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Safety in Accident and Emergency Care

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Enhancing Safety in Accident and Emergency Care

Report of a series of studies funded by the National Patient Safety Research Programme

May 2006


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Copyright Notice © Queen’s Printer and Controller of HMSO 2005

This report may be freely reproduced for the purposes of private research and study and extracts may be

included in professional journals provided that suitable acknowledgement is made and the reproduction is

not associated with any form of advertising. Applications for commercial reproduction should be

addressed to the Patient Safety Research Programme, The Department of Health, Richmond House, 79

Whitehall, London SW1A 2NL.

Enhancing Safety in Accident and Emergency Care

Maria Woloshynowych

Rachel Davis

Ruth Brown†

Robert Wears*

Charles Vincent

Melinda Lyons**

Competing interests declared: ‘none’

The Clinical Safety Research Unit Imperial College, University of London Department of Bio-Surgery & Surgical Technology

10th Floor QEQM, St Mary’s Hospital

Praed Street

London W2 1NY

England

Phone: 020 7886 2124

www.csru.org.uk

* Dept. of Emergency Medicine, University of Florida, Jacksonville, Florida, USA

† Accident and Emergency Department, St Mary’s Hospital, Praed Street, London W2 1NY ** Engineering Design Centre, Department of Engineering, University of Cambridge, Cambridge, CB2 1PZ


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ACKNOWLEDGEMENTS

Patient Safety Research Programme

The Department of Health

Richmond House

79 Whitehall

London

SW1A 2NL

http://www.pcpoh.bham.ac.uk/publichealth/psrp/

The Nuffield Trust

59 New Cavendish Street

London

W1G 7LP

[email protected]

Smith and Nephew Foundation

15 Adam Street,

London

WC2N 6LA

http://www.snfoundation.org.uk/

We are grateful to Dr Sally Adams, who has advised on human factors aspects of the studies in this

report; to Catherine Tighe for data collection and analysis on the incident reporting and contribution to the

communication studies; and to Dr Melinda Lyons for her contribution to the design, data collection and

analysis of the triage and the barrier analysis studies. We thank our medical, nursing, managerial and

administration colleagues for their time, support and co-operation in this research. In particular, we thank

Jo Fisher, Julia Gamston, and Martin Frowd in the Accident and Emergency department for their

contribution. We also thank Professor Sir Ara Darzi FRCS for supporting this research.


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LIST OF ABBREVIATIONS A&E Accident and Emergency Department

AHRQ Agency for Health Care Research and Quality

ANOVA Analysis of Variance

CDU Clinical Decisions Unit

CE Communication Event

COM Communication Observation Method

CRM Crew Resource Management

CSRU Clinical Safety Research Unit

DoH Department of Health, UK

ED Emergency Department

ENP Emergency Nurse Practitioner

GP General Practitioner

HRA Human Reliability Analysis

HTA Hierarchical task-analysis

ITU Intensive Care Unit or Intensive Therapy Unit

NHS National Health Service, UK

NIC Nurse in Charge

NPSA National Patient Safety Agency

SD Standard Deviation

SHO Senior House Officer

SN Staff Nurse

Sr Sister

UK United Kingdom

US United States


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EXECUTIVE SUMMARY

The Clinical Safety Research Unit was funded by the Patient Safety Research Programme in autumn of

2003 to carry out a Programme of work on ‘Enhancing the safety of emergency medicine’. This funding

helped to establish a unique centre of research in the UK dedicated to enhancing safety in healthcare.

The work was performed within a single Emergency department in a London teaching hospital during

2003-5. The purpose was to explore certain issues and solutions in this department that might be

transferable to other departments, recognising the variation in processes and case mix in Emergency

departments in this country. The complexity of the emergency care pathway and the wide clinical case

mix meant that we concentrated on looking at safety aspects of processes that aid clinical decision

making rather than the care of clinical entities themselves. The work was undertaken while the four hour

target for time in the department was being introduced and the study department was therefore

undergoing a period of enormous change. This had impact on some of the studies and interpretation of

data. The work carried out on this grant was exploratory and a considerable number of studies were

carried out on a range of topics:

A retrospective study evaluating the incident reporting process, described in Chapter 3, showed that there

were more near misses and minor events reported in the dataset than those judged to be serious or

moderate. The largest group of reported incidents reflected problems of delay in the accident and

emergency department which may reflect the emphasis on time in department during that period.

Analysis of the system did demonstrate inaccuracies and allowed the department to raise awareness of

the reporting requirement.

A retrospective case analysis is illustrated in Chapter 4 which provides a graphical representation as well

as a narrative summary of a patient with chest pain who received delayed treatment. This method may be

a useful additional tool in the analysis of incidents. Chapter 5 shows how conducting a prospective

barrier/safeguard analysis can generate creative solutions to problems. We have shown that barrier

analysis, a method of error reduction used in other industries, can be successfully adapted for healthcare

and produced useful results. An additional potential benefit is that staff may start to naturally consider

barriers in their work – which could have a positive effect on practice as well as safety culture.

Two ethnographic studies are described in chapters 6 and 7. A communication study shows that the

nurses in charge of the accident and emergency department had to deal with high levels of

communication as part of their daily working activities and the potentially serious implications for patient

safety. In chapter 7 we describe a study to evaluate the efficiency of the triage process. The mean time

that patients waited to be seen for triage was 13 minutes 33 seconds and the triage process on average

took 4 minutes and 19 seconds. Efficiency was not enhanced by seniority of staff but was dependent on

external factors or the requirement to conduct non clinical tasks.


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There are various clinical implications regarding these findings. We have evidence of the high level of

communication for the nurse in charge in a busy London A&E department as well as support for previous

studies regarding waiting and triage process times. Evaluation of the reporting system together with local

initiatives have resulted in various changes including the piloting of an electronic reporting system. It is

anticipated that this will improve the reporting rate and that subsequently we will have a better impression

of the types of incidents that occur in A&E, thereby enabling more effective interventions to reduce such

incidents and so improve patient safety.

In summary, providing health care in emergency settings is complex, hazardous work that is vulnerable to

failure. Human Factors and ergonomics studies of hazardous work in other settings have produced

useful insights, innovations, and have contributed to improving safety in those fields, so there is great

interest in applying similar methods to the study of clinical work. However, the clinical environment

presents some unique challenges to researchers. We discuss some of those challenges and offer

suggestions for future work in this area including a review of the recently introduced electronic reporting

system, assessing the effect of analysis tools of staff’s understanding of safety, develop additional

systems to redirect unnecessary communications for the nurse in charge and monitor the effect of

electronic handover at triage, using non clinical staff in different ways. Other areas of interest include

attitudes to the incident reporting process, staff perception of board rounds and unscheduled returns to

the accident and emergency department.


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Contents

Page number

Acknowledgements

3

List of abbreviations

4

Executive Summary

5

Chapter

1. Introduction

8

2. Safety Research in A&E: the nature of the problem

13

3. Incident reporting in A&E 17

4. Case analysis: Graphical Representation of Incidents in A&E 23

5. Using Barrier/Safeguard Analysis to help improve patient safety within the medication process

28

6. Communication patterns in Accident and Emergency 34

7. Evaluation of the Triage Process 44

8. Conclusion 49

References

53

Appendices

60


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1 Introduction 1.1 Background Several important new initiatives in the last few years underline the increasing attention paid to medical

error and patient safety. Studies in the United States, Australia and Britain suggest that 4-16% of

patients admitted to acute hospitals are harmed in some way by medical interventions1,1-3. The report of

the Institute of Medicine on ‘Building a Safer Healthcare System' starkly set out the scale of harm of

patients and an ambitious and radical agenda for change, which attracted Presidential backing in the

United States4. In Britain, the Department of Health commissioned a major report ‘An Organisation with

Memory', a report covering similar ground to the Institute of Medicine report, but in a British context5. This

was followed by ‘Building a safer NHS for patients' which describes the new national incident reporting

system and establishes the ‘National Patient Safety Agency' 6.

Human error is routinely blamed for disasters in the air, on the railways, in complex surgery and in

healthcare generally. However, quick judgements and routine assignment of blame obscure a more

complex truth. While a particular action or omission may be the immediate cause of an incident, closer

analysis usually reveals a series of events and departures from safe practice, each influenced by the

working environment and the wider organisational context. True high reliability organisations are

cognisant of the need to examine and attend to the whole system of work and its design and

management. Understanding the characteristics of a safe and high performance unit or hospital therefore

requires research on a number of interrelated topics. Some of the most important of these, in the context

of Accident and Emergency (A&E), are the development and maintenance of individual skills, the crucial

role of both formal and informal communication, the impact of working conditions on team performance

and the need to understand the particular environment of A&E. In addition the culture of a unit or an

organisation is likely to be highly influential7.

1.2 The Accident and Emergency Environment The emergency department is a complex and difficult environment in which to provide medical care and

differs substantially from more traditional settings in the organizational and cognitive burdens placed on

caregivers. A&E typically consists of the following physical areas: reception where patients register for

treatment, triage room for their initial assessment by a trained nurse and, depending on the urgency or

their condition, their allocation to physically separate areas of the Department. These are called ‘minors’,

‘majors’ or resus (resuscitation) and “paeds” if there is a dedicated paediatric department. The Minors

area is for less serious injuries such as sprains, cuts and bruises, and these patients are referred to as

the "walking wounded". The Majors area is for seriously ill or injured patients who tend to arrive by

ambulance. Some departments also have a Clinical Decisions Unit (CDU) for patients who require a

longer period of observation before discharge or await a time critical diagnostic test before treatment can

be given. The recent introduction of the 4 hour targets are a considerable influence on the work in A&E8.


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These targets specify that A&E care should be completed within four hours from time of arrival at hospital

to the time that the patient is admitted, transferred or discharged. In addition, there are several aspects

of emergency care that make it qualitatively different from care rendered in more traditional settings, and

likely make it more vulnerable to error. Wears and Sutcliffe 9 have identified six factors that characterize

the emergency environment and which together make it unique in healthcare settings:

Unboundedness. Unlike other care areas the demand for emergency care has no upper limit. It has

been remarked that, “ A&E is the only infinitely expansible part of the hospital,” alluding to the common

practice of holding their patients in A&E to deal with blocked beds elsewhere.

Multiplicity. Emergency caregivers typically treat many patients simultaneously; while this occurs in other

settings, it occurs to a much greater extent in A&E. Multiplicity creates a potential for cognitive overload,

in that workers can only attend to a finite number of tasks simultaneously, and the tremendous variability

of clinical problems encountered. Emergency caregivers must simultaneously manage children and

adults, surgical and medical complaints, life-threatening and trivial conditions

Uncertainty. A&E clinicians operate with much greater levels of uncertainty than other clinicians. First,

there is in no limit to the range of problems that may be encountered. In contrast a cardiologist, for

instance, can in general count on his or her next patient to have a heart problem, however unspecified.

Second, information that is known and present somewhere in the system is frequently unknown or

unavailable to emergency caregivers at the time of the patient encounter. Current and past medications,

allergies, results of past diagnostic evaluations are frequently unobtainable.

Time constraints. While production pressures are certainly present in other care areas, the time

constraints of A&E care are severe (clinicians in some departments typically average between 4 to 6

patient dispositions per hour during peak times). This can cause a narrowing of focus and a rush to

judgment, creating both false positive and false negative errors in a form of speed - accuracy tradeoff. In

addition, in some true emergencies (e.g., upper airway obstruction) the window of opportunity for

successful action is brief and physicians must rapidly commit to a course of action without waiting for

greater certainty if they are to have any chance at success.

