IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v284y2020i3p847-860.html
   My bibliography  Save this article

The effect of cancelled appointments on outpatient clinic operations

Author

Listed:
  • Harris, Shannon L.
  • May, Jerrold H.
  • Vargas, Luis G.
  • Foster, Krista M.

Abstract

This paper studies how appointment cancellations affect scheduling strategies in outpatient healthcare clinics. While cancellation rates in outpatient clinics have been reported to be as high as 27%, cancelled appointments are often ignored, or grouped with no-shows in healthcare scheduling models. We find that there exists a value of total demand that, when calculated over a scheduling horizon, marks the boundary between where cancellations hurt or help a clinic. We refer to that value as the switch point. Up to the switch point, clinics can achieve a greater reward when patients do not cancel. However, for values of expected total demand greater than the switch point, the clinic reward is reduced if more patients retain (do not cancel) appointments. To assist us in evaluating the switch point, we construct a mixed-integer nonlinear programming model to solve a multi-day outpatient scheduling problem. The model accounts for both inter-day (appointment day) and intra-day (appointment time slot) scheduling decisions, while balancing service benefits against service costs. We include probabilities of no-show and cancellation, which allows us to discuss how cancellations affect scheduling decisions through the switch point. The knowledge of the switch point allows a clinic to understand when appointment no-shows and cancellations negatively affect clinic service, and can assist the clinic in determining the number of patients for which it is committed to provide service, i.e., its panel size. In this paper, we discuss methodologies for calculating the switch point, and discuss its sensitivity to model parameters.

