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Operations Research for Health Care

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In highly congested hospitals it may be common for patients to overstay at Intensive Care Units (ICU) due to blockages and imbalances in capacity. This is inadequate clinically, as patients occupy a service they no longer need; operationally, as it disrupts flow from upstream units; and financially as ICU beds are more expensive than ward beds. Step-down beds, also known as Level 2 beds, have become an increasingly popular and less expensive alternative to ICU beds to deal with this issue. We developed a discrete event simulation model that estimates Level 2 bed needs for a large university hospital. The model innovates by simulating the entirety of the hospital’s inpatient flow and most importantly, the ICU’s daily stochastic flows based on a nursing workload scoring metrics called “Nine Equivalents of Nursing Manpower Use Score” (NEMS). Using data from a large academic hospital, the model shows the benefits of Level 2 beds in improving both patient flow and costs.


This work was supported by: The Ontario Trillium Scholarship program (OTS) (2012-2016, UWO); The Ivey International Centre for Health Innovation (IICHI) (MITACS - IT08920); Natural Sciences and Engineering Research Council of Canada (NSERC) , and the Universidade Federal do Parana (UFPR) (23075.015354/2014-94). These funding sources had no active role in the study design, collection, analysis, interpretation of data, writing of the report or decision to submit the article for publication. This research is approved by Western University’s and LHSC’s Research Ethics Board under the file # REB 105583.

We would like to acknowledge the contribution of the following: J. Kojlak, Dr. C. Martin and F. Priestap from London Health Sciences Center, London, Ontario, N6A 5W9, Canada.

This is the peer reviewed version of the following article: F. Rodrigues, G.S. Zaric, D.A. Stanford, Discrete event simulation model for planning Level 2 “step-down” bed needs using NEMS, In Operations Research for Health Care, 2017, which has been published in final form at This article may be used for non-commercial purposes in accordance with Elsevier’s Terms and Conditions for Self-Archiving." embargo period: November 7th, 2019.

Available for download on Saturday, November 16, 2019

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