Lack of feedback. Emergency caregivers routinely receive little to no feedback on the results of their care.

Systems for returning outcome information to A&E practitioners are uncommon to nonexistent. It would

seem almost impossible for learning from experience to occur under such conditions.

Reduced opportunity to practise. In many other domains, expert practitioners routinely perform their most

dangerous tasks frequently. For example, pilots take off and land several times a day, anesthesiologists

induce, intubate, and recover frequently, and surgeons operate daily, but in A&E the riskiest procedures

(e.g., emergency intubation, cricothyrotomy, thrombolysis) are among the least commonly performed,

sometimes on the order of monthly, yearly, or even less often. This makes it easy for practitioners in

emergency settings to become mis-calibrated about their own capabilities. Such a wide variety of


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presenting complaints result in even the straightforward diagnoses being seen only rarely in one

individual’s term of employment, particularly if only employed for 4 months in a particular department.

These six factors are not the only ones that affect performance in A&E; for example, shift work, sleep

loss, and heavy dependence on services outside the A&E (laboratory, radiology, consulting services, etc.)

also play a role10. A crucial factor in the British context is the junior level of most staff and the lack of

suitable training and skills brought to major emergencies11. In addition, the use of other independent

practitioners in A&E is increasing. Emergency Nurse Practitioners are able to function autonomously

after a short training period (6 weeks); these and other physician extenders (e.g., paramedics) can

discharge “minor” cases without review by senior colleagues according to local protocols. This lack of

senior review exposes the department to risk on a daily basis. This is compounded by a rapid turnover

among nurses, particularly in some busy inner city hospitals. Furthermore, in the UK where emergency

medicine is a relatively new specialty, only about 30% of patients are reviewed by a physician with more

than 18-24 months experience, and that review is initiated by the junior physician, rather than being

performed systematically. The recent introduction of European directives on doctors’ working hours may

have reduced the effect of fatigue on performance but the effect of this on staffing levels along with recent

changes in medical school training in the UK and lack of supervision are likely to have other knock-on

effects on patient care.

1.3 Studies of Adverse Events and Care Processes in A&E

There have been few focused investigations of errors, incidents and adverse events in A&E, and even

fewer into their nature and contributory factors. What is available in the literature offers glimpses of the

problem but does not provide a great deal of understanding into the origin, nature, causes or prevention

of errors and incidents.

Major epidemiological investigations have consistently identified significant rates of preventable error

occurring in all stages during episodes of care within emergency departments1,2,12,13. These studies all

suggest that while emergency care accounts for only a few percent of the total adverse events in

hospitalized patients, roughly three quarters of them were judged highly preventable, a proportion much

higher than any other area of care. Because these studies were based on record reviews, and only

included review of the care of patients who were admitted (while roughly 80% of A&E patients are not

admitted to inpatient units), it is likely that the burden on preventable injury is even higher.

More direct studies of emergency care have borne out these results, both globally14,15 and in specific

problem areas such as chest pain and cardiac disease16 patient complaints and negligence cases17-20.

Studies of work processes in the A&E have shown that interruptions are frequent21,22, averaging roughly

once every 6 minutes, and that most interruptions led to a change in task. Similarly, observational

(ethnographic) studies have shown that direct communication among caregivers is particularly important,


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although almost a third of the communications were interruptions23-25, suggesting that the combination of

interruptions and multiple concurrent tasks may contribute to failures.

1.4 Human factors approaches in medicine Human factors is a discipline that spans engineering, cognitive psychology and ergonomics and emerged

specifically in response to the safety concerns of high risk industries. While theoretically based it has a

resolutely practical emphasis, always aiming to bridge the gap between theory and application26. The

human factors community outside healthcare has developed a variety of approaches and techniques to

assist in error identification, containment and prevention. Initially, the focus was retrospective in that past

incidents and accidents were investigated and analysed in order to develop error reduction strategies to

prevent future failure. However, the focus has only recently moved towards direct observation of work27

and anticipation of problems, using such techniques as probabilistic safety assessments, which assess all

types of human, hardware, environmental and software failures.

Within medicine Reason’s organisational accident model has been an influential general framework,

which integrated much of the available human error theory and human factors knowledge28,29. This

model illustrates how the conditions in which people work influence their performance. These working

conditions relate to a whole range of factors including management decisions and organisational

processes. Reason’s work has been a powerful influence in shifting the safety culture of healthcare from

one of blame and retribution to a learning organisation. The Reason Model has been adapted specifically

for use in healthcare and a protocol for the investigation and analysis of clinical incidents has been

developed and tested in a number of clinical settings30-32. This adapted model is described in chapter 4.

Vincent and Taylor-Adams have developed the protocol for investigating and analysing adverse incidents

in healthcare, to include other root cause analysis techniques33. They have also developed the theory of

human error by dissecting its essential ingredients to help understand the underlying cognitive failure

mechanisms, which will subsequently improve error reduction. Human factors is now being incorporated

into healthcare by other researchers. For instance, Joice et al. have utilised Human Reliability Analysis

(HRA) within endoscopic procedures34. Mistakes and their precursors have been investigated in high

hazard cardiac surgery35 and pharmacy36.

The work carried out on this grant was exploratory and a considerable number of studies were carried out

on a range of topics. The work was performed within a single Emergency department in a London

teaching hospital during 2003-5. The purpose was to explore certain issues and solutions in this

department that might be transferable to other departments, recognising the variation in processes and

case mix in Emergency departments in this country. The complexity of the emergency care pathway and

the wide clinical case mix meant that we concentrated on looking at safety aspects of processes that aid

clinical decision making rather than the care of clinical entities themselves. The work was undertaken

while the four hour target for time in the department was being introduced and the study department was


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therefore undergoing a period of enormous change. This had impact on some of the studies and

interpretation of data.

The full details of these studies are in the process of being published in a series of papers. In this report

we aim to provide a succinct overview of the whole programme of work. Therefore, this report includes

illustrative findings for each study to show the breadth of the work carried out. It is structured in the

following way: the next chapter explores the difficulties in conducting patient safety research in healthcare

with particular attention to the A&E setting, including ethical approval which was obtained from the

institutional ethics committee. This is followed by work which looked at the incident reporting process in

A&E. This process is described and evaluated in Chapter 3, with a illustrative case to show a detailed

analysis of an incident in Chapter 4. A prospective method of error reduction was applied to the

medication process in Chapter 5 and Chapter 6 describes a study on communication load for the nurse in

charge of A&E. Chapter 7 gives an account of time spent on the various tasks in triage. The final chapter

discusses the implications of these studies and suggestions for further work.


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2 Safety Research in A&E: the nature of the problem 2. 1 Introduction

Accident and Emergency is a field of practice where risk is high and failure a constant threat. Therefore it

would seem a natural laboratory for researchers interested in understanding and improving human

performance under demanding conditions. However, our experience in both the US and the UK has

demonstrated multiple barriers to effective research efforts.

The analysis reported here is based on the direct experience from various current and previous research

projects, involving teamwork among clinical professionals37, ethnographic analyses of emergency

care38,39, organisational factors in patient safety40, shift change reports and transitions in care in the

A&E41-44, reporting of incidents and adverse events45, use of artefacts to support shared cognition46, and

the effects of technology on clinical work safety47,48. In this chapter we use a fundamental ergonomic

question (“What makes this work hard?”) reflexively, to ask: “What makes studying this work hard?”

In these studies, we have encountered a number of expected and unexpected difficulties. Some of these

barriers are generic, applying to many areas of healthcare, while others seem specific to studies in A&E.

2.2 What Makes Studying Clinical Work Difficult?

Problems generic to all healthcare settings Many of the problems we have encountered in studying safety in A&E have also been encountered in

other areas of healthcare. We briefly review six of the more common ones here and suspect that, except

for the last category, they will all be somewhat familiar to field researchers.

First, developing the sustained and substantive collaboration needed for productive work can be difficult.

Clinicians are generally unfamiliar with the methods of the “safety sciences”, and by nature and training

tend to assume that they will take the lead in solving problems. They need the insights, tools, theories

and particularly, the knowledge of the “blind alleys” that human factors professionals bring, but are often

unaware of their need. Human factors researchers, in turn, need help in acquiring access to clinical

areas and healthcare professionals, and in understanding and clarifying the semantics of the domain49,50

and the particular norms and culture of each clinical area in each institution.

Second, the complexity of healthcare is daunting. The scale of healthcare activity is immense, the

number of different activities is enormous, and the number of potential interactions between actors and

processes seems nearly unimaginable. The truth is “in the details”, but knowing (in advance) which

details are important and worthy of attention is difficult. Researchers have tended to react to this

complexity by “bounding it out”, doing small focused studies on parts of processes, but Nemeth and Cook


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have argued that such a strategy is not appropriate for a problem space about which little is

understood49,50.

Third, developing the requisite trust of the subjects to be studied can be difficult. Health care

professionals are extremely busy, and so have little time to get to know researchers, especially if the

interactions only occur on a sporadic or occasional basis. Most will begin with an underlying suspicion

that the researchers will either not understand the issues they face, or will sensationalize their problems,

or both. They are also likely to interpret safety research as being a search for errors and culprits, due to

the pervasive culture of personal responsibility and blame that health professionals share8. Because of

this, they will wear a variety of masks when dealing with outsiders that may be difficult to penetrate50.

Fourth, healthcare organizations are organizations only in a very loose sense of the word. Clinical

workers belong to multiple overlapping and intersecting groups which live together in tense social webs49.

Researchers who fail to recognize this larger context may find themselves unwittingly co-opted into intra-

organizational struggles that can impede their effectiveness.

Fifth, is the problem of facility, an issue that human factors professionals are familiar with. The great

expertise that clinicians have in their field of work ensures that the difficulties they face and the

adaptations they make to overcome them disappear, to both observer and observed49.

Finally, studies in health care bring pragmatic and regulatory issues that are uncommon in other areas

ergonomists have studied. In contrast to human factors studies in industry or the military, virtually all

human research conducted in health care is subject to regulatory and ethical review before beginning the

research project, and to continued oversight during its execution. These problems are further

compounded by the fact that the local ethics boards are generally only familiar with biomedical research,

and thus have a great deal of difficulty in assessing ethnographic, observational or qualitative research

designs, and can be expected to struggle with issues of scientific validity, identifying who the subjects

are, and whether consent is needed, and from whom.

Problems Specific to A&E In addition to the generic difficulties common to safety research in all areas of health care, we have seen

a number of problems that, if not unique to the A&E setting, seem more commonly encountered there. At

least 5 major issues are prominent in this area.

The first issue is one of multiplicity. Most safety research in health care to date has concentrated on

single tasks, such as the course of an operation or an anaesthetic. We realize there are in fact many

complex tasks in these, but they are for the most part subsumed into the larger task; thus the issue is one

of understanding many logically unrelated but interacting tasks. Clinical work in emergency care is

characterized most strongly by the management of multiple different tasks in parallel – “managing the

stack”. This raises several problems for researchers. With many tasks and activities underway, it is

difficult to know which ones to attend to or even how to make such a decision. In addition, there do not

seem to be good tools for representing this dimension of the complexity of emergency work. The


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narratives about failures or near misses, although rich and complex, inevitably seem to boil down to

single task stories, involving a small set of actors dealing only with a single problem: as it were, one

doctor, one nurse, and one patient. The reality of clinical work is far from this sense-making

simplification, but we have not yet developed tools that allow us to capture and express the multiplicity of

the work. This tends to make judgments retrospective and dependent on knowledge of the outcome, with

all the difficulties that entails51-53.

