2010; 32: 65–70

Distributed simulation – Accessibleimmersive training

ROGER KNEEBONE1, SONAL ARORA1, DOMINIC KING1, FERNANDO BELLO1, NICK SEVDALIS1,EVA KASSAB1, RAJ AGGARWAL1, ARA DARZI1 & DEBRA NESTEL1,2

1Imperial College London, UK, 2Monash University, Victoria, Australia

Abstract

Distributed simulation (DS) is the concept of high-fidelity immersive simulation on-demand, made widely available wherever and

whenever it is required. DS provides an easily transportable, self-contained ‘set’ for creating simulated environments within an

inflatable enclosure, at a small fraction of the cost of dedicated, static simulation facilities. High-fidelity simulation is currently

confined to a relatively small number of specialised centres. This is largely because full-immersion simulation is perceived to

require static, dedicated and sophisticated equipment, supported by expert faculty. Alternatives are needed for healthcare

professionals who cannot access such centres. We propose that elements of immersive simulations can be provided within a

lightweight, low-cost and self-contained setting which is portable and can therefore be accessed by a wide range of clinicians. We

will argue that mobile simulated environments can be taken to where they are needed, making simulation more widely available.

We develop the notion that a simulation environment need not be a fixed, static resource, but rather a ‘container’ for a range of

activities and performances, designed around the needs of individual users. We critically examine the potential of DS to widen

access to an otherwise limited resource, putting flexible, ‘just in time’ training within reach of all clinicians. Finally, we frame DS as

a ‘disruptive innovation’ with potential to radically alter the landscape of simulation-based training.

Background

Simulation is a vital part of building a safer healthcare system

and is one of the top 10 challenges for the health service in the

next decade (Donaldson 2009). Simulation can address many

limitations of traditional training imposed by a rapidly

changing landscape of care (Ziv et al. 2003; Gaba 2004a;

Issenberg & Scalese 2008) and has been shown to be

educationally effective (Issenberg et al. 2005). Key drivers

include dwindling opportunities for clinical experience (both

at the bedside and in the interventional settings such as the

operating theatre and the procedure suite); the explosion

in new surgical techniques (requiring clinicians to learn

new procedures throughout their career); and a growing

awareness of patient safety as a central issue within clinical

care, highlighting the unacceptability of learners ‘practising on

patients’.

These drivers affect clinical training across all disciplines

and at every level of experience, but are especially evident in

surgery. Surgeons in training require core skills in assisting,

dissecting, camera-holding and dealing with unexpected

problems such as bleeding, yet reductions in work hours are

reducing operative experience to alarming levels (Kneebone &

Aggarwal 2009). Earlier in training, medical students in the past

were routinely exposed to the operating theatre, becoming

acculturated to its practices through learning to scrub, gown

and assist. Curricular changes make routine attendance much

less common, generating a real need for novices to undergo

systematic induction to the operating theatre environment.

Simulation has the potential to address many of these issues

(Aggarwal et al. 2006), provided that an immersive environ-

ment can be designed which meets the requirements of effec-

tive education without jeopardising patient safety (Kneebone

2005). Learning from mistakes is regarded as a powerful

educational experience (Ziv et al. 2005) and surgeons them-

selves value simulation-based training as an arena to make

mistakes without causing harm (Arora et al. 2008). Unlike

clinical care, where the patient is at the centre of the process

and learning takes place as a by-product, simulation enables

the learner to be at the centre of the educational process.

Increasingly sophisticated simulators and simulations (a dis-

tinction we will return to later) now make it possible to

rehearse and assess the complex set of competencies required

for safe practice in an authentic environment which corre-

sponds closely to the conditions of actual practice (Moorthy

et al. 2003, 2005, 2006; Undre et al. 2007b; Arora & Sevdalis

2008; Koutantji et al. 2008).

Practice points

. Simulation has the potential to address many of the

challenges facing medical training.

. Static simulation facilities have drawbacks including cost

and availability.

. Distributed simulation represents a disruptive innovation

which provides an accessible, portable and inexpensive

training environment.

Correspondence: Dr Roger Kneebone, Reader in Surgical Education, Department of Biosurgery and Surgical Technology, 10th Floor, QEQM,

St Mary’s Hospital, Paddington, London, W2 1NY, UK. Tel: þ44(0)20 3312 1310; fax: þ44(0)20 3312 6950; email: r.kneebone@imperial.ac.uk

ISSN 0142–159X print/ISSN 1466–187X online/10/010065–6 � 2010 Informa Healthcare Ltd. 65DOI: 10.3109/01421590903419749

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Yet for all these benefits, static high-fidelity simulation has

drawbacks. Most obvious are the practical ones of cost and

availability. To date, high-fidelity simulation has usually taken

place in dedicated centres, addressing the needs of ‘high-end

users’ in established surgical teams. Such centres are expen-

sive to establish and run and are a scarce resource. Although

many such simulation centres run at full capacity, economic

and organisational pressures typically prevent them from

being routinely used within the curriculum for residents,

undergraduate medical students, nurses and others at earlier

stages of clinical learning. The number of clinicians who

receive regular training in dedicated centres is relatively small,

rendering simulation’s uptake amongst key potential markets

low (Arora et al. 2009).

