]. Meanwhile, Schneider et al [54] and Abedini et al [18] schedule clustered surgery groups according to their length of stay (LoS) and surgery duration.…”

Section: Types Of Surgery Groupmentioning

confidence: 99%

“…Not considered elective patients to non-elective blocks shift for high urgent cases. [65] Hierarchical approach to solving MSSP, Hybrid VNS-GA and Late Acceptance Hill Climbing.…”

Section: Types Of Surgery Groupmentioning

confidence: 99%

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Research Trends in the Optimization of the Master Surgery Scheduling Problem

et al. 2022

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The Master Surgery Scheduling Problem (MSSP) allocates operating theatre time to surgery groups such as medical specialities or surgeons, which is essential for daily operational planners. Many researchers have highlighted issues in the optimization of surgical scheduling problems. However, most recent reviews limited the issues at the operational level and excluded the problem characteristics such as surgery group type and schedule cyclicity. This study aims to review the state-of-the-art of MSSP and identify new trends in optimization strategies (problem characteristics and objective function), uncertainty scheduling factors (types and approaches), and solution and evaluation methods. These aspects are the key components in developing an effective MSSP optimization model. This paper reviews articles published between 2000 and 2021 that addressed MSSP, concentrating on papers between 2016 and 2021. We underlined the popularity of medical specialities as the surgery group, one-week horizon length, a cyclic schedule, multi-objective optimization and evaluation by benchmarking. The analysis shows that surgery duration is the most prominent uncertainty type, while strategies for handling this are stochastic programming, robust optimization, and fuzzy programming. We highlighted the role of heuristic approaches in addressing the MSSP's computational complexity. This review's trends, challenges, and potential solutions are essential for future researchers in developing optimization models for MSSP.

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“…Require human intervention for solution. [50,65,66,73]. Two papers have a horizon length of more than 365 days [49,63].…”

Section: Author Contribution Applicability Of the Findings/resultsmentioning

confidence: 99%

Section: Types Of Surgery Groupmentioning

confidence: 99%

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Research Trends in the Optimization of the Master Surgery Scheduling Problem

et al. 2022

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“…Marques et al [ 25 ] combine the strategic and tactical level by introducing case mix planning into the development of a new MSS while considering two downstream units. Britt et al [ 8 ] present a hierarchical approach consisting of seven goals: minimizing idle time, variations of assignments to surgeons across weekdays, the total number of expected patients in the recovery ward, variations in the recovery ward utilization, differences from planned and realized surgeries all while meeting external waiting time targets. Our approach is to level the workload in downstream units while maintaining the current MSS to earn the support of all involved medical specialties for the implementation of the new surgery scheduling policy.…”

Section: Literature Overviewmentioning

confidence: 99%

Balancing control and autonomy in master surgery scheduling: Benefits of ICU quotas for recovery units

Heider

Schoenfelder

Koperna

et al. 2022

Health Care Manag Sci

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When scheduling surgeries in the operating theater, not only the resources within the operating theater have to be considered but also those in downstream units, e.g., the intensive care unit and regular bed wards of each medical specialty. We present an extension to the master surgery schedule, where the capacity for surgeries on ICU patients is controlled by introducing downstream-dependent block types – one for both ICU and ward patients and one where surgeries on ICU patients must not be performed. The goal is to provide better control over post-surgery patient flows through the hospital while preserving each medical specialty’s autonomy over its operational surgery scheduling. We propose a mixed-integer program to determine the allocation of the new block types within either a given or a new master surgery schedule to minimize the maximum workload in downstream units. Using a simulation model supported by seven years of data from the University Hospital Augsburg, we show that the maximum workload in the intensive care unit can be reduced by up to 11.22% with our approach while maintaining the existing master surgery schedule. We also show that our approach can achieve up to 79.85% of the maximum workload reduction in the intensive care unit that would result from a fully centralized approach. We analyze various hospital setting instances to show the generalizability of our results. Furthermore, we provide insights and data analysis from the implementation of a quota system at the University Hospital Augsburg.

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“…e producer delivers once to each buyer at regular intervals so that they achieve the required inventory. Britt et al [15] proposed a stochastic multi-objective model for master surgical scheduling and inventory problem. e intended uncertainty was considered as a scenario.…”

Section: Introductionmentioning

confidence: 99%

Presenting a Multi‐Echelon and Multi‐Product Model for Inventory Control considering Shortages Using a Heuristic Algorithm

Ara

Toofani

Kaveh

et al. 2022

Discrete Dynamics in Nature and Society

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In the present study, a mathematical model is provided for inventory management in a three-level supply chain including a supplier, a manufacturer, and a distributor, taking into account the potential for product deficiency. Significant parameters such as the optimal order size for raw materials, optimal production rate, optimal allowed deficiencies at each supply chain level, the of the vehicles and the number of times the products are delivered between the supply chain components have been provided aiming at minimizing inventory management costs in the supply chain. The problem was solved using a heuristic algorithm. The proposed model is implemented for 20 different numerical examples. According to the results, the difference between the solutions obtained from the algorithm and the solutions obtained from the optimal values with the real variables is an average of 1.52%.

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A stochastic hierarchical approach for the master surgical scheduling problem

Cited by 16 publications

References 61 publications

Research Trends in the Optimization of the Master Surgery Scheduling Problem

Research Trends in the Optimization of the Master Surgery Scheduling Problem

Balancing control and autonomy in master surgery scheduling: Benefits of ICU quotas for recovery units

Presenting a Multi‐Echelon and Multi‐Product Model for Inventory Control considering Shortages Using a Heuristic Algorithm

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