IDEAS home Printed from https://ideas.repec.org/a/kap/hcarem/v23y2020i1d10.1007_s10729-019-09485-1.html
   My bibliography  Save this article

Symbiotic simulation for the operational management of inpatient beds: model development and validation using Δ-method

Author

Listed:
  • David Oakley

    (Lancaster University Management School, Lancaster University)

  • Bhakti Stephan Onggo

    (University of Southampton)

  • Dave Worthington

    (Lancaster University Management School, Lancaster University)

Abstract

In many modern hospitals, resources are shared between patients who require immediate care, and must be dealt with as they arrive (emergency patients), and those whose care requirements are partly known to the hospital some time in advance (elective patients). Catering for these two types of patients is a challenging short-term operational decision-making problem, since some portion of each resource must be set aside for emergency patients when planning for the number and type of elective patients to admit. This paper shows how symbiotic simulation can help hospitals with important short-term operational decision making. We demonstrate how a symbiotic simulation model can be developed from an existing simulation model by adding the ability to load the state of the physical system at run-time and by making use of conditional length-of-stay distributions. The model is parameterised using 18 months of patient administrative data from an Anonymised General Hospital. Further, we propose a new Δ-Method that is suitable for validating a stochastic symbiotic simulation model. We demonstrate the benefit of our symbiotic simulation by showing how it can be used as an early warning system, and how additional patient-level information which might only become available after admission, can affect the predicted bed census.

Suggested Citation

  • David Oakley & Bhakti Stephan Onggo & Dave Worthington, 2020. "Symbiotic simulation for the operational management of inpatient beds: model development and validation using Δ-method," Health Care Management Science, Springer, vol. 23(1), pages 153-169, March.
  • Handle: RePEc:kap:hcarem:v:23:y:2020:i:1:d:10.1007_s10729-019-09485-1
    DOI: 10.1007/s10729-019-09485-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10729-019-09485-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10729-019-09485-1?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Steven Littig & Mark Isken, 2007. "Short term hospital occupancy prediction," Health Care Management Science, Springer, vol. 10(1), pages 47-66, February.
    2. J B Jun & S H Jacobson & J R Swisher, 1999. "Application of discrete-event simulation in health care clinics: A survey," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 50(2), pages 109-123, February.
    3. De Angelis, Vanda & Felici, Giovanni & Impelluso, Paolo, 2003. "Integrating simulation and optimisation in health care centre management," European Journal of Operational Research, Elsevier, vol. 150(1), pages 101-114, October.
    4. Adrian Fletcher & Dave Worthington, 2009. "What is a ‘generic’ hospital model?—a comparison of ‘generic’ and ‘specific’ hospital models of emergency patient flows," Health Care Management Science, Springer, vol. 12(4), pages 374-391, December.
    5. A. Bruin & R. Bekker & L. Zanten & G. Koole, 2010. "Dimensioning hospital wards using the Erlang loss model," Annals of Operations Research, Springer, vol. 178(1), pages 23-43, July.
    6. Jonathan E. Helm & Mark P. Van Oyen, 2014. "Design and Optimization Methods for Elective Hospital Admissions," Operations Research, INFORMS, vol. 62(6), pages 1265-1282, December.
    7. Abo-Hamad, Waleed & Arisha, Amr, 2013. "Simulation-based framework to improve patient experience in an emergency department," European Journal of Operational Research, Elsevier, vol. 224(1), pages 154-166.
    8. Kusters, Rob J. & Groot, Petra M. A., 1996. "Modelling resource availability in general hospitals design and implementation of a decision support model," European Journal of Operational Research, Elsevier, vol. 88(3), pages 428-445, February.
    9. P R Harper & A K Shahani, 2002. "Modelling for the planning and management of bed capacities in hospitals," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(1), pages 11-18, January.
    10. John H. Milsum & Efraim Turban & Ilan Vertinsky, 1973. "Hospital Admission Systems: Their Evaluation and Management," Management Science, INFORMS, vol. 19(6), pages 646-666, February.
    11. Robert W. Klein & Robert S. Dittus & Stephen D. Roberts & James R. Wilson, 1993. "Simulation Modeling and Health-care Decision Making," Medical Decision Making, , vol. 13(4), pages 347-354, December.
    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. Kerryn R Owen & Ripon K Chakrabortty, 2024. "Verification, validation, and accreditation for models and simulations in the Australian defence context: a review," The Journal of Defense Modeling and Simulation, , vol. 21(2), pages 205-227, April.

