Operations planning in outpatient chemotherapy with hybrid simulation modelling

被引：0

作者：

Heshmat M. ^{[1
]}

Eltawil A.B. ^{[2
]}

Abdelghany M. ^{[3
]}

机构：

[1] Department of Mechanical Design and Production Engineering, Faculty of Engineering, Assiut University

[2] Industrial and Manufacturing Engineering, Egypt-Japan University of Science and Technology, New Borg El-Arab City, Alexandria

[3] Mechanical Engineering Department, Faculty of Engineering, Fayoum University

来源：

International Journal of Simulation and Process Modelling | 2022年 / 18卷 / 04期

关键词：

ABS; agent-based simulation; DES; discrete event simulation; outpatient chemotherapy; patient appointment scheduling; simulation;

D O I：

10.1504/IJSPM.2022.10053303

中图分类号：

学科分类号：

摘要：

Outpatient chemotherapy clinics (OCCs) are a crucial medical units where cancer is diagnosed, and treatment is provided. However, they face planning and scheduling challenges. In this paper, two problems in OCCs are addressed: how to accurately compute the utilisation of the nurses, and the patient appointment scheduling problem. An agent-based simulation is used to simulate the nurse activities and thus the nurse utilisation is computed. A discrete event simulation model is developed to evaluate the performance of the current patient appointment practice. However, the resulted nurse utilisation could not be accurately computed. Therefore, a hybrid discrete event and agent-based simulation model is developed to simulate the whole system including the nurse activities. Moreover, the proposed simulation model is used to determine the best patient appointment scenario. The results can be used to accurately compute the nurse utilisation in the OCCs beside the other key performance indicators (KPIs) in OCCs. Copyright © 2022 Inderscience Enterprises Ltd.

引用

页码：296 / 303

页数：7

共 31 条

[1]

Cancer Progress Report, (2014)

[2]

Abdelghany M., Eltawil A.B., Linking approaches for multi-methods simulation in healthcare systems planning and management, International Journal of Industrial and Systems Engineering, 26, 2, pp. 275-290, (2017)

[3]

Cancer Statistics, (2015)

[4]

Multi-Method Simulation Software, (2017)

[5]

Arena Simulation Software, (2017)

[6]

Baril C., Gascon V., Miller J., Et al., The importance of considering resource’s tasks when modeling healthcare services with discrete-event simulation: an approach using work sampling method, Journal of Simulation, 11, 2, pp. 103-114, (2016)

[7]

Comis M., Cleophas C., Busing C., Patients, primary care, and policy: agent-based simulation modeling for health care decision support, Health Care Management Science, 24, 4, pp. 799-826, (2021)

[8]

Cancer Therapy Advisor, (2016)

[9]

Ershadi M.M., Shafaeizadeh A., Simulation-based improvement and modification for performances of hospitals: a case study, International Journal of Simulation and Process Modelling, 16, 2, pp. 90-104, (2021)

[10]

Fragapane G., Zhang C., Sgarbossa F., Et al., An agent-based simulation approach to model hospital logistics, Int. J. Simul. Model, 18, 4, pp. 654-665, (2019)

← 1 2 3 4 →