IDEAS home Printed from https://ideas.repec.org/a/spr/jcomop/v42y2021i4d10.1007_s10878-019-00487-x.html
   My bibliography  Save this article

Outpatient appointment scheduling problem considering patient selection behavior: data modeling and simulation optimization

Author

Listed:
  • Xuanzhu Fan

    (Dongbei University of Finance and Economics)

  • Jiafu Tang

    (Dongbei University of Finance and Economics)

  • Chongjun Yan

    (Dongbei University of Finance and Economics)

  • Hainan Guo

    (Shenzhen University)

  • Zhongfa Cao

    (Dalian Dermatosis Hospital)

Abstract

In medical outpatient services, due to patients’ imbalanced selection for doctors of different levels and for different visiting periods, inefficiency of resource utilization and dissatisfaction of patients have become the main problems faced by hospital managers. For the first time, this research has considered patients’ preference between high-ranking professional titles of general doctor and expert doctor. Through analyzing real data of the outpatient clinic at Dalian City Dermatology Hospital, the behavioral pattern of patients’ patience limit adjusted with expected waiting time was obtained. This research also established a data-driven discrete event simulation model that takes into account walk-in patients’ time preferences, appointment patients’ no-shows and cancellations, and considers complex patient flow caused by unbalanced selection of doctor resources and patience limit of waiting time. To optimize scheduling for appointment patients with two types of doctors, this research put forward a simulation optimization framework that maximized hospital benefit and minimized patients’ dissatisfaction. At the same time, simulation budget allocation based on multi-objective optimization and genetic algorithm were combined to obtain the approximate Pareto joint capacity plan of multi-servers and a patient scheduling scheme. The simulation model was validated through a case study based on real data of outpatient service for the whole year, and the proposed optimization method can comprehensively improve performance of outpatient service scheduling system. The simulation optimization framework can provide an effective scheduling scheme for all multi-server service systems involving consumer selection and impatient behavior.

Suggested Citation

  • Xuanzhu Fan & Jiafu Tang & Chongjun Yan & Hainan Guo & Zhongfa Cao, 2021. "Outpatient appointment scheduling problem considering patient selection behavior: data modeling and simulation optimization," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 677-699, November.
    • Handle: RePEc:spr:jcomop:v:42:y:2021:i:4:d:10.1007_s10878-019-00487-x
    DOI: 10.1007/s10878-019-00487-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10878-019-00487-x
    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/s10878-019-00487-x?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. Shan Wang & Huiqiao Su & Guohua Wan, 2015. "Resource-constrained machine scheduling with machine eligibility restriction and its applications to surgical operations scheduling," Journal of Combinatorial Optimization, Springer, vol. 30(4), pages 982-995, November.
    2. Diwas S. Kc & Christian Terwiesch, 2009. "Impact of Workload on Service Time and Patient Safety: An Econometric Analysis of Hospital Operations," Management Science, INFORMS, vol. 55(9), pages 1486-1498, September.
    3. Jian Chang & Lingjuan Zhang, 2019. "Case Mix Index weighted multi-objective optimization of inpatient bed allocation in general hospital," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 1-19, January.
    4. Loo Lee & Ek Chew & Suyan Teng & David Goldsman, 2010. "Finding the non-dominated Pareto set for multi-objective simulation models," IISE Transactions, Taylor & Francis Journals, vol. 42(9), pages 656-674.
    5. Ying Yang & Shoucheng Luo & Jing Fan & Xinye Zhou & Chunyu Fu & Guochun Tang, 2019. "Study on specialist outpatient matching appointment and the balance matching model," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 20-39, January.
    6. Marynissen, Joren & Demeulemeester, Erik, 2019. "Literature review on multi-appointment scheduling problems in hospitals," European Journal of Operational Research, Elsevier, vol. 272(2), pages 407-419.
    7. Huaxin Qiu & Dujuan Wang & Yanzhang Wang & Yunqiang Yin, 2019. "MRI appointment scheduling with uncertain examination time," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 62-82, January.
    8. Dujuan Wang & Feng Liu & Yunqiang Yin & Jianjun Wang & Yanzhang Wang, 2015. "Prioritized surgery scheduling in face of surgeon tiredness and fixed off-duty period," Journal of Combinatorial Optimization, Springer, vol. 30(4), pages 967-981, November.
    9. 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.
    10. Huidan Lin & Qun Li & Xueguo Xu & Ping Li, 2019. "Optimal arrangement of the pulmonary interventional surgeries considering timely distribution of medical consumables," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 271-285, January.
    11. Ling Gai & Jiandong Ji, 2019. "An integrated method to solve the healthcare facility layout problem under area constraints," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 95-113, January.
    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. J. Behnamian & Z. Gharabaghli, 2023. "Multi-objective outpatient scheduling in health centers considering resource constraints and service quality: a robust optimization approach," Journal of Combinatorial Optimization, Springer, vol. 45(2), pages 1-35, March.
    2. Majed Hadid & Adel Elomri & Regina Padmanabhan & Laoucine Kerbache & Oualid Jouini & Abdelfatteh El Omri & Amir Nounou & Anas Hamad, 2022. "Clustering and Stochastic Simulation Optimization for Outpatient Chemotherapy Appointment Planning and Scheduling," IJERPH, MDPI, vol. 19(23), pages 1-34, November.

