ArticlePeerJ. Computer science2020
Lean thinking by integrating with discrete event simulation and design of experiments: an emergency department expansion.
Article in PeerJ. Computer science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.
- Effectiveness of Mathematical and Simulation Models for Improving Quality of Care in Emergency Departments: A Systematic Literature Review.Applied clinical informatics · 2025Pooled it
- Data-Driven Leadership in Internal Medicine Clinics: A DES-DOE Framework for Optimizing Patient Flow and Turnaround Time.Journal of healthcare leadership · 2025Article
- Discrete-Event Simulation Modeling in Healthcare: A Comprehensive Review.International journal of environmental research and public health · 2021Review
- A Systematic Review on Lean Applications' in Emergency Departments.Healthcare (Basel, Switzerland) · 2021Review
- An efficient approach for low latency processing in stream data.PeerJ. Computer science · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMany management tools, such as Discrete Event Simulation (DES) and Lean Healthcare, are efficient to support and assist health care quality. In this sense, the study aims at using Lean Thinking (LT) principles combined with DES to plan a Canadian emergency department (ED) expansion and at meeting the demand that comes from small care centers closed. The project's purpose is reducing the patients' Length of Stay (LOS) in the ED. Additionally, they must be assisted as soon as possible after the triage process. Furthermore, the study aims at determining the ideal number of beds in the Short Stay Unit (SSU). The patients must not wait more than 180 min to be transferred.
methodsFor this purpose, the hospital decision-makers have suggested planning the expansion, and it was carried out by the simulation and modeling method. The emergency department was simulated by the software FlexSim Healthcare
resultsThe results show that the emergency department cannot meet expected demand in the initial planning scenario. Only 17.2% of the patients were completed treated, and LOS was 2213.7 (average), with a confidence interval of (2131.8-2295.6) min. However, after changing decision variables and applying LT techniques, the treated patients' number increased to 95.7% (approximately 600%). Average LOS decreased to 461.2, with a confidence interval of (453.7-468.7) min, about 79.0%. The time to be attended after the triage decrease from 404.3 min to 20.8 (19.8-21.8) min, around 95.0%, while the time to be transferred from bed to the SSU decreased by 60.0%. Moreover, the ED reduced human resources downtime, according to Lean Thinking principles.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.