The second issue is the distributed nature of A&E clinical work. Work is distributed over patients, over

space, and over providers. The distribution over patients is expressed in the multiplicity issue discussed

previously, but the distribution over space and providers creates practical impediments to research that

uses observation methods. In sharp contrast to the cockpit, or the operating theatre, where the activity

that is the subject of the observations is physically restricted to a relatively small area, A&E work goes on

simultaneously in multiple, physically removed locations. This makes it hard to keep track of all that is

going on, and difficult to use recording devices as aids to observation except for limited purposes.

Furthermore, if observers choose to follow providers (or patients), then the observations will be as

fragmented as the work is. The distribution of the workload between workers is equally problematic, since

workers will be physically distributed and their tasks will be logically and temporally distributed.

The third issue relates to documentation. Since direct observation of A&E care presents difficulties, an

alternate strategy might be to examine the traces of work that are left in the artefacts clinical workers

use54. Unfortunately, there are still difficulties here in A&E care. Some of the important artefacts, such as

the status board, are evanescent, with information being added or removed as patients enter or leave the

A&E. Thus artefacts such as the status board are memory-less; they give snapshots of current work, but

no traces of previous work. Documentation or record keeping in emergency care is traditionally scanty,

for several reasons: time pressure limits the amount that providers are willing to record. A small study to

see if review of the A&E chart could successfully detect incidents that had been previously reported in an

anonymous reporting system showed that the majority of such incidents were undetectable55. Both the

UK and the US have problems in settings when some records are maintained on computer and others on

paper.

Other potential traces documenting A&E clinical work have been similarly problematic. Diagnostic coding

is often assigned at the end of a hospital admission, and so reflects many other processes than A&E

care, and there is no standardized coding for presenting complaints. Studies of clinicians dealing with

problematic cases (such as chest pain suggestive of cardiac ischemia, or headache suggestive of an

intracranial haemorrhage), have been hindered by the tendency of receptionists to use broad general

categories (such as “unwell adult”) when registering such patients.

The fourth major issue is the natural time scale on which events unfold. Things tend to happen rapidly in

A&E, so rapidly that it may be difficult for observers or practitioners to grasp them, and especially to grasp

the features of the context that are pertinent to understanding how things went wrong or how practitioners

were (un)able to recover.


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The fifth difficulty is in discovering outcomes. In inpatient settings, the patient’s course is generally

observable or retrievable, but this is not the case for outpatients, who may go elsewhere for their

subsequent care. Since approximately 80% A&E patients are discharged directly from A&E, the potential

loss to follow-up is great. And, although those discharged are, on average, less ill (or injured) than those

admitted to hospital, some of the most consequential failures in A&E care stem from discharging a patient

who should have been admitted (for example, with unrecognized myocardial ischemia). These are often

the cases safety researchers are most interested in, but are difficult to identify, and even more difficult to

retrieve and analyze if the patient’s pathway crosses institutional boundaries.

2.3 Implications for the research programme The characteristics of emergency work highlighted in this chapter make both the study and practice of

safety particularly challenging. There were numerous occasions where observations or data collection

had to be abandoned or postponed due to the high work load, or unpredictable and urgent nature of the

A&E environment. Initially we had difficulties being accepted by the A&E staff, making it difficult for

research staff to familiarise themselves in this busy and unpredictable environment. Part of the difficulty

was that some staff misunderstood our purpose, thinking that we were there to observe any mistakes

they might make. Furthermore, changes to systems used by staff (such as the introduction of a new

patient information computing system) and national changes (i.e. the introduction of four hour targets)

have a knock on effect on our research aims, objectives and subsequent achievements. Clinical staff

have had to adapt to these changes which has been and we’ve had to postpone data collection or even

change the focus of the research.

Our work in A&E was necessarily exploratory and a prelude to more focused studies on the key issues of

decision making and communication in the future. Our aim was to explore different areas to identify

possible lines of enquiry. A preliminary safety culture survey was conducted to demonstrate the research

process to staff in particular timely feedback to reassure staff that we were not there to observe for errors.

This proved very valuable and enabled us to build a good working relationship with the A&E staff. We

have explored the range of areas in the proposal but have focussed on the projects that make up the next

five chapters. These projects were chosen as they give an insight into the different aspects of the unique

A&E environment and provide a broad basis on which to conduct future research. We have used a range

of different methods of research. In addition, these studies reflect the interests and areas of concern of

our clinical colleagues.


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3 Incident reporting in A&E 3.1 Introduction

The development of clinical risk management in the United Kingdom and elsewhere led to the

establishment of local incident reporting systems in hospitals. There may be a designated list of incidents

that might prompt a report, a “trigger list”, although staff are free to report other issues that do not fall into

these categories. Generally the incident is classified as to the type of incident i.e. drug error, lack of

records, missed diagnosis, as well as allocating contributory factors.

When an error or clinical incident occurs it needs to be reported so that lessons can be learnt from the

incident. In addition, reporting reduces the possibility of reoccurrence and enables monitoring of patient

safety issues particular to the department involved and the trust as a whole. The incident reporting and

reviewing process within the study A&E department is reported elsewhere45. Despite efforts to

encourage reporting and the establishment of a national reporting system at the National Patient Safety

Agency (NPSA), there are still a number of barriers to reporting such as fear of reprisals, loss of

reputation, extra work or poor understanding of the process of investigation of an incident56. Furthermore,

there are mixed responses to the investigations of errors, some of which have the potential for learning

and improving care57.

The overall aim of the study was to evaluate the use and effectiveness of the reporting system as used in

the A&E department. The objective of the study was to assess the process of reporting and reviewing

incidents within the department, using historical data to explore the usefulness of the data recorded. We

also wished to make recommendations to the department for revision of internal processes so that the

department maximises the accuracy of data reported centrally and can learn from it.

The reporting process The staff member who becomes aware of the incident, fills in the incident report form and discusses the

reported incident with the nurse in charge of the shift or most senior doctor present. The person reporting

the incident at the time classifies the incident according to the categories supplied with the incident report

book. They provide the information on those involved and a factual description of what happened,

including any injury and treatment given.

The form is then reviewed by one of the members of the A&E clinical risk management committee (senior

clinicians), who makes an initial assessment of the potential impact of the incident including the

consequence of the incident in terms of severity and the likelihood of recurrence (ranging from ‘rare’ to

‘almost certain’). These two judgements combine to give a risk evaluation score. Comments on

preventive measures taken or planned (such as an investigation) are also included. They also note any

obvious contributory factors at that time.


18

At this stage a copy of the form is sent to the Trust clinical risk management office. This naturally occurs

before the full investigation is completed, and the department aims to get the forms to the central risk

management team for recording on the electronic system within 1 working day of the incident. The

evaluation of the severity, contributory factors and action points is therefore an estimate at this time

pending the result of the investigation. Serious untoward clinical incidents (unexpected death or serious

outcome) are escalated within 24 hours to the trust Executive director for Clinical Governance and

investigated via a different mechanism.

Once a month a short report listing all recent incidents, including serious untoward incidents, is sent to

the A&E clinical risk management committee. This summary report is then discussed at the next A&E risk

management meeting (usually at least a month after the incidents occurred). Each incident is discussed

and the relevant senior member of the committee gives an update on results of their investigation and

further action points. Information is not routinely updated onto the system from these minutes as there is

no clear line of responsibility for this action.

3.2 A review of the incident reporting system

Method We reviewed 13 consecutive months of data from the A&E section of the Trust electronic database of

clinical incidents. The data reviewed included the 174 incidents reported during the period from March

2003 to March 2004. The researchers used the free text information stored as the incident description on

the database, and compared this with the category and the severity score recorded on the database. The

contributory factors recorded and relevance to the clinical incident described were also noted. The

descriptions of incidents are short, and so this required some interpretation. Therefore only major

discrepancies between the event that was described in the incident notes and the category type allocated

were noted.

Results 1. Description of the incidents reported.

a) Types of incidents – completed by staff reporting incident

Figure 3.1 shows the types of incidents reported using the trust categories and an additional one for delay

to patient care as this type of incident is featured in more than one grouping. The largest category,

delays, were due to various causes; lack of porters or difficulty in arranging for patients to be seen

promptly by specialty doctors were the main features. Staff also reported instances when patients were

not discharged from A&E within the national 4 hour targets. 38 incidents in the ‘General’ grouping

included 5 cases of ‘sub-optimal care’ (where staff reporting the incident judged that the patient did not

receive adequate or appropriate care in the department) and 15 ‘drug’-related incidents. Of the 34

‘Patient Care’ grouping, 8 cases related to ‘lack of facilities or equipment’ and there were 5 incidents

where patients ‘did not wait’. The ‘other’ category includes a variety of incidents that were judged by the

staff not to fit the themes already mentioned.


19

b) Severity of incidents – reported by staff reviewing and investigating incident

The incidents ranged in severity: 95 Near Misses, 37 Minor, 16 Moderate and 20 Serious incidents. Six

incidents were not categorised in terms of severity. Incidents classed as ‘Near Misses’ had the potential

to cause harm to the patient but did not actually result in any harm. It is encouraging that staff regularly

reported Near Miss incidents as safety can be improved from learning from these incidents as well as

incidents which result in actual harm. The number of ‘Serious’ incidents reported was considerably lower

than incidents classified as minor or near misses. Examples of serious, moderate and minor incidents are

shown in Box 3.1.

Figure 3.1: Types of incidents

* delay is featured in more than one grouping and has been given a separate category in this report.

BOX 3.1: Examples of Severity ratings for incidents Near Miss

Very unwell patient was transferred by ambulance with no handover from a different hospital except

'deterioration'. There was no prior warning to A&E department.

Minor

SHO asked for bloods to be collected from majors. The porter was bleeped, there was no reply and the

doctor was informed that there were only two porters in hospital, and no A&E porter.

Moderate

A clinically unstable patient was transferred to a ward.

Serious

A patient with acute chest pain was triaged as category 3. There was a delay of 14 minutes for ECG. ECG

showed that the patient had suffered an acute MI.

010203040506070

delay*

Genera

lDiag

nostics

Patien

t car

eStaf

fing

Proced

ural

Non cl

inical

Other


20

c) Contributory factors completed by staff investigating

Contributory factors were mentioned in 22 of the 174 reported incidents (see Table 3.1). The most

common factors identified were ‘Communication problem’ and ‘staff shortages/skill mix’. 152 incidents

had no contributory factor identified on the database.

Table 3.1: Identification of contributory factors

Contributory factor Frequency

Communication problem 6

Staff shortages /skill mix 6

Failure of checking procedure 3

Missing or delayed: Results/ X-rays / Patient 2

Delay /difficulty in obtaining assistance 1

High work load 1

Deviation from policy/ guideline/ ICP 1

Lack of equipment 1

Failure of cover/ Handover/ Bleep system 1

d) Positive action from incident reporting

The Risk Management team in the department routinely identified positive action to be taken from the

incident reports. For example, there was a long delay in getting the blood products and appropriate

reversal for a warfarinised patient with haematemesis. This prompted a trust wide protocol for dealing

with warfarinised patients with Gastrointestinal bleeding with recommendations for reversal of

warfarinisation as well as re-education on the massive blood transfusion protocol for staff. In addition,

new guidance for calling a consultant in from home was agreed between consultants and this was

circulated to staff.

Other new positive aspects introduced since the study of the incident reporting and review system in the

A&E department is the quarterly newsletters which highlighted learning points from incidents. These

newsletters acted as reminders to all staff of good practice for aspects of their work which was related to

the incidents reported as well as reminders of new policies that have developed out of the clinical incident

reporting.