There are other drawbacks too. Because the locations of

simulation centres are fixed, anyone wishing to train in them

has to travel. For obvious practical reasons, it is difficult for a

whole team to attend a distant simulator centre, reducing

realism still further. Once there, the conditions within a

simulation centre may not mirror those in participants’ home

institutions, raising concerns that the centres’ agendas take

precedence over learners’ individual needs. Thus some

simulations may be perceived as taking place in their own

universe, disconnected from the daily practice of those who

come there to learn. Of course there are exceptions.

We acknowledge the crucial importance of such centres.

Much seminal work has taken place in these environments,

establishing the value of simulation-based training, especially

for team working and handling complex situations (Gaba et al.

2001; Gaba 2004b; Undre et al. 2007a). Yet the stark reality is

that such facilities are not universally accessible. Indeed in

many countries they are either not available at all, or confined

to a small number of specialist units, thereby excluding a large

group of professionals who could potentially benefit.

The challenge of contextualisation

An obvious alternative is low and medium fidelity simulators,

which require less elaborate facilities. These are in widespread

use, mostly for learning specific procedural skills. However,

there is a danger of engendering a task-focused approach

which privileges psychomotor and dexterity skills over the

wider aspects of clinical performance. Indeed much more than

technical skill is required for safe surgical practice, with

high-profile studies, highlighting that it is often the failure of

clinical judgment, teamwork, leadership, communication and

professional skills that leads to adverse events (Calland et al.

2002/2006; Vincent et al. 2001, 2004; Undre et al. 2009).

An unhelpful preoccupation with simulator technology can

cloud the picture. Elsewhere we have argued for a con-

textualised approach emphasising simulations (whole clinical

encounters) rather than simulators (specific items of equip-

ment) (Kneebone et al. 2006a, 2007). Such simulations can

‘activate’ a wide range of responses in clinicians, developing a

holistic approach and discouraging a task-focused emphasis

(Kneebone et al. 2006b). Work by our group has used real

people (actors) to play the part of patients within procedural

simulations (patient focused simulation) and thereby ensuring

that human interaction underpins any clinical procedure

(Kneebone et al. 2002a). In our experience, much is gained

by positioning simulation-based training of invasive proce-

dures within an authentic clinical setting (Kneebone et al.

2002b; Donaldson 2009).

So how can such contextualisation be achieved? One

possibility is the provision of ‘in-situ’ simulations within a true

clinical context, placing a mannikin, simulated patient or

procedural simulation in an actual ward or operating theatre

(Kneebone et al. 2005; LeBlanc 2008; Miller et al. 2008; Rall

et al. 2008; Nunnink et al. 2009). This concept is attractive,

especially as it allows individuals and professional teams to

train in their own environment (Kneebone et al. 2002c).

However, such simulations rely on unused capacity and ‘down

time’ within clinical areas. Within current health systems,

certainly in the UK’s National Health Service (NHS), pressures

on bed occupancy are so high that such simulations would be

impossible to schedule reliably.

If high-fidelity simulation could be of widespread benefit

within contemporary surgical training, how might such simu-

lation be made available to all who need it? The idea of

‘portable’ or mobile simulations is gaining currency. Such

approaches usually provide mannikin-based training in mobile

facilities (Paige et al. 2009). Although such simulations may

provide some sense of context by taking place close to

participants’ clinical environment, they may not respond to

the educational needs of a given clinical team. And like

immersive simulations in static centres, penetration of the total

healthcare workforce by in situ and current portable simula-

tions remains low.

Another possibility is to develop self-contained simulated

environments which can be provided alongside clinical space

and where ‘just-in-time’ (Spencer 2003) or situation-related

training can take place. This would break down the conceptual

wall between simulation and real-world practice, replacing it

with a permeable membrane which allows learners to link

simulation-based training with actual clinical issues (Kneebone

et al. 2004). Such an environment would act as a ‘container’ for

contextualised simulation, locating each procedure within an

authentic setting of place and people.

What is distributed simulation?