    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. Willoughby, Keith A. & Chan, Benjamin T.B. & Marques, Shauna, 2016. "Using simulation to test ideas for improving speech language pathology services," European Journal of Operational Research, Elsevier, vol. 252(2), pages 657-664.
    2. Yong-Hong Kuo & Omar Rado & Benedetta Lupia & Janny M. Y. Leung & Colin A. Graham, 2016. "Improving the efficiency of a hospital emergency department: a simulation study with indirectly imputed service-time distributions," Flexible Services and Manufacturing Journal, Springer, vol. 28(1), pages 120-147, June.
    3. Hui Zhang & Thomas J. Best & Anton Chivu & David O. Meltzer, 2020. "Simulation-based optimization to improve hospital patient assignment to physicians and clinical units," Health Care Management Science, Springer, vol. 23(1), pages 117-141, March.
    4. 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.
    5. Eren Demir & Christos Vasilakis & Reda Lebcir & David Southern, 2015. "A simulation-based decision support tool for informing the management of patients with Parkinson’s disease," International Journal of Production Research, Taylor & Francis Journals, vol. 53(24), pages 7238-7251, December.
    6. Kaya, Onur & Teymourifar, Aydin & Ozturk, Gurkan, 2020. "Analysis of different public policies through simulation to increase total social utility in a healthcare system," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    7. Mahdavi, Mahdi & Malmström, Tomi & van de Klundert, Joris & Elkhuizen, Sylvia & Vissers, Jan, 2013. "Generic operational models in health service operations management: A systematic review," Socio-Economic Planning Sciences, Elsevier, vol. 47(4), pages 271-280.
    8. Arnoud Bruin & A. Rossum & M. Visser & G. Koole, 2007. "Modeling the emergency cardiac in-patient flow: an application of queuing theory," Health Care Management Science, Springer, vol. 10(2), pages 125-137, June.
    9. Hessam Bavafa & Charles M. Leys & Lerzan Örmeci & Sergei Savin, 2019. "Managing Portfolio of Elective Surgical Procedures: A Multidimensional Inverse Newsvendor Problem," Operations Research, INFORMS, vol. 67(6), pages 1543-1563, November.
    10. Veneklaas, W. & Leeftink, A.G. & van Boekel, P.H.C.M. & Hans, E.W., 2021. "On the design, implementation, and feasibility of hospital admission services: The admission lounge case," Omega, Elsevier, vol. 100(C).
    11. Broyles, James R. & Cochran, Jeffery K. & Montgomery, Douglas C., 2010. "A statistical Markov chain approximation of transient hospital inpatient inventory," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1645-1657, December.
    12. 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.
    13. Fermín Mallor & Cristina Azcárate & Julio Barado, 2016. "Control problems and management policies in health systems: application to intensive care units," Flexible Services and Manufacturing Journal, Springer, vol. 28(1), pages 62-89, June.
    14. Fermín Mallor & Cristina Azcárate, 2014. "Combining optimization with simulation to obtain credible models for intensive care units," Annals of Operations Research, Springer, vol. 221(1), pages 255-271, October.
    15. Carter, Michael W. & Busby, Carolyn R., 2023. "How can operational research make a real difference in healthcare? Challenges of implementation," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1059-1068.
    16. Vahab Vahdat & Jacqueline Griffin & James E. Stahl, 2018. "Decreasing patient length of stay via new flexible exam room allocation policies in ambulatory care clinics," Health Care Management Science, Springer, vol. 21(4), pages 492-516, December.
    17. Peter VanBerkel & John Blake, 2007. "A comprehensive simulation for wait time reduction and capacity planning applied in general surgery," Health Care Management Science, Springer, vol. 10(4), pages 373-385, December.
    18. Kim, Seung-Chul & Horowitz, Ira, 2002. "Scheduling hospital services: the efficacy of elective-surgery quotas," Omega, Elsevier, vol. 30(5), pages 335-346, October.
    19. Sebastian Rachuba & Andrew Salmon & Zhivko Zhelev & Martin Pitt, 2018. "Redesigning the diagnostic pathway for chest pain patients in emergency departments," Health Care Management Science, Springer, vol. 21(2), pages 177-191, June.
    20. Lauren Cipriano & Bert Chesworth & Chris Anderson & Gregory Zaric, 2007. "Predicting joint replacement waiting times," Health Care Management Science, Springer, vol. 10(2), pages 195-215, June.

    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:kap:hcarem:v:23:y:2020:i:1:d:10.1007_s10729-019-09485-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.