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Modeling Emergency Department crowding: Restoring the balance between demand for and supply of emergency medicine.

Publication ,  Journal Article
Ansah, JP; Ahmad, S; Lee, LH; Shen, Y; Ong, MEH; Matchar, DB; Schoenenberger, L
Published in: PLoS One
2021

Emergency Departments (EDs) worldwide are confronted with rising patient volumes causing significant strains on both Emergency Medicine and entire healthcare systems. Consequently, many EDs are in a situation where the number of patients in the ED is temporarily beyond the capacity for which the ED is designed and resourced to manage-a phenomenon called Emergency Department (ED) crowding. ED crowding can impair the quality of care delivered to patients and lead to longer patient waiting times for ED doctor's consult (time to provider) and admission to the hospital ward. In Singapore, total ED attendance at public hospitals has grown significantly, that is, roughly 5.57% per year between 2005 and 2016 and, therefore, emergency physicians have to cope with patient volumes above the safe workload. The purpose of this study is to create a virtual ED that closely maps the processes of a hospital-based ED in Singapore using system dynamics, that is, a computer simulation method, in order to visualize, simulate, and improve patient flows within the ED. Based on the simulation model (virtual ED), we analyze four policies: (i) co-location of primary care services within the ED, (ii) increase in the capacity of doctors, (iii) a more efficient patient transfer to inpatient hospital wards, and (iv) a combination of policies (i) to (iii). Among the tested policies, the co-location of primary care services has the largest impact on patients' average length of stay (ALOS) in the ED. This implies that decanting non-emergency lower acuity patients from the ED to an adjacent primary care clinic significantly relieves the burden on ED operations. Generally, in Singapore, there is a tendency to strengthen primary care and to educate patients to see their general practitioners first in case of non-life threatening, acute illness.

Duke Scholars

Published In

PLoS One

DOI

EISSN

1932-6203

Publication Date

2021

Volume

16

Issue

1

Start / End Page

e0244097

Location

United States

Related Subject Headings

  • Singapore
  • Referral and Consultation
  • Primary Health Care
  • Physicians
  • Patient Transfer
  • Patient Discharge
  • Patient Admission
  • Organizational Policy
  • Length of Stay
  • Humans
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Ansah, J. P., Ahmad, S., Lee, L. H., Shen, Y., Ong, M. E. H., Matchar, D. B., & Schoenenberger, L. (2021). Modeling Emergency Department crowding: Restoring the balance between demand for and supply of emergency medicine. PLoS One, 16(1), e0244097. https://doi.org/10.1371/journal.pone.0244097
Ansah, John Pastor, Salman Ahmad, Lin Hui Lee, Yuzeng Shen, Marcus Eng Hock Ong, David Bruce Matchar, and Lukas Schoenenberger. “Modeling Emergency Department crowding: Restoring the balance between demand for and supply of emergency medicine.PLoS One 16, no. 1 (2021): e0244097. https://doi.org/10.1371/journal.pone.0244097.
Ansah JP, Ahmad S, Lee LH, Shen Y, Ong MEH, Matchar DB, et al. Modeling Emergency Department crowding: Restoring the balance between demand for and supply of emergency medicine. PLoS One. 2021;16(1):e0244097.
Ansah, John Pastor, et al. “Modeling Emergency Department crowding: Restoring the balance between demand for and supply of emergency medicine.PLoS One, vol. 16, no. 1, 2021, p. e0244097. Pubmed, doi:10.1371/journal.pone.0244097.
Ansah JP, Ahmad S, Lee LH, Shen Y, Ong MEH, Matchar DB, Schoenenberger L. Modeling Emergency Department crowding: Restoring the balance between demand for and supply of emergency medicine. PLoS One. 2021;16(1):e0244097.

Published In

PLoS One

DOI

EISSN

1932-6203

Publication Date

2021

Volume

16

Issue

1

Start / End Page

e0244097

Location

United States

Related Subject Headings

  • Singapore
  • Referral and Consultation
  • Primary Health Care
  • Physicians
  • Patient Transfer
  • Patient Discharge
  • Patient Admission
  • Organizational Policy
  • Length of Stay
  • Humans