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Outpatient appointment scheduling with unpunctual patients

Author

Listed:
  • Han Zhu
  • Youhua (Frank) Chen
  • Eman Leung
  • Xing Liu

Abstract

This study examines the design of appointment scheduling policies with considerations of not only the conventional factors, for example, the random consultation time and multiple patient types, but also of a new factor, particularly, patient unpunctuality, that is, one patient may arrive earlier or later than the appointment time. Patient unpunctuality negatively affects the appointment scheduling system, for example, such behaviour, reduces provider productivity and clinical efficiency, increases health care costs, and limits the ability of a clinic to serve its patients population by reducing the clinic’s effective capacity. In this study, while considering patient unpunctuality, we first introduce an analytical model and show the optimality of a fixed-interval policy for a simplified two-patient model. Motivated by the result, we propose an easy-to-implement heuristic policy with a simple structure using a simulation framework to improve the performance of the appointment scheduling system. The simulation result shows that our policy is overwhelmingly preponderant in current practice. We also measure the effect of patient unpunctuality and other factors. Actual data are used to add realism to the input parameters, and practical guidelines are developed for appointment scheduling.

Suggested Citation

  • Han Zhu & Youhua (Frank) Chen & Eman Leung & Xing Liu, 2018. "Outpatient appointment scheduling with unpunctual patients," International Journal of Production Research, Taylor & Francis Journals, vol. 56(5), pages 1982-2002, March.
  • Handle: RePEc:taf:tprsxx:v:56:y:2018:i:5:p:1982-2002
    DOI: 10.1080/00207543.2017.1355574
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    Cited by:

    1. Wu, Xueqi & Zhou, Shenghai, 2022. "Sequencing and scheduling appointments on multiple servers with stochastic service durations and customer arrivals," Omega, Elsevier, vol. 106(C).
    2. Sharan Srinivas, 2020. "A Machine Learning-Based Approach for Predicting Patient Punctuality in Ambulatory Care Centers," IJERPH, MDPI, vol. 17(10), pages 1-15, May.
    3. Martin Bichler & Soeren Merting, 2021. "Randomized Scheduling Mechanisms: Assigning Course Seats in a Fair and Efficient Way," Production and Operations Management, Production and Operations Management Society, vol. 30(10), pages 3540-3559, October.
    4. Pan, Xingwei & Geng, Na & Xie, Xiaolan, 2021. "Appointment scheduling and real-time sequencing strategies for patient unpunctuality," European Journal of Operational Research, Elsevier, vol. 295(1), pages 246-260.
    5. Karmel S. Shehadeh & Amy E. M. Cohn & Ruiwei Jiang, 2021. "Using stochastic programming to solve an outpatient appointment scheduling problem with random service and arrival times," Naval Research Logistics (NRL), John Wiley & Sons, vol. 68(1), pages 89-111, February.
    6. 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.

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