Quality improvement theory and practice in healthcare

Ruth Boaden
Gill Harvey
Claire Moxham
Nathan Proudlove
Foreword by Helen Bevan,
Director of Service Transformation,
NHS Institute for Innovation and
Improvement
QUALITY IMPROVEMENT: THEORY AND PRACTICE IN HEALTHCARE
Ruth Boaden, Gill Harvey, Claire Moxham, Nathan Proudlove
This report, written in conjunction with the Manchester Business School, focuses on quality
improvement in healthcare, and summarises the evidence about how it has been
implemented and the results of this process.
It has a focus on the role of various industrial quality improvement approaches in this
process: the Plan-Do-Study-Act (PDSA) cycle, Statistical Process Control, Six Sigma, Lean,
Theory of Constraints and Mass Customisation. It also outlines the development of quality
from a clinical perspective and the way in which industrial approaches are now being
applied in healthcare.
The purpose of this report is:
• to provide a guide to the main approaches being used, in terms of their context as
well as their impact. This shows the emphasis and focus of these approaches, so
that guidance on the situations where they might be most effective can be
developed
• to enable links to be made between aspects of quality improvement
which are often regarded as separate; specifically improvement
from clinical and organisational perspectives.
Quality Improvement: Theory and Practice in Healthcare will
be of use to all healthcare leaders who are interested in
quality improvement, and will also be very relevant to
clinical staff across a range of settings.
ISBN: 978-1-906535-33-9
© NHS Institute for Innovation and Improvement 2008. All rights reserved.
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This report has had a long genesis. It began life in 2004 as a supplementary report to the
Manchester Business School (MBS) evaluation of the Six Sigma training programme run by
the NHS Modernisation Agency.
The report was never formally published, but versions of it emerged whenever there were
discussions about the nature and role of quality in the NHS. The NHS leaders who got access
to it enthused about it. There was no other publication available that set out the principles
and approaches to quality in healthcare so comprehensively or effectively. Word spread.
Eventually, there was such a groundswell of interest in this clandestine, unofficial paper that
the NHS Institute asked Manchester Business School to review and update the paper for
publication and widespread dissemination.
The timing of publication is fortuitous, just after Lord Darzi’s report from the Next Stage
Review of the NHS, High Quality Care for All. The Next Stage Review gives a significant and
welcome prominence to quality improvement in the next stage of NHS reform. It also sets
out, in chapter five, the “core elements of any approach to leadership”. These include
method: “the management method (leaders) will use for implementation, continuous
improvement and measuring success”.
Quality healthcare is dependent on method. Each of us, whether commissioner or
provider, needs to develop skills and knowledge in methods for improvement. The
authors of this report have summarised the improvement approaches and methods that
have been successfully utilised by industry over the past 50 years. They have evaluated
all the approaches from a healthcare perspective. They have assessed the full spectrum,
from the previous favourites such as Total Quality Management and Re-engineering, to
current preferences like Lean and Six Sigma to concepts such as Mass Customisation
that are newly emerging from the international healthcare improvement movement.
There are some key messages for NHS leaders in this report. Firstly, when we treat clinically-
led improvement (audit, clinical governance, etc) as a separate entity from managerially-led
performance improvement, we do so at our peril. Leading organisations in healthcare quality
have aligned improvement objectives and operate with a definition of quality that covers
both clinical and managerial domains. Secondly, from a research evidence viewpoint, none of
the approaches stands out as being more successful in healthcare than any of the others.
Having an improvement method or model can make a significant difference to achieving
outcomes but it does not seem to matter which approach it is. The authors conclude that the
process of improvement is more important than the specific approach or method. When
quality improvement efforts fail to deliver, it is rarely an “approach” problem or a “tool”
problem. Rather, it is a “human dynamics” or “leadership” problem. Thirdly, for healthcare
leaders, seriously adopting and committing to the method for as long as it takes to deliver
the results for patients is as important as selecting the specific method of improvement.
1Quality Improvement: Theory and Practice in Healthcare
Foreword

Fourthly, there are many paths (and many method options) to successful, sustained
quality improvement. The most important factor is the leadership ability to address many
simultaneous challenges and to adapt solutions and strategies to the organisation’s own
context.
I welcome this report as an important contribution to the body of evidence on quality in
healthcare at a time when quality improvement is rightfully gaining a high strategic priority in
the NHS. And I am delighted that, after four years, a report that has so much to teach those
of us who want to provide safe, effective care and a great patient experience has finally seen
the light of day!
Helen Bevan
Director of Service Transformation
2 Quality Improvement: Theory and Practice in Healthcare

GLOSSARY 8
EXECUTIVE SUMMARY 9
Where did the information come from? 9
How robust is the information? 9
Clinical quality improvement 10
What is quality? 10
Industrial approaches to quality improvement 10
Quality improvement approaches 11
Plan-Do-Study-Act (PDSA) cycle 11
Statistical Process Control (SPC) 12
Six Sigma 12
Lean 13
Theory of Constraints 14
Mass Customisation 15
Underlying concepts 15
Systems and processes 15
The role of the customer 16
Balancing supply and demand 16
Translating improvement approaches to the healthcare context 17
Does quality improvement work? 17
1. INTRODUCTION 19
1.1 Who should read the report? 19
1.2 Which parts of the report are most relevant? 20
1.3 Presentation style 20
2. INFORMATION SOURCES AND METHODOLOGY 21
2.1 Where did the information come from? 21
2.1.1 Database searches 21
2.1.2 Grey literature 21
2.1.3 Prior knowledge 22
2.2 Methodology: how robust is this information? 22
2.2.1 The relevance of controlled trials 22
2.2.2 Quality improvement is a complex social intervention 23
2.2.3 Is more than one methodology needed? 24
2.3 Is this a new field of research? 25
3. QUALITY IN HEALTHCARE 27
3.1 The history of clinical quality improvement 27
3.1.1 Codman 28
3.1.2 Donabedian 28
3.1.3 Berwick 28
3.1.4 The role of other clinical professions 29
Table Of Contents

3.2 Influences on the development of clinical quality improvement 29
3.2.1 Clinical guidelines 29
3.2.2 Care pathways 29
3.2.3 Clinical governance 30
3.3 Defining and assessing healthcare quality 30
3.3.1 Defining quality 30
3.3.2 Process and outcome 32
3.3.3 Assessing performance 34
3.3.4 Balancing elements of performance 35
4. INDUSTRIAL QUALITY IMPROVEMENT 38
4.1 Quality improvement in industry 38
4.2 The quality gurus 39
4.2.1 Deming 39
4.2.2 Juran 41
4.2.3 Crosby 41
4.2.4 Feigenbaum 41
4.2.5 Differences and similarities 42
4.3 Total Quality Management 43
4.4 Applying approaches from manufacturing in the service sector 44
4.5 Quality awards and business excellence 44
4.6 Business Process Re-engineering 45
5. QUALITY IMPROVEMENT APPROACHES 46
5.1 The Plan-Do-Study-Act model 47
5.1.1 Outline of the approach 47
5.1.2 How the approach fits with others 49
5.1.3 Where the approach has been used in healthcare: the
collaborative approach 50
5.1.4 Outcomes that have been reported 52
5.2 Statistical Process Control 57
5.2.3 Where the approach has been used in healthcare 59
5.3 Six Sigma 61
5.4 Lean 72
Table Of Contents

5.5 Theory of Constraints 93
5.6 Mass Customisation 97
5.6.1 Outline of what the approach is 97
5.6.2 How the approach fits with other approaches 99
6. UNDERLYING CONCEPTS 101
6.1 Systems and processes 102
6.1.1 Systems thinking in healthcare 103
6.1.2 The process view 103
6.1.3 Process design in healthcare 104
6.1.4 Managing flow 106
6.1.5 Variation 106
6.2 The role of the customer 107
6.2.1 Who is the customer in healthcare? 108
6.3 Balancing supply and demand 109
6.3.1 Capacity management 109
6.3.2 Demand management 111
6.3.3 Inventory management 112
6.4 Underlying concepts and approaches to improvement 114
7. TRANSLATING IMPROVEMENT APPROACHES TO THE
HEALTHCARE CONTEXT 115
7.1 The difference between healthcare and other sectors 115
7.1.1 Healthcare is a professional service 115
7.1.2 Healthcare has a complex structure 117
7.1.3 Healthcare is difficult and complex to change 117
7.2 The implications for people 119
7.2.1 Culture 119
7.2.2 Leadership 119
7.2.3 The healthcare workforce 121
7.3 Does quality improvement work? 123
7.3.1 Methodology 123
7.3.2 Definition 124
7.3.3 Critical success factors 124
7.3.4 The process of implementation is more important than the approach 125
Table Of Contents

8. CONCLUSIONS 127
8.1 Quality improvement: the theory 127
8.1.1 The applicability of quality improvement approaches 127
8.1.2 Are the approaches really different? 127
8.1.3 So which approach should be used? 127
8.1.4 How do we know what works? 127
8.1.5 Is it what works or why? 128
8.2 Quality improvement: the practice 128
8.2.1 Define quality first 128
8.2.2 Identify the process 128
8.2.3 Beware of exclusive promotion of one approach 128
8.2.4 Think about who the customer is 129
8.2.5 Understand the people 129
8.2.6 Get data about quality before you start 129
8.2.7 Recognise the importance of whole system leadership 129
REFERENCES 130
APPENDIX 1 - The authors of the report 146
Table Of Contents

