IDEAS home Printed from https://ideas.repec.org/a/inm/oropre/v68y2020i1p250-275.html
   My bibliography  Save this article

Queueing Models for Patient-Flow Dynamics in Inpatient Wards

Author

Listed:
  • Jing Dong

    (Columbia University Business School, New York, New York 10027)

  • Ohad Perry

    (Industrial Engineering and Management Sciences, Northwestern University, Evanston, Illinois 60208)

Abstract

Hospital-related queues have unique features that are not captured by standard queueing assumptions, necessitating the development of specialized models. In this paper, we propose a queueing model that takes into account the most salient features of queues associated with patient-flow dynamics in inpatient wards, including the need for a physician’s approval to discharge patients and subsequent discharge delays. In this setting, fundamental quantities, such as the (effective) mean hospitalization time and the traffic intensity, become functions of the queueing model’s primitives. We, therefore, begin by characterizing these quantities and quantifying the impacts that the discharge policy has on the average bed utilization and maximal throughput. We then introduce a deterministic fluid model to approximate the nonstationary patient-flow dynamics. The fluid model is shown to possess a unique periodic equilibrium, which is guaranteed to be approached as time increases so that long-run performance analysis can be carried out by simply considering that equilibrium cycle. Consequently, evaluating the effects of policy changes on the system’s performance and optimizing long-run operating costs are facilitated considerably. The effectiveness of the fluid model is demonstrated via comparisons to data from a large hospital and simulation experiments.

Suggested Citation

  • Jing Dong & Ohad Perry, 2020. "Queueing Models for Patient-Flow Dynamics in Inpatient Wards," Operations Research, INFORMS, vol. 68(1), pages 250-275, January.
    • Handle: RePEc:inm:oropre:v:68:y:2020:i:1:p:250-275
    DOI: 10.1287/opre.2019.1845
    as

    Download full text from publisher

    File URL: https://doi.org/10.1287/opre.2019.1845
    Download Restriction: no
    File URL: https://libkey.io/10.1287/opre.2019.1845?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
    ---><---