This article presents distributed simulation (DS) as a potential

solution. We use the term to describe accessible, portable and

self-contained simulated environments, which can be used

for teaching and assessment. DS sets out to strike a balance

between the realism of the clinical setting and the functionality

of the simulation centre.

Our concept is that simulation should provide an approach

to learning which is generally accessible, which can become

part of the normal range of educational facilities and which can

be tailored to the needs of individual groups. The adjective

‘distributed’ resonates with the terminology of operational

research, where distributed systems technology (i.e. linking of

computer systems over networks) enables models to be

coupled and interoperate during a simulation run (Boer et al.

2009). The term also links to ‘distributed cognition’ and other

applications (Hutchins 1996).

R. Kneebone et al.

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In DS we identify key elements of real clinical settings and,

through a process of ‘selective abstraction’ based on observa-

tion within real settings, present these elements within a

lightweight, inexpensive and portable environment that can be

easily transported and set up at any hospital or learning

institution, providing a ‘container’ within which clinical

scenarios can be created and replayed (Figure 1). Again this

resonates with the literature on operational research, where

conceptual modelling underpins the selection of essential

elements of a real world system to be included in the

underlying for representation in simulation (Wang & Brooks

2007; Onggo 2009).

Active design

Central to DS is a process of ‘active design’. Key elements of

the clinical environment are first identified through close

observation of clinical practice by a team of design engineers.

This is followed by ‘selective abstraction’ of essential

components, using design principles to capture and recreate

the essence of each. This process ensures that conditions for

perceived realism are aligned with practical constraints and

educational requirements.

The intention is not to reproduce every aspect of a clinical

setting, but only those components which are necessary to

achieve a sense of realism. In providing such a ‘minimalist’

approach, some compromise is clearly necessary. An accept-

able balance must provide key cues, but without the full

panoply of an operating theatre, ward or other complex

setting. The emphasis is placed on simulation function rather

than structure.

From this theoretical perspective, the specifications of

DS are:

. a self-contained immersive environment which can be

closed off from its surroundings, allowing any available

space to be converted into a convincing ‘clinical’ setting for

the duration of the simulation

. minimum necessary cues (visual, auditory and kinaesthetic)

to recreate a realistic ‘clinical’ environment (including

clinical equipment and sounds)

. key affordances of static simulation centres (for observing,

recording, playback and debriefing) in a simple, user-

friendly format

. practical, lightweight and easily transportable components

which can be erected quickly by a minimal team

. the flexibility to recreate a range of clinical settings

according to individual requirements, using appropriate

physical or hybrid simulations without the need for com-

plex and costly mannikins (Figure 2)

. minimal cost

Creating the DS environment

Using these principles of active design, we have explored the

DS concept in several domains including operating theatre,

clinic/trauma room and intensive care unit settings. Key

elements are as follows:

. A self-contained and enclosable space is provided by an

inflatable structure which can be easily erected. Inflation by

a muted electric pump takes 3 min, resulting in a structure

with a footprint of 5 m� 4 m and a height of 2 m. When

collapsed, the inflatable folds into a bag in the size of a

family tent.

. A tripod-mounted portable operating lamp, recreating

many of the features of inbuilt surgical illumination (circu-

lar, multiple bright lights, adjustable position) but made of

lightweight moulded plastic and using low-voltage LEDs.

A video camera and microphone are built into the central

handle.

Figure 1. The DS operating room.

Distributed simulation

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. Pull-up banners with high-resolution photographs of clin-

ical equipment (anaesthetic machine, equipment trolley)

provide representations of key components of a clinical

space.

. Lightweight speakers hidden within the inflatable structure

allow clinical sounds (heart monitor, ventilator, ambient

clinical noise) to be played. The monitor beep frequency

can be controlled from the system computer.

Figure 3. A simulated operation demonstrated at a recent conference.

Figure 2. A Hybrid DS using advanced prosthetics.

R. Kneebone et al.

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. Lightweight cameras offer a flexible configuration for

recording details of procedures and an overall view of

team activity. Recording and playback are controlled via a

simple customised interface on a remotely controlled laptop

computer which is used for debriefing and feedback.

The environment can be set up by two people within an

hour, and the key components can be transported in the

boot of a small car. The total cost of providing a DS setting is a

small percentage of that of most fully equipped static

installations.

Preliminary work has demonstrated high-perceived value

of DS. We are currently exploring its potential and limitations

across a range of clinical applications and conducting formal

validation studies. The outcomes of this research lie beyond

the scope of this concept article.

The concept is already giving rise to considerable

professional and public interest, as evidenced by the

recent NHS Healthcare Innovation Expo (2009) and presenta-

tions at the UK and overseas conferences (Kneebone 2009)

(Figure 3).