Table 1 - Definitions of healthcare quality 31
Table 2 - Deming’s 14 Points 40
Table 3 - Determinants of the effectiveness of improvement collaboratives
(Wilson et al. 2003) 55
Table 4 - Challenges for successful improvement collaboratives
(Øvretveit et al. 2002) 56
Table 5 – Six sigma levels of certification 63
Table 6 – TQM and Six Sigma (Lazarus 2003) 66
Table 7 – Outcomes from applying Six Sigma in healthcare 70
Table 8 – Delivering Operational Excellence: the Toyota Production System 74
Table 9 – Tools associated with a Lean approach 75
Table 10 – The seven wastes 77
Table 11 – Six Sigma and Lean 81
Table 12 – Characteristics of healthcare that might imply that Lean is applicable 82
Table 13 – Guidance on Lean in healthcare 84
Table 14 – Implementing Lean 85
Table 15 – Reported outcomes from the application of Lean 88
Table 16 – Reported applications of Lean in the NHS 91
Table 17 – Command and control versus systems thinking (Seddon 2005a) 102
Table 18 - IHI approach to improving flow
(Institute for Healthcare Improvement 2003) 106
Table 19 – The relationship of the approaches to the main concepts 114
Table 20 – Comparison of hospital professional and TQM models
(Short & Rahmin 1995) 116
Table 21 – What leaders should do to change culture
(Bibby & Reinertsen undated) 119
Table 22 – core challenges to organising for quality (Bate et al. 2008) 125
Figures
Figure 1 – The Model for Improvement (Langley et al. 1996) 48
Figure 2 - The Model for Improvement used over time (Schon 1988) 48
Figure 3 - Example c-chart using number of emergency admissions on
consecutive Mondays (Mohammed, Worthington & Woodall 2008) 58
Figure 4 - The main steps in DMAIC (Brassard, Finn, Ginn et al. 2002). 64
Figure 5 – The Toyota Way 73
Figure 6 – Lean and its tools (Hines et al. 2004). 78
Figure 7 – Lean Six Sigma (NHS Institute for Innovation and Improvement 2006) 81
Figure 8 – The phases of clinical process redesign (Ben-Tovim et al. 2008b) 105
Figure 9 - Statistical Thinking in Quality Improvement (Snee 1990) 107
Figure 10 – Reducing the level of inventory enables management to see the
problems (Slack et al. 2006) 112
Tables

5S Sort, simplify/straighten/set in order, shine/scrub, standardise/stabilise,
sustain/self discipline
A&E Accident and Emergency
BB Black Belt
BPR Business Process Reengineering
CLAB Central line associated bloodstream (infection)
CQI Continuous Quality Improvement
DBR Drum – Buffer - Rope
DFSS Design for Six Sigma
DMADV Define – Measure – Analyse – Design – Verify (a Six Sigma DFSS roadmap)
DMAIC Define – Measure – Analyse – Improve – Control (the main Six Sigma roadmap)
DoH Department of Health (UK)
DPMO Defects Per Million Opportunities
EBD Experience Based Design
EFQM European Foundation for Quality Management
GB Green Belt
GE General Electric company
IHI Institute for Healthcare Improvement
JIT Just in time (supply of materials etc.)
MA NHS Modernisation Agency (2001-2005)
MBB Master Black Belt
MCN Managed Clinical Networks
NHS National Health Service
NDP National Demonstration Project
NHS Institute NHS Institute for Innovation and Improvement
OPT Optimised Production Technology
PCT Primary Care Trust
PDCA Plan - Do - Check - Act cycle
PDSA Plan - Do - Study - Act
RCT Randomised Controlled Trial
RIE Rapid Improvement Event
SD Standard Deviation
SPC Statistical Process Control
ToC Theory of Constraints
TPS Toyota Production System
TPs Thinking Processes
TQI Total Quality Improvement
TQM Total Quality Management
VOC Voice of the Customer
VUT A formula for calculating waiting time in a queue based on system
Variability, Utilisation and (processing) Time
Glossary

This report, written in conjunction with the Manchester Business School, focuses on quality
improvement in healthcare, and summarises the evidence about how it has been
implemented and the results of this process.
It has a focus on the role of various industrial quality improvement approaches in this process:
the Plan-Do-Study-Act (PDSA) cycle, Statistical Process Control, Six Sigma, Lean, Theory of
Constraints and Mass Customisation. It also outlines the development of quality from a
clinical perspective and the way in which industrial approaches are now being applied
in healthcare.
The report draws on academic literature as well as other sources, including accounts
published on the web, but recognises the methodological limitations of accounts of success
in quality improvement without any comparative data being made available.
• to provide a guide to the main approaches being used, in terms of their context as well as
their impact. This shows the emphasis and focus of these approaches, so that guidance on
the situations where they might be most effective can be developed
• to enable links to be made between aspects of quality improvement which are often
regarded as separate; specifically improvement from clinical and organisational perspectives.
Where did the information come from?
The information was obtained from searches of academic databases, grey literature sources
as well as the prior knowledge of the authors and staff from the NHS Institute for Innovation
and Improvement (NHS Institute).
How robust is the information?
Relatively few papers which provided analytical reviews of the application of improvement
approaches were found; most appeared to be descriptive case studies based on a single site.
These were relatively small scale before and after studies, making it difficult to determine
whether any reported changes are directly attributable to the quality improvement
intervention or not.
The papers found used a wide range of methods to gather the data reported. A debate
about the relevance (or otherwise) of randomised controlled trial methods to investigate the
effectiveness of quality improvement approaches was also identified. Some authors argued
that quality improvement is a complex social intervention, for which methods designed to
‘control out’ the influence of context on the implementation of the intervention are
not relevant.
Executive Summary

This report concludes that a number of methods are needed and that no single one will be
sufficient to assess the full impact of quality improvement. More focus on how a particular
approach can be used is needed, since research to date shows that most approaches work
sometimes, although there is little evidence about which contextual factors influence this.
Clinical quality improvement
The history of clinical quality improvement goes back to conceptualisations of clinical work as
craft with individuals responsible for the quality of the outcome, and as early as 1916
Codman focused on the end results system of auditing clinical care. Other individuals with a
significant influence on clinical quality improvement include Donabedian, who outlined a
definition of quality which focused on structure, process and outcome, and Berwick, who
spearheaded the application of industrial approaches within a clinical environment.
Influences on the development of clinical quality improvement include clinical audit, clinical
guidelines, care pathways and clinical governance, with recent attempts to integrate these
more closely with organisational issues.
What is quality?
Quality can be defined in a variety of ways, and increasingly the terms quality and safety are
being used interchangeably. This report shows that safety may be regarded as one element
of quality, with the most widely used definition probably being that of quality as healthcare
that is safe, effective, patient-centred, timely, efficient and equitable.
Assessing quality as an element of performance can be complex; a ‘balancing act’ between
organisational and clinical aspects, as well as process and outcomes. This is a challenge for
healthcare systems in many contexts.
Industrial approaches to quality improvement
These developed in manufacturing industry, in practice after the Second World War, but
being based on earlier statistical approaches developed in the 1920s. Key figures (gurus) who
influenced this process include Deming, Juran, Crosby and Feigenbaum, and their approaches
share a common focus on the role of customers and management as well as teamwork,
systematic approach to work and the use of appropriate improvement tools, whilst differing
in their emphasis on these factors.
Executive Summary

Many elements of these approaches were incorporated into Total Quality Management
(TQM) in the 1980s which attempted to apply quality improvement at the organisational
level, although as an approach it has not been shown to be very successful. This is not
dissimilar to other organisation-wide approaches to change and improvement, including
Business Process Re-engineering (BPR). Frameworks for assessing organisational quality were
also developed, linked to ‘awards’ in Japan, the USA and Europe.
At the same time, there was an increasing focus on quality improvement in service
organisations, with the development of service quality as a field of study. This necessitated
more focus on marketing and relationship with customers, as well as the role of staff in
quality improvement.
Quality improvement approaches
Plan-Do-Study-Act (PDSA) cycle
• Outline of the approach: The plan-do-study-act (PDSA) model was developed by Deming
(Deming 1986) – and termed by him the Shewhart cycle (Dale 2003). Deming’s initial
terminology was plan-do-check-act (PDCA), but he later changed this to PDSA to better
reflect his thinking. PDSA is the term generally used in healthcare and which will therefore
be used here. PDSA cycles are small tests of change, used as part of a continuous
improvement approach. A change practitioner will plan a test of change, carry out the
change (do), study the results and act on them in the next cylce of change.
• How the approach fits with others: there are few reports of the approach being used with
others, although tools from a variety of approaches can be used at any stage of the PDSA
cycle and PDSA is sometimes suggested in the ‘improve’ phase of Six Sigma and as part of
Rapid Improvement Events in Lean.
• Where the approach has been used in healthcare: it has been widely used, particularly as
the main framework for the collaborative approach – the ‘breakthrough’ approach to
improvement. The impact appears to depend on the focus of the collaborative, the
participants and their host organisation and the style and method of implementing the
collaborative.
• Outcomes that have been reported: the approach has been relatively well studied in terms
of its application in healthcare (compared with the other approaches considered in this
report) although there is little evidence (to date) to suggest it is more cost-effective that
any other approach. The longer term impact in terms of sustainability and spread of the
approach has not yet been evaluated.
Executive Summary