    References listed on IDEAS

    as
    1. J. G. Dai & Pengyi Shi, 2019. "Inpatient Overflow: An Approximate Dynamic Programming Approach," Manufacturing & Service Operations Management, INFORMS, vol. 21(4), pages 894-911, October.
    2. Philipp Afèche, 2013. "Incentive-Compatible Revenue Management in Queueing Systems: Optimal Strategic Delay," Manufacturing & Service Operations Management, INFORMS, vol. 15(3), pages 423-443, July.
    3. Randolph Hall & David Belson & Pavan Murali & Maged Dessouky, 2006. "Modeling Patient Flows Through the Healthcare System," International Series in Operations Research & Management Science, in: Randolph W. Hall (ed.), Patient Flow: Reducing Delay in Healthcare Delivery, chapter 0, pages 1-44, Springer.
    4. Hummy Song & Anita L. Tucker & Karen L. Murrell, 2015. "The Diseconomies of Queue Pooling: An Empirical Investigation of Emergency Department Length of Stay," Management Science, INFORMS, vol. 61(12), pages 3032-3053, December.
    5. Carri W. Chan & Vivek F. Farias & Nicholas Bambos & Gabriel J. Escobar, 2012. "Optimizing Intensive Care Unit Discharge Decisions with Patient Readmissions," Operations Research, INFORMS, vol. 60(6), pages 1323-1341, December.
    6. Noah Gans & Ger Koole & Avishai Mandelbaum, 2003. "Telephone Call Centers: Tutorial, Review, and Research Prospects," Manufacturing & Service Operations Management, INFORMS, vol. 5(2), pages 79-141, September.
    7. Song-Hee Kim & Ward Whitt, 2014. "Are Call Center and Hospital Arrivals Well Modeled by Nonhomogeneous Poisson Processes?," Manufacturing & Service Operations Management, INFORMS, vol. 16(3), pages 464-480, July.
    8. J. G. Dai & Pengyi Shi, 2017. "A Two-Time-Scale Approach to Time-Varying Queues in Hospital Inpatient Flow Management," Operations Research, INFORMS, vol. 65(2), pages 514-536, April.
    9. Pengyi Shi & Mabel C. Chou & J. G. Dai & Ding Ding & Joe Sim, 2016. "Models and Insights for Hospital Inpatient Operations: Time-Dependent ED Boarding Time," Management Science, INFORMS, vol. 62(1), pages 1-28, January.
    10. Costis Maglaras & John Yao & Assaf Zeevi, 2018. "Optimal Price and Delay Differentiation in Large-Scale Queueing Systems," Management Science, INFORMS, vol. 64(5), pages 2427-2444, May.
    11. Linda V. Green & Sergei Savin, 2008. "Reducing Delays for Medical Appointments: A Queueing Approach," Operations Research, INFORMS, vol. 56(6), pages 1526-1538, December.
    12. Thomas J. Best & Burhaneddin Sandıkçı & Donald D. Eisenstein & David O. Meltzer, 2015. "Managing Hospital Inpatient Bed Capacity Through Partitioning Care into Focused Wings," Manufacturing & Service Operations Management, INFORMS, vol. 17(2), pages 157-176, May.
    13. Carri W. Chan & Jing Dong & Linda V. Green, 2017. "Queues with Time-Varying Arrivals and Inspections with Applications to Hospital Discharge Policies," Operations Research, INFORMS, vol. 65(2), pages 469-495, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Noa Zychlinski, 2023. "Applications of fluid models in service operations management," Queueing Systems: Theory and Applications, Springer, vol. 103(1), pages 161-185, February.
    2. Galit B. Yom-Tov & Carri W. Chan, 2021. "Balancing admission control, speedup, and waiting in service systems," Queueing Systems: Theory and Applications, Springer, vol. 97(1), pages 163-219, February.
    3. Masoud Kamalahmadi & Kurt M. Bretthauer & Jonathan E. Helm & Alex F. Mills & Edwin C. Coe & Alisa Judy-Malcolm & Areeba Kara & Julian Pan, 2023. "Mixing It Up: Operational Impact of Hospitalist Caseload and Case-Mix," Management Science, INFORMS, vol. 69(1), pages 283-307, January.
    4. Jinsheng Chen & Jing Dong & Pengyi Shi, 2020. "A survey on skill-based routing with applications to service operations management," Queueing Systems: Theory and Applications, Springer, vol. 96(1), pages 53-82, October.