Conclusions

DS offers a possible solution to some of the most pressing

limitations of immersive high-fidelity simulation, namely

access and expense. By making lightweight, portable yet

self-contained facilities, widely available at low cost, DS

addresses a constituency of healthcare professionals who

would otherwise not be using contextualised simulation at all.

Although DS cannot provide all the facilities of static centres

(e.g. a dedicated control room), our initial investigations

suggest that many of those elements can be created to an

acceptable level, providing ‘good enough’ simulation which

allows effective training for procedural skills in a team setting.

Crucially, the environment is physically self-contained, creat-

ing a customised clinical universe which meets the educational

needs of its users while remaining insulated from the

distractions of surrounding activity.

In addition, DS offers potential advantages over static

facilities, obviating the need for dedicated space and storage.

Furthermore, temporarily setting up simulation facilities along-

side existing clinical space allows professional teams to work

together without having to take time out to travel to distant

centres.

In Christensen’s terms, we are addressing the needs of

‘non-consumers’, developing a disruptive innovation which

achieves many (although not all) of the goals of traditional

simulation but at a far lower cost (Christensen et al. 2007,

2008). Like Christensen, we see great positive potential for

disruptive technology within education.

Our intention in this article is to promote debate on the

place of simulation in healthcare education. Restricted access

has been one of the key brakes on the widespread uptake of

immersive simulation. Innovative, low-cost solutions will be

essential if simulation is to realise its potential in supporting the

education of a multiprofessional workforce in a changing

healthcare landscape.

Acknowledgements

The authors wish to acknowledge the invaluable contribution

made by Cian Plumbe, Matt Harrison (both of Studiohead)

and Max Campbell in providing design expertise during

the development of DS. The authors thank the BUPA

Foundation and the London Deanery Simulation and

Technology-enhanced Learning Initiative (SteLI) for funding

this research.

Declaration of interest: Dr Kneebone reports owning

shares in Medical Skills Ltd, which provides training in

procedural skills using multimedia CD-ROMs and models for

simple clinical procedures. The other authors report no

conflicts of interest. The authors alone are responsible for

the content and writing of the article and all contributed to the

research and the work involved in the preparation of this

manuscript.

Notes on contributors

ROGER KNEEBONE trained first as a general surgeon and then as a general

practitioner. In 2003 he joined Imperial College London, where his research

focuses on simulation and the contextualisation of clinical learning, using

innovative hybrids of models and simulated patients. Roger directs

Imperial’s Masters in Education (MEd) in Surgical Education.

SONAL ARORA is a general surgery trainee and clinical research fellow,

currently completing a PhD in simulation-based training of non-technical

skills for surgeons. Sonal is interested in assessing and training

safety-related skills in operating theatre teams. She is currently exploring

simulation as a training tool, alongside other training modules.

DOMINIC KING is a specialty registrar in General Surgery in London and is

undertaking a PhD in Behavioural Economics and Health Policy at Imperial

College London. He has a Masters in Surgical Education from Imperial

College London and maintains a significant interest in undergraduate and

postgraduate teaching and education research

FERNANDO BELLO is a senior lecturer in Surgical Graphics and

Computing. His research interests include modelling and simulation,

medical virtual environments and haptic interaction. His work spans

across technology and education, including development of patient specific

simulation and exploring the integration of computer-based simulation and

context via patient-focused simulation.

NICK SEVDALIS is an experimental psychologist, currently a lecturer in

patient safety in Imperial College London. Nick leads a research team that is

carrying out research in real and simulated clinical settings, with a focus on

non-technical skills (communication, team working, leadership) in surgical

teams, and decision-making in physicians and patients.

EVA KASSAB holds an MSc in Cognitive and Decision Sciences and is

currently a research psychologist in Imperial College London. Eva is

interested in assessing non-technical skills in surgical teams in real and

simulated procedures. She is currently working on developing further the

DS environment and assessment tools.

RAJ AGGARWAL is a specialist registrar in General Surgery in London and

an academic clinical lecturer in Surgery at Imperial College London. His

research interests include the validation of simulation training and training

curriculum development for surgeons.

ARA DARZI holds the Chair of Surgery at Imperial College London and is an

honorary consultant surgeon at St Mary’s Hospital, London. His main

clinical and academic interests lie in minimally invasive therapy and

educational research. His teams were awarded the 2001 Queen’s

Anniversary Prize for Excellence in Higher and Further Education.

DEBRA NESTEL is a professor of Medical Education at Gippsland Medical

School, Monash University and consultant to Imperial College London. Her

research interests are in clinical communication, simulated based educa-

tion, especially simulated patient methodology and programme evaluation.

Distributed simulation

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