2. Evaluation of Information on the database.

In examining the incidents in the database the researchers identified apparent weaknesses with the local

internal processes in reporting incidents and limitations with the information recorded on the database.


21

Examples of issues identified include: Inconsistent use of categories. Some incidents were classified

under different names from the trust classification list on different occasions, e.g. missing patient (left with

venflon in situ) / sub-optimal care (left with venflon in situ); and Incomplete reports, missing information,

e.g. missing information on incident/ classification/ contributory factors, etc.

The lack of detailed information on the type of incident or contributory factors means that important

information which could lead to patient safety improvements was sometimes missing, thus not giving

enough detail to be able to monitor trends and issues. If clinical incident reporting is to be an alarm

system to prevent serious incidents or adverse events from re-occurring5 it is very important that we are

able to recognise real patient safety issues. For example, if we are unaware of the frequency with which

we are unable to find an ITU bed for a patient in a particular district or area, we will not recognise when

such an issue needs to be brought to the attention of NHS managers.

3.3 Discussion Incident information on the database was comprehensive enough to allow descriptions of the type and

severity of incidents to be summarised. We know that not all incidents which occur are reported58. There

are various reasons for this56 which might explain why there are more near misses and minor events in

this dataset than those judged to be serious or moderate.

Studies have also shown that even with explicit criteria and definitions, inter-rater reliability can still be

relatively low; for example, when judgements are made on the presence of an adverse event when

reviewing patients’ records59. Despite these limitations in human judgments and actions we have

suggested changes to the following aspects of the incident reporting system: Updating the database

The information on the database was not complete in that for some cases a full investigation had been

carried out but that this was not updated on the database, and so the loop was not closed. To remedy this

we recommend use of an electronic reporting system where staff investigating the incidents are also able

to include additional information as it becomes available and hold the information locally until we have

complete information before sending it on to the central trust database. This will ensure that the trust is

informed of the outcome of the case as well as the staff locally. Classification of incidents

Classification of incidents is carried out by junior staff who do not necessarily appreciate the process or

the definition of the categories. We recommend providing training for all staff so that they appreciate the

full incident reporting process and the importance of completing the forms as fully as possible; that only

senior staff fill in this section or at least confirm the classification at the monthly A&E risk management

committee meetings.


22

The effectiveness of the intra departmental reporting system is somewhat difficult to assess, particularly

as the system in the study department was undergoing development during the study period. For minor

incidents the outcome of the incident or process was not always fed back to the person(s) concerned.

Sometimes information was given to the wider clinical staff, such as reminders about changes in

protocols. The staff do not receive a structured summary of the nature of incidents reported on a regular

basis, although they receive a copy of the newsletter highlighting learning points and new policies

introduced, and a regular structured summary of incidents for staff is being planned. Recommendations

therefore include individual feedback to the staff reporting the incident in addition ot the planned regular

structure summaries as well as those mentioned above. This all contributes to the learning loop which

reflects the cyclical process of reporting or monitoring, investigation, analysis, feedback, implementation

of changes and back to monitoring and subsequently could be extended to the wider organisation5.


23

4 Case analysis: Graphical Representation of Incidents in A&E 4.1 Introduction

Investigation of accidents and incidents (near misses) in healthcare is now commonly required. However,

the methods and techniques to support such analyses for learning are in their infancy. In practice, their

use often suffers from hindsight bias and a narrow search for the “root cause”60,61. The term root cause

analysis is sometimes mistakenly thought of as having one root cause33. This has been referred to as

“first story” analysis. In contrast, “second story” analysis identifies deeper vulnerabilities; problems that

often remain in systems of care even after “fixes” have been implemented for problems identified by “first

story” analysis47. We have adapted an analytic model used in high hazard industries (and tested in

obstetrics) to the emergency setting and have modified engineering methods for graphically representing

an incident in an A&E setting. These methods appear to more clearly identify fundamental vulnerabilities

that are persistent in the particular organization, which need to be addressed for healthcare to make

fundamental advances in patient safety.

The aim of this study was to use a case analysis to illustrate how graphical representation, in addition to

enhanced systems analysis33, can show how “second story” analysis reveals the underlying

vulnerabilities.

4.2 Methods

We used Vincent et al.’s33,62, analytic framework to structure the results. These levels of contributing

factors are: patient, provider, task (and tools), team, work environment, organisation, and the societal-

legal-regulatory milieu. We used an investigative approach developed by Dekker61 to gather the data and

formulate a sophisticated understanding of the factors behind these incidents. Finally, we adapted 2

graphical methods of representing accident scenarios (Multi-Event Sequencing63 and Event & Causal

Factors notation64) to express our understanding of how these events came to pass in graphical form.

The Case A chest pain patient presented for treatment, but was inadvertently misclassified at registration and so not

identified in the triage nurses’ work queue. The usual receptionist (registration clerk) was out and a clerk

from another area had been substituted. Several triage nurses were working at the time, and several

handovers occurred among the triage nurses, but none identified the patient as awaiting triage. A family

member asked about the lack of progress after roughly 75 minutes of waiting. The patient was promptly

triaged to the acute area and was admitted to the hospital for cardiac ischemia.


24

4.3 Results

Table 4.1 shows the various aspects of Vincent et al.’s 33,62, analytic framework, including the care

delivery problems, contributory factors, positive aspects of the case and recommendations.

Table 4.1: Cases analysis using Vincent et al.’s framework

Care Delivery Problems

1. Incorrect coding for the location for the patient – i.e. should have been on the screen that the

patient was waiting for triage.

2. Nurse in triage was not informed of patient with chest pain by receptionist.

3. The ‘extra’ patient (or patient not accounted for) was not identified during handover.

Contributory Factors

Clinical Context and

Patient Factors

• no patient factors (but it was fortunate that daughter asked about him being

seen)

Individual Factors

• Receptionist’s training regarding codings earlier in the evening and assumption

that didn’t need to tell nurse in triage

Task Factors

• There was inadequate time for the receptionist to inform the triage nurse of this

patient

• Nature of the task is such that it is easy to enter the wrong code

• There is no systematic way of ensuring that all patients in the waiting room are

accounted for as there is no way of easily distinguishing between patients

and relatives

Team Factors

• Receptionist should have informed the nurse of patient

• Patient or relative should have been told that he (or his condition) is a priority

and that he would be called next

• The patient’s daughter waited 1¼ hours before asking about the patient.

• The computer failed to display that there is a patient with chest pain waiting to

be seen for triage (this is part of the program)

• Handover error – Sr H did not know about the patient

• SN R was not given a handover.

Work/Environmental

Factors

• There was a sudden increase in workload: 7 patients arrived at the same time.

• There is nothing to prevent the mistake of entering the wrong code nor is there

any way of checking for such a mistake


25

Table 4.1: Cases analysis using Vincent et al.’s framework

Organisational and

Management

Factors

• Choice of computer system for patient information

• Emphasis of handover for busy times

• Currently there is no system to pick up missed patients

• Selection of staff and training for receptionists.

Positive Points

• The receptionist realised she made a mistake as soon as it was pointed out to her

• Nurse acted quickly once she realised there was a problem.

• An additional nurse was allocated to triage to cope with the high workload

• There is already a system in place to recover from incorrect coding of patients’ main complaint – that of

informing the triage nurse of a patient with chest pain – as was demonstrated earlier that evening.

Recommendations

• Once we know the reason for the incorrect code for location – then we may be able to suggest possible

ways of preventing it. There is already a back up system for entering the wrong code – that of

informing the triage nurse of patients with chest pain.

• Introduce a system for checking code input, especially during busy periods – i.e. when for example

more than 5 patients arrive at the same time and when nurses have their handover.

• Need a process of accounting for all persons in the waiting area, particularly at times of shift change or

handover.

• Involve patients in this procedure, inform them and their relatives that they will be seen next for triage.

In Figures 4.1 and 4.2 time proceeds from left to right; events are shown as rectangles and contributory

factors as ovals. Events or contributory factors supported by evidence are shown in solid lines; those

supported only by presumptive evidence are shown in dashed lines. Arrows show dependency and

precedence, not necessarily causation.


26

Figure 4.1: Prelude to incident.

Chest pain pt presents to registration

Longstanding practice of registration before triage

Usual registration clerk out

Substituted by clerk inexperienced in emergency

procedures

Wrong code entered

Pt does not appear on triage nurse’s

screen

Clerk tells nurse about chest pain

patient

Nurse, clerk discuss

discrepancy

Clerk now believes unnecessary to tell

nurse if code is entered correctly

Figure 4.2: The incident

Another chest pain pt presents to registration

Wrong code entered

Pt does not appear on triage nurse’s

screen

Clerk does not tell nurse about chest

pain patient

?Pick-list problem

From Fig 4 - 1

Sudden influx of 7 patients

No method to determine if all pts

in waiting room have been triaged

Multiple handovers among

triage nurses

Pt not told he will be prioritized

Pt waits patiently for 75 minutes w/ continued chest

pain

Family member present, questions

long wait

Rapid assessment, admission to cardiology


27

4.4 Discussion

The “first story” of this incident is deceptively simple – the receptionist made a “mistake”. The “second

story” is richer and identifies more potentially correctable vulnerabilities. This incident occurred during a

busy time and at a time when staff were changing shifts. If there had been a system in place for patients

to be identified then this error might have been discovered earlier. Responding to the first story

(retraining the clerk using typical person approach to human error65) is unlikely to have as sustained an

effect as addressing the second story (or system) problems, such as having patients see a health

professional first, implementing mechanisms to assure all patients have been triaged, introduce a system

for checking code input, especially during busy periods – i.e. when for example more than 5 patients

arrive at the same time and when nurses have their handover, introduce a process of accounting for all

persons in the waiting area, particularly at times of shift change or handover, or involve patients in this

procedure, inform them and their relatives that they will be seen next for triage.

The use of narrative descriptions, tables or graphical representations of complex accident scenarios is a

communicative and analytic convenience, but has several drawbacks. It tends to make causal

connections seem clearer and the world more orderly than it is actually experienced by actors in a field of

practice; it also tends to make contributing conditions seem like discrete events, when they actually may

have developed insidiously66. An additional difficulty is that the two dimensional format forces some

factors to be in close physical proximity, which tends to suggest a close or important relationship that may

not exist, while others may have to be represented at some distance, which may erroneously suggest the

reverse.

A variety of methods for eliciting the deeper vulnerabilities that underlie the superficially apparent

“causes” of accidents and incidents are available. Textual, narrative descriptions are important in

creating understanding, but are sometimes difficult to follow, are not compact. This has led to a variety of

graphical methods of representation63,64,66,67. While these representations cannot stand alone, they seem

useful aids to narrative descriptions. In addition, they may prove particularly useful tools to accident

investigation teams, since they afford a method of recording events, vulnerabilities, violations and

influencing factors at the time they are suspected but before they have been fit into a coherent narrative

description. The ‘systems analysis’33 we have used here differs considerably from the standard root

cause analyses in the following ways: by showing complexity of the genesis of incidents; the use of

graphical representation; and providing a full exploration of contributory factors.


28

5 Using Barrier/Safeguard Analysis to help improve patient safety within the medication process

5.1 Introduction

Whilst techniques that assess human reliability or error analysis have been well-accepted and integrated

into the safety management process in other industries, the application of such techniques to the problem

of risks in healthcare is rare. These techniques (collectively known as Human Reliability Analysis - HRA)

identify the errors and weaknesses in the system by examining the systems of work including those who

work in the system. The ultimate goal of HRA is to improve reliability and safety. The main influence of

human reliability approaches has been on the analysis of serious clinical incidents in healthcare, using

the critical incident technique68, root cause analysis69 and other methods70. In the last few years there

has been growing interest in a wider range of safety and reliability techniques used in other industries.

