Success and failure in the simulation of an Accident and Emergency department

Bowers, John; Ghattas, Mikhail; Mould, Gillian

doi:10.1057/jos.2009.5

Cited by 24 publications

(14 citation statements)

References 15 publications

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“…As such, the time needed for detailed modelling (and associated data collection) to make an impact is rarely available. This is similar to the experience of Bowers et al (2009) who found initial 'simple' analyses and work useful for an ED, but the time needed for more complex M&S meant that delivery was too late for impact. The literature on the M&S of ED's is extensive, as illustrated by a recent reviews (Gul and Guneri 2015;Saghafian et al 2015).…”

Section: Where Next For Ed Simulation?supporting

confidence: 64%

Using simulation to help hospitals reduce emergency department waiting times: Examples and impact

Monks¹,

Meskarian²

2017

2017 Winter Simulation Conference (WSC)

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In recent years, all acute hospitals in the UK have experienced unprecedented emergency department waiting times and hospital bed pressures. The consequences are overcrowded emergency departments, ambulance shortages, cancelled elective operations, low staff morale and financial penalties. To deal with the increasing numbers of patient admissions and delayed discharges hospitals must turn now to modelling and simulation to help increase their flexibility and ability to deal with demand variation. Hospitals face several issues that reduce their flexibility including the need for extreme value-for-money and specialization of care. This talk presents three ED case studies undertaken by an analytics team in the UK. The paper considers the impact of the work and challenges arising from their experiences of simulation modelling in acute hospitals. Final thoughts consider the future of ED simulation. INTRODUCTIONEmergency department (ED) overcrowding is common in the United Kingdom's (UK) National Health Service (NHS). In England, performance of EDs are publicly reported using the (infamous) four hour waiting (cycle) time target. The target was originally set to a 100% level of compliance, but was quickly relaxed to 98% in 2004 and then 95% from 2010. The pressure felt in an NHS ED is closely linked to bed pressure within the main hospital (Cooke et al. 2004). Bed pressures and subsequent poor ED performance are due to systemic issues ranging from capacity in community based care, such as social services and nursing homes, lack of investment in public health, and the aging population. While the long term solutions to the systemic problem are sought, hospitals must find ways to increase their short term flexibility to deal with variation in demand and length of patient stay. Many of the flexibility issues experienced by hospitals can be conceptualized as queuing problems. Modelling and Simulation (M&S) therefore has a key role to play in finding solutions that ease the pressure on ED's and hospitals. M&S has been used extensively to study EDs (Gul and Guneri 2015). The majority of studies take a discrete-event simulation approach (DES; e.g. Coats and Michalis 2001;Günal and Pidd 2009;Paul and Lin 2012;Chavis et al. 2016;Oh et al. 2016;Wong et al. 2016;Yang et al. 2016). DES studies have typically focused on the number and scheduling of resources within the ED (Saghafian et al. 2015). Few studies appear to have worked with hospitals to examine the flexibility of the ED and associated processes to deal with variation in demand. With the exception of a few large centers in the UK, hospitals are unlikely to have the finance for substantial increases in their ED staffing. Hence the efficiency and flexibility of processes has become ever more important. This paper first presents some of the challenges UK hospitals face in managing demand and the options they have used in order to have the flexibility to meet waiting time targets in the face of hospital bed pressures. We describe available data sources for M&S and deta...

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Section: Where Next For Ed Simulation?supporting

confidence: 64%

Using simulation to help hospitals reduce emergency department waiting times: Examples and impact

Monks¹,

Meskarian²

2017

2017 Winter Simulation Conference (WSC)

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“…This poses a major modelling challenge: simulating the whole hospital is one approach but more commonly A&E simulations strive to capture the critical characteristics of these interactions without a commitment to producing a model of the whole hospital in detail. The NHS Fife A&E simulation has been described elsewhere (Bowers et al, 2009); the summary below focuses on the contribution of the simulation to the redesign process and the relationship with the client.…”

Section: Simulation Of Accident and Emergency Care In Nhs Fifementioning

confidence: 99%

Exploring alternative routes to realising the benefits of simulation in healthcare