    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. Tinglong Dai & Sridhar Tayur, 2020. "OM Forum—Healthcare Operations Management: A Snapshot of Emerging Research," Manufacturing & Service Operations Management, INFORMS, vol. 22(5), pages 869-887, September.
    2. Jim G. Dai & Pengyi Shi, 2021. "Recent Modeling and Analytical Advances in Hospital Inpatient Flow Management," Production and Operations Management, Production and Operations Management Society, vol. 30(6), pages 1838-1862, June.
    3. Jinsheng Chen & Jing Dong & Pengyi Shi, 2020. "A survey on skill-based routing with applications to service operations management," Queueing Systems: Theory and Applications, Springer, vol. 96(1), pages 53-82, October.
    4. J. G. Dai & Pengyi Shi, 2019. "Inpatient Overflow: An Approximate Dynamic Programming Approach," Manufacturing & Service Operations Management, INFORMS, vol. 21(4), pages 894-911, October.
    5. Carri W. Chan & Linda V. Green & Suparerk Lekwijit & Lijian Lu & Gabriel Escobar, 2019. "Assessing the Impact of Service Level When Customer Needs Are Uncertain: An Empirical Investigation of Hospital Step-Down Units," Management Science, INFORMS, vol. 65(2), pages 751-775, February.
    6. Dongyuan Zhan & Amy R. Ward, 2019. "Staffing, Routing, and Payment to Trade off Speed and Quality in Large Service Systems," Operations Research, INFORMS, vol. 67(6), pages 1738-1751, November.
    7. Jiekun Feng & Pengyi Shi, 2018. "Steady‐state diffusion approximations for discrete‐time queue in hospital inpatient flow management," Naval Research Logistics (NRL), John Wiley & Sons, vol. 65(1), pages 26-65, February.
    8. Jian-Jun Wang & Zongli Dai & Ai-Chih Chang & Jim Junmin Shi, 2022. "Surgical scheduling by Fuzzy model considering inpatient beds shortage under uncertain surgery durations," Annals of Operations Research, Springer, vol. 315(1), pages 463-505, August.
    9. Silviya Valeva & Guodong Pang & Andrew J. Schaefer & Gilles Clermont, 2023. "Acuity-Based Allocation of ICU-Downstream Beds with Flexible Staffing," INFORMS Journal on Computing, INFORMS, vol. 35(2), pages 403-422, March.
    10. Hummy Song & Anita L. Tucker & Ryan Graue & Sarah Moravick & Julius J. Yang, 2020. "Capacity Pooling in Hospitals: The Hidden Consequences of Off-Service Placement," Management Science, INFORMS, vol. 66(9), pages 3825-3842, September.
    11. Jingui Xie & Weifen Zhuang & Marcus Ang & Mabel C. Chou & Li Luo & David D. Yao, 2021. "Analytics for Hospital Resource Planning—Two Case Studies," Production and Operations Management, Production and Operations Management Society, vol. 30(6), pages 1863-1885, June.
    12. Yanting Chen & Jingui Xie & Taozeng Zhu, 2023. "Overflow in systems with two servers: the negative consequences," Flexible Services and Manufacturing Journal, Springer, vol. 35(3), pages 838-863, September.
    13. Carri W. Chan & Vivek F. Farias & Gabriel J. Escobar, 2017. "The Impact of Delays on Service Times in the Intensive Care Unit," Management Science, INFORMS, vol. 63(7), pages 2049-2072, July.
    14. Rachuba, Sebastian & Imhoff, Lisa & Werners, Brigitte, 2022. "Tactical blueprints for surgical weeks – An integrated approach for operating rooms and intensive care units," European Journal of Operational Research, Elsevier, vol. 298(1), pages 243-260.
    15. Yuta Kanai & Hideaki Takagi, 2021. "Markov chain analysis for the neonatal inpatient flow in a hospital," Health Care Management Science, Springer, vol. 24(1), pages 92-116, March.
    16. Ersin Körpeoğlu & Zachary Kurtz & Fatma Kılınç-Karzan & Sunder Kekre & Pat A. Basu, 2014. "Business Analytics Assists Transitioning Traditional Medicine to Telemedicine at Virtual Radiologic," Interfaces, INFORMS, vol. 44(4), pages 393-410, August.
    17. Britt W. J. Mathijsen & A. J. E. M. Janssen & Johan S. H. Leeuwaarden & Bert Zwart, 2018. "Robust heavy-traffic approximations for service systems facing overdispersed demand," Queueing Systems: Theory and Applications, Springer, vol. 90(3), pages 257-289, December.
    18. Shen, Zuo-Jun Max & Xie, Jingui & Zheng, Zhichao & Zhou, Han, 2023. "Dynamic scheduling with uncertain job types," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1047-1060.
    19. Wenqi Hu & Carri W. Chan & José R. Zubizarreta & Gabriel J. Escobar, 2018. "An Examination of Early Transfers to the ICU Based on a Physiologic Risk Score," Manufacturing & Service Operations Management, INFORMS, vol. 20(3), pages 531-549, July.
    20. Wenhui Zhou & Dongmei Wang & Weixiang Huang & Pengfei Guo, 2021. "To Pool or Not to Pool? The Effect of Loss Aversion on Queue Configurations," Production and Operations Management, Production and Operations Management Society, vol. 30(11), pages 4258-4272, November.

    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:inm:oropre:v:68:y:2020:i:1:p:250-275. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.