One technique that has potential in healthcare is Barrier Analysis.

Barrier Analysis has been used primarily by the nuclear and chemical process industries to reduce error

by looking at the barriers put in place to protect vulnerable objects from the hazard caused by the transfer

of harmful energy71. The term barrier can be inter-changed with the words control, defence or safeguard.

Barrier analysis considers what safeguards are present in a process to protect vulnerable objects or

individuals such as patients from harmful objects or actions, including healthcare treatment. There are

four main types of barriers: physical, natural, human action and administrative. Physical barriers block the

route of harmful energy to the vulnerable object, such as walls or a radiographer’s lead apron. Natural

barriers of distance or time are used to protect the patients or staff from harm, such as isolating an

infected patient or staff distancing themselves from an X-ray machine when in use. Human Action

barriers are procedures that remove the vulnerable object from risk of harm or reinforce other types of

barriers, such as checking the dose of a drug before administering it. Administrative barriers refer to

rules, protocols and training, such as the controlled drugs policy. Barrier analysis also considers the

respective strength of each barrier – that is, the degree to which they provide effective and reliable

protection from harm. In other words: Can these barriers be easily broken? And do they always work?

Once barriers and their strengths have been assessed, it is then possible to see what improvements are

required, whether to reinforce current barriers or to introduce new barriers. Cost and feasibility of any

improvements can then be considered and implemented.

Barrier Analysis can be used both retrospectively, to examine a particular incident, or prospectively, to

examine a specific process by looking at the possible risks associated with it and what barriers are

currently in place to protect the patient, staff or equipment in question.


29

The aim of this study was to show that prospective Barrier Analysis can be applied to healthcare using an

example from A&E.

5.2 An example of Prospective Barrier /Safeguard Analysis

Medication error is one of the most prevalent types of medical error. In hospitals, errors occur in 1.5% of

prescriptions72, and 4-8% of medication administrations73. Interventions such as computer order entry

have been shown to substantially reduce the rate of medication error74, but most interventions have been

directed at ward care. Here we consider the much more fluid and unpredictable environment of the

emergency department. The risk of “a medication prescription not checked by a nurse before being administered by a nurse” was

identified as a concern for the Accident and Emergency (A&E) department. To narrow the scope of the

process, all participants were asked to consider this event as occurring in the prescription and

administration of oral drugs in ‘majors’.

Method Team members consisted of 2 A&E Consultants, 1 Registrar, 1 Matron, 3 Emergency Nurse Practitioners

and a Senior Staff Nurse. They took part in this individually or in small groups depending on availability.

First they were introduced to the concept and process of Barrier analysis. Second they were then

presented with the medication administration problem and were asked to identify the barriers already in

place to prevent the above risk, the associated strengths and overall suggestions for improvements.

Once all of these had been collected from every member of the group, they were then asked to judge the

cost implications and identify the system or individual who would be responsible for implementing the

suggested changes.

Findings from the Barrier/safeguard analysis

Table 5.1 shows 13 barriers or safeguards identified by the A&E staff regarding the problem of “a

medication prescription not checked by a nurse before being administered by a nurse”. These are

grouped into the main types of barriers. No natural barriers were identified. Some barriers identified were

general such as ‘policies’ or ‘culture’, whereas others were specific, e.g. an ‘electronic pop-up warning on

a computer system’.


30

Table 5.1: Barriers or safeguards to prevent a dangerous occurrence: Prescription not checked by nurse before being administered

BARRIERS / SAFEGUARDS IDENTIFIED BY STAFF STRENGTH

Administrative Barriers

Electronic pop-up warning on a computer system Strong

Policies Strong /Medium/ Weak

Nurse’s code for administration – the 5 Rs * Strong/ Weak

Procedure of writing on prescription / signing off Medium

Procedures Weak

Requirement to look in policy booklet Weak

Culture Weak

Human Action Barriers

Doctor training – where nurses are responsible for teaching them and

therefore are more likely to check their own procedures

Strong

Any other colleague Medium

Supervision by Senior colleagues Weak

Patient questioning Weak

Training Weak

Physical Barriers

Drugs physically locked away where you can’t get them before you can

prove to another member of staff by showing the prescription

Strong

* the 5 Rs refers to: (1) the right medication (2) be given to the right patient (3) in the right dose

(4) by the right route (5) at the right time

Table 5.2 displays 16 improvements suggested by staff. These have been grouped into the following

categories: education and training; supervision and checking; feedback; resources; software design; and

cultural and organisational change. Each tick represents a judgement by each member of staff. There

was some disagreement regarding the costs for most, except for those relating to changing ‘undesirable

attitudes’, improving software systems or increasing staffing levels.


31

Table 5.2: Improvements suggested to prevent the dangerous occurrence:

Prescription not checked by nurse before administration

Costs Responsibility Improvements Identified By Staff

High Med Low NHS Trust Medical &

nurse

education

Prof.

body

Local

staff

Education and training

Further training for doctors in

administration practice

Allow an experienced nurse to

prescribe drugs (and thus shoulder the

responsibility themselves!)

Reinforce training

Supervision and checking

Supervised practise for junior staff

Double-checking by senior colleagues

Double-checking of charts by other

members of staff

Feedback

Feedback on practice and near misses

Rewarding good practice

Appraisals to address “undesirable”

attitude – e.g. Over-confidence

Resources

More written resources – on frequently

used drugs and doses / infrequently

used drugs and doses

Up to date written resources

Greater availability of written resources

Software design

Improved design of software systems

Cultural and organisational change

Change culture & behaviour

Question everything

Increase staffing levels


32

When asked about responsibility of implementing the list of improvements, most staff considered these

improvements should be addressed at local level, though sometimes more than one section of the

organisation might be involved, particularly those related to education and training, or to cultural or

organisational change. Only one improvement, staffing levels, were identified by all staff as the sole

responsibility of the Trust. The Trust was also identified by at least one respondent as being partly

responsible for implementing nearly all suggestions for improvements.

5.3 Discussion

The results of this study show that the barrier analysis technique is feasible for application in a healthcare

setting. With a relatively small number of participants, a reasonable number of barriers and improvements

have been identified. Staff identified 13 barriers related to a prescription for oral medication not checked

by a nurse before being administered by a nurse in majors. The barriers elicited were mostly

administrative or related to human actions. There was discrepancy in the judgements of barrier

strengths, for policies and for the 5 Rs Nurse’s code for administration. The strength of barriers can be

defined in terms of its type e.g. physical barriers are generally strong, whereas administrative barriers are

weak75,76. Such staff perceptions of “strength” has important implications for Trusts when considering

what sorts of safeguards to put into place - particularly when barriers which are expensive to implement

or maintain are mistakenly thought to be strong. One solution might be to include the advice of a human

factors expert or someone experienced in barrier analysis following the data collection stage.

While the physical changes relating to software and staffing levels were thought to be costly, changes

relating to individual action or behaviour were thought of as inexpensive. For the recommendations

relating to ‘double-checking’ the judged costs spanned the full range. Improvements relating to the

individual, such as ‘question everything’, appraisals for over-confident staff, feedback, a change in culture

and behaviour were judged to have low costs. No obvious physical barriers or safeguards were

generated. This is further evidence that healthcare relies heavily on policies and procedures to manage

safety issues and when the system is pushed to the limit, the effectiveness of such barriers is clearly

compromised.

The response from those in a position to implement and drive change was extremely positive. In some

cases, the improvements suggested were already in place and this highlighted a need to disseminate this

information more effectively. For example, the request for “greater availability of written resources” had

already been addressed by providing this information on the computer systems. A further response was

to consider the safe practice of the medication process specifically within the in-house training schedule.

Within the department, this will now be a set topic within the nurse teaching schedule. In addition, the

process of prescribing and checking drugs is something that will now be emphasised during the doctors’

departmental induction.


33

The fact that such improvements have been accepted so readily highlights another positive attribute of

the barrier analysis technique. Many of the improvements suggested were feasible within the practical

running of the department and were not idealistic requests for expensive or impractical solutions.

Furthermore, it was suggested that now the staff are familiar and comfortable with the no-blame

systematic concept of barrier analysis this could be followed with using retrospective barrier analysis to

look at which barriers failed (resulting in drug errors) and how they could be enforced or improved.


34

6 Communication patterns in Accident and Emergency

6. 1 Introduction Healthcare staff are accountable for between 60-90% of all information transactions in the healthcare

system77,78. Poor communication between healthcare staff can substantially contribute to medical

error2,12,13. In Australia, a retrospective review of 14,000 in-hospital deaths showed that communication

errors were the lead cause, and were held accountable for twice as many errors as inadequate clinical

skill2. Further, an incident monitoring study reported that communication problems were involved in 50%

of all adverse events79.

Interruptions in healthcare settings are ubiquitous. The ED in particular has been described as an

interrupt-driven healthcare environment. Findings from the United States and Australia have shown that

interruptions in work processes are frequent, occurring on average ten times per hour21-23. Furthermore,

healthcare staff often have to deal with two or more tasks concurrently22. These findings are of concern

for two reasons. Interruptions can disrupt memory and generate errors80; and multitasking may result in

memory overload, causing some of the information to be lost before processing is complete81.

In the study department, a senior nurse is allocated the “nurse in charge” role. This role encompasses

responsibility for the team of nurses and junior doctors for supervising, giving clinical advice, allocating

tasks and ensuring co-ordination of workload . In addition the NIC is expected to be aware of the clinical

condition of all patients in 5 areas of the department, to receive information from a number of sources

regarding clinical, operational and strategic events, process that information and relay it to other relevant

departments. He or she is also the receiver of non urgent information that might impact on future shifts, or

previous shifts which must be documented and acted upon. The nurse in charge works in the majors or

trolley cubicle area of the department where the coordination of patients is assisted by a white board list

of present case load. They also utilise paper records of other key information and carry a bleep. The

nurse in charge therefore has a pivotal role in ensuring the smooth functioning of this complex clinical

environment. Thus it is important to study levels and patterns of communication exchange in this

particular staff group.

In 2002 a method to measure communication patterns in the clinical environment was produced. The

method is based on previous research23,77,82 and is known as the Communication Observation Method

(COM). It provides a validated ethnographic (or structured observational) method in which to measure the

communication load of different healthcare staff83.

The primary aims of the present study were to use the COM to investigate the communication load of the

nurse in charge in an inner city London A&E department and to build on this method by collecting

additional information that would help us to interpret the data, such as patient throughput and staffing

levels. This supplemental material would be used to validate the communications, and to contextualise


35

the shift in terms of workload. A secondary aim was to modify the COM to make it more user friendly and

time efficient.

6.2 Method Initials stages of the study Before data collection commenced, a pilot study was conducted to test the feasibility of the study and to

identify any potential methodological difficulties. We identified the following technical problems relating to

the recording equipment: tape recorder would get switched off accidentally whilst in the nurse’s pocket;

and the speech recognition function would get adjusted resulting in unintelligible recordings. These were

resolved by protecting these sensitive parts of the equipment with tape.

Participants Eleven nurses in charge of an inner city hospital A&E department were observed while they conducted

their daily nursing activities. The sample comprised two males and nine females of varying ages ranging

from 27-46 years old (mean 33.78, SD 5.65). Six nurses were G grade and the remaining were F grades.

Four nursing staff were observed more than once.

