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Performance evaluation of candidate appointment schedules using clearing functions

Author

Listed:
  • Katsumi Morikawa

    (Hiroshima University)

  • Katsuhiko Takahashi

    (Hiroshima University)

  • Daisuke Hirotani

    (Prefectural University of Hiroshima)

Abstract

This study is concerned with the problem of reducing the waiting times of outpatients. Both scheduled patients and walk-ins are included among the outpatients to reflect the typical medical environment in Japan. The consultation time of a hospital is divided into several blocks, and each scheduled patient is given the start time of a block as his or her scheduled time of the consultation as an appointment. It is assumed that all scheduled patients arrive at the hospital at their scheduled times, while walk-ins arrive randomly. A set of candidate appointment schedules is given, and the process of selecting promising schedules in terms of average waiting times is the focus of the work. To support the selection process without conducting a conventional simulation, the notion of a clearing function is adopted to evaluate each candidate schedule. The clearing function of a system gives the expected output or throughput of the system under varying levels of workload of the system. Although it is necessary to conduct exploratory experiments in advance to obtain the clearing function, the expected waiting time can be estimated by simple calculations with the aid of the clearing function. The average waiting times of four schedules in two scenarios are calculated and compared with those obtained from conventional simulations. It is revealed that the proposed procedure based on the clearing function gives acceptable estimated average values.

Suggested Citation

  • 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.
  • Handle: RePEc:spr:joinma:v:29:y:2018:i:3:d:10.1007_s10845-015-1134-5
    DOI: 10.1007/s10845-015-1134-5
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    References listed on IDEAS

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    1. Hubert Missbauer & Reha Uzsoy, 2011. "Optimization Models of Production Planning Problems," International Series in Operations Research & Management Science, in: Karl G. Kempf & Pınar Keskinocak & Reha Uzsoy (ed.), Planning Production and Inventories in the Extended Enterprise, chapter 0, pages 437-507, Springer.
    2. Chrwan-Jyh Ho & Hon-Shiang Lau, 1992. "Minimizing Total Cost in Scheduling Outpatient Appointments," Management Science, INFORMS, vol. 38(12), pages 1750-1764, December.
    3. Sabine Sickinger & Rainer Kolisch, 2009. "The performance of a generalized Bailey–Welch rule for outpatient appointment scheduling under inpatient and emergency demand," Health Care Management Science, Springer, vol. 12(4), pages 408-419, December.
    4. Mahmoud H. Alrefaei & Sigrún Andradóttir, 1999. "A Simulated Annealing Algorithm with Constant Temperature for Discrete Stochastic Optimization," Management Science, INFORMS, vol. 45(5), pages 748-764, May.
    5. 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.
    6. Wen-Ya Wang & Diwakar Gupta, 2011. "Adaptive Appointment Systems with Patient Preferences," Manufacturing & Service Operations Management, INFORMS, vol. 13(3), pages 373-389, July.
    7. Linda V. Green & Sergei Savin, 2008. "Reducing Delays for Medical Appointments: A Queueing Approach," Operations Research, INFORMS, vol. 56(6), pages 1526-1538, December.
    8. Guido Kaandorp & Ger Koole, 2007. "Optimal outpatient appointment scheduling," Health Care Management Science, Springer, vol. 10(3), pages 217-229, September.
    9. 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.
    10. 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.
    11. 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.
    12. Rachel R. Chen & Lawrence W. Robinson, 2014. "Sequencing and Scheduling Appointments with Potential Call-In Patients," Production and Operations Management, Production and Operations Management Society, vol. 23(9), pages 1522-1538, September.
    13. Morikawa, Katsumi & Takahashi, Katsuhiko & Hirotani, Daisuke, 2014. "Make-to-stock policies for a multistage serial system under a make-to-order production environment," International Journal of Production Economics, Elsevier, vol. 147(PA), pages 30-37.
    14. Linda V. Green & Sergei Savin & Ben Wang, 2006. "Managing Patient Service in a Diagnostic Medical Facility," Operations Research, INFORMS, vol. 54(1), pages 11-25, February.
    15. 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.
    16. Julia Pahl & Stefan Voß & David Woodruff, 2007. "Production planning with load dependent lead times: an update of research," Annals of Operations Research, Springer, vol. 153(1), pages 297-345, September.
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