Evidence map›Paper›PMID 37444740›Full record

ArticleHealthcare (Basel, Switzerland)2023

The Impact of Patient Infection Rate on Emergency Department Patient Flow: Hybrid Simulation Study in a Norwegian Case.

Gaute Terning, Idriss El-Thalji, Eric Christian Brun

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Key performance indicators in emergency department simulation: a scoping review.Scandinavian journal of trauma, resuscitation and emergency medicine · 2025
    Article
  3. Patient flow modeling and simulation to study HAI incidence in an Emergency Department.Smart health : international conference, ICSH ... ICSH (Conference : Smart Health) · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Gaute TerningDepartment of Safety, Economics, and Planning, University of Stavanger, 4036 Stavanger, Norway.ORCID 0000-0002-7152-8561
Idriss El-ThaljiDepartment of Mechanical and Structural Engineering and Materials Science, University of Stavanger, 4036 Stavanger, Norway.ORCID 0000-0003-0184-3985
Eric Christian BrunDepartment of Safety, Economics, and Planning, University of Stavanger, 4036 Stavanger, Norway.ORCID 0000-0002-1668-1707

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic put emergency departments all over the world under severe and unprecedented distress. Previous methods of evaluating patient flow impact, such as in-situ simulation, tabletop studies, etc., in a rapidly evolving pandemic are prohibitively impractical, time-consuming, costly, and inflexible. For instance, it is challenging to study the patient flow in the emergency department under different infection rates and get insights using in-situ simulation and tabletop studies. Despite circumventing many of these challenges, the simulation modeling approach and hybrid agent-based modeling stand underutilized. This study investigates the impact of increased patient infection rate on the emergency department patient flow by using a developed hybrid agent-based simulation model. This study reports findings on the patient infection rate in different emergency department patient flow configurations. This study's results quantify and demonstrate that an increase in patient infection rate will lead to an incremental deterioration of the patient flow metrics average length of stay and crowding within the emergency department, especially if the waiting functions are introduced. Along with other findings, it is concluded that waiting functions, including the waiting zone, make the single average length of stay an ineffective measure as it creates a multinomial distribution of several tendencies.

Indexed as

agent-based hybrid modelCOVID-19 pandemicemergency departmenthealthcaremulti-agent hybrid modelpandemic decision supportpatient flowpatient infection rate

Identifiers

PMID37444740
PMCPMC10340372

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.