Data collection Prior to data collection a description of the study method was circulated to the nursing staff. This

information was also presented verbally by the researcher during the recruitment process. Data

collection took place over a 6 month period (January - June 2005) on a typical weekday between 9am-

6pm. A total of 20 hours of data were collected from 18 study periods of varying duration, ranging from

30-90 minutes.

Pre-observation data

After receiving informed consent, the researcher asked the NIC to ‘Describe briefly what your role will be

during the observation period?’. Demographic information was also collected.

Observation data

A lapel microphone was attached to the NIC, connected to a small tape recorder which was placed in

their pocket. The researcher shadowed the NIC for an agreed duration, taking field notes on the NIC’s

activities throughout the observation. The NIC was able to suspend the recording at any time or to

exclude information from the recordings retrospectively.

Modifications to the COM data collection process

A number of post-observation questions were asked: 1) ‘Were there any unnecessary communications?’;

2) ‘Were there any unresolved communications?’; 3) ‘What was the most annoying thing about this time

period with respect to communication?’. The NIC was also asked to indicate from a checklist any

potential problems (e.g., with equipment, mislabelled specimens) during the recording period; and to

clarify the nature of any observed CE’s which were not completely clear to the researcher at the time of


36

recording.

Data on medical and nursing staffing levels of different A&E staff on duty at the time of the recordings

were collected (i.e., consultants, senior house officers, registrars and nurses) and information on patient

levels were gathered.

Data analysis Data were collected in accordance with Coiera et al’s Communication Observation Method83. The

researcher’s field notes were transcribed and were used in conjunction with the tape recording to identify

individual communication events (CE’s). The purpose of communication, communication channel, and

interaction type were ascribed for each CE83 (see appendix A for further information).

Modifications to the COM data analysis process

For the purpose of the present study the following modifications were made to Coiera et al’s

methodology: 1) additional channels of communication were included (see table 6.1 for the full list); 2)

‘study’ and ‘equipment’ subcategories were added to the ‘purposes of communication’ list. The

subcategory of ‘patient management’ was adjusted to include all aspects related to patient care (e.g.,

administer medications, get test results, diagnosis and suggested treatment modality, attending to

patients pain); 3) the term ‘greeting’ under the ‘interaction’ category was renamed ‘general’ and

encompassed general conversational communication (e.g., greeting, thanking, apologising); 4) the term

‘3rd party interruption’ was used to explain a CE (face-to-face, telephone) that was initiated by a third

party, occurring whilst the NIC was already involved in a synchronous CE. We maintained Coiera et al’s

definition of an ‘interruption’: when communication was initiated by someone other than the NIC.

6.3 Results Pre observation information to elicit the NICs’ views on their workload before observation were collected

on 17 of the 18 recordings. On one occasion the NIC was too busy to answer the question.

To the pre-observation question ‘Describe briefly what your role will be during the observation period?’

the NIC provided general responses of their duties: 4 described their role in relation to management of

the department only; 5 as management of staff and department and 8 included three aspects of their role:

management of A&E, staff management and patient management. In addition, specific tasks the NIC

needed to carry out during the recording that would not usually form part of their everyday workload were

mentioned on 2 of the 17 observations. These consisted of: dealing with a patient that required a psych

liaison nurse; trying to sort out difficulties with the heating in Majors; and problems with the PODS (the

vessel in which haematology samples get placed to be sent through to the relevant department, e.g.,

haematology/microbiology).


37

Communication load We identified a total of 2019 distinct CE’s. 1183 (59%) were initiated by the NIC. Communication

multitasking (e.g., talking to someone and writing on the whiteboard) was evident on 286 (14%)

occasions. This was in addition to any other concurrently active tasks that did not involve communication

of any form (e.g., filing, handling equipment). The NIC was interrupted (i.e., other person initiated the

conversation) on 836 (41%) occasions. There were 47 (2%) third party interruptions, where a person

interrupted an on-going synchronistic communication event.

Recordings were suspended by the NIC 6 times on 5 separate observation periods. Reasons for

suspension were due to confidential discussions with members of staff or patients.

Type of CE’s A total of 19 different communication channels were identified (see table 6.1). Synchronous

communication (N = 1672), accounted for 83% of all CE’s, with face to face communication and

telephone conversation occurring on 1528 (76%), and 144 (7%), of occasions respectively.

Table 6.1: Type of Communication Event

Type of Communication Channel Number of CE

Face to face* 1528 (76%)

Telephone* 144 (7%)

Computer 107 (5%)

Whiteboard 104 (5%)

Pager 35 (2%)

Patient records 35 (2%)

4 Hour Target 19 (1%)

Paper source 14 (1%)

Tannoy 7 (<1%)

Staff Allocation Sheet 6 (<1%)

Off Duty 5 (<1%)

A&E activity Sheet 4 (<1%)

Patient Transport form 3 (<1%)

Agency Form 2 (<1%)

Message Book 2 (<1%)

Evacuation Form 1 (<1%)

Booking Request Form 1 (<1%)

Incident Reporting Form 1 (<1%)

Emergency Form 1 (<1%)

* Synchronous communication channels


38

Purpose of CE Eight distinct task communication purposes were identified (see table 6.2). 961 (48%) CE’s were

concerned with patient management.

Table 6.2: Purpose of CE

Purpose of CE Total

Management of the Department 961 (48%)

Staff Management 362 (18%)

Patient Management 327 (16%)

Administration 112 (5%)

Equipment 102 (5%)

Social 72 (4%)

Study 64 (3%)

Education 19 (1%)

Interaction type The majority of interactions involved the NIC giving information (e.g., to another person, writing on the

whiteboard, typing on the computer) or the NIC asking someone a question; accounting for 546 (27%)

and 465 (23%), respectively (see table 6.3). Of the remaining CE’s, 428 (21%) involved the NIC being

asked a question (e.g., ‘is the patient in cubicle D going home?’), 380 (19%) involved the NIC being given

information (e.g., ‘Patient in cubicle C is going to CDU’), 117 (6%), concerned the NIC instructing an

individual to perform a task (e.g., ‘ please can you keep an eye on the patient in cubicle E’s blood

pressure?’), 68 (3%) involved ‘general’ synchronous communication (e.g., ‘hello’) and, lastly, only 15 (1%)

involved the NIC being instructed to perform a specific duty by another person (e.g., ‘please can you give

these keys to the occupational therapists when you see them?’).

Table 6.3: Communication interaction type

Interaction Type Total

Giving information 546 (27 %)

Give request 465 (23 %)

Receive request 428 (21 %)

Receiving information 380 (19 %)

Instruct request 117 (6 %)

General 68 (3 %)

Instruct receive 15 (1 %)


39

Post observation data Eleven of the 17 nurses questioned stated there had been no unnecessary CE’s during the time of

recording. Four nurses said that there had been unnecessary CE’s though none of them elaborated on

this any further. Out of the remaining two nurses, one did not answer the question and another could not

answer the question as the A&E department became too busy and they were needed elsewhere.

In response to the question concerning unresolved CE’s, eleven nurses reported there had been no

unresolved CE’s (the remaining six nurses provided no response). However, from this sub-group the field

notes and recording providing evidence to show that where were in fact 3 unresolved CE’s out of the 11

recordings. Specifically, these concerned the incompletion of a CE due to the NIC being interrupted: 1) by

a sister whilst having a conversation with a junior sister; 2) by a SHO whilst having a conversation with a

nurse; 3) by a member of admin staff whilst in discussion with a sister. For example, the NIC is

explaining to the junior sister about what is happening with the patients that are in majors that are soon to

be breach (i.e., whether they will be discharged or admitted). The NIC tells the junior sister that there are

three beds on CDU. The NIC is then interrupted by a nurse who informs her that he has patient X’s notes.

The nurse asks the NIC whether she wants the patient’s notes. The NIC tells the nurse that patient X has

gone to CDU and asks whether he could take the patient notes over to CDU. The NIC does not go back

to the previous conversation with the junior sister (for the duration of the recording) about the patients that

are about to breach in Majors.

With regards to the question ‘What was the most annoying thing about this time period with respect to

communication?’ data were collected from 14 nurses (the remaining 4 nurses were too busy to answer

the question). From this sample a common recurring problem that they had too may things to deal with at

once (N=8; see table 6.4) grouped into general and specific responses.

Table 6.4: NICs’ (verbatim) self-report post responses on the most annoying thing (regarding communication) during the observation period

General responses Specific responses

Trying to deal with too many things at

once

Trying to do with a phone call to NHS

Professionals during which time many different

people spoke to me

Trying to do two things at once

Talking to a member of staff whilst on the phone

at the same time

There was a lot of things going on at

once

Trying to ensure the efficient running of all the

sub departments of A&E simultaneously

Having to deal with lots of different things

at once

Having to deal with two phone calls at once


40

In addition, in 4 of the 14 observations, the NIC reported a communication problem that specifically

related to the given observation period (i.e., a communication problem that would not be a typical

occurrence on a daily basis). Responses (verbatim) were; ‘problems with trying to sort out an account cab

to take a patient to another hospital’; ‘heating problems’; ‘having to wait for the porter to take a patient to

the ward (the patient was getting irate)’; ‘an ex-patient kept ringing up the A&E department and was being

very awkward’.

In addition to the above responses, on 2 out of the 14 observations the NIC stated that there was

‘nothing’ annoying (i.e., no more than usual) about the recording period with respect to communication.

Staff levels Data were collected for the number of nursing and medical staff on duty in the ED and was considered in

relation to the mean number of CE’s to ascertain whether staff levels had an effect on communication

levels. This was examined by using the range of the mean number of CE’s per minute for each

observation that had the same number of staff for each profession working (e.g., the CE range for all

observations that had, for example, 4 SHO’s on duty; see Table 6.5).

There were no relationship between the number of Consultants on duty and the mean number of CE’s

observed, r17 = 0.248, ns; and between the number of nurses on duty and the mean number of CE’s

observed, r17 = 0.423, ns. However, there was a moderate relationship between the rest of the medical

staff working during the observation period and the mean number of CE’s observed: r17 = 0.469, p ≤ 0.05

and r17 = 0.526, p < 0.05, for Registrars and Senior House Officers (SHO’s), respectively. This

relationship shows that the more junior medical staff on duty the greater the number of communication

events.

Patient levels Table 6.7 displays the total number of patients that were in the A&E department during the data collection

period. The number of patients who left the department during the observation period is also provided

including: those who arrived after the observation commenced and left before the observation finished;

and those who were already in the department and left during the observation period.

A Spearman’s correlation revealed a moderate relationship between the number of patients in the

department and communication load: the greater the total number of patients in the department, the

greater the number of CE (r17 = 0.628, p < 0.01).


41

Table 6.5 The range of Communication Events per minute for the different numbers of medical and nursing staff on Duty

Number of staff on duty Number of observations

Range of no. of CE per minute

Consultants

2 2 1.78-1.85

3 6 1.64-2.18

4 5 1.23-1.96

5 5 1.32-2.12

Registrars

2 10 1.23-1.96

3 1 1.6

4 7 1.51-2.18

SHOs

2 1 1.23

3 3 1.32-1.96

4 4 1.24-1.85

5 2 1.73-2.18

6 2 1.51-1.78

7 1 2.12

8 3 1.64-1.96

11 1 1.89

Nurses

17 2 1.56-1.85

15 1 1.24

14 1 1.32

13 7 1.51-1.96

12 5 1.23-2.18

11 1 1.96

10 1 2.12

Further correlations were then conducted to explore whether there was a relationship between the

number of patients that left the department during the observation period and the mean number of CE’s

observed. The results revealed no significant relationships r = 0.124, ns.


