IDEAS home Printed from https://ideas.repec.org/a/spr/jcomop/v37y2019i1d10.1007_s10878-017-0232-z.html
   My bibliography  Save this article

Patient scheduling in hemodialysis service

Author

Listed:
  • Zhenyuan Liu

    (Huazhong University of Science and Technology
    Key Laboratory of Education Ministry for Image Processing and Intelligent Control)

  • Jiongbing Lu

    (Huazhong University of Science and Technology
    Key Laboratory of Education Ministry for Image Processing and Intelligent Control)

  • Zaisheng Liu

    (Huazhong University of Science and Technology
    Key Laboratory of Education Ministry for Image Processing and Intelligent Control)

  • Guangrui Liao

    (Huazhong University of Science and Technology
    Key Laboratory of Education Ministry for Image Processing and Intelligent Control)

  • Hao Howard Zhang

    (University of Maryland School of Medicine)

  • Junwu Dong

    (Pu ai Hospital)

Abstract

The patient scheduling presents a number of operations management challenges in hemodialysis service center. The homogeneity of the break time between treatments, satisfying the patients preferences on time, space and equipment and the multi-function dialysis devices make for an interesting and complex scheduling problem that could benefit from computerized decision support. In this paper, patient scheduling problem in hemodialysis service is formulated as a synthetic-objective optimization model combined with several criteria on minimizing the gross utilization cost of devices, the number of night treatment, satisfying the patients preferences and the equilibrium of the devices. A basic heuristics and a rollout algorithm based on the heuristics are developed for solving the problem where three levels of treatment schedule sets are constructed one by one. The performances of the rollout algorithm and the basic heuristics are compared on the real cases. Computational results show that significant improvement of patients degree of satisfaction can be achieved with the rollout algorithm while simultaneously considering to reduce the number of night shifts.