Statistical Process Control (SPC)
• Outline of the approach: The roots of this approach can be traced to work by Shewhart in
the 1920s which identified the difference between ‘natural’ variation in measures of a
process – termed ‘common cause’ - and that which could be controlled – ‘special’ or
‘assignable’ cause variation. Processes that exhibited only common cause variation were
said to be in statistical control. It is argued that the use of this approach for quality
improvement gave it a scientific and statistical focus.
• How the approach fits with others: it was widely promoted as a key tool in the TQM
approach, is also used in Six Sigma and sometimes with Theory of Constraints and the
PDSA cycle. Some argue that its growth would have been more rapid if it did not
challenge the focus on short-term cost reduction, which is often one element in quality
improvement. It provides guidance for action in a way which more conventional statistical
analyses do not.
• Where the approach has been used in healthcare: recognition of the importance of
variation in healthcare has led to an interest in SPC, with a wide variety of applications
reported. Systematic review of SPC application in patient monitoring found it to be a
simple, low-cost and effective approach although there is always debate about its
applicability. It is used both to report performance data at board level and to provide
guidance for healthcare practitioners on treatment effectiveness.
• Outcomes that have been reported: systematic review showed that SPC could be used to
improve communication between clinicians, managers and patients by providing a shared
language, to describe and quantify variation, to identify areas for potential improvement
and to assess the impact of change interventions. Its application may be limited by the
extent to which the objective of improvement is the reduction of variation, the complexity
and appropriateness of data sets representing aggregations of different types of patients or
management units and the implications on the underlying statistics of having very small or
very large data sets.
Six Sigma
• Outline of the approach: Six Sigma is an improvement or (re)design approach developed
initially by Motorola in the 1980s, initially in manufacturing, although it is now becoming
popular in the service sector especially with US-owned firms. It has its roots in the work of
Shewhart and Deming, but there is no universally accepted definition. However, most
authors agree that it may be regarded as a method for process improvement and product
development that utilises a systematic approach, relying on statistical methods to improve
defect rates (as defined by the customer). It consists of:
o an underlying philosophy of identifying customer needs and then establishing the
root causes of variation in meeting these needs
o elements that support this, including a certification structure for various levels of
competence in applying the approach (black and green ‘belts’) and a structured
Executive Summary

way of deploying the approach and coaching of projects throughout the
organisation, supported by training
o structured methodologies (including define, measure, analyse, improve and
control (DMAIC)) are used
o these are supported by a variety of tools for improvement, many of which are
common to other quality improvement approaches
• How the approach fits with others: many organisations appear to have re-labelled TQM as
Six Sigma, and a recent development is the use of Lean Six Sigma (see following section)
• Where the approach has been used in healthcare: there are numerous reports of the
application of Six Sigma but few that take a systematic approach to assessing its
effectiveness. The approach is heavily promoted in the US, in line with its current
popularity in all types of organisations
• Outcomes that have been reported: the evidence is descriptive, with no fundamental
critique or examination of its effectiveness, or independent evaluation. This may be due to
its relatively recent popularity, with a number of academics acknowledging that the
academic perspective is currently lagging the practice.
Lean
• Outline of the approach: The term Lean has been developed in the context of
manufacturing from the way in which Toyota, and other Japanese motor manufacturers,
organise their production processes. The approach can be described as either:
o the five principles of Lean: identify customer value, manage the value stream,
‘flow’ production, pull work through the process and pursue perfection through
reducing all forms of waste in the system, or
o the ‘Toyota Production System’ (TPS) as summarised in the ‘Toyota Way: problem-
solving, people and partners, process and philosophy’.
A variety of tools can be used to support the Lean approach, many of which are common
to other approaches, and there is no definitive list. Commonly used ones include value
stream mapping, rapid improvement events and 5S (sort, simplify/straighten/set in order,
shine/scrub, standardise/stabilise, sustain/self discipline).
• How the approach fits with others: many authors believe that Lean can be integrated with
other approaches. The most common integration appears to be with Six Sigma, to form
Lean Six Sigma, although some argue that this has been because of diminishing returns
from the use of either approach on its own. Most of these attempts bring Lean tools and
approaches into the overall Six Sigma framework (most often the DMAIC methodology).
Some authors describe the different focus of Lean (reducing waste) and Six Sigma
(identifying cause and effect) and arguing that organisations need both.
• Where the approach has been used in healthcare: there is an increasing emphasis on Lean
approaches in healthcare, with some authors arguing that its features make it especially
Executive Summary

applicable, as well as a developing community of those using the approach. In particular,
the complexity of healthcare processes, the difficulty in seeing where there are problems
and the inappropriate measures of performance are highlighted. Some authors argue that
Lean needs to be adapted to be successfully applied to services. They believe that Lean has
an inappropriate focus on standardisation of work and the definition of value from a
customer perspective, when customers may be multiple and their needs hard to identity.
There is some empirical evidence to support the need for Lean to be adapted if it is to be
successfully implemented in public sector organisations. There is a wide range of ‘how to’
guides available for implementing Lean in healthcare, but it is difficult to identify an
evidence base for the guidance.
• Outcomes that have been reported: evidence from manufacturing shows that Lean is
beneficial, with most studies having focused on one aspect of Lean and focused on
quantitative and comparative research. Within healthcare there are numerous reports of
the application of Lean but, as with Six Sigma, these are not comparative, independent
or critical.
Theory of Constraints
• Outline of the approach: Theory of Constraints (ToC) developed from the Optimised
Production Technology (OPT) system first proposed by Goldratt in the early 1980s.
The basic concepts of ToC are that every system has at least one constraint - anything that
limits the system from achieving higher performance in terms of its goal, and the existence
of constraints represents opportunities for improvement. The approach consists of
three elements:
o the pre-requisites (establishing the goal of the system and what performance
measurement system will support its achievement)
o the thinking processes: a set of logic tools to establish and communicate what to
change, what to change to, and how to bring about the change
o the five focusing steps: identify the system’s constraints, decide how to exploit
them, subordinate everything else to that, elevate the system’s constraints, if a
constraint is broken, repeat the process.
The drum-buffer-rope method for managing constraints is key: the rate of work of the
constraint sets the pace for the whole process.
• How the approach fits with others: the approach tends to be exclusive, though it has been
used with SPC in some situations.
• Where the approach has been used in healthcare: there are relatively few accounts of its
application in healthcare that use empirical data although there is some theoretical work,
and where accounts are available they are anecdotal and fragmented. Within the NHS
there is some evidence of the thinking processes being used and more of the five focusing
steps; buffer management is becoming quite common, supported by software, being used
to improve achievement of A&E target times and expected inpatient target discharge dates.
Executive Summary

• Outcomes that have been reported: there are numerous accounts of the application of ToC
in industry in general, but little in healthcare and that data which is available lacks rigour in
the way it has been gathered.
Mass Customisation
• Outline of the approach: The approach focuses on the ability to produce products or
services in high volume, yet vary their specification to the needs of individual customers or
type of customer and is closely linked to variation. It attempts to address the conflict
between high volume, ‘mass production’ of services which is often linked to lower unit cost
and lower volume higher variety services, with higher associated costs but increased
customer satisfaction and fit of service with customer needs.
• How the approach fits with others: while not strictly an approach to quality improvement,
its focus on system and process design means it is closely linked with improvement since
system and process design has been shown to have a major impact on quality.
• Where the approach has been used in healthcare: despite a lot of evidence for its use in
manufacturing, there is little to show how it has been applied in healthcare, despite
increasing theoretical emphasis on its potential to support healthcare improvement.
• Outcomes that have been reported: there are to date no independently reported results of
the application of mass customisation in healthcare.
Underlying concepts
The approaches to quality improvement detailed in this report are all based on a series of
underlying concepts, with different emphasis on each one depending on the approach
concerned. The report outlines these concepts and demonstrates how they support the
various approaches to quality improvement, as well as the implications for using the
approaches in practice. These concepts might be described as those underlying operations
management, a well-established academic discipline, although the concepts are described in
different ways by different authors.
Every organisation has a function that can be described as ‘operations’. Operations
management focuses on examining the processes used to produce goods and services.
Effective operations management has the potential to keep costs down, improve revenue,
appropriately allocate resources and develop future competitive advantage, although research
in healthcare rarely take an operations management perspective.
Systems and processes
The systems view is fundamental both to operations management and to much of the
thinking around improvement, particularly to Deming’s insights. This may make operations
management approaches applicable in healthcare, which also focuses on the whole system.
Executive Summary

• Systems thinking in healthcare is especially apparent when network forms of organisation
of healthcare services are considered. There is an increasing body of evidence supporting
the effectiveness of this form of organisation, and the benefits in terms of sharing
knowledge which result.
• The process view is essentially systems thinking at a more detailed level, down to the work
of individuals within systems viewed as comprising series of processes. Healthcare often
appears to experience conflict between clinical and managerial processes, with
improvement approaches applied to one or the other, rather than considering how they
might be integrated.
• Process design in healthcare is underpinned by a series of principles for any process design,
which include consideration of explicit and implicit benefits from the process for the
customer (e.g. the patient) as well as design of the way in which the service is delivered
and the goods required to support this activity. There is a wide range of process redesign
activity within healthcare, sometimes labelled as one of the quality improvement
approaches (particularly Lean).
• Managing flow is one element of process management and is the emphasis for the Lean
approach to improvement, with ToC also considering this. It is argued that consideration of
flow will lead to systems thinking since flow through one element of the healthcare system
cannot be considered in isolation.
• Variation underpins many of the quality improvement approaches, specifically SPC and Six
Sigma. Lean and ToC will have an impact on variation although it is not the main focus of
the approaches, whilst it is an explicit input to the mass customisation process. The extent
to which variation is inherent in healthcare processes, and thus can be reduced (or not) is a
matter of debate.
The role of the customer
The customer has an important role in defining quality in most of the approaches in this
report – particularly Lean and Six Sigma. In healthcare it is not necessarily the patient who is
the customer; other stakeholders may include carers, society, taxpayers (where the system is
publicly funded) and the processes by which decisions are made (which may dictate certain
steps in a process which would otherwise be regarded as unnecessary).
Balancing supply and demand
Generally there is little evidence that well-established approaches for managing this inevitable
tension in other industries are being applied in healthcare, in anything other than a
piecemeal way.
• Capacity management: whilst a necessary part of any service provision, there is little
evidence of its explicit consideration within healthcare. Bed management is one activity
which attempts to manage capacity. Strategies for managing capacity include:
Executive Summary

Executive Summary
o level capacity with resultant queues at times of excess demand
o chase demand by adjusting capacity to meet demand, which often has an impact
on the quality of service
o ‘Coping’, which is often an unintentional strategy and may again lead to decline
in quality of service.
• Demand management: there is some evidence of this in healthcare but only to a limited
extent. Of more importance perhaps is the extent of ‘failure demand’ – when services are
provided again because the customer was not satisfied the first time or because an
alternative service is not available when required.
• Inventory management: the major example of this within healthcare is queues (waiting
lists) for services.
Translating improvement approaches to the healthcare
context
Healthcare may be regarded as different from other sectors because it is a professional
service, with a complex structure and a history of being difficult and complex to change, for
a variety of reasons. The NHS is particularly complex due to the autonomy of its many
stakeholder groups and the lack of connection between much resource decision making and
financial consequences.
The implications of translating these approaches are important when the impact on people is
considered. Organisational culture, which stems from the beliefs of those who comprise the
organisation, as well as leadership are shown to be influential. Assumptions that the
workforce at large are motivated to change for the sake of improved quality of care are
challenged by some authors, while others highlight the need for long-term stability of
employment if quality improvement is to be successful.
Does quality improvement work?
Whilst the evidence for the effectiveness of particular approaches to quality
improvement has already been considered, and shown to be lacking in many cases,
there are some wider studies which consider the impact of quality improvement as a
generic organisational change, rather than any single labelled approach. Issues of
methodology – and in particular the lack of comparative studies – are raised, as it is the
issue of definition of quality improvement.
While a number of lists of success factors have been produced, some of which are based on
extensive empirical evidence, it is clear that the main issue is the way in which the
improvement is implemented, rather than the nature of the improvement itself.