42

Table 6.7: Patient levels during the observation period

Date of

observation

1. Number of

patients who

arrived during

the

observation

period

2. Number of

patients already

in the

department

when the

observation

commenced

Total no.

of

patients

present

or arriving

3. Number

of patients

who left the

department

Total in A&E

at time of

observations

Mean

CE

duration

in

minutes

No. of CE's

per minute

(total CE's

observed ÷

duration of

observation)

25/02/2005 11 15 26 3 23 0.46 2.18

09/06/2005 20 25 45 18 27 0.47 2.12

20/06/2005 33 19 52 17 35 0.51 1.96

22/06/2005 13 44 57 17 30 0.51 1.96

22/03/2005 17 25 42 12 30 0.52 1.91

02/03/2005 11 31 42 13 29 0.53 1.89

21/06/2005 13 19 32 7 25 0.54 1.85

01/06/2005 28 11 39 19 20 0.56 1.78

02/06/2005 20 18 38 14 24 0.58 1.73

31/03/2005 19 10 29 8 21 0.58 1.73

18/02/2005 6 27 33 11 22 0.61 1.64

12/04/2005 14 6 20 3 17 0.62 1.63

03/03/2005 5 22 27 7 20 0.63 1.60

15/06/2005 28 11 39 14 25 0.64 1.56

24/01/2005 15 29 44 15 29 0.66 1.51

12/05/2005 13 10 23 12 11 0.76 1.32

23/06/2005 23 14 37 16 21 0.80 1.24

14/06/2005 17 8 25 12 13 0.81 1.23

6.4 Discussion

Our study showed that the senior nurses in charge of A&E had to deal with high levels of information

exchange as part of their daily working activities, with a new CE occurring on average every 0.59 minute

(36 seconds).

In accordance with previous research13 staff members in A&E seem to favour synchronous

communication channels (i.e., talking face-to-face or via the telephone) when talking to the NIC, as

opposed to asynchronous communication channels (e.g., whiteboard), which accounted for 83% (n =


43

1672) of all CE’s. On 836 (41%) occasions synchronous communication was initiated by someone other

than the NIC. This is similar to Coiera et al.’s findings, that interruptions in A&E healthcare staff

accounted for 30.6% (n = 393), of all observed CE’s13. In addition, third party interruptions accounted for

2% (n = 47) of all communication events.

Based on our results we feel that the number of times in which the NIC was ‘interrupted’ could pose

salient implications for the effective exchange of information. If the NIC is distracted from what they are

doing (e.g., writing on the whiteboard), this may disrupt their thought process, which in turn, could have

adverse effects on the quality and completeness of the previous intended message.

Communication multitasking (i.e., the NIC conducting two CE’s simultaneously) was observed on 286

(14%) occasions. This together with other concurrently active tasks that the NIC was involved in (i.e., that

did not involve communication of any form), could be a serious threat to the effective exchange of

communication between the NIC and healthcare staff. This view is based on research which suggests

that several concurrent tasks may disrupt memory because the number of items that can be held in

working memory is small81.

There is a significant need to reduce the sheer volume of communication load that the NIC has to deal

with on a daily basis. Future research could investigate the following: potential methods in which

communication, particularly synchronous communication, can be reduced for the NIC; and specific

strategies to lower the number of times that the NIC is ‘disturbed’ or ‘interrupted’ from what they are

doing. These could include better integrated IT systems to reproduce paper data collection and require

documentation only once, use of texts and emails rather than phone calls, and support for senior nurse

by task analysis and role redefinition. In addition training the senior nurses for communication capacity,

time management and delegation may reduce the number of interruptions.

We feel that the efforts and resources to undertake such work would be modest in comparison to the

benefits that the findings could have to patients, health professionals and the health system as a whole.

Improving communication between healthcare staff by reducing the levels of interruptions and minimising

the volume of irrelevant or unnecessary information exchange could therefore have important implications

for patient safety.


44

7 Evaluation of the Triage Process

7.1 Introduction

In A&E triage refers to a process of assessing incoming patients to the most appropriate care pathway

according to the urgency of their symptoms or preliminary diagnosis. In some cases, this may involve

treatment in the triage area and/or being sent to another healthcare provider outside of the emergency

department – a process known as “see and treat”. In many cases, the triage process not only evaluates

patients but also facilitates the efficiency of the care process within and beyond the emergency

department by foreseeing the need for tests or the care of particular specialties and initiating these from

triage.

There have been a number of attempts to impose time restrictions on A&E processes to ensure that

those needing urgent care receive timely intervention. In 2000 the DoH announced in The NHS plan that

“By 2004, no-one should be waiting more than four hours in accident and emergency from arrival to

admission, transfer or discharge”8. and the promise to patients laid out in “Your Guide to the NHS” 84 that

on arrival in A&E “you should be assessed by a nurse or doctor, depending on how urgent your case is,

within 15 minutes of your arrival…”. As well as these policies, the requirements of the triage task itself

impose a degree of time pressure on the triage staff. They must spend adequate time collecting

information from the current patient to make the best possible triage decision but also not delay those

waiting in reception who are, as yet, of unknown criticality.

A number of studies have examined the nature and effectiveness of the triage process. In the US,

Paulson85 carried out a retrospective review study of the impact of nurse qualification level on triage

waiting time. Within this, time to triage (defined as the time from sign-in to the start of triage) took an

average time of 17 minutes for a licensed nurse (data from 1998) or 15 minutes for unlicensed assistive

personnel. The time from triage to treatment was significantly reduced (from 127 to 54 minutes) when the

more qualified nurses were responsible for triage. Thus the minimal time saved in the wait for triage by

using less-skilled staff greatly reduces the efficiency of the overall care process. Lindley-Jones &

Finlayson demonstrated that when x-rays were ordered by triage staff, walking wounded patients were

treated quicker without compromising service quality86,87. The inclusion of extended skills in the triage

nurse from “test ordering” to full “See and Treat” offers further potential for greater efficiency, though

potentially at the cost of causing an influx of GP patients causing stress and overwork for the A&E staff88.

Issues of efficiency, quality (accuracy of judgement) and role definition in triage have not yet been fully

and objectively assessed or evaluated. Simmons89 suggested that to be able to implement any changes

in A&E, for them to have the desired effect on quality and efficiency, it would be necessary to support

these with changes throughout the healthcare system as triage is but a small part of total patient

pathway. A study by Locker and Mason90 looked at the total time in the department of a large cohort of

patients from all over the UK, and mapped the frequency distribution of total times. Whilst a


45

disproportionate number of patients appeared to leave the department immediately before the 4 hour

target time there were also many others with long times. However, from the data supplied, it cannot be

established the reasons behind some of the long attendances or any bottlenecks in the system. For this

reason, looking at the fine detail of triage using a systems approach provides an objective non-

judgemental evaluation of the efficiency and or effectiveness of a process to identify potential early time

saving process issues but at the same time, keeping the people who carry out the work involved in

defining the current tasks and work environment as well as identifying realistic solutions to the problems.

The aim of the study was to evaluate the efficiency of the triage process from a systems perspective

using tools from human factors. It is a two-phase study incorporating a task analysis and ethnographic

study. Verbal consent was obtained from both staff and patients for the study and patient confidentiality

was attained through independent coding of data.

7.2 Methods

97 patients were observed being triaged in the waiting room triage area over 11 days from August to

October 2004. They were seen by 12 different triage staff (five E grades, two F grades, two G grades, two

ENPs and one consultant physician) to develop the task analysis (see appendix B) and study protocol.

For the ethnographic study, 258 patients were observed for their attendance in the in the waiting room

triage area sampled during day-time triage sessions over a period of two months (Jan/Feb 2005).

Measures

For each patient, the following information was recorded:

• Time from registration to being called for triage

• Time for the duration of triage

• Time spent alone within triage

For each member of staff, the following information was taken:

• Length of triage session observed

• Number of patients triaged within observed period

• Time absent from the triage booth within observed period

• Grade of triage staff

Procedure

Sixteen hours of observations in triage and 12 interviews were carried out with 12 nurses, two ENPs and

an Emergency department consultant physician who were all experienced at triage. Using the task

analysis processes described in Kirwan & Ainsworth91, these data were used: to produce and agree a

generic representational flowchart for the triage process (see Appendix B), to prioritise the relevant issues


46

to triage efficiency and patient safety; and to develop a list of measures as a protocol for the ethnographic

study.

For the ethnographic study, data were recorded in the triage area for over 1882 minutes, on 16 different

members of staff carrying out the triage task on 258 patients

7.3 Results The mean time that patients waited from being registered on the computer in reception to entering the

triage booth was 13 minutes 33 seconds (n=246). This included six patients whose triage was delayed

because they were not in the waiting area when called into triage.

The mean time for all data to triage a patient – from entry to the triage booth to departure was 4 minutes

and 19 seconds (n=247).

Significant differences were found in the times taken to triage a patient between the areas to which a

patient was triaged, Kruskal-Wallis χ2 = 25.026, p ≤ 0.001, as well as the persons responsible for their

care, χ2 = 18.738, p ≤ 0.001. There was a significant difference between those triaged to A&E staff in

Majors and A&E staff in Minors, Mann-Whitney U = 2701.50, p ≤ 0.02.

There was no significant difference between those triaged to the A&E staff in Minors or the ENP, Mann-

Whitney U = 825.000, ns, the GP within Minors or the patient’s own GP, Mann-Whitney U = 7.5, ns.

Furthermore, there was no significant difference between those “seen and treated and sent home” and

those “advised to see alternative care providers”, Mann-Whitney U = 59.5, p ≤ 0.397.

There was a significant increase in the time it took to triage to a specialty working within the department

from that taken to triage a patient to majors, Mann-Whitney U = 289.5, p ≤ 0.01, but no significant

difference to triage a patient to an alternate care provider than to triage to an internal specialty, Mann-

Whitney U = 79.5, ns. There was a significant increase in triage time for those triaged to the responsibility

of specialty staff compared with those triaged to the responsibility of A&E staff, Mann-Whitney U =

1077.5, p ≤ 0.001. Together, these tests suggest that any contact with a speciality, regardless of where

the patient is to be seen, results an increase in triage time. There was no significant difference in triage

time between those patients who were triaged to different areas but whom were all to be seen by

specialty staff, Kruskal-Wallis χ2 = 2.555, ns.

Five (2%) of the 247 patients arrived in the triage area with all the paperwork consistent with a specialty

referral but the specialties did not accept responsibility of the patient. In this case, the triage requires all

the time involved in a specialty referral but the patient was triaged into the Emergency department. Within

this study, there was an overall increase in the time to triage patients that were deemed as requiring

specialty care, Mann-Whitney U = 1795, N=28, p ≤ 0.001, but no difference in triage time as to whether


47

the specialties accepted or refused, Mann-Whitney U = 47, ns. This confirms that it is the communication

required with specialties in the process that impacts on the triage time – irrespective of the outcome.

There were 34 patients who were “Seen and Treated” in triage, including those who were advised to see

their own GP. There was no significant difference in the time taken to “See and Treat” patients from

triaging into the department, Mann-Whitney U = 3022, ns. This seems unlikely to have an overall negative

effect on the running of the triage process. In many cases, the active “See and Treat” was carried out

when waiting times were low and the triage / reception area was clear.

The “rate” of triaging patients was on average 8.4 patients triaged per hour (one patient every 7 minutes

and 8 seconds including the necessary time of preparation between patients). There was no difference

between staff grades or individual staff member, χ2 = 3.187, df = 4, ns, χ2 = 18.318, df=15, ns,

respectively.

