A Mathematical Model for Scheduling Elective Surgeries for Minimizing the Waiting Times in Emergency Surgeries

Yazdi, M.; Zandieh, M.; Haleh, Hassan

doi:10.5829/ije.2020.33.03c.09

Cited by 5 publications

(6 citation statements)

References 17 publications

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“…The computational results indicate an increase in the patient satisfaction level, as well as the improvement of the efficiency and productivity of the medical center. Yazd i et al [15] proposed a mathematical model for the problem of scheduling elective and emergency surgeries. This model considers surgeries as multi-activities projects.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Here, to verify the applicability of the proposed algorithms, the aforementioned metrics are applied to the considered test problems. These 12 test problems are divided into small-sized (1-4), medium-sized (5-8), and large-sized (9)(10)(11)(12)(13)(14)(15).…”

Section: 3 Metrics For Comparing Algorithmsmentioning

confidence: 99%

“…So, the increasingly growing demand for surgeries and resource constraints have caused medical centers to efficiently manage their resources, especially expensive resources such as operating rooms and special medical staff. Scheduling surgical operations, including sequencing surgeries, allocating resources, and determining start times, is a complicated task for the medical center manager [15]. The problem of operating room planning and scheduling seeks to propose a solution to reduce costs, increase the efficiency of operating room utilization, and attain other related goals [16].…”

Section: Introductionmentioning

confidence: 99%

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Operating Room Scheduling Optimization Based on a Fuzzy Uncertainty Approach and Metaheuristic Algorithms

Maghzi

Mohammadi

Pasandide

et al. 2022

IJE

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T oday, planning and scheduling problems are the most significant issues in the world and make a great impact on improving organizational productivity and serving systems such as medical and healthcare providers. Since operating room planning is a major problem in healthcare organizations, the optimization of medical staff and equipment plays an essential role. Thus, this study presents a multiobjective mathematical model with a new categorization (preoperative, intraoperative, and postoperative) to minimize operating room scheduling and the risk of using equipment. Time constraints in healthcare systems and medical equipment limited capacity are the most significant considered limitation in the present study. In this regard, since the duration of patient preparation and implementation of treatment processes occur in three states of optimistic, pessimistic, and normal, the introduced parameters are examined relying on a fuzzy uncertainty analysis of the problem. Hence, the model is measured in a real numerical solution sample in a medical center to evaluate and confirm the proposed mathematical model. T hen, two meta-heuristic algorithms (NRGA and NSGAII) are implemented on the mathematical model to analyze the proposed model. Finally, the research results indicate that the NSGA-II is more efficient in the operating room scheduling problem.

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Section: Literature Reviewmentioning

confidence: 99%

Section: 3 Metrics For Comparing Algorithmsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Operating Room Scheduling Optimization Based on a Fuzzy Uncertainty Approach and Metaheuristic Algorithms

Maghzi

Mohammadi

Pasandide

et al. 2022

IJE

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“…Many scientific studies from various fields of study have recently addressed the problem of improving the quality of healthcare services through the use of managerial, statistical, and modeling tools to address issues such as prolonged hospital stays, increased waiting times, appointment scheduling, and other issues [7][8][9][10][11][12][13][14][15][16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Overcrowding analysis in emergency department through indexes: a single center study

et al. 2022

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Introduction Overcrowding in the Emergency Department (ED) is one of the major issues that must be addressed in order to improve the services provided in emergency circumstances and to optimize their quality. As a result, in order to help the patients and professionals engaged, hospital organizations must implement remedial and preventative measures. Overcrowding has a number of consequences, including inadequate treatment and longer hospital stays; as a result, mortality and the average duration of stay in critical care units both rise. In the literature, a number of indicators have been used to measure ED congestion. EDWIN, NEDOCS and READI scales are considered the most efficient ones, each of which is based on different parameters regarding the patient management in the ED. Methods In this work, EDWIN Index and NEDOCS Index have been calculated every hour for a month period from February 9th to March 9th, 2020 and for a month period from March 10th to April 9th, 2020. The choice of the period is related to the date of the establishment of the lockdown in Italy due to the spread of Coronavirus; in fact on 9 March 2020 the Italian government issued the first decree regarding the urgent provisions in relation to the COVID-19 emergency. Besides, the Pearson correlation coefficient has been used to evaluate how much the EDWIN and NEDOCS indexes are linearly dependent. Results EDWIN index follows a trend consistent with the situation of the first lockdown period in Italy, defined by extreme limitations imposed by Covid-19 pandemic. The 8:00–20:00 time frame was the most congested, with peak values between 8:00 and 12:00. on the contrary, in NEDOCS index doesn’t show a trend similar to the EDWIN one, resulting less reliable. The Pearson correlation coefficient between the two scales is 0,317. Conclusion In this study, the EDWIN Index and the NEDOCS Index were compared and correlated in order to assess their efficacy, applying them to the case study of the Emergency Department of “San Giovanni di Dio e Ruggi d’Aragona” University Hospital during the Covid-19 pandemic. The EDWIN scale turned out to be the most realistic model in relation to the actual crowding of the ED subject of our study. Besides, the two scales didn’t show a significant correlation value.

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“…The flow Shop Scheduling Problem (FSSP) covers many real case studies in practical problems [1]. Some papers described the applications of the two-machine flow shop scheduling problem (FSSP) [2][3][4]. Total completion time minimizes Work in Process (WIP) costs and the rapid turnaround of jobs.…”

mentioning

confidence: 99%

Robust and Stable Flow Shop Scheduling Problem under Uncertain Processing Times and Machines’ Disruption

Abtahi

Sahraeian

2021

IJE

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This paper presents a predictive robust and stable approach for a two-machine flow shop scheduling problem with machine disruption and uncertain job processing time. Indeed, a general approach is proposed that can be used for robustness and stability optimization in an m-machine flow shop or job shop scheduling problem. The robustness measure is the total expected realized completion time. The expected sum of squared aberration between each jobs' completion time in the realized and initial schedules is the stability measure. We proposed and compared two methods to deal with such an NPhard problem; a method based on decomposing the problem into subproblem and solving each subproblem, and a theorem-based method. The extensive computational results indicated that the second method has a better performance in terms of robustness and stability, especially in large-sized problems. In other words, the second method is preferable because of the better manufacturer responsiveness to the customer and the production staff satisfaction enhancement.The expected real completion time of job j on the machine i

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A Mathematical Model for Scheduling Elective Surgeries for Minimizing the Waiting Times in Emergency Surgeries

Cited by 5 publications

References 17 publications

Operating Room Scheduling Optimization Based on a Fuzzy Uncertainty Approach and Metaheuristic Algorithms

Operating Room Scheduling Optimization Based on a Fuzzy Uncertainty Approach and Metaheuristic Algorithms

Overcrowding analysis in emergency department through indexes: a single center study

Robust and Stable Flow Shop Scheduling Problem under Uncertain Processing Times and Machines’ Disruption

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