Quality improvement theory and practice in healthcare

This report focuses on quality improvement in healthcare, and summarises the evidence
about how it has been implemented and the results of this process.
It has a focus on the role of various industrial quality improvement approaches in this process:
the Plan-Do-Study-Act (PDSA) cycle, Statistical Process Control, Six Sigma, Lean and Theory of
Constraints. It also outlines the development of quality from a clinical perspective and the
way in which industrial approaches are now being applied in healthcare.
The report draws on academic literature as well as other sources, including accounts
published on the Web, but recognises the methodological limitations of accounts of success
in quality improvement without any comparative data being made available.
• to provide a guide to the main approaches being used, in terms of their context as well as
their impact
• to highlight the different focus for improvement that underpins these approaches, so that
guidance on the situations where they might be most effective can be developed
• to enable links to be made between aspects of quality improvement which are
often regarded as separate; specifically improvement from clinical and
organisational perspectives
This review is limited in that it is not a full systematic review, although the intention was
to cover all the main areas of literature. We have attempted to include all key sources,
but apologise if something has been missed. We hope that this review can act as a
starting point for some integration of the diverse literature and evidence on quality
improvement which can contribute to the improvement of healthcare quality in practice
through clearer understanding.
1.1 Who should read the report?
This report will be helpful for:
• Clinicians
• Chief Executives of PCTs, NHS Trusts, SHAs and other NHS organisations
• Chairs of PCTs, PECs and NHS Trust Boards
• Directors: including those with responsibility for clinical care, nursing, operations, strategy,
performance, improvement and human resources
• NHS improvement leaders
• Those in pre-registration or vocational training who are studying healthcare quality and
improvement
1. INTRODUCTION

1.2 Which parts of the report are most relevant?
Whilst the whole of the report contains information that will be helpful for those reading it,
in order to guide readers from different backgrounds the following is suggested:
If you:
• have little time … read the Executive Summary and the Conclusions (section 8)
• have some time but do not want all the detail … follow the Executive Summary by
reading the sections on the development of quality and improvement in healthcare and
industry (sections 3 and 4), the description of the concepts underlying the various
approaches (section 6) and the section on translating improvement approaches to
healthcare (section 7). This misses out all the detail on the various approaches
• are interested in how the evidence in this report was gathered … read section 2
• want to know what evidence was used … look at the list of references at the end of the
body of the report
• want to know more about the context and development of quality in healthcare … read
section 3
• want to understand the development of industrial methods for quality improvement …
read section 4
• want to know about a particular approach to improvement: Plan-Do-Study-Act (PDSA)
cycle Statistical Process Control (SPC), Six Sigma, Lean, Theory of Constraints, Mass
Customisation … read the relevant part of section 5
• want to know what these approaches have in common, and the principles which they
emphasise … read section 6
• want to know where improvement approaches have been applied in healthcare and the
outcomes that have been reported … read the third and fourth part of the sub-section
about each approach in section 5
• want to know more about translating industrial improvement approaches to healthcare …
read section 7
1.3 Presentation style
• There are a large number of references to published work in the report; these are shown
in the text by the author(s) and the year of publication and then listed in alphabetical order
by author from page 85
• Throughout the text boxes are used to highlight key points and to provide explanation of
terminology used
• A glossary of key terms and abbreviations can be found on page 8.

2.1 Where did the information come from?
This report is based on reviews of available evidence about the effectiveness of various quality
improvement approaches, and their application in healthcare. The methods used to gather
this information are described in subsequent sections. However, the way in which the
evidence has been synthesised and presented is the responsibility of the authors of the
report, and does not in any way represent UK National Health Service (NHS) policy.
2.1.1 Database searches
This review did not employ formal systematic review methods, however a number of semi-
systematic searches on the key approaches described were carried out. In general these
yielded very few papers which provided analytical reviews of the application of improvement
approaches; most appeared to be descriptive case studies based on a single site. These were
relatively small scale, before and after studies, making it difficult to determine whether any
reported changes are directly attributable to the quality improvement intervention or not.
It was also notable that many projects applied quality improvement approaches to support
processes within the healthcare sector (e.g. pathology) or to those patient care processes
which have clear parallels with industrial processes (e.g. radiography) rather than processes
directly providing patient care.
2.1.2 Grey literature
Grey literature can be defined as “Information produced on all levels of government,
academics, business and industry in electronic and print formats not controlled by
commercial publishing i.e. where publishing is not the primary activity of the producing
body.”1. Given the diversity of grey (i.e. information not formally published) literature, we did
not make any attempt to search this type of literature in a systematic sense, but followed up
sources recommended or known to us as well as using links from the websites of the NHS
Institute for Innovation and Improvement (NHS Institute) and the Institute for Healthcare
Improvement (IHI).
We received anecdotal information about the application of various approaches across the
world, but have concentrated here on information ‘published’ in some form and publicly
available through the web or from academic journals. It should be noted that we have
formed the impression that there is an increasing amount of information about improvement
being published and we have done our best to ensure that the information here is up
to date.
2. INFORMATION SOURCES AND
METHODOLOGY
2. http://www.greynet.org/

2.1.3 Prior knowledge
Due to work by various members of the team in previous research and consultancy, they
were able to bring information and knowledge to the research. A brief résumé of the
research team and their background is given in Appendix 1. We have also utilised the
experience of staff from the NHS Institute to supplement literature found through
formal searching.
2.2 Methodology: How robust is this information?
There are several issues to consider when information about quality improvement is
presented: not only concerning the appropriateness of the methods by which this
information has been gathered, but also the nature of the information itself and its scope
and completeness, and whether calls for a new field of research should be heeded.
2.2.1 The relevance of controlled trials
There are few large-scale, rigorously conducted trials (from a scientific perspective) that
provide conclusive evidence to support the assertion that implementing quality improvement
programmes and methods leads to improved processes and outcomes of care (Perneger
2006). Typically, randomised controlled trials (RCTs) are designed to evaluate the impact of a
single, discrete intervention (for example, the introduction of a new surgical technique for
joint replacement), where the aim is to establish causality (i.e. new techniques leads to
improved patient outcomes). In the design and conduct of the study, the focus is on
controlling for as many extraneous variables as possible to limit any unintended bias. An RCT,
by definition, tends to ‘control out’ the context-dependent variables that are argued by some
to determine the success or failure of the intervention (Pawson, Greenhalgh, Harvey et
al. 2005).
A review of quality improvement research (Grol, Baker & Moss 2004) summarises the
methods used to date as:
• audits of care
• determinants of variations in care provision
• studies of the effectiveness of change strategies (mostly trials)
In addition, there is a prevalence of case reports and before-and-after papers, which are able
to disseminate results quickly, although “weak designs … do not allow internally valid
conclusions and the consequence is that the science of quality improvement will proceed
ineffectively in healthcare” (Speroff & O’Connor 2004).

Recent work has argued that urgency and robust evidence are not alternative choices: “it is
both possible and wise to remain alert and vigilant for problems while testing promising
changes very rapidly and with a sense of urgency” (Berwick 2008, p.1183)
2.2.2 Quality improvement is a complex social intervention
Those questioning the use of experimental methods also argue that they are not appropriate
in “investigating and understanding complex social interventions” (Walshe 2007, p.57).
Like many other organisational level change management programmes, quality improvement
can be described as a complex intervention that typically involves a number of inter-related
components e.g. training in specific improvement methods and approaches, the creation of
improvement teams, data feedback, tailored facilitation and support (Lilford 2003). Complex
interventions are characteristically active, non-linear, embedded in social systems, and prone
to modification and change (Pawson et al. 2005), and these factors are important to take
into account when designing evaluations.
Trials may not be an appropriate method for researching
quality improvement because …
… they do not promote learning: “The RCT is a powerful, perhaps unequalled, research
design to explore the efficacy of conceptually neat components of clinical practice – tests,
drugs, procedures. For other crucially important learning purposes, however, it serves less
well” (Berwick 2008, p.1182). “‘Where is the randomized trial?’ is, for many purposes,
the right question, but for many others it is the wrong question, a myopic one. A better
one is broader: ‘What is everyone learning?’” (Berwick 2008, p.1184).
… they impede progress: emphasis on experimental methods “can seriously hamper
those both researching and implementing quality improvement in healthcare”
(Walshe 2007, p.57).
… it is not feasible or ethical to apply them (Speroff & O’Connor 2004).
… they are not sensitive to the things that influence the success of change: the “array of
influences: leadership, changing environments, details of implementation, organizational
history, and much more” that influence the ‘success’ of change and describe the RCT as
an “impoverished way to learn” (Berwick 2008, p.1183).

