Reducing Emergency Department overcrowding - five patient buffer concepts in comparison

Kolb,; Schoening,; Lee, Myeong Soo

doi:10.1109/wsc.2008.4736232

Cited by 38 publications

(35 citation statements)

References 23 publications

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“…26–34,38 The search of Medline, Inspec (Web of Knowledge), and Scopus produced 5,115 citations (Figure). After removing duplicates, we reviewed 4,776 unique citations.…”

Section: Resultsmentioning

confidence: 99%

“…Adding a fast track unit for low acuity patients33 and adding a holding area to remove boarding patients from ED treatment spaces as well as discharge lounge for patient awaiting a ride home or to skilled nursing facilities38 were predicted to each reducing diversion time by between 4–14%. Adding both a holding area and discharge lounge was expected to reduce diversion time by 18–24% 38. Adding an ED observation unit was predicted to have little to no effect on reducing diversion time 38.…”

Section: Resultsmentioning

confidence: 99%

“…Adding both a holding area and discharge lounge was expected to reduce diversion time by 18–24% 38. Adding an ED observation unit was predicted to have little to no effect on reducing diversion time 38. Finally, one study found that decreasing the average lab turnaround time from 120 minutes to 60 minutes would reduce the time the ED spent on diversion by at least 2 hours per day 34…”

Section: Resultsmentioning

confidence: 99%

See 2 more Smart Citations

Reducing Ambulance Diversion at the Hospital and Regional Levels: Systemic Review of Insights from Simulation Models

Delgado

Meng²,

Mercer³

et al. 2013

WestJEM

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Introduction:Optimal solutions for reducing diversion without worsening emergency department (ED) crowding are unclear. We performed a systematic review of published simulation studies to identify: 1) the tradeoff between ambulance diversion and ED wait times; 2) the predicted impact of patient flow interventions on reducing diversion; and 3) the optimal regional strategy for reducing diversion.Methods:Data Sources: Systematic review of articles using MEDLINE, Inspec, Scopus. Additional studies identified through bibliography review, Google Scholar, and scientific conference proceedings. Study Selection: Only simulations modeling ambulance diversion as a result of ED crowding or inpatient capacity problems were included. Data extraction: Independent extraction by two authors using predefined data fields.Results:We identified 5,116 potentially relevant records; 10 studies met inclusion criteria. In models that quantified the relationship between ED throughput times and diversion, diversion was found to only minimally improve ED waiting room times. Adding holding units for inpatient boarders and ED-based fast tracks, improving lab turnaround times, and smoothing elective surgery caseloads were found to reduce diversion considerably. While two models found a cooperative agreement between hospitals is necessary to prevent defensive diversion behavior by a hospital when a nearby hospital goes on diversion, one model found there may be more optimal solutions for reducing region wide wait times than a regional ban on diversion.Conclusion:Smoothing elective surgery caseloads, adding ED fast tracks as well as holding units for inpatient boarders, improving ED lab turnaround times, and implementing regional cooperative agreements among hospitals are promising avenues for reducing diversion.

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“…26–34,38 The search of Medline, Inspec (Web of Knowledge), and Scopus produced 5,115 citations (Figure). After removing duplicates, we reviewed 4,776 unique citations.…”

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Reducing Ambulance Diversion at the Hospital and Regional Levels: Systemic Review of Insights from Simulation Models

Delgado

Meng²,

Mercer³

et al. 2013

WestJEM

View full text Add to dashboard Cite

show abstract

“…Alternative options to create buffer capacity are to create an 'observation unit' (i.e. a centralized unit for patients that require a longer observation or treatment time but are unlikely to require admission [3,28]), or a dedicated 'acute medical admission unit' (AMAU) or 'holding area' [28] for patients that need to be admitted. Regardless of the practical implementation, adding buffer capacity aims to increase the number of ED beds available for patients that still require treatment.…”

Section: Model Experimentationmentioning

confidence: 99%

A Decision Support System for Capacity Planning in Emergency Departments

Carmen¹,

Defraeye²,

Nieuwenhuyse³

2015

Int. j. simul. model.

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In this article, we present a decision support system (DSS) for improving patient flow in emergency departments (EDs). The core of the system is a discrete-event simulation (DES) model that aims to support capacity planning in the ED, in view of controlling patients' length of stay (LOS). Conceptually, it regards the patient LOS as the result of different queueing systems, the behaviour of which is influenced by different types of capacities. Taking inputs from ED patient record data, the DSS allows to analyse the impact of different capacity changes on patient flow, and to detect efficient capacity combinations using data envelopment analysis (DEA). We report on the insights obtained from a case study in a large regional hospital in Belgium.

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“…It can be found in literature studies about waiting time reduction, LWOT or staffing planning using techniques like queuing theory, systems dynamics and discrete-event simulation (Broyles and Cochran 2007;Ferrin, Miller, and McBroom 2007;Roche and Cochran 2007;Brailsford 2008;Kolb et al 2008;Medeiros, Swenson, and DeFlitch 2008), but few papers focuses on the design of diversion policies. However, The objective of this research is to analyze the effects of the setting of the ED, the number of beds in the ED and the diversion state trigger on various performance measures of the emergency system, such as the waiting time, the LWOT percentage and especially on the percentage of time on diversion, considering a large-size hospital.…”

Section: Introductionmentioning

confidence: 99%

Analysis of ambulance diversion policies for a large-size hospital

Ramírez¹,

Fowler²,

Wu³

2009

Proceedings of the 2009 Winter Simulation Conference (WSC)

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The overcrowding of Emergency Departments (EDs) is a well-known problem that has been analyzed on multiple occasions. Queuing theory and simulation have been applied extensively to specific ED situations, such as staff planning, waiting time reduction and capacity investment. However, there are remaining problems in the EDs that need more study. One of them is the ambulance diversion, which may cause a delay in the treatment of urgent patients therefore jeopardizing their welfare. Since ED are complex system and setting the diversion state in EDs is a subjective decision, a detailed modeling and analysis of cause and effects of such a decision is beneficial. In this research, we build a case-study and analyze the impact of diversion policies in various performance measures of the ED through a designed experiment using a discrete-event simulation model.

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Reducing Emergency Department overcrowding - five patient buffer concepts in comparison

Cited by 38 publications

References 23 publications

Reducing Ambulance Diversion at the Hospital and Regional Levels: Systemic Review of Insights from Simulation Models

Reducing Ambulance Diversion at the Hospital and Regional Levels: Systemic Review of Insights from Simulation Models

A Decision Support System for Capacity Planning in Emergency Departments

Analysis of ambulance diversion policies for a large-size hospital

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