IDEAS home Printed from https://ideas.repec.org/a/kap/hcarem/v17y2014i1p60-76.html
   My bibliography  Save this article

Dynamic scheduling with due dates and time windows: an application to chemotherapy patient appointment booking

Author

Listed:
  • Yasin Gocgun
  • Martin Puterman

Abstract

We study a scheduling problem in which arriving patients require appointments at specific future days within a treatment specific time window. This research is motivated by a study of chemotherapy scheduling practices at the British Columbia Cancer Agency (Canada). We formulate this problem as a Markov Decision Process (MDP). Since the resulting MDPs are intractable to exact methods, we employ linear-programming-based Approximate Dynamic Programming (ADP) to obtain approximate solutions. Using simulation, we compare the performance of the resulting ADP policies to practical and easy-to-use heuristic decision rules under diverse scenarios. The results indicate that ADP is promising in several scenarios, and that a specific easy-to-use heuristic performs well in the idealized chemotherapy scheduling setting we study. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Yasin Gocgun & Martin Puterman, 2014. "Dynamic scheduling with due dates and time windows: an application to chemotherapy patient appointment booking," Health Care Management Science, Springer, vol. 17(1), pages 60-76, March.
    • Handle: RePEc:kap:hcarem:v:17:y:2014:i:1:p:60-76
    DOI: 10.1007/s10729-013-9253-z
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10729-013-9253-z
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10729-013-9253-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. Jonathan Patrick & Martin L. Puterman & Maurice Queyranne, 2008. "Dynamic Multipriority Patient Scheduling for a Diagnostic Resource," Operations Research, INFORMS, vol. 56(6), pages 1507-1525, December.
    2. Anton J. Kleywegt & Jason D. Papastavrou, 1998. "The Dynamic and Stochastic Knapsack Problem," Operations Research, INFORMS, vol. 46(1), pages 17-35, February.
    3. Lamiri, Mehdi & Xie, Xiaolan & Dolgui, Alexandre & Grimaud, Frederic, 2008. "A stochastic model for operating room planning with elective and emergency demand for surgery," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1026-1037, March.
    4. Yigal Gerchak & Diwakar Gupta & Mordechai Henig, 1996. "Reservation Planning for Elective Surgery Under Uncertain Demand for Emergency Surgery," Management Science, INFORMS, vol. 42(3), pages 321-334, March.
    5. Jonathan Patrick, 2012. "A Markov decision model for determining optimal outpatient scheduling," Health Care Management Science, Springer, vol. 15(2), pages 91-102, June.
    6. Brant E. Fries & Vijay P. Marathe, 1981. "Determination of Optimal Variable-Sized Multiple-Block Appointment Systems," Operations Research, INFORMS, vol. 29(2), pages 324-345, April.
    7. Sauré, Antoine & Patrick, Jonathan & Tyldesley, Scott & Puterman, Martin L., 2012. "Dynamic multi-appointment patient scheduling for radiation therapy," European Journal of Operational Research, Elsevier, vol. 223(2), pages 573-584.
    8. Nan Liu & Serhan Ziya & Vidyadhar G. Kulkarni, 2010. "Dynamic Scheduling of Outpatient Appointments Under Patient No-Shows and Cancellations," Manufacturing & Service Operations Management, INFORMS, vol. 12(2), pages 347-364, September.
    Full references (including those not matched with items on IDEAS)