Some claim that quality improvement methods “were never intended to stand up to the
rigour demanded in a full-scale medical research study” (Plsek 1999).
There is an increasing emphasis on context as a key influence on implementation (Walshe
2007) with consideration of content (the nature of the intervention itself) as well as
application (the process through which the intervention is delivered) and the outcomes
(results) of the intervention.
In order to address the more complex nature of the intervention, staged approaches such as
the Medical Research Council’s framework for evaluating complex interventions have been
developed (Campbell, Fitzpatrick, Haines et al. 2000). This is a phased approach using
different research methods in each phase; following a theoretical phase, the components of
the intervention are defined, an exploratory trial carried out followed by an RCT and then
long term implementation. However, many authors are now arguing for more than one
method to be used.
2.2.3 Is more than one methodology needed?
Given the broad scope and focus of quality improvement and the fact that it draws on
knowledge and learning from a range of disciplines both within healthcare and outside, it
seems likely that a range of research approaches and methodologies may be considered
appropriate to evaluate its implementation (Grol, Berwick & Wensing 2008). The need to
conduct the research both rigorously and ethically remains paramount, but the use of other
methods does not imply that rigour must be sacrificed (Berwick 2008).
The key issues concerning methodology focus on the question which research is trying to
address, and it is argued for quality improvement that:
“The aim is not to find out ‘whether it works’, as the answer to that question is
almost always ‘yes, sometimes’. The purpose is to establish when, how and why the
intervention works, to unpick the complex relationship between context, content,
application and outcomes” (Walshe 2007, p.58).
This view is supported by others who emphasise that “the research should focus on
understanding why the provision and outcomes of care vary as well as on interventions to
change provision” (Grol et al. 2008, p.74).
It is also important to note that simply utilising the most appropriate methodology does not
guarantee ‘good’ research and certainly the pragmatic approach to quality improvement
places more emphasis on the outcomes of the research than the methodology used. Given
the paucity of literature in the field it was decided that studies using a variety of research
methodologies would be included as limiting the criteria of inclusion would have left even
fewer studies available. No attempt has been made here to judge research quality.

2.3 Is this a new field of research?
The call for quality improvement (and increasingly patient safety) to develop as an “important
new field for health services research” (Grol et al. 2004) is growing (Stevens 2005) –
although, as highlighted by the preceding discussion, it is debatable whether there can ever
be an “optimal methodology” (Grol et al. 2004) for this, given the need for different
disciplines to collaborate.
The traditional development of an academic field can take many years, although some argue
that in the case of healthcare quality improvement, the “social imperative to make health
care better and safer” means that this is happening more quickly in this area (Stevens 2005).
Recent commentaries on the state of quality improvement research have concluded that
perhaps the key issue is that research in this area is not yet fully developed, and may be due
to lack of clarity about the research agenda, as well as research capacity and policy emphasis
(Grol et al. 2008).
There has been some discussion about the concept of ‘improvement science’ as a discipline.
This term was described as “knowledge of general truths or the operation of general laws
especially that obtained and tested through the scientific method (Langley, Nolan, Nolan et
al. 1996) and it is recognised that in order to improve, knowledge about the problem at
hand must be obtained. It is claimed that “Improvement science is now a central component
of healthcare” (Stevens 2007, p.242).
Searches on academic databases using this term yielded very little apart from:
• the description of the Model for Improvement (Langley et al. 1996)
• a framework for improvement science (Clarke, Reed, Wainwright et al. 2004) with five
primary categories:
o user needs focused
o change methods and strategies – includes learning organisation concepts
o knowledge management
o professional subject knowledge and development
o working in context
The paper distinguishes between ‘modernist’ approaches to improvement (technical
rationality) which are considered to be relatively mechanistic, and this discipline which
emphasises plural voices, dynamics of politics and unequal distribution of power amongst
stakeholders, to be more post-modern. Change is also viewed as context specific, with
diffusion of innovation principles being universal but practices local
• a paper using the principles of improvement science to improve access to services for
children with autism (Manning-Courtney 2007)

It is the view of the authors that there is little justification for the development of a new
discipline. The challenges are to integrate the disciplines that already exist, and to reconcile
the current conflicts over methodology and epistemology so that healthcare can continue
to improve in a way that learns from all perspectives rather than the “unhappy tension”
(Berwick 2008, p.1182) that currently exists.
QUESTIONS TO THINK ABOUT:
What do you regard as an appropriate methodology to use when finding out how
effective quality improvement is?
How much do you take context into account when evaluating whether
a particular approach to improvement works?

Two main strands of activity in healthcare quality improvement are evident in the literature,
namely those focusing on clinically-led improvement and those concerned with quality from a
management perspective. Historically, these have often been treated as discrete, parallel
activities within an organisation, with the resulting risk of misaligned objectives, duplication
of effort and a lack of focus on the improving both clinical evidence and the process of care
(Berwick 2008).
The challenge for healthcare organisations is to improve both clinical and managerial quality,
whilst also recognising their interaction. To do this, it is important to understand the roots of
both clinical and industrial improvement so that common themes and interactions
can be identified.
3.1 The history of clinical quality improvement
From a clinical perspective, the development of quality has been heavily influenced by the
medical profession, with its strong roots in a craft-based approach to work, where quality is
seen to be almost solely dependent on the skill of the craftspeople. This craft-based approach
to professional practice vests the control of quality with individual clinicians, largely at an
implicit level, within the overall scope of their professional practice. Consequently, the
competence of individual practitioners is a major contributor to the delivery of high quality
care; something that has traditionally been regulated through controlling entry into the
profession and upholding standards of professional education.
The influence of the craft-based model is apparent in some of the early approaches to quality
evaluation in medical practice:
• in outcome-related morbidity and mortality studies, clinical case conferences and the early
introduction of medical audit, the emphasis was on closed discussions about quality and
standards, typically through applying peer review methods (Harvey 1996)
• as quality became a more prominent feature in healthcare policy, so too more formal
requirements for doctors to engage in quality and audit emerged, for example through the
mandatory introduction of medical audit in the UK in the late 1980s (Department of
Health 1989). For some doctors, these changes were seen as a threat to the traditional
craft-based organisation of medical work, resulting in resistance to medical audit and
distinctions being drawn between audit as an internal, peer review activity and audit as an
external, regulatory mechanism (Shaw 1980).
Throughout these developments, a number of prominent clinicians have challenged
traditional ways of thinking and pioneered developments in medical quality evaluation and
improvement. An excellent review (Kenney 2008) highlights the role of a number of
key individuals:
3. QUALITY IN HEALTHCARE

3.1.1 Codman
As early as 1916, Ernest Codman, a US surgeon, used and published the ‘ends results’
system of auditing surgical care (Codman 1916). He is acknowledged by many as the
founder of outcomes-based patient care. He believed that such information should be made
public so that it could guide patient choice of hospital and physician.
3.1.2 Donabedian
In the 1960s and 70s, Avedis Donabedian went further, presenting quality as a
multidimensional concept, influenced not just by the technical quality of care, but also by
features of the interpersonal relationship between doctor and patient and by the physical
amenities of care (Donabedian 1966). Donabedian also promoted an early systems-based
approach to thinking about medical quality, with his well-known structure-process-outcome
model (see section 3.3.2).
3.1.3 Berwick
Don Berwick has been interested in quality improvement throughout his career as a doctor,
but he spent time in the 1980s studying and working on the application of industrial models
of quality improvement in healthcare, including that of the quality gurus (see section 4.2).
He established the National Demonstration Project on Quality Improvement in Health Care
(more commonly known as the National Demonstration Project – NDP) in 1987 which led to
the development of a group of like-minded people in US healthcare who could see the
possibilities of the application of industrial improvement methods in healthcare.
Berwick has since led the way in calling for a move beyond medical audit towards more
improvement-based approaches to quality (Berwick, Endhoven & Bunker 1992) largely
because of perceived failures to act on the results of audit to achieve meaningful change.
He has published numerous articles and papers, and has an international reputation in this
area (Kenney 2008). Berwick and colleagues have proposed that the medical profession
needs to look beyond its immediate sphere of knowledge and experience in defining and
measuring standards and criteria, towards more general theories of organisational change
and industry-based approaches to quality improvement (Berwick 2008). As such, the narrow
evaluation of practitioner performance needs to be widened to a more patient/client focused
view of quality, with clinicians taking on a so-called new set of clinical skills, incorporating
team working, process analysis, guideline development and collaborative working with
patients, managers and other professional colleagues (Berwick et al. 1992). There was also a
recognition that the medical culture, which discouraged the disclosure of errors, “actually
worked against quality improvement” (Kenney 2008) and thus the link between quality and
safety was made more explicit.