    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. Xuanzhu Fan & Jiafu Tang & Chongjun Yan & Hainan Guo & Zhongfa Cao, 0. "Outpatient appointment scheduling problem considering patient selection behavior: data modeling and simulation optimization," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-23.
    2. Ying Yang & Huijing Wu & Caixia Yan, 2021. "Medical consumable usage control based on Canopy_K-means clustering and WARM," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 722-739, November.
    3. Ying Yang & Huijing Wu & Caixia Yan, 0. "Medical consumable usage control based on Canopy_K-means clustering and WARM," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-18.
    4. Ruiping Wang & Mei Wang & Jian Chang & Zai Luo & Feng Zhang & Chen Huang, 2021. "An optimized approach of venous thrombus embolism risk assessment," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 1053-1063, November.
    5. Ruiping Wang & Mei Wang & Jian Chang & Zai Luo & Feng Zhang & Chen Huang, 0. "An optimized approach of venous thrombus embolism risk assessment," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-11.
    6. Ling Gai & Zhiyue Peng & Jiming Zhang & Jiafu Zhang, 2021. "Emergency medical center location problem with people evacuation solved by extended TODIM and objective programming," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 1004-1029, November.
    7. Golmohammadi, Davood & Zhao, Lingyu & Dreyfus, David, 2023. "Using machine learning techniques to reduce uncertainty for outpatient appointment scheduling practices in outpatient clinics," Omega, Elsevier, vol. 120(C).
    8. Ling Gai & Zhiyue Peng & Jiming Zhang & Jiafu Zhang, 0. "Emergency medical center location problem with people evacuation solved by extended TODIM and objective programming," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-26.
    9. Zhao, Meng & Wang, Yajun & Zhang, Xueyi & Xu, Chang, 2023. "Online doctor-patient dynamic stable matching model based on regret theory under incomplete information," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    10. Qian Li & Wei Zhang, 2021. "An improved linear convergence of FISTA for the LASSO problem with application to CT image reconstruction," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 831-847, November.
    11. Sean Harris & David Claudio, 2022. "Current Trends in Operating Room Scheduling 2015 to 2020: a Literature Review," SN Operations Research Forum, Springer, vol. 3(1), pages 1-42, March.
    12. Qian Li & Wei Zhang, 0. "An improved linear convergence of FISTA for the LASSO problem with application to CT image reconstruction," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-17.
    13. Sebastiano, Antonio & Belvedere, Valeria & Grando, Alberto & Giangreco, Antonio, 2017. "The effect of capacity management strategies on employees' well-being: A quantitative investigation into the long-term healthcare industry," European Management Journal, Elsevier, vol. 35(4), pages 563-573.
    14. Zhiguo Wang & Lufei Huang & Cici Xiao He, 2021. "A multi-objective and multi-period optimization model for urban healthcare waste’s reverse logistics network design," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 785-812, November.
    15. J. Behnamian & Z. Gharabaghli, 2023. "Multi-objective outpatient scheduling in health centers considering resource constraints and service quality: a robust optimization approach," Journal of Combinatorial Optimization, Springer, vol. 45(2), pages 1-35, March.
    16. Diwas Singh KC & Bradley R. Staats, 2012. "Accumulating a Portfolio of Experience: The Effect of Focal and Related Experience on Surgeon Performance," Manufacturing & Service Operations Management, INFORMS, vol. 14(4), pages 618-633, October.
    17. Vasiliki Kostami & Sampath Rajagopalan, 2014. "Speed–Quality Trade-Offs in a Dynamic Model," Manufacturing & Service Operations Management, INFORMS, vol. 16(1), pages 104-118, February.
    18. Mirko Kremer & Francis de Véricourt, 2022. "Mismanaging diagnostic accuracy under congestion," ESMT Research Working Papers ESMT-22-01, ESMT European School of Management and Technology.
    19. Sezer Ülkü & Chris Hydock & Shiliang Cui, 2022. "Social Queues (Cues): Impact of Others’ Waiting in Line on One’s Service Time," Management Science, INFORMS, vol. 68(11), pages 7958-7976, November.
    20. Michael Freeman & Susan Robinson & Stefan Scholtes, 2021. "Gatekeeping, Fast and Slow: An Empirical Study of Referral Errors in the Emergency Department," Management Science, INFORMS, vol. 67(7), pages 4209-4232, July.

    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:42:y:2021:i:4:d:10.1007_s10878-019-00487-x. 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.