Suggested Citation

  • Zhenyuan Liu & Jiongbing Lu & Zaisheng Liu & Guangrui Liao & Hao Howard Zhang & Junwu Dong, 2019. "Patient scheduling in hemodialysis service," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 337-362, January.
    • Handle: RePEc:spr:jcomop:v:37:y:2019:i:1:d:10.1007_s10878-017-0232-z
    DOI: 10.1007/s10878-017-0232-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10878-017-0232-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10878-017-0232-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Liwei Zhong & Shoucheng Luo & Lidong Wu & Lin Xu & Jinghui Yang & Guochun Tang, 2014. "A two-stage approach for surgery scheduling," Journal of Combinatorial Optimization, Springer, vol. 27(3), pages 545-556, April.
    2. Nelishia Pillay, 2016. "A review of hyper-heuristics for educational timetabling," Annals of Operations Research, Springer, vol. 239(1), pages 3-38, April.
    3. De Bruecker, Philippe & Van den Bergh, Jorne & Beliën, Jeroen & Demeulemeester, Erik, 2015. "Workforce planning incorporating skills: State of the art," European Journal of Operational Research, Elsevier, vol. 243(1), pages 1-16.
    4. Luca Bertazzi, 2012. "Minimum and Worst-Case Performance Ratios of Rollout Algorithms," Journal of Optimization Theory and Applications, Springer, vol. 152(2), pages 378-393, February.
    5. F. Guerriero, 2008. "Hybrid Rollout Approaches for the Job Shop Scheduling Problem," Journal of Optimization Theory and Applications, Springer, vol. 139(2), pages 419-438, November.
    6. Barry McCollum & Andrea Schaerf & Ben Paechter & Paul McMullan & Rhyd Lewis & Andrew J. Parkes & Luca Di Gaspero & Rong Qu & Edmund K. Burke, 2010. "Setting the Research Agenda in Automated Timetabling: The Second International Timetabling Competition," INFORMS Journal on Computing, INFORMS, vol. 22(1), pages 120-130, February.
    7. Xingong Zhang & Hui Wang & Xingpeng Wang, 2015. "Patients scheduling problems with deferred deteriorated functions," Journal of Combinatorial Optimization, Springer, vol. 30(4), pages 1027-1041, November.
    8. Chongjun Yan & Jiafu Tang & Bowen Jiang & Richard Y.K. Fung, 2015. "Sequential appointment scheduling considering patient choice and service fairness," International Journal of Production Research, Taylor & Francis Journals, vol. 53(24), pages 7376-7395, December.
    9. Ahmadi-Javid, Amir & Jalali, Zahra & Klassen, Kenneth J, 2017. "Outpatient appointment systems in healthcare: A review of optimization studies," European Journal of Operational Research, Elsevier, vol. 258(1), pages 3-34.
    10. Riise, Atle & Mannino, Carlo & Lamorgese, Leonardo, 2016. "Recursive logic-based Benders’ decomposition for multi-mode outpatient scheduling," European Journal of Operational Research, Elsevier, vol. 255(3), pages 719-728.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mostafa Khatami & Amir Salehipour, 2021. "Coupled task scheduling with time-dependent processing times," Journal of Scheduling, Springer, vol. 24(2), pages 223-236, April.
    2. Reihaneh, Mohammad & Ansari, Sina & Farhadi, Farbod, 2023. "Patient appointment scheduling at hemodialysis centers: An exact branch and price approach," European Journal of Operational Research, Elsevier, vol. 309(1), pages 35-52.
    3. Bozkir, Cem D.C. & Ozmemis, Cagri & Kurbanzade, Ali Kaan & Balcik, Burcu & Gunes, Evrim D. & Tuglular, Serhan, 2023. "Capacity planning for effective cohorting of hemodialysis patients during the coronavirus pandemic: A case study," European Journal of Operational Research, Elsevier, vol. 304(1), pages 276-291.
    4. Farbod Farhadi & Sina Ansari & Francisco Jara-Moroni, 2023. "Optimization models for patient and technician scheduling in hemodialysis centers," Health Care Management Science, Springer, vol. 26(3), pages 558-582, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bertazzi, Luca & Bosco, Adamo & Laganà, Demetrio, 2015. "Managing stochastic demand in an Inventory Routing Problem with transportation procurement," Omega, Elsevier, vol. 56(C), pages 112-121.
    2. Yadong Wang & Baoqiang Fan & Jingang Zhai & Wei Xiong, 2019. "Two-machine flowshop scheduling in a physical examination center," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 363-374, January.
    3. Wenjuan Fan & Yi Wang & Tongzhu Liu & Guixian Tong, 2020. "A patient flow scheduling problem in ophthalmology clinic solved by the hybrid EDA–VNS algorithm," Journal of Combinatorial Optimization, Springer, vol. 39(2), pages 547-580, February.
    4. Goodson, Justin C. & Thomas, Barrett W. & Ohlmann, Jeffrey W., 2017. "A rollout algorithm framework for heuristic solutions to finite-horizon stochastic dynamic programs," European Journal of Operational Research, Elsevier, vol. 258(1), pages 216-229.
    5. Ahmadi-Javid, Amir & Jalali, Zahra & Klassen, Kenneth J, 2017. "Outpatient appointment systems in healthcare: A review of optimization studies," European Journal of Operational Research, Elsevier, vol. 258(1), pages 3-34.
    6. Wenhua Li & Xing Chai, 2019. "The medical laboratory scheduling for weighted flow-time," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 83-94, January.
    7. Sharan Srinivas & A. Ravi Ravindran, 2020. "Designing schedule configuration of a hybrid appointment system for a two-stage outpatient clinic with multiple servers," Health Care Management Science, Springer, vol. 23(3), pages 360-386, September.
    8. Xi Chen & Liu Zhao & Haiming Liang & Kin Keung Lai, 2019. "Matching patients and healthcare service providers: a novel two-stage method based on knowledge rules and OWA-NSGA-II algorithm," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 221-247, January.
    9. Bowen Jiang & Jiafu Tang & Chongjun Yan, 2019. "A comparison of fixed and variable capacity-addition policies for outpatient capacity allocation," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 150-182, January.
    10. Gang Du & Xinyue Li & Hui Hu & Xiaoling Ouyang, 2018. "Optimizing Daily Service Scheduling for Medical Diagnostic Equipment Considering Patient Satisfaction and Hospital Revenue," Sustainability, MDPI, vol. 10(9), pages 1-23, September.
    11. Fabian Dunke & Stefan Nickel, 2023. "A matheuristic for customized multi-level multi-criteria university timetabling," Annals of Operations Research, Springer, vol. 328(2), pages 1313-1348, September.
    12. Shuwan Zhu & Wenjuan Fan & Shanlin Yang & Jun Pei & Panos M. Pardalos, 2019. "Operating room planning and surgical case scheduling: a review of literature," Journal of Combinatorial Optimization, Springer, vol. 37(3), pages 757-805, April.
    13. Edmund K. Burke & Yuri Bykov, 2016. "An Adaptive Flex-Deluge Approach to University Exam Timetabling," INFORMS Journal on Computing, INFORMS, vol. 28(4), pages 781-794, November.
    14. Tugba Cayirli & Pinar Dursun & Evrim D. Gunes, 2019. "An integrated analysis of capacity allocation and patient scheduling in presence of seasonal walk-ins," Flexible Services and Manufacturing Journal, Springer, vol. 31(2), pages 524-561, June.
    15. Opacic, Luke & Sowlati, Taraneh & Mobini, Mahdi, 2018. "Design and development of a simulation-based decision support tool to improve the production process at an engineered wood products mill," International Journal of Production Economics, Elsevier, vol. 199(C), pages 209-219.
    16. Symitsi, Efthymia & Stamolampros, Panagiotis & Daskalakis, George & Korfiatis, Nikolaos, 2021. "The informational value of employee online reviews," European Journal of Operational Research, Elsevier, vol. 288(2), pages 605-619.
    17. Beibei Li & Zhihong Zhao & Xuan Shen & Cendi Xue & Liwei Zhong, 2015. "Fitting $$\alpha $$ α $$\beta $$ β -crystalline structure onto electron microscopy based on SO(3) rotation group theory," Journal of Combinatorial Optimization, Springer, vol. 30(4), pages 906-919, November.
    18. Jing Li & Ming Dong & Yijiong Ren & Kaiqi Yin, 2015. "How patient compliance impacts the recommendations for colorectal cancer screening," Journal of Combinatorial Optimization, Springer, vol. 30(4), pages 920-937, November.
    19. Wei Gao & Wuping Bao & Xin Zhou, 2019. "Analysis of cough detection index based on decision tree and support vector machine," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 375-384, January.
    20. Yanqin Bai & Xiao Han & Tong Chen & Hua Yu, 2015. "Quadratic kernel-free least squares support vector machine for target diseases classification," Journal of Combinatorial Optimization, Springer, vol. 30(4), pages 850-870, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:jcomop:v:37:y:2019:i:1:d:10.1007_s10878-017-0232-z. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.