IDEAS home Printed from https://ideas.repec.org/a/sae/medema/v38y2018i2p246-261.html
   My bibliography  Save this article

A Discrete Event Simulation Model of Patient Flow in a General Hospital Incorporating Infection Control Policy for Methicillin-Resistant Staphylococcus Aureus (MRSA) and Vancomycin-Resistant Enterococcus (VRE)

Author

Listed:
  • Erica S. Shenoy
  • Hang Lee
  • Erin E. Ryan
  • Taige Hou
  • Rochelle P. Walensky
  • Winston Ware
  • David C. Hooper

Abstract

Background . Hospitalized patients are assigned to available staffed beds based on patient acuity and services required. In hospitals with double-occupancy rooms, patients must be additionally matched by gender. Patients with methicillin-resistant Staphylococcus aureus (MRSA) or vancomycin-resistant Enterococcus (VRE) must be bedded in single-occupancy rooms or cohorted with other patients with similar MRSA/VRE flags. Methods . We developed a discrete event simulation (DES) model of patient flow through an acute care hospital. Patients are matched to beds based on acuity, service, gender, and known MRSA/VRE colonization. Outcomes included time to bed arrival, length of stay, patient-bed acuity mismatches, occupancy, idle beds, acuity-related transfers, rooms with discordant MRSA/VRE colonization, and transmission due to discordant colonization. Results . Observed outcomes were well-approximated by model-generated outcomes for time-to-bed arrival (6.7 v. 6.2 to 6.5 h) and length of stay (3.3 v. 2.9 to 3.0 days), with overlapping 90% coverage intervals. Patient-bed acuity mismatches, where patient acuity exceeded bed acuity and where patient acuity was lower than bed acuity, ranged from 0.6 to 0.9 and 8.6 to 11.1 mismatches per h, respectively. Values for observed occupancy, total idle beds, and acuity-related transfers compared favorably to model-predicted values (91% v. 86% to 87% occupancy, 15.1 v. 14.3 to 15.7 total idle beds, and 27.2 v. 22.6 to 23.7 transfers). Rooms with discordant colonization status and transmission due to discordance were modeled without an observed value for comparison. One-way and multi-way sensitivity analyses were performed for idle beds and rooms with discordant colonization. Conclusions . We developed and validated a DES model of patient flow incorporating MRSA/VRE flags. The model allowed for quantification of the substantial impact of MRSA/VRE flags on hospital efficiency and potentially avoidable nosocomial transmission.

Suggested Citation

  • Erica S. Shenoy & Hang Lee & Erin E. Ryan & Taige Hou & Rochelle P. Walensky & Winston Ware & David C. Hooper, 2018. "A Discrete Event Simulation Model of Patient Flow in a General Hospital Incorporating Infection Control Policy for Methicillin-Resistant Staphylococcus Aureus (MRSA) and Vancomycin-Resistant Enterococ," Medical Decision Making, , vol. 38(2), pages 246-261, February.
    • Handle: RePEc:sae:medema:v:38:y:2018:i:2:p:246-261
    DOI: 10.1177/0272989X17713474
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0272989X17713474
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0272989X17713474?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. S J E Taylor & T Eldabi & G Riley & R J Paul & M Pidd, 2009. "Simulation modelling is 50! Do we need a reality check?," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 69-82, May.
    Full references (including those not matched with items on IDEAS)

    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. Ricciardi, Francesca & De Bernardi, Paola & Cantino, Valter, 2020. "System dynamics modeling as a circular process: The smart commons approach to impact management," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    2. Gogi, Anastasia & Tako, Antuela A. & Robinson, Stewart, 2016. "An experimental investigation into the role of simulation models in generating insights," European Journal of Operational Research, Elsevier, vol. 249(3), pages 931-944.
    3. R J Ormerod, 2010. "OR as rational choice: a decision and game theory perspective," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(12), pages 1761-1776, December.
    4. Mohsen Jahangirian & Simon J E Taylor & Terry Young & Stewart Robinson, 2017. "Key performance indicators for successful simulation projects," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(7), pages 747-765, July.
    5. Hideki Higashi & Jan J Barendregt, 2011. "Cost-Effectiveness of Total Hip and Knee Replacements for the Australian Population with Osteoarthritis: Discrete-Event Simulation Model," PLOS ONE, Public Library of Science, vol. 6(9), pages 1-11, September.
    6. Proudlove, N.C. & Bisogno, S. & Onggo, B.S.S. & Calabrese, A. & Levialdi Ghiron, N., 2017. "Towards fully-facilitated discrete event simulation modelling: Addressing the model coding stage," European Journal of Operational Research, Elsevier, vol. 263(2), pages 583-595.
    7. Harper, Alison & Mustafee, Navonil & Yearworth, Mike, 2021. "Facets of trust in simulation studies," European Journal of Operational Research, Elsevier, vol. 289(1), pages 197-213.
    8. K J Cairns & A H Marshall & F Kee, 2011. "Using simulation to assess cardiac first-responder schemes exhibiting stochastic and spatial complexities," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(6), pages 982-991, 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:sae:medema:v:38:y:2018:i:2:p:246-261. 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: SAGE Publications (email available below). General contact details of provider: .

    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.