3.1.4 The role of other clinical professions
Other professional groups in healthcare have been less influenced by the craft-based model
of practice, largely as a result of their position in the professional hierarchy relative to
medicine. The nursing profession, for example, had its own pioneer of quality and standards
in the early work of Florence Nightingale. However, early developments in nursing quality
evaluation were largely focused on methods of external monitoring through the
development and application of quality indicators and measurement instruments (Harvey
1996). Such developments were superseded by more practitioner-based methods that
typically involved local teams of practitioners working together to identify and work on topics
for improvement. These approaches had more in common with industry-based approaches
such as quality circles, but often failed to become integrated within overall organisational
systems for quality management (Morrell, Harvey & Kitson 1997).
3.2 Influences on the development of clinical quality
improvement
More recently, developments emanating from the evidence-based medicine movement and
from public inquiries into major healthcare failures have introduced a number of new
concepts to the field of clinical quality, which may have the potential to create better
integration with wider organisational quality initiatives.
3.2.1 Clinical guidelines
The evidence-based practice agenda, with its focus on synthesising existing research through
systematic review methods, has contributed to the development of clinical guidelines,
described as “systematically developed statements to assist practitioner and patient decisions
about appropriate healthcare for specific clinical circumstances” ((Institute for Medicine 1992)
cited in (Duff, Kitson, Seers et al. 1996, p.888)). A key defining attribute of clinical guidelines
is that they should be based on available research evidence (Duff et al. 1996). However,
despite the extent of investment in guideline development, evidence to date suggests that
their impact on actual practice and patient outcomes is variable (Grimshaw, Thomas,
Maclennan et al. 2004), highlighting the challenges and complexities involved in translating
evidence into practice.
3.2.2 Care pathways
Care pathways are another tool that has been applied in healthcare in an attempt to
standardise processes of care delivery. Pathways have been used in different ways, for
example as a way of translating national guidelines into local practice or as a way of mapping
ideal processes for specific care groups. Typically they are presented as structured,
multidisciplinary plans of care designed to support the implementation of clinical guidelines
and protocols, providing guidance about each stage of the management of a patient with a

particular condition, including details of both process and outcome. They aim to improve
continuity and coordination of care and enable more effective resource planning, as well as
providing comparative data on many aspects of quality of care. There are claims they reduce
variation and improve outcomes (Middleton, Barnett & Reeves 2001).
3.2.3 Clinical governance
Clinical governance, defined as the “action, the system or the manner of governing clinical
affairs” (Lugon & Secker-Walker 1999, p.1), developed as an overall strategy within a policy
on quality in the NHS (Department of Health 1989). After a high profile failure of care in a
hospital providing paediatric cardiac surgery services which highlighted organisational
shortcomings (Kennedy 2001), statutory changes were introduced to impose a legal duty of
quality on the chief executives and boards of NHS organisations in the UK, for the first time
creating a corporate responsibility for the quality of clinical care. At a strategic level, this
policy issued a very strong signal that clinical and managerial processes of managing and
improving quality within healthcare organisations needed to be coordinated and led from
board level.
3.3 Defining and assessing healthcare quality
3.3.1 Defining quality
Developments in healthcare quality have been professionally led and reflect the different
traditions and ways of working within the profession. As a consequence, a range of
healthcare definitions and dimensions of quality have developed (see Table 1).

Table 1 - Definitions of healthcare quality
It should be noted that increasingly the terms quality and safety are being used synonymously
and reasons for this may include:
• safety is a pre-requisite for quality: “achieving a high level of safety is an essential first step
in improving the quality of care overall” (Hurtado, Swift & Corrigan 2001)
• there is “substantial ambiguity in the definition of patient safety … the boundary between
safety and quality of care is indistinct”. (Cooper, Sorensen, Anderson et al. 2001, p.2)
• there is a tendency to utilise the most fashionable term; “patient safety has become the
issue ‘du jour’ and so almost everything gets redefined in that” (Cooper et al. 2001, p.8)
• manner in which
practitioner manages
the personal interaction
with the patient
• patient’s own
contribution to care
• amenities of the settings
where care is provided
• facility in access to care
• social distribution of
access
• social distribution of
health improvements
attributable to care
• access to services
• relevance to need
• effectiveness
• equity
• social acceptability,
efficiency and
economy
• performance
• features
• time
• reliability
• durability
• uniformity
• consistency
• serviceability
• aesthetics
• personal
interaction
• flexibility
• harmlessness
• perceived quality
• usability
• safety
• effectiveness
• patient-
centredness
• timeliness
• efficiency
• equity
(Donabedian 1987) (Maxwell 1984)
(Langley et al.
1996)
Institute of Medicine
(Hurtado, Swift &
Corrigan 2001)

The variety of definitions of quality, and the implications of this, have been described by a
number of authors and it is not necessarily the case that some are right and others wrong:
“several formulations are both possible and legitimate, depending on where we are located
in the system of care and on what the nature and extent of our responsibilities are”
(Donabedian 1988). A key paper (Blumenthal 1996) highlights the differences between
definitions of quality from the physician, patient, system and purchaser perspectives and
concludes that the aim of such a debate is “the development of approaches to its definition,
measurement, and management that integrate the perspectives of the many groups that
play a part in the health care system” (Donabedian 1988).
3.3.2 Process and outcome
Outcomes are not necessarily the same as quality. There is some criticism of the use of
outcomes as a major focus of quality, because it can lead to unintended consequences:
“We conclude that the use of outcome data and throughput to judge quality of
care should be diligently avoided. We have shown that when such measures are
used to judge quality of care, they often result in several predictable reactions
ranging from resistance to gaming. This response was predicted by Deming … who
argued that the key to improvement was knowledge, and such knowledge would
emerge from the incorporation of the scientific method into improvement efforts.
For performance management to work it must focus on quality directly—that is on
clinical and institutional process.” (Lilford, Mohammed, Spiegelhalter et al.
2004, p.1151)
Donabedian proposed the structure-process-outcome model of quality of care and which has
been the basis for much work in healthcare quality since its original description in 1980
(Donabedian 1980). This model can also be used to assess performance in a more general
sense where it is assumed that good performance = high quality of care. This model can also
be compared with the models for assessing service quality in general which distinguish
between the process and the outcome (Johnston & Clark 2005).
Structure = the characteristics of the providers of care – the “tools and resources (human,
physical and financial) they have at their disposal … the physical and organizational settings
in which they work” (Donabedian 1980, p.81). This definition is wider however than the
factors of production and includes the organisation of the staff within the healthcare provider
organisation. Structure is essentially relatively stable – it functions to produce care and
influences the kind of care that is provided. Structure is relevant to quality (and therefore to
performance) in that “it increases or decreases the probability of good performance”
(Donabedian 1980, p.82).

Process = a set of activities that go on between clinical practitioners and patients. However,
this process comprises both technical and interpersonal elements:
• technical = appropriate application of professional knowledge and skills to promote
healthcare
• interpersonal = relationship between patients and healthcare professionals, as well as the
contextual aspects of care, including amenities – with satisfaction being the appropriate
“outcome” here (according to Donabedian).
Technical and interpersonal are also linked – e.g. poor consideration of psychosocial issues
can affect technical process performance. Also, maximising technical factors can lead to
conflict with interpersonal care e.g. teaching hospitals (see Flood 1994 for examples). Patients
can be highly satisfied with bad technical care.
Outcome = a change in the patient’s current and future health status – including social and
psychological function as well as patient attitudes (including satisfaction), “health-related
knowledge and health-related behavioural change” (Donabedian 1980, p.83). A broad
definition of health is implied here in order to include all these factors.
The reason given by Donabedian for this distinction between process and outcome (which he
acknowledges is seen by some as pedantic) is that changes in health status “do not serve as
a measure of the quality of care until other sources for such changes have been eliminated,
and one is reasonably sure that previous care is responsible for the change, which can then
truly be called an ‘outcome’” (Donabedian 1980, p.83).
This approach can be summarised as “the structural characteristics of the settings in which
care takes place have a propensity to influence the process of care … changes in the process
of care … will influence the effect of care on health status, broadly defined” (Donabedian
1980, p.84). However, it should be noted that “failures of process do not necessarily result in
poor outcomes” (Crombie & Davies 1998, p.31) because the relationship between health
system effectiveness and improved health outcomes “remains unsettled” (Arah, Klazinga,
Delnoij et al. 2003, p.392). Some studies have however shown a positive relationship
between system effectiveness and outcomes (Lilford et al. 2004, Marshall, Shekelle,
Leatherman et al. 2000).
Do you have an agreed definition of quality in your organisation?
Have you considered the relationship between process and outcome measures of quality?

3.3.3 Assessing performance
Performance within the context of healthcare refers to clinical performance and health
outcomes for individuals and groups of patients, but also to organisational performance and
process data.
“Performance … can encompass measures of clinical process, health outcomes,
safety, access, efficiency, productivity, employee and user satisfaction, and financial
balance, to name but a few” (Davies, Mannion, Jacobs et al. 2007, p.48)
There is likely to be a predominance of hard quantifiable information (Goddard, Mannion &
Smith 1999) and aggregated measures (e.g. star ratings) will often be used, despite the
evidence that they can be misleading (Jacobs, Goddard & Smith 2007)
“Aggregated measures of complex system performance, especially single ratios, can
never capture the “reality” of performance” (Micheli, Mason, Kennerley et al.
2005, p.70).
“Any single performance indicator may be a misleading guide to the overall
performance of an organisation as it covers only one dimension of that
performance, and concentration on one aspect of care may produce perverse
incentives to ignore other aspects of performance. If performance indicators are to
be used, it is important that they cover the full range of outputs and inputs for the
sector in question “(Giuffrida, Gravelle & Roland 1999, p.97).
There are a variety of perspectives that can be used when assessing healthcare organisational
performance, but it can be argued that some factors are actually outside the control of the
organisation. External influences include the fact that care can be provided in other
organisational settings before or after the event being studied, the patient themselves can
influence performance through, for example, compliance with therapy, and there are the
inevitable constraints and incentives imposed on the organisation by the environment (e.g.
market competition, regulation).
• “Organizations protest strongly if they think that measures of their patients’ outcomes did
not sufficiently consider the severity of illness” (Flood 1994, p.391)
• “While health outcome should be related to crude rates of adverse events in the
population, performance indicators should relate only to those aspects of care that can be
altered by the staff whose performance is being measured” (Giuffrida et al. 1999, p.97)

• This view is supported by empirical evidence: a number of studies have shown that “a
non-trivial proportion of the variation in the indicators used in the performance assessment
system was associated with factors that are not under managerial control”
• A large proportion of variation in organisational performance has also been shown to be
unexplained; 70-80% in one study (Jacobs, Martin, Goddard et al. 2006).
3.3.4 Balancing elements of performance
At a strategic level, many organisations use a so-called balanced scorecard approach to
performance measurement to ensure that overall performance is judged against a set of key
indicators (financial, internal process, customer and learning and growth measures), thus
enabling a more complete picture of quality to be obtained. The challenge for organisations
is for leaders to enable balance between the elements, and to ensure that performance
measurement and assessment supports the strategy of the organisation.
In practice, there is a danger that some sets of performance metrics get prioritised above
others, particularly where external inspection and ranking of organisational performance
takes place, as is the case, for example, with many national, government-led performance
management systems. Within healthcare this issue is exacerbated by other debates about
what constitutes performance and quality, depending on whether the clinical or managerial
perspective is dominant (see section 2.4.3).
Focusing on one dimension of quality – in this case, reconfiguration and meeting
government performance targets – can lead to serious consequences for patients.