7.4 Discussion

This study has highlighted some important issues in the management and implementation of the triage

process.

The mean time that patients waited to be seen for triage was 13 minutes 33 seconds. This is close to the

15 minutes national target and is similar to Paulson’s85 research where the mean wait time for triage was

13.71 minutes. However, unlike Paulson’s study, the difference between grades was not reflected in our

study. On average staff took 4 minutes and 19 seconds to triage a patient. For patients who were

expected by specialties and/or triaged to specialties, the triage process appeared longer. This process

generally required supplementary phone communications. Furthermore, this did not seem to be

compensated by the fact that, if expected by the specialty, the tests and vital signs had already been

carried out by a GP and they were clinically easier to sort as their pathway had been pre-determined.

This study supported Lindley-Jones & Finlayson’s86,87 findings that ordering x-rays appears to be efficient

use of time and did not have any significant impact or detriment on the time to triage. Only a few patients

(n=6) were actively “seen and treated” in the triage area. This had a significant impact on the triage time.

While this was carried out when there were few patients waiting to be triaged, consideration might be

given to introducing guidelines when this could be optimally carried out for the benefit of more patients

without jeopardising the recommended 15 minute waiting target time for other patients.

Within this study, the time data relied on the output of the triage computer giving time data in ‘minutes’

rather than the more accurate ‘seconds’. This could also facilitate the examination of more detailed

features of the triage task by carrying out a time-line analysis, i.e. knowing how long individual tasks take

and whether they can be carried out in parallel would inform us whether certain tasks should be carried


48

out in triage or whether this is to the detriment of the current as well as subsequent patients. Similarly, a

broader sample including patients at night-time and weekends would be more representative.

In this study, it was apparent that staff overcame a whole range of problems, including language

difficulties, patients presenting with an inappropriate history or interruptions from other staff, visitors or

other patients that interfere with the efficiency of their tasks.


49

8 Conclusion

We have learned a great deal about the difficulties of studying emergency care and, we hope, made

progress towards improving our understanding of how better to study it. We view many of the issues

outlined in this report particularly in chapter 2 as difficult, but manageable, especially if they can be

anticipated in project planning, rather than reacted to as surprises during execution. This report illustrates

the range of studies summarised below.

The incident reporting study described in Chapter 3 showed that there were more near misses and minor

events reported in the dataset than those judged to be serious or moderate. The largest group of

reported incidents reflected problems of delay in A&E. This was due to various factors including the fact

that A&E depends on other departments, specialist and staff not based in A&E, such as porters. The

reporting process had several good aspects including a regular systematic review by the departmental

clinical risk management team and feedback in the form of newsletters. The findings of this evaluation

have been presented to the staff stressing that incident investigation analysis results in identification of

what, how and why an incident occurred92.

Retrospective case analysis as illustrated in Chapter 4 remain important in their contribution to our

understanding of adverse events and near misses. Furthermore, while textual, narrative descriptions are

important in creating understanding, they are sometimes difficult to follow especially when cases are

complex resulting in necessarily lengthy narratives. The range of graphical methods of

representation63,64,66,67 are useful aids to these descriptions and are obviously beneficial for both by

clinicians and researchers. In particular these methods can assist in reassuring clinical staff of the various

factors that contribute to the risks of any incidents they may be involved in.

In Chapter 5 we showed that there are many benefits to conducting a prospective barrier/safeguard

analysis including the structured format of the technique which can generate creative solutions to

problems. We have shown that barrier analysis, a method of error reduction used in other industries, can

be successfully adapted for healthcare. There are still some areas where training for this method could be

improved. For example, in relation to the identification of physical safeguards for reducing the risk of harm

to the patient. This is further evidence that healthcare relies heavily on weak barriers such as policies and

procedures to manage safety issues and when the system is pushed to the limit, the effectiveness of

such barriers is clearly compromised. Barrier analysis has also been developed by the NPSA and is

likely to be widely used in the future93. The formal process of barrier analysis can be lengthy and time

consuming, though the results repay the time invested. An additional potential benefit is that staff may

start to naturally consider barriers in their work – which could have a positive effect on practice as well as

safety culture.

The communication study described in Chapter 6 showed that the nurses in charge of A&E had to deal

with high levels of information exchange as part of their daily working activities. The number of times in

which the NIC was ‘interrupted’ has potentially serious implications for the effective exchange of


50

information. If the NIC is distracted from what they are doing (e.g., writing on the whiteboard), this may

disrupt their thought process, which in turn, could have adverse effects on the quality and completeness

of the previous intended message. There is a significant need to reduce the sheer volume of

communication load that the NIC has to deal with on a daily basis. Improving communication between

healthcare staff by reducing the levels of interruptions and minimising the volume of irrelevant or

unnecessary information exchange could therefore have important implications for patient safety.

In Chapter 7 we evaluated the efficiency of the triage process. The mean time that patients waited to be

seen for triage was 13 minutes 33 seconds and the triage process on average took 4 minutes and 19

seconds. Furthermore, the triage process appeared longer for patients who were expected by specialties

or triaged to specialties. This study supported previous findings87 that ordering tests such as x-rays

appears to be efficient use of time and did not have any significant impact or detriment on the time to

triage. Only a few patients were actively seen and treated in the triage area, and though this took longer

compared with those ‘triaged and not treated’ it obviously was beneficial for the individual patient and the

fact that they would not need to be treated by staff in other areas of the department, namely minors.

Clinical implications

These exploratory studies have provided us with further insight into conducting safety research in A&E as

well as helped to build a mutually beneficial partnership with the clinical staff thereby attempting to

address some of the issues described in Chapter 2. In particular some of the studies have contributed to

changes, such as the piloting of an electronic incident reporting system. Early impressions suggest that

there has been an increase in the number of reported incidents using this new system. This has obvious

implications for clinical risk management in that the more incidents that are reported the more we can find

out about the nature and frequency of such incidents, especially as in healthcare not all incidents are

reported58. This will then have other knock-on effects such as a better understanding of the underlying

factors that contribute to incidents and near misses, enabling management and senior staff to make more

informed decisions about which changes to implement to improve patient safety. This together with the

staff experiences of the barrier analysis process can help them to identify solutions to problems and

factors that have led to could potentially lead to incidents and near misses in the future.

The ethnographic studies of communication with the nurse in charge and the triage process also have

implications regarding patient safety. We have already mentioned how the sheer level of communication

events needs to be reduced, particularly with the level of interruptions that will distract the NIC from

completing a task, including relaying information or making decisions regarding the management of

patients. Similarly in triage dealing with other specialties seemed to add to the work load and subsequent

triage time for patients. This has important implications to the overall four hour targets as well as for the

15 minute waiting targets for triage, particularly for other patients who are not expected by particular

specialties.


51

Future research

One of the problems identified in chapter 2 was the lack of permanent traces of work can be mitigated in

some cases by judicious use of technology. Technology can be used in other areas of A&E to enhance

efficiency as well as some of the specific difficulties related to documentation for study. For example, the

status board which represents current work in minors, which although this physical artefact is ephemeral

(i.e., information is erased once a patient has left the department – whether admitted or discharged), it

can be captured using a small video camera, for example, and reviewed off-line. Cook (personal

communication) has suggested that the problem of the rapid time scale in the A&E might be handled by

progressively moving from slower-paced to more rapid environments; for example, from the operating

theatre, to the Intensive Care Unit, to A&E. In this way, researchers could build their observational skills

in a relatively easier setting, and then move on to more difficult situations. This sort of skill building would

require time, sustained commitment, and the development of good working relationships in multiple

departments of the hospital. Another example of a technological intervention is information provided for

staff. The efficiency of the triage process (and other areas of A&E) could be enhanced by providing

supplementary information required by the staff, such as maps, addresses of other clinical centres, bleep

numbers, information from the British National Formulary or Guy’s Hospital poisons unit in a

complimentary format, such as incorporated into the current computing system. It is possible that these

alternative sources of information may contribute to fewer interruptions to the NIC.

Table 8.1: A summary of lessons learnt and options for further research for each area studied

Area Key lessons learnt Options for further research workIncident reporting Retrospective analysis of incident

patterns helps enhance the reporting system and raises awareness

Compare to National data Electronic reporting in place and will be

reviewed Monitor effect of raised awareness on

the prevalence of certain incidents Incident analysis Use of graphical representation of

contributory factors is a useful additional tool developed to assist in analysis of incidents

Assess effect of using tool on staff understanding of safety

Barrier analysis Barrier analysis is applicable in healthcare

Conduct barrier analysis on high risk areas identified from incident reporting review

Communication load Senior clinical nurse working in the department has excessive communication load which may impact on effectiveness

Develop additional systems to redirect unnecessary communications

Triage process The process of initial assessment is made more inefficient by geographical issues, and non-clinical tasks

Monitor the effect of electronic handover at triage, using non clinical staff in different ways

Look at effectiveness of time spent in initial assessment on total time in department and reduction of clinical risk


52

Future research in A&E would incorporate our understanding and build on the studies described in this

report (see Table 8.1). In particular we have already starting looking at staff attitude to incident reporting,

staff perception of board rounds (A&E equivalent of ward rounds) and unscheduled returns to A&E. We

plan to undertake research in clinical decision making, particularly with respect to specific presentation of

symptoms, and factors that affect diagnosis. Despite the various challenges we experienced we have

succeeded in conducting various research projects and have built positive working relationship with the

staff who are keen for us to continue to conduct research in this field. Furthermore as indicated in

chapter 5 staff responded positively to recommendations that were elicited from these projects. The

implementations of any changes would necessarily require the endorsement of senior staff and staff in

general are likely to accept change when they see how it could have beneficial consequences.


53

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Appendix A Table A1: Channel and purpose of communication Channels of communication Purpose of communication Channel Acronym Purpose AcronymFace to face FF Management of the Department MD Telephone T Staff Management SM Computer C Patient Management PM Whiteboard WB Administration A Pager P Equipment E Patient records PR Social S 4 hour target 4 Study STY Paper source Paper Education ED Tannoy TNY Staff allocation sheet SAS Off Duty OD A&E activity sheet A&E Patient transport form PTF Agency form AF Message book MB Evacuation form EF Booking request form BRF Incident reporting form IRF Emergency form EF Table A2: Interaction type Interaction type Description Acronym Give request A request for information by the subject, that

is, the subject is asking for information GR

Receiving information Receipt of information by the subject RI Receive request Receipt of a request by the subject, that is,

the subject is being asked for information RR

Giving information Sending information from the subject GI Instruct request A request for action by the subject IR Instruct receive Receipt of instruction for action by the subject IRCV General Any communication which does not relate to

any of the above, e.g., greeting, thanking, apologising.

G


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Appendix B: Generic top-level task analysis of triage process

2. Call patient

4. Verify information on patient shown on computer is correct

1. Click on patient details

6 Enter/check information on computer (during process as required)

9 Examine observable signs (if appropriate) (examine wounds, bruises)

7 Elicit more information on problem ( pain?, vomiting?, known cause?)

8 Collect additional patient information (on medication? diabetic? pregnant? allergies?)

10. Look at additional information (documentation) if available (letters from GP, old ECG)

11. Contact specialty (if required) (contact medics,/ surgeons, gynaecology)

12. Perform additional tests (investigation) if appropriate

13. Order other tests (if required) (x-ray, blood, urine)

14. Offer and give painkillers (if appropriate)

15. Treat (dress wounds / give advice) (If appropriate)

16. Direct / Take patient to next area (A&E / clinic / home)

3. Ensure patient is reassured

5 Elicit key information on problem from patient (ask “what brings you here today?”)

TIME

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