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Improving resource utilization for diagnostic services through flexible inpatient scheduling: A method for improving resource utilization

Author

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  • J Patrick

    (University of British Columbia)

  • M L Puterman

    (University of British Columbia)

Abstract

We present a method to increase the utilization of and reduce the waiting times for an under-capacitated diagnostic resource in the presence of uncertain demand with several priority levels. We consider the case of a computed tomography (CT) scanning department that services both high-priority in-patients and lower priority outpatients. Current practice calls for all in-patient demand to be met on the day of the request. Our proposal looks at the benefit of reserving space for carrying over a percentage of non-emergency in-patient demand to the next day and utilizing a pool of on-call outpatients who can respond quickly to available capacity. We formulate and solve an optimization problem that returns a reservation policy that minimizes unused capacity subject to an overtime constraint. We use a simulation to demonstrate a significant reduction in the growth rate of outpatient waiting time resulting from using the proposed method and investigate the sensitivity of results to several model assumptions.

Suggested Citation

  • J Patrick & M L Puterman, 2007. "Improving resource utilization for diagnostic services through flexible inpatient scheduling: A method for improving resource utilization," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(2), pages 235-245, February.
    • Handle: RePEc:pal:jorsoc:v:58:y:2007:i:2:d:10.1057_palgrave.jors.2602242
    DOI: 10.1057/palgrave.jors.2602242
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    References listed on IDEAS

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    Cited by:

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    2. 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.
    3. Namakshenas, Mohammad & Mazdeh, Mohammad Mahdavi & Braaksma, Aleida & Heydari, Mehdi, 2023. "Appointment scheduling for medical diagnostic centers considering time-sensitive pharmaceuticals: A dynamic robust optimization approach," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1018-1031.
    4. 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.
    5. 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.
    6. Yiting Xing & Ling Li & Zhuming Bi & Marzena Wilamowska‐Korsak & Li Zhang, 2013. "Operations Research (OR) in Service Industries: A Comprehensive Review," Systems Research and Behavioral Science, Wiley Blackwell, vol. 30(3), pages 300-353, May.
    7. 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.
    8. 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.
    9. Gang Du & Xinyue Li & Hui Hu & Xiaoling Ouyang, 2018. "Optimizing Daily Service Scheduling for Medical Diagnostic Equipment Considering Patient Satisfaction and Hospital Revenue," Sustainability, MDPI, vol. 10(9), pages 1-23, September.
    10. Geng, Na & Xie, Xiaolan, 2012. "Optimizing contracted resource capacity with two advance cancelation modes," European Journal of Operational Research, Elsevier, vol. 221(3), pages 501-512.
    11. 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.
    12. Na Geng & Letian Chen & Ran Liu & Yanhong Zhu, 2017. "Optimal patient assignment for W queueing network in a diagnostic facility setting," International Journal of Production Research, Taylor & Francis Journals, vol. 55(19), pages 5609-5631, October.
    13. Yifei Sun & Usha Nandini Raghavan & Vikrant Vaze & Christopher S Hall & Patricia Doyle & Stacey Sullivan Richard & Christoph Wald, 2021. "Stochastic programming for outpatient scheduling with flexible inpatient exam accommodation," Health Care Management Science, Springer, vol. 24(3), pages 460-481, September.
    14. 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.
    15. Eduardo Pérez & Lewis Ntaimo & César Malavé & Carla Bailey & Peter McCormack, 2013. "Stochastic online appointment scheduling of multi-step sequential procedures in nuclear medicine," Health Care Management Science, Springer, vol. 16(4), pages 281-299, December.
    16. Hejer Khlif Hachicha & Farah Zeghal Mansour, 2018. "Two-MILP models for scheduling elective surgeries within a private healthcare facility," Health Care Management Science, Springer, vol. 21(3), pages 376-392, September.
    17. 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.
    18. Merehau Cindy Mervin & Sukhan Jackson, 2009. "How can we improve waiting time for elective surgery in Australian public hospitals?," Discussion Papers Series 387, School of Economics, University of Queensland, Australia.

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