UMMS Affiliation

Department of Emergency Medicine; Department of Quantitative Health Sciences; Center for Innovation and Transformational Change, UMass Memorial Health Care; Operational Excellence, UMass Memorial Health Care

Publication Date

3-28-2017

Document Type

Article

Disciplines

Biomedical Engineering and Bioengineering | Computer Sciences | Emergency Medicine | Health Information Technology | Mathematics | Statistics and Probability

Abstract

Emergency departments (EDs) are seeking ways to utilize existing resources more efficiently as they face rising numbers of patient visits. This study explored the impact on patient wait times and nursing resource demand from the addition of a fast track, or separate unit for low-acuity patients, in the ED using a queue-based Monte Carlo simulation in MATLAB. The model integrated principles of queueing theory and expanded the discrete event simulation to account for time-based arrival rates. Additionally, the ED occupancy and nursing resource demand were modeled and analyzed using the Emergency Severity Index (ESI) levels of patients, rather than the number of beds in the department. Simulation results indicated that the addition of a separate fast track with an additional nurse reduced overall median wait times by 35.8 +/- 2.2 percent and reduced average nursing resource demand in the main ED during hours of operation. This novel modeling approach may be easily disseminated and informs hospital decision-makers of the impact of implementing a fast track or similar system on both patient wait times and acuity-based nursing resource demand.

Keywords

emergency departments, patient wait times, nursing resource demand, fast track, low-acuity patients, queues, Monte Carlo simulation, MATLAB

Rights and Permissions

Copyright © 2017 Kristin Fitzgerald et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

DOI of Published Version

10.1155/2017/6536523

Source

J Healthc Eng. 2017;2017:6536523. doi: 10.1155/2017/6536523. Epub 2017 Mar 28. Link to article on publisher's site

Journal/Book/Conference Title

Journal of healthcare engineering

Related Resources

Link to Article in PubMed

PubMed ID

29065634

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

 
 

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