Bowers

Ghattas

Mould

2012

Journal of the Operational Research Society

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Discrete event simulation should offer numerous benefits in designing healthcare systems but the reality is often problematic. Healthcare modelling faces particular challenges: genuine, fundamental variations in practice and an opposition to any suggestion of standardisation from some professional groups. This paper compares the experiences of developing a new simulation in an Accident and Emergency (A&E) Department, a subsequent adaptation for modelling an outpatient clinic and applications of a generic A&E simulation. These studies provide examples of three distinct approaches to realising the potential benefits of simulation: the bespoke, the reuse and the generic route. Reuse has many advantages: it is relatively efficient in exploiting previous modelling experience, delivering timely results while providing scope for adaptations to local practice. Explicitly demonstrating this willingness to adapt to local conditions and engaging with stakeholders is particularly important in healthcare simulation.

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“…A review of this literature reveals that only 6 of the papers even make mention of the 4-hour standard (Codrington-Virtue et al 2006;Gunal and Pidd 2006;Bowers, Ghattas and Mould 2009;Gunal and Pidd 2009;Maulla et al 2009) and of these only two include it in their analysis of the throughput times. Maulla et al (2009) conclude that "…it is not a case of medical staff misreporting the LoS [Length of Stay] but of adapting their behaviour to meet the 4 h target" while Gunal and Pidd (2009) state "…it is reasonable to suppose that the looming breach point caused the department to find ways to quickly complete the processing of a small proportion of their patients."…”

Section: Literature Reviewmentioning

confidence: 99%

Meeting the four‐hour deadline in an A&E department

Eatock

Clarke

Picton³

2011

Journal of Health Organization and Management

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Purpose: A&E departments experience a secondary peak in patient Length of Stay (LoS) at around 4-hours, caused by the coping strategies used to meet the operational standards imposed by government. We aim to build a discrete-event simulation model that captures the coping strategies and more accurately reflects the processes that occur within an A&E department.Design/methodology/approach: A Discrete-event simulation (DES) model was used to capture the A&E process at a UK hospital and record the LoS for each patient. Input data on 4150 arrivals over three one-week periods and staffing levels was obtained from hospital records, while output data was compared with the corresponding records. Expert opinion was used to generate the pathways and model the decision-making processes Findings : We were able accurately to replicate the LoS distribution for the hospital. The model was then applied to a second configuration which had been trialled there, again the results also reflected the experiences of the hospital. Practical implications:This demonstrates the coping strategies, such as re-prioritising patients based on current length of time in the department, employed in A&E departments have an impact on LoS of patients and therefore need to be considered when building predictive models if confidence in the results is to be justified. Originality/value:As far as the authors are aware this is the first time that these coping strategies have been included within a simulation model, and therefore the first time that the peak around the four-hour has been so accurately analysed using a model. Biography: Having completed his doctoral research in laser spectroscopy Terry Young moved into industrial research using Finite Elements and other simulation techniques to model photonic switches, filters and other components for optical communication networks. Moving up-system and through layers of management, he migrated to a role that informed corporate strategy in healthcare. In 2001 he became Professor of Healthcare Systems at Brunel, since when his research has embraced care delivery, organisationally and in technological terms. His grant portfolio has included both the MATCH and RIGHT projects, under which and through which, this research was performed. Keywords 1Meeting the four-hour deadline in an A&E Department Abstract Purpose: A&E departments experience a secondary peak in patient Length of Stay (LoS) at around 4-hours, caused by the coping strategies used to meet the operational standards imposed by government. We aim to build a discrete-event simulation model that captures the coping strategies and more accurately reflects the processes that occur within an A&E department.Design/methodology/approach: A Discrete-event simulation (DES) model was used to capture the A&E process at a UK hospital and record the LoS for each patient. Input data on 4150 arrivals over three one-week periods and staffing levels was obtained from hospital records, while output data was compared with the corresponding records. Expert opinio...

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Success and failure in the simulation of an Accident and Emergency department

Cited by 24 publications

References 15 publications

Using simulation to help hospitals reduce emergency department waiting times: Examples and impact

Using simulation to help hospitals reduce emergency department waiting times: Examples and impact

Exploring alternative routes to realising the benefits of simulation in healthcare

Meeting the four‐hour deadline in an A&E department

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