ArticleBMC medical informatics and decision making2014
A flexible simulation platform to quantify and manage emergency department crowding.
Article in BMC medical informatics and decision making, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Effectiveness of Mathematical and Simulation Models for Improving Quality of Care in Emergency Departments: A Systematic Literature Review.Applied clinical informatics · 2025Pooled it
- Associations Between Anthropogenic Factors, Meteorological Factors, and Cause-Specific Emergency Department Admissions.GeoHealth · 2024Article
- Main Features and Control Strategies to Reduce Overcrowding in Emergency Departments: A Systematic Review of the Literature.Risk management and healthcare policy · 2023Review
- Modelling Granular Process Flow Information to Reduce Bottlenecks in the Emergency Department.Healthcare (Basel, Switzerland) · 2022Article
- Exploring overcrowding trends in an inner city emergence department in the UK before and during COVID-19 epidemic.BMC emergency medicine · 2021Article
- Forecasting emergency department overcrowding: A deep learning framework.Chaos, solitons, and fractals · 2020Article
- The Application of GSCM in Eliminating Healthcare Waste: Hospital EDC as an Example.International journal of environmental research and public health · 2019Review
- Simulation of a Novel Schedule for Intensivist Staffing to Improve Continuity of Patient Care and Reduce Physician Burnout.Critical care medicine · 2017Article
- A preliminary study of a novel emergency department nursing triage simulation for research applications.BMC research notes · 2017Article
- A generic method for evaluating crowding in the emergency department.BMC emergency medicine · 2016Observational
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHospital-based Emergency Departments are struggling to provide timely care to a steadily increasing number of unscheduled ED visits. Dwindling compensation and rising ED closures dictate that meeting this challenge demands greater operational efficiency.
methodsUsing techniques from operations research theory, as well as a novel event-driven algorithm for processing priority queues, we developed a flexible simulation platform for hospital-based EDs. We tuned the parameters of the system to mimic U.S. nationally average and average academic hospital-based ED performance metrics and are able to assess a variety of patient flow outcomes including patient door-to-event times, propensity to leave without being seen, ED occupancy level, and dynamic staffing and resource use.
resultsThe causes of ED crowding are variable and require site-specific solutions. For example, in a nationally average ED environment, provider availability is a surprising, but persistent bottleneck in patient flow. As a result, resources expended in reducing boarding times may not have the expected impact on patient throughput. On the other hand, reallocating resources into alternate care pathways can dramatically expedite care for lower acuity patients without delaying care for higher acuity patients. In an average academic ED environment, bed availability is the primary bottleneck in patient flow. Consequently, adjustments to provider scheduling have a limited effect on the timeliness of care delivery, while shorter boarding times significantly reduce crowding. An online version of the simulation platform is available at http://spark.rstudio.com/klopiano/EDsimulation/.
conclusionIn building this robust simulation framework, we have created a novel decision-support tool that ED and hospital managers can use to quantify the impact of proposed changes to patient flow prior to implementation.
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