SynthesisBMJ open2017
Synthesis in BMJ open, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 5 of them syntheses 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
40 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Pooled it
- Patient flow in emergency departments: a comprehensive umbrella review of solutions and challenges across the health system.BMC health services research · 2024Pooled it
- Pooled it
- Mathematical modelling for health systems research: a systematic review of system dynamics and agent-based models.BMC health services research · 2019Pooled it
- Simulation Modelling in Healthcare: An Umbrella Review of Systematic Literature Reviews.PharmacoEconomics · 2017Pooled it
- Cost-effectiveness of anti-vascular endothelial growth factor and macular laser treatments for people with centre-involving diabetic macular oedema and central retinal thickness of at least 400 micrometres.Eye (London, England) · 2025Article
- "A banana in the tailpipe": a qualitative study of patient flow in the healthcare system.BMC health services research · 2025Article
- A Markov model assessing the cost-effectiveness of various anti-vascular endothelial growth factor drugs and panretinal photocoagulation for the treatment of proliferative diabetic retinopathy.Eye (London, England) · 2025Article
- Review
- Key performance indicators in emergency department simulation: a scoping review.Scandinavian journal of trauma, resuscitation and emergency medicine · 2025Article
- Optimizing Emergency Department Operations: A Simulation Framework for Managerial Decision-Making.Journal of nursing management · 2025Article
- Improving COVID-19 vaccination centre operation through computer modelling and simulation.Health systems (Basingstoke, England) · 2025Article
- Early COVID-19 Pandemic Preparedness: Informing Public Health Interventions and Hospital Capacity Planning Through Participatory Hybrid Simulation Modeling.International journal of environmental research and public health · 2024Article
- Work Systems Analysis of Emergency Nurse Patient Flow Management Using the Systems Engineering Initiative for Patient Safety Model: Applying Findings From a Grounded Theory Study.JMIR human factors · 2024Article
- Article
- New horizons in systems engineering and thinking to improve health and social care for older people.Age and ageing · 2024Article
- What impact would reducing low-acuity attendance have on emergency department length of stay? A discrete event simulation modelling study.Emergency medicine journal : EMJ · 2023Article
- Article
- The Impact of Patient Infection Rate on Emergency Department Patient Flow: Hybrid Simulation Study in a Norwegian Case.Healthcare (Basel, Switzerland) · 2023Article
- The Patient Flow Effect of Pandemic Policies: A Hybrid Simulation Study in a Norwegian Emergency Department.Healthcare (Basel, Switzerland) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesOvercrowding in the emergency department (ED) is common in the UK as in other countries worldwide. Computer simulation is one approach used for understanding the causes of ED overcrowding and assessing the likely impact of changes to the delivery of emergency care. However, little is known about the usefulness of computer simulation for analysis of ED patient flow. We undertook a systematic review to investigate the different computer simulation methods and their contribution for analysis of patient flow within EDs in the UK.
methodsWe searched eight bibliographic databases (MEDLINE, EMBASE, COCHRANE, WEB OF SCIENCE, CINAHL, INSPEC, MATHSCINET and ACM DIGITAL LIBRARY) from date of inception until 31 March 2016. Studies were included if they used a computer simulation method to capture patient progression within the ED of an established UK National Health Service hospital. Studies were summarised in terms of simulation method, key assumptions, input and output data, conclusions drawn and implementation of results.
resultsTwenty-one studies met the inclusion criteria. Of these, 19 used discrete event simulation and 2 used system dynamics models. The purpose of many of these studies (n=16; 76%) centred on service redesign. Seven studies (33%) provided no details about the ED being investigated. Most studies (n=18; 86%) used specific hospital models of ED patient flow. Overall, the reporting of underlying modelling assumptions was poor. Nineteen studies (90%) considered patient waiting or throughput times as the key outcome measure. Twelve studies (57%) reported some involvement of stakeholders in the simulation study. However, only three studies (14%) reported on the implementation of changes supported by the simulation.
conclusionsWe found that computer simulation can provide a means to pretest changes to ED care delivery before implementation in a safe and efficient manner. However, the evidence base is small and poorly developed. There are some methodological, data, stakeholder, implementation and reporting issues, which must be addressed by future studies.
Indexed as
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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.