Balancing clinical and organisational priorities: A case of focusing on
performance targets at the expense of quality of care
In the English National Health Service (NHS), as in many other healthcare systems across
the world, explicit performance monitoring and management by central government is
now commonplace. NHS organisations are subject to an annual performance rating,
determined by a composite measure of a number of key performance indicators,
including financial and waiting time targets, alongside broader measures of performance
such as staff and patient survey data.
One hospital (trust) providing acute services was subject to a special investigation by the
external regulator for healthcare standards in England and Wales (the Healthcare
Commission) following two outbreaks of Clostridium difficile infection, each of which
resulted in nineteen patient deaths. The investigation report (Healthcare Commission
2006b) highlighted the failure of senior managers to prioritise infection control, as
illustrated by their decision not to set up isolation facilities for infected patients, despite
the advice of infection control specialists. This decision was attributed to the
management’s concern at the cost of establishing an isolation ward and the knock-on
effect this would have on the achievement of their key performance targets. The
investigation team were particularly critical at the time of the second outbreak of
infection, that the organisation’s leaders failed to learn from the first outbreak and
remained focused on other targets at the expense of managing clinical risk. This is
reflected in the following remarks made in the official report of the investigation.
“Following the first major outbreak, the trust’s leaders chose to implement some changes
but none that might compromise their strategic objectives. They failed to bring the
second outbreak quickly under control because they were too focused on the
reconfiguration of services and the meeting of the Government’s targets, and
insufficiently focused on the management of clinical risk. It took the involvement of the
Department of Health and national publicity to change their perspective ….The failure of
the trust to implement the lessons from the first outbreak, combined with a dysfunctional
system for governance which did not incorporate the assessment of risk into its decision
making, nor make the board aware of the significance of the outbreaks, meant that it
took longer than it should to control the second outbreak. There was a serious failing at
the highest levels of the trust to give priority to the management of the second major
outbreak. The trust followed neither the advice of its own infection control team nor that
of the Health Protection Agency. We are clear that this failing is on the part of the trust
and its incorrect interpretation of national priorities. It is our conclusion that the approach
taken by the trust compromised the control of infection and hence the safety of patients.
This was a significant failing, and we would reiterate to NHS boards that the safety of
patients is not to be compromised under any circumstances.” (Healthcare
Commission 2006b, p.9)

A review of investigations carried out in organisations where there had been significant
failures in terms of patient care (Healthcare Commission 2008) showed that underlying
themes included:
• Leadership – especially the board which “must also maintain their focus on clinical quality
throughout” (Healthcare Commission 2008, p.8)
• Management and targets – which is argued to have always been part of managing
healthcare organisations
• Governance and the use of information
• The impact of organisational change, especially mergers.
It is therefore clear that performance is influenced by a number of factors, but that “it is not
acceptable – nor is it necessary – for the safety of patients to be compromised by any other
objectives, no matter how compelling these may seem” (Healthcare Commission 2008, p.9).
What measures are used to assess performance in terms of quality in your organisation?
What elements of performance need to be balanced when quality is being assessed?

4.1 Quality improvement in industry
The academic field of study that is quality management/improvement in general (as opposed
to clinical quality improvement) developed from the field of production/operations
management, which is itself characterised by an empirical focus (Voss 1995). However, the
concept of “quality” and its management is much older, with its formalisation sometimes
being attributed to the work of Shewhart on SPC in the 1930s (Shewhart 1931).
As the study of quality as a concept and the management of quality within organisations has
developed, a number of academic disciplines have made contributions – including services
marketing, organisation studies, human resource management and organisational behaviour,
especially change management. The term industrial is used here to reflect the fact that these
approaches were first developed and applied within the manufacturing industry, as well as to
distinguish them from approaches to clinical quality improvement. However they are now
being applied in healthcare (Young, Brailsford, Connell et al. 2004) as later sections of this
report will demonstrate.
The appeal of the term quality may be that “it can be used to legitimize all sorts of measures
and changes in the name of a self-evident good” (Wilkinson & Willmott 1995). However, the
diverse meanings of the term make it “an elusive topic of study” (Wilkinson &
Willmott 1995).
The historical perspective is important and an understanding of the geography and
development of industry after the Second World War are relevant in this context. Alternative
views describe the eras of quality management from inspection through quality control and
quality assurance to TQM (Garvin 1988), or by a chronology of events from the Hawthorne
studies to 1990 (Martinez-Lorente, Dewhurst & Dale 1998). This review will focus on the key
figures in the development of quality improvement and the way in which their ideas have
been adapted and adopted, with a particular focus on healthcare.
4. INDUSTRIAL QUALITY
IMPROVEMENT

4.2 The quality gurus
There are a variety of individuals who have influenced the development of quality
management and they are often referred to as gurus although there is no definitive list of
who might qualify for such a term, and there are probably more influential Japanese gurus
than those commonly mentioned. There is however no doubt that the gurus would include
the following:
4.2.1 Deming
W E Deming was an American who first went to Japan in 1947 to join a statistical mission
documenting the “level of devastation from the war” (Davids 1999). His ideas were adopted
by the Japanese and the subsequent success of Japanese manufacturing was attributed to
the implementation of these ideas, with the Japanese eventually creating a Deming prize for
achievement in product quality.
Deming had been influenced by Shewhart and he was aware of the limits of numbers:
“knowing that numbers don’t give you the answers, only the questions that need to be
asked” (Gabor 1990). Deming developed a 14-point approach (Deming 1986) for his
management philosophy for improving quality and changing organisational culture which is
shown in Table 2.

Table 2 - Deming’s 14 points
Create constancy of purpose toward improvement of product and service, with the aim to
become competitive and to stay in business, and to provide jobs
Adopt the new philosophy. We are in a new economic age. Western management must
awaken to the challenge, must learn their responsibilities, and take on leadership for change
Cease dependence on inspection to achieve quality. Eliminate the need for inspection on a
mass basis by building quality into the product in the first place
End the practice of awarding business on the basis of price tag. Instead, minimise total
cost. Move toward a single supplier for any one item, on a long-term relationship of loyalty
and trust
Improve constantly and forever the system of production and service, to improve quality
and productivity, and thus constantly decrease costs
Institute training on the job
Institute leadership. The aim of supervision should be to help people and machines and
gadgets to do a better job. Supervision of management is in need of overhaul, as well as
supervision of production workers
Drive out fear, so that everyone may work effectively for the company
Break down barriers between departments. People in research, design, sales, and
production must work as a team, to foresee problems of production and in use that may
be encountered with the product or service
Eliminate slogans, exhortations, and targets for the work force asking for zero defects and
new levels of productivity. Such exhortations only create adversarial relationships, as the
bulk of the causes of low quality and low productivity belong to the system and thus lie
beyond the power of the work force
Eliminate work standards (quotas) on the factory floor. Substitute leadership
Eliminate management by objective. Eliminate management by numbers, numerical goals
Substitute leadership
Remove barriers that rob the hourly worker of his right to pride of workmanship. The
responsibility of supervisors must be changed from sheer numbers to quality
Remove barriers that rob people in management and in engineering of their right to pride
of workmanship. This means, inter alia, abolishment of the annual or merit rating and of
management by objective
Institute a vigorous program of education and self-improvement
Put everybody in the company to work to accomplish the transformation. The
transformation is everybody’s job

He was also responsible for developing the concept of the PDCA (plan-do-check-action)
cycle. As his work developed, he identified the seven “deadly diseases” which he used to
criticise Western management and organisational practices. His final contribution was to
develop the Deming system of profound knowledge, which is still marketed today but
appears to have had relatively less impact than his “14 points” which have undoubtedly been
influential in challenging leaders to “transform the organisation around the concept of
continuous improvement” (Vinzant & Vinzant 1999). However it should be noted that he did
not ever use the term Total Quality Management (TQM) and made clear his low regard for it
(Petersen 1999). It is also argued that his ideas have influenced the development of the field
of strategic management both directly and indirectly (Vinzant & Vinzant 1999).
4.2.2 Juran
In the 1950s Joseph Juran, a member of the team implementing statistical process control
(SPC) at the Western Electric Hawthorne works in the 1920s, also went to Japan. He had
earlier published his book The Quality Control Handbook (Juran 1951) and he focused on the
managerial aspects of implementing quality. His approach can be summarised as quality,
through a reduction in statistical variation, improves productivity and competitive position..
He promoted a trilogy of quality planning, quality control and quality improvement and
maintained that providing customer satisfaction must be the chief operating goal (Nielsen,
Merry, Schyve et al. 2004).
4.2.3 Crosby
Philip Crosby was an American management consultant whose philosophy is summarised as
higher quality reduces costs and raises profit, and who defined quality as ‘conformance to
requirements’. He too had 14 steps to quality and his ideas were very appealing to both
manufacturing and service organisations, but can be viewed as lacking substance. He is best
known for the concepts of do it right first time and zero defects and believed that
management had to set the tone for quality within an organisation.
4.2.4 Feigenbaum
Armand Feigenbaum was the General Electric (GE) chief of manufacturing in the 1960s and
he defined quality as a way of managing (rather than a series of technical projects) and the
responsibility of everyone. His major contribution was the categorisation of quality costs into:
appraisal, prevention and failure, and his insistence that management and leadership are
essential for quality improvement. He believed that cost reduction was a result of total
quality control. He was the first to use the term total in relation to quality management.
His work has been described as relevant to healthcare by Don Berwick (Berwick 1989).

