The impact of an ED-only full-capacity protocol

Watase, Taketo; Fu, Rongwei; Foster, Denise; Langley, Denise; Handel, Daniel A.

doi:10.1016/j.ajem.2011.09.017

Cited by 7 publications

(6 citation statements)

References 17 publications

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“…OCM interventions, especially full-capacity protocols, have been advocated by expert organizations, 1,7,8 yet their evidence base remains weak. 9 Most studies reporting improvement in flow outcomes have featured uncontrolled pre-post designs and/or follow-up periods of less than 1 year 3,6,10–16 ; note also that the exceptions 17-19 assessed multifaceted or otherwise atypical interventions. Qualitative research on OCM has been limited to one study on the initial implementation of full-capacity protocols 20 and 2 linked studies describing patient and staff perspectives on the practice of off-servicing.…”

Section: Introductionmentioning

confidence: 99%

“Working Against Gravity”: The Uphill Task of Overcapacity Management

Kreindler

Star

Hastings

et al. 2020

Health�Serv�Insights

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While most health systems have implemented interventions to manage situations in which patient demand exceeds capacity, little is known about the long-term sustainability or effectiveness of such interventions. A large multi-jurisdictional study on patient flow in Western Canada provided the opportunity to explore experiences with overcapacity management strategies across 10 diverse health regions. Four categories of interventions were employed by all or most regions: overcapacity protocols, alternative locations for emergency patients, locations for discharge-ready inpatients, and meetings to guide redistribution of patients. Two mechanisms undergirded successful interventions: providing a capacity buffer and promoting action by inpatient units by increasing staff accountability and/or solidarity. Participants reported that interventions demanded significant time and resources and the ongoing active involvement of middle and senior management. Furthermore, although most participants characterized overcapacity management practices as effective, this effectiveness was almost universally experienced as temporary. Many regions described a context of chronic overcapacity, which persisted despite continued intervention. Processes designed to manage short-term surges in demand cannot rectify a long-term mismatch between capacity and demand; solutions at the level of system redesign are needed.

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Section: Introductionmentioning

confidence: 99%

“Working Against Gravity”: The Uphill Task of Overcapacity Management

Kreindler

Star

Hastings

et al. 2020

Health�Serv�Insights

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“…The evidence underpinning “continuous flow” is encouraging but slight. A handful of mostly before and after studies suggest that this model most consistently improves ambulance performance (offload times, diversion) and has some benefit for emergency departments, including shorter patient waiting times 45678. The only study looking at patient mortality found no increase associated with implementing a continuous flow model and boarding patients in hospital corridors 4.…”

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confidence: 99%

Continuous flow models in urgent and emergency care

Vaughan

Bruijns

2022

BMJ

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“…Shortage strategies: Protocols for managing ED capacity shortage have been formalized in an ED Surge Capacity Protocol in Alberta (Alberta Health Services 2010) and elsewhere (The College of Emergency Medicine 2014, Viccellio and Santora 2012) and medical researchers have investigated the impact of such protocols on ED crowding (Cha et al 2009, Watase et al 2012. Modelers have studied how to shift focus between triage and treatment when congestion in an ED exceeds a threshold (Zayas-Caban et al 2019).…”

Section: Literature Reviewmentioning

confidence: 99%

Modeling Yellow and Red Alert Durations for Ambulance Systems

Rastpour

Ingolfsson

Kolfal

2020

Production and Operations Management

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E mergency systems are designed to almost always have enough capacity to respond to emergencies. However, capacity shortage periods do occur and these systems need to recover quickly. In this study, we apply queueing models and study whether it is better for an emergency system to add or to expedite servers, in order to quickly recover from a capacity shortage period. We focus on emergency medical service (EMS) systems and use Erlang loss models to study Red Alerts (when all ambulances are busy) and Yellow Alerts (when the number of available ambulances falls below a threshold). We analyze two loss models: one with Markovian state-dependent service rates and one with generally and independently distributed service times. We validate the two models against EMS data sets from two cities. Despite the fact that the distribution of ambulance service times is a mixture of lognormal distributions, which is far from being exponential, we find that the loss model with Markovian state-dependent service rates provides a better representation of empirical Yellow and Red alert statistics. We build on the model with state-dependent rates and use the theory of absorbing Markov chains to quantify the impact of adding or expediting ambulances, with respect to two performance measures: (i) the duration of alert periods, and (ii) the number of lost calls. This quantification helps EMS staff (dispatchers and supervisors) to make better decisions to avoid, and to recover from, alert periods. For example, staff should not wait until a Red Alert before adding ambulances, which is a common practice, because the expected number of lost calls rapidly increases as the number of available ambulances at the action epoch decreases.

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The impact of an ED-only full-capacity protocol

Cited by 7 publications

References 17 publications

“Working Against Gravity”: The Uphill Task of Overcapacity Management

“Working Against Gravity”: The Uphill Task of Overcapacity Management

Continuous flow models in urgent and emergency care

Modeling Yellow and Red Alert Durations for Ambulance Systems

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