    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. Adam Diamant, 2021. "Dynamic multistage scheduling for patient-centered care plans," Health Care Management Science, Springer, vol. 24(4), pages 827-844, December.
    2. Silva, Thiago A.O. & de Souza, Mauricio C., 2020. "Surgical scheduling under uncertainty by approximate dynamic programming," Omega, Elsevier, vol. 95(C).
    3. Yongbo Xiao & Yan Zhu, 2016. "Value management of diagnostic equipment with cancelation, no‐show, and emergency patients," Naval Research Logistics (NRL), John Wiley & Sons, vol. 63(4), pages 287-304, June.
    4. Yasin Gocgun, 2018. "Simulation-based approximate policy iteration for dynamic patient scheduling for radiation therapy," Health Care Management Science, Springer, vol. 21(3), pages 317-325, September.
    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. Van-Anh Truong, 2015. "Optimal Advance Scheduling," Management Science, INFORMS, vol. 61(7), pages 1584-1597, July.
    7. Liping Zhou & Na Geng & Zhibin Jiang & Shan Jiang, 2022. "Integrated Multiresource Capacity Planning and Multitype Patient Scheduling," INFORMS Journal on Computing, INFORMS, vol. 34(1), pages 129-149, January.
    8. Tu San Pham & Antoine Legrain & Patrick De Causmaecker & Louis-Martin Rousseau, 2023. "A Prediction-Based Approach for Online Dynamic Appointment Scheduling: A Case Study in Radiotherapy Treatment," INFORMS Journal on Computing, INFORMS, vol. 35(4), pages 844-868, July.
    9. Camila Ramos & Alejandro Cataldo & Juan–Carlos Ferrer, 2020. "Appointment and patient scheduling in chemotherapy: a case study in Chilean hospitals," Annals of Operations Research, Springer, vol. 286(1), pages 411-439, March.
    10. Miao Bai & Bjorn Berg & Esra Sisikoglu Sir & Mustafa Y. Sir, 2023. "Partially partitioned templating strategies for outpatient specialty practices," Production and Operations Management, Production and Operations Management Society, vol. 32(1), pages 301-318, January.
    11. Kazim Topuz & Timothy L. Urban & Robert A. Russell & Mehmet B. Yildirim, 2024. "Decision support system for appointment scheduling and overbooking under patient no-show behavior," Annals of Operations Research, Springer, vol. 342(1), pages 845-873, November.
    12. Woonghee Tim Huh & Nan Liu & Van-Anh Truong, 2013. "Multiresource Allocation Scheduling in Dynamic Environments," Manufacturing & Service Operations Management, INFORMS, vol. 15(2), pages 280-291, May.
    13. Navid Izady, 2015. "Appointment Capacity Planning in Specialty Clinics: A Queueing Approach," Operations Research, INFORMS, vol. 63(4), pages 916-930, August.
    14. Jiang, Yangzi & Abouee-Mehrizi, Hossein & Diao, Yuhe, 2020. "Data-driven analytics to support scheduling of multi-priority multi-class patients with wait time targets," European Journal of Operational Research, Elsevier, vol. 281(3), pages 597-611.
    15. Paola Cappanera & Filippo Visintin & Carlo Banditori & Daniele Feo, 2019. "Evaluating the long-term effects of appointment scheduling policies in a magnetic resonance imaging setting," Flexible Services and Manufacturing Journal, Springer, vol. 31(1), pages 212-254, March.
    16. Qu, Xiuli & Peng, Yidong & Shi, Jing & LaGanga, Linda, 2015. "An MDP model for walk-in patient admission management in primary care clinics," International Journal of Production Economics, Elsevier, vol. 168(C), pages 303-320.
    17. Hans-Jörg Schütz & Rainer Kolisch, 2013. "Capacity allocation for demand of different customer-product-combinations with cancellations, no-shows, and overbooking when there is a sequential delivery of service," Annals of Operations Research, Springer, vol. 206(1), pages 401-423, July.
    18. Jacob Feldman & Nan Liu & Huseyin Topaloglu & Serhan Ziya, 2014. "Appointment Scheduling Under Patient Preference and No-Show Behavior," Operations Research, INFORMS, vol. 62(4), pages 794-811, August.
    19. Agrawal, Deepak & Pang, Guodong & Kumara, Soundar, 2023. "Preference based scheduling in a healthcare provider network," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1318-1335.
    20. 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.

    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:kap:hcarem:v:17:y:2014:i:1:p:60-76. 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.