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Comparison of Two Scheduling Systems

Author

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  • A. Soriano

    (Institute for Defense Analyses, Arlington, Virginia)

Abstract

The delays that outpatients have to undergo before getting their medical treatment are often excessively long. The most commonly used patterns of scheduling appointments to patients are classified into three categories: (1) Pure Block Appointment systems, (2) Individual Appointment Systems, and (3) Mixed Block-Individual Appointment Systems. Several analytical studies have been concerned with the comparison of some of these appointment systems, and their highlights are described briefly. There are many other possible ways of assigning appointments to patients; one such way, referred to as the Two-at-a-Time Appointment System, is described. The advantages of the Two-at-a-Time Appointment System over any of the commonly used ones are discussed. Finally, the steady-state waiting time distribution functions that will correspond to the Two-at-a-Time Appointment System and the Individual Appointment System, as applied to the Wilmer Outpatient Clinic, have been obtained and are compared.

Suggested Citation

  • A. Soriano, 1966. "Comparison of Two Scheduling Systems," Operations Research, INFORMS, vol. 14(3), pages 388-397, June.
    • Handle: RePEc:inm:oropre:v:14:y:1966:i:3:p:388-397
    DOI: 10.1287/opre.14.3.388
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    Cited by:

    1. Brian Denton & James Viapiano & Andrea Vogl, 2007. "Optimization of surgery sequencing and scheduling decisions under uncertainty," Health Care Management Science, Springer, vol. 10(1), pages 13-24, February.
    2. 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.
    3. Qingxia Kong & Chung-Yee Lee & Chung-Piaw Teo & Zhichao Zheng, 2013. "Scheduling Arrivals to a Stochastic Service Delivery System Using Copositive Cones," Operations Research, INFORMS, vol. 61(3), pages 711-726, June.
    4. Kum Khiong Yang & Mun Ling Lau & Ser Aik Quek, 1998. "A new appointment rule for a single‐server, multiple‐customer service system," Naval Research Logistics (NRL), John Wiley & Sons, vol. 45(3), pages 313-326, April.
    5. Shehadeh, Karmel S. & Cohn, Amy E.M. & Epelman, Marina A., 2019. "Analysis of models for the Stochastic Outpatient Procedure Scheduling Problem," European Journal of Operational Research, Elsevier, vol. 279(3), pages 721-731.
    6. Tugba Cayirli & Kum Khiong Yang & Ser Aik Quek, 2012. "A Universal Appointment Rule in the Presence of No‐Shows and Walk‐Ins," Production and Operations Management, Production and Operations Management Society, vol. 21(4), pages 682-697, July.
    7. 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.
    8. Kuiper, Alex & de Mast, Jeroen & Mandjes, Michel, 2021. "The problem of appointment scheduling in outpatient clinics: A multiple case study of clinical practice," Omega, Elsevier, vol. 98(C).
    9. Marie Matta & Sarah Patterson, 2007. "Evaluating multiple performance measures across several dimensions at a multi-facility outpatient center," Health Care Management Science, Springer, vol. 10(2), pages 173-194, June.
    10. Shenghai Zhou & Yichuan Ding & Woonghee Tim Huh & Guohua Wan, 2021. "Constant Job‐Allowance Policies for Appointment Scheduling: Performance Bounds and Numerical Analysis," Production and Operations Management, Production and Operations Management Society, vol. 30(7), pages 2211-2231, July.
    11. Qu, Xiuli & Rardin, Ronald L. & Williams, Julie Ann S. & Willis, Deanna R., 2007. "Matching daily healthcare provider capacity to demand in advanced access scheduling systems," European Journal of Operational Research, Elsevier, vol. 183(2), pages 812-826, December.
    12. 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.
    13. Ho, Chrwan-Jyh & Lau, Hon-Shiang, 1999. "Evaluating the impact of operating conditions on the performance of appointment scheduling rules in service systems," European Journal of Operational Research, Elsevier, vol. 112(3), pages 542-553, February.
    14. Brian T. Denton & Andrew J. Miller & Hari J. Balasubramanian & Todd R. Huschka, 2010. "Optimal Allocation of Surgery Blocks to Operating Rooms Under Uncertainty," Operations Research, INFORMS, vol. 58(4-part-1), pages 802-816, August.
    15. Lawrence W. Robinson & Rachel R. Chen, 2011. "Estimating the Implied Value of the Customer's Waiting Time," Manufacturing & Service Operations Management, INFORMS, vol. 13(1), pages 53-57, February.
    16. 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.
    17. 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.
    18. Creemers, Stefan & Lambrecht, Marc R. & Beliën, Jeroen & Van den Broeke, Maud, 2021. "Evaluation of appointment scheduling rules: A multi-performance measurement approach," Omega, Elsevier, vol. 100(C).

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