4.2.5 Differences and similarities
From these four - and other - gurus it is very difficult to define an over-arching philosophy.
There has been considerable debate about the similarities and differences between the
various gurus (Dale 2003) - the differences are ascribed to the focus of their approach (Dale
2003). It is argued that the ‘golden thread’ through all their approaches is adopting quality as
a fundamental business strategy permeating the culture of the whole organisation (McBryde
1986). The key points are summarised by (Bendell, Penson & Carr 1995) as:
• management commitment and employee awareness are essential (Deming)
• actions need to be planned and prioritised (Juran)
• teamwork plays a vital part (Ishikawa – who pioneered the quality circle concept)
• tools are needed (e.g. seven quality control tools promoted by Ishikawa)
• management tools/approaches will also be needed (Feigenbaum)
• customer focus (Deming)
Some authors argue that whilst some of the gurus were working in Japan to pursue
“unending improvement and innovation through mobilising the entire workforce in pursuit
of these aims”, the West was focusing on “conformance to standards, control of processes
and command of personnel” (Wright 1997). It is only from the 1980s onwards that the West
has been working to cross this divide.
“Can the gurus’ concepts cure healthcare?” (Nielsen et al. 2004)
This paper examined the state of quality in healthcare in the US, then asking four experts
to surmise what four quality “gurus” might say. Their conclusions were that:
• Crosby would continue to emphasise the role of leadership in pursuing zero defects
• Deming would continue to emphasise transformation (as he did in the 14th of his 14
points – see Table 2) whilst being disappointed at the reactive behaviour of healthcare
organisations and individuals with “far too little pursuit of constant improvement”
(Nielsen et al. 2004)
• Feigenbaum would focus on clearer identification of the customer and the application
of evidence based medicine
• Juran’s emphasis would be on building quality into processes from the start (what he
termed ‘quality planning’).

4.3 Total Quality Management
Other terminology that is also used to describe quality improvement includes Total Quality
Management (TQM), Continuous Quality Improvement (CQI) (McLaughlin & Simpson 1999)
and Total Quality Improvement (TQI) (Iles & Sutherland 2001). Such terms appear to be
interchangeable in usage (although whether their meaning is the same is the subject of some
debate (Larson & Muller 2002/3)). The link between quality management and TQM has been
the subject of much speculation (Dahlgaard 1999).
It may be that “[TQM] has become mainly a banner under which a potpourri of essentially
unrelated organisational changes are undertaken” (Hackman & Wageman 1995). TQM is
considered by some to be particularly attractive in practice because it offers “a unified set of
principles which can guide managers through the numerous choices [open to them] or might
even make choosing unnecessary” (Huczynski 1993).
This is not the appropriate place to provide a full review of what TQM is, or how it has been
implemented in both the US and the UK. Suffice to say, there is significant disagreement
about how it can be defined, what it constitutes and whether it was simply a fad. However,
TQM is usually described as a “management philosophy and business strategy” (Iles and
Sutherland, 2001 p.48) and the common themes may be summarised as (Berwick et al.
1992, Hackman & Wageman 1995):
• organisational success depends on meeting customer needs, including internal customers
• quality is an effect caused by the processes within the organisation which are complex but
understandable
• most human beings engaged in work are intrinsically motivated to try hard and do well
• simple statistical methods, linked with careful data collection, can yield powerful insights
into the causes of problems within processes
Thus, TQM can be regarded as including many of the approaches/tools described in
this review.

4.4 Applying approaches from manufacturing in the
service sector
Until the 1980s most of the emphasis on quality improvement, and most of the empirical
utilisation of the associated tools, was within manufacturing industry. However, the field of
service quality developed with input from marketing academics – led from Scandinavia
(Groonroos 1984) and the US (Berry, Zeithaml & Parasuraman 1985). One of the most
commonly utilised tools from this period is the SERVQUAL questionnaire (Parasuraman,
Zeithaml & Berry 1988). The concept of the ‘moment of truth’ and an emphasis on service
recovery were also prominent. This development was also underpinned by the increasing
economic importance of the service sector in the West.
The nature of service organisations as more people-intensive than much of manufacturing led
to increasing interest in the role of people in quality improvement and to a tension between
‘hard’ (systems) approaches and ‘soft’ (people/culture) issues (Wilkinson 1992). This was also
driven by concerns about the promotion of TQM as a universal panacea, regardless of
context, and of its disinclination to “refer to previous management literature – or, indeed, to
reference anything outside of the quality management field” (Wilkinson & Willmott 1995).
The gradual emergence of a field comprised largely of prescriptive research was also
influential. Change management/ organisational behaviour perspectives became more
prominent (Hackman & Wageman 1995) with summaries of such studies being produced
(Webb 1995).
4.5 Quality awards and business excellence
Achievements in the area of quality improvement have been increasingly the subject of
national awards. The Deming Application Prize (Japan) led to the development of the
Malcolm Baldrige National Quality Award (USA) and then in Europe to the European
Foundation for Quality Management (EFQM) Award/ Excellence Model (Europe), with its
associated national and sector-specific derivatives. Quality was increasingly assessed by
organisations themselves as a means of improvement: what is termed self-assessment
(European Foundation for Quality Management 1999). These models attempted to integrate
the hard and soft factors, and the term quality appeared to be replaced by ‘excellence’.

4.6 Business Process Re-engineering
The Business Process Reengineering (BPR) approach to improvement was first described in the
early 1990s (Hammer & Champy 1993) to describe the redesign of business processes. It can
be summarised as having a series of underpinning concepts (Iles & Sutherland 2001):
• organisations should be organised around key processes rather than specialist
functions
• narrow specialists should be replaced by multi-skilled workers, often working in self
managed teams
• BPR requires radical rethinking, not incremental improvement
• the direction for this rethinking comes from top management
There is a relatively substantial evidence base about the success (or otherwise) of BPR but it is
beset by the same methodological issues as TQM, and as improvement initiatives in general
and many initiatives reported have only considered the re-engineering of a single process
rather than the whole organisation. Reviews of the key initiatives within the NHS (McNulty &
Ferlie 2002) argue there is conflict between this revolutionary approach and the belief that
consideration of context is important in securing organisational change (Buchanan 1997).
Experience of BPR has shown that a purely top-down imposed approach is unlikely to
succeed (Iles & Sutherland 2001).
Do you think that it is helpful to focus improvement efforts around a particular guru
or label?
To what extent might the fact that healthcare is a service organisation make a difference
to how quality improvement is carried out?

This section covers the major approaches to quality improvement that have been used in
healthcare. Many of these have their roots in the work of the quality gurus (section 4.2) and
some draw on similar principles to those of TQM (section 4.3), although the variety of
definitions of TQM have led to a lack of clarity about exactly what constitutes many of
these approaches.
We draw a distinction here between:
• Approaches: something promoted as a way of working – which may include a variety of
different tools, sometimes to be used at specific points along a methodological
‘roadmap’... They may be applied to the organisational system as a whole, and may also
be applied to systems spanning organisations. Some people may come to regard an
approach as merely a fad or label.
• Tools: techniques used for improvement which may be used alone, or in combination with
others. More than one approach may suggest the use of the same tool.
There is also debate about whether these approaches are really new, or just repackaging of
existing concepts: “Techniques touted as today’s “core competencies” all too often become
tomorrow’s failed programs. However, digging a little deeper shows that many such
techniques have useful content. It should come as little surprise then that many currently
popular innovations are little more than old ideas with new acronyms. The core disciplines
associated with statistical process control and variance reduction become six-sigma”
(Repenning & Sterman 2001, p.64). This review will attempt to identify where this
has occurred.
5. QUALITY IMPROVEMENT
APPROACHES
Are tools useful on their own?
There is considerable debate about whether tools are of much value on their own, or
whether they need to be deployed as part of a wider improvement approach across the
organisation. Some argue that “teaching tools very rarely results in a change to the
system” (Seddon 2005b) and certainly the notion that it is system issues which determine
quality has a long history, from Deming (see section 4.2.1) to Don Berwick’s application of
these principles in healthcare (see section 3.1.3): “The opportunities for improvement of
quality lie in improved design of systems … I believe that this is also true of healthcare
systems” (Kenney 2008)

Four aspects of each approach are considered:
• outline of the approach
• how the approach fits with others
• where the approach has been used in healthcare
• outcomes that have been reported.
5.1 The Plan-Do-Study-Act model
5.1.1 Outline of the approach
The plan-do-study-act (PDSA) model was developed by Deming (Deming 1986) – and termed
by him the Shewhart cycle (Dale 2003). Deming’s initial terminology was plan-do-check-act
(PDCA), but he later changed this to PDSA to better reflect his thinking. PDSA is the term
generally used in healthcare and which will therefore be used here.
The use of the PDSA is to improve processes and therefore outcomes (Deming 1986). Some
view it simply as a problem-solving methodology (Pescod 1994), and others as part of a
continuous improvement approach (Dale 2003). PDSA is very clearly a continuous
improvement approach, rather than a breakthrough approach, and this may be in conflict
with current management styles or past experience of improvement (Silvester, Lendon, Bevan
et al. 2004).
PDSA appears to have been first formally proposed in healthcare by (Langley et al. 1996). The
term “model for improvement” (Langley et al. 1996) (see Figure 1) is now also commonly
used, and the text by Langley is regarded as the basis for much of what is now applied in
healthcare in both the US and the UK. This links the PDSA cycle with three key questions
(see Figure 1) and it is argued that it parallels learning developments and processes in
education (Kolb 1984, Schon 1988).

Figure 1 – The Model for Improvement (Langley et al. 1996)
The use of this model over time to achieve improvement is often referred to as rapid-cycle
improvement (Horton 2004), where a number of small PDSA cycles take place one after the
other (see Figure 2).
Figure 2 - The Model for Improvement used over time (Schon 1988)

5.1.2 How the approach fits with others
There is no reference in the key text (Langley et al. 1996) to any other tools being a part of
this approach. However, the notion of a change concept is relevant here. The model for
improvement has developed into an approach rather than a tool and one which can be used