Suggested Citation

  • Harris, Shannon L. & May, Jerrold H. & Vargas, Luis G. & Foster, Krista M., 2020. "The effect of cancelled appointments on outpatient clinic operations," European Journal of Operational Research, Elsevier, vol. 284(3), pages 847-860.
    • Handle: RePEc:eee:ejores:v:284:y:2020:i:3:p:847-860
    DOI: 10.1016/j.ejor.2020.01.050
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221720300874
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2020.01.050?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. Dantas, Leila F. & Fleck, Julia L. & Cyrino Oliveira, Fernando L. & Hamacher, Silvio, 2018. "No-shows in appointment scheduling – a systematic literature review," Health Policy, Elsevier, vol. 122(4), pages 412-421.
    2. Peter A. Salzarulo & Stephen Mahar & Sachin Modi, 2016. "Beyond Patient Classification: Using Individual Patient Characteristics in Appointment Scheduling," Production and Operations Management, Production and Operations Management Society, vol. 25(6), pages 1056-1072, June.
    3. 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.
    4. Seung Jun Lee & Gregory R. Heim & Chelliah Sriskandarajah & Yunxia Zhu, 2018. "Outpatient Appointment Block Scheduling Under Patient Heterogeneity and Patient No†Shows," Production and Operations Management, Production and Operations Management Society, vol. 27(1), pages 28-48, January.
    5. Wen-Ya Wang & Diwakar Gupta, 2011. "Adaptive Appointment Systems with Patient Preferences," Manufacturing & Service Operations Management, INFORMS, vol. 13(3), pages 373-389, July.
    6. Christos Zacharias & Michael Pinedo, 2017. "Managing Customer Arrivals in Service Systems with Multiple Identical Servers," Manufacturing & Service Operations Management, INFORMS, vol. 19(4), pages 639-656, October.
    7. Refael Hassin & Sharon Mendel, 2008. "Scheduling Arrivals to Queues: A Single-Server Model with No-Shows," Management Science, INFORMS, vol. 54(3), pages 565-572, March.
    8. Guido Kaandorp & Ger Koole, 2007. "Optimal outpatient appointment scheduling," Health Care Management Science, Springer, vol. 10(3), pages 217-229, September.
    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. Bjorn P. Berg & Michael Murr & David Chermak & Jonathan Woodall & Michael Pignone & Robert S. Sandler & Brian T. Denton, 2013. "Estimating the Cost of No-Shows and Evaluating the Effects of Mitigation Strategies," Medical Decision Making, , vol. 33(8), pages 976-985, November.
    11. K J Glowacka & R M Henry & J H May, 2009. "A hybrid data mining/simulation approach for modelling outpatient no-shows in clinic scheduling," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(8), pages 1056-1068, August.
    12. Bo Zeng & Ayten Turkcan & Ji Lin & Mark Lawley, 2010. "Clinic scheduling models with overbooking for patients with heterogeneous no-show probabilities," Annals of Operations Research, Springer, vol. 178(1), pages 121-144, July.
    13. Lawrence W. Robinson & Rachel R. Chen, 2010. "A Comparison of Traditional and Open-Access Policies for Appointment Scheduling," Manufacturing & Service Operations Management, INFORMS, vol. 12(2), pages 330-346, June.
    14. Samorani, Michele & LaGanga, Linda R., 2015. "Outpatient appointment scheduling given individual day-dependent no-show predictions," European Journal of Operational Research, Elsevier, vol. 240(1), pages 245-257.
    15. Avishai Mandelbaum & Petar Momčilović & Nikolaos Trichakis & Sarah Kadish & Ryan Leib & Craig A. Bunnell, 2020. "Data-Driven Appointment-Scheduling Under Uncertainty: The Case of an Infusion Unit in a Cancer Center," Management Science, INFORMS, vol. 66(1), pages 243-270, January.
    16. 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.
    17. Awi Federgruen & Henri Groenevelt, 1986. "The Greedy Procedure for Resource Allocation Problems: Necessary and Sufficient Conditions for Optimality," Operations Research, INFORMS, vol. 34(6), pages 909-918, December.
    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. Christos Zacharias & Tallys Yunes, 2020. "Multimodularity in the Stochastic Appointment Scheduling Problem with Discrete Arrival Epochs," Management Science, INFORMS, vol. 66(2), pages 744-763, February.
    2. 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.
    3. Soltani, Mohamad & Samorani, Michele & Kolfal, Bora, 2019. "Appointment scheduling with multiple providers and stochastic service times," European Journal of Operational Research, Elsevier, vol. 277(2), pages 667-683.
    4. Oualid Jouini & Saif Benjaafar & Bingnan Lu & Siqiao Li & Benjamin Legros, 2022. "Appointment-driven queueing systems with non-punctual customers," Queueing Systems: Theory and Applications, Springer, vol. 101(1), pages 1-56, June.
    5. Li Luo & Ying Zhou & Bernard T. Han & Jialing Li, 2019. "An optimization model to determine appointment scheduling window for an outpatient clinic with patient no-shows," Health Care Management Science, Springer, vol. 22(1), pages 68-84, March.
    6. Murtaza Nasir & Nichalin Summerfield & Ali Dag & Asil Oztekin, 2020. "A service analytic approach to studying patient no-shows," Service Business, Springer;Pan-Pacific Business Association, vol. 14(2), pages 287-313, June.
    7. Katsumi Morikawa & Katsuhiko Takahashi & Daisuke Hirotani, 2018. "Performance evaluation of candidate appointment schedules using clearing functions," Journal of Intelligent Manufacturing, Springer, vol. 29(3), pages 509-518, March.
    8. Dongyang Wang & Kumar Muthuraman & Douglas Morrice, 2019. "Coordinated Patient Appointment Scheduling for a Multistation Healthcare Network," Operations Research, INFORMS, vol. 67(3), pages 599-618, May.
    9. Yu Fu & Amarnath Banerjee, 2021. "A Stochastic Programming Model for Service Scheduling with Uncertain Demand: an Application in Open-Access Clinic Scheduling," SN Operations Research Forum, Springer, vol. 2(3), pages 1-32, September.
    10. Van-Anh Truong, 2015. "Optimal Advance Scheduling," Management Science, INFORMS, vol. 61(7), pages 1584-1597, July.
    11. Dogru, Ali K. & Melouk, Sharif H., 2019. "Adaptive appointment scheduling for patient-centered medical homes," Omega, Elsevier, vol. 85(C), pages 166-181.
    12. Yong-Hong Kuo & Hari Balasubramanian & Yan Chen, 2020. "Medical appointment overbooking and optimal scheduling: tradeoffs between schedule efficiency and accessibility to service," Flexible Services and Manufacturing Journal, Springer, vol. 32(1), pages 72-101, March.
    13. Simsek, Serhat & Dag, Ali & Tiahrt, Thomas & Oztekin, Asil, 2021. "A Bayesian Belief Network-based probabilistic mechanism to determine patient no-show risk categories," Omega, Elsevier, vol. 100(C).
    14. Yu Zhang & Vidyadhar G. Kulkarni, 2017. "Two-day appointment scheduling with patient preferences and geometric arrivals," Queueing Systems: Theory and Applications, Springer, vol. 85(1), pages 173-209, February.
    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. 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.
    17. Christos Zacharias & Michael Pinedo, 2017. "Managing Customer Arrivals in Service Systems with Multiple Identical Servers," Manufacturing & Service Operations Management, INFORMS, vol. 19(4), pages 639-656, October.
    18. Jiayi Liu & Jingui Xie & Kum Khiong Yang & Zhichao Zheng, 2019. "Effects of Rescheduling on Patient No-Show Behavior in Outpatient Clinics," Manufacturing & Service Operations Management, INFORMS, vol. 21(4), pages 780-797, October.
    19. Xuanzhu Fan & Jiafu Tang & Chongjun Yan, 2020. "Appointment scheduling optimization with two stages diagnosis for clinic outpatient," Computational Statistics, Springer, vol. 35(2), pages 469-490, June.
    20. 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).

    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:eee:ejores:v:284:y:2020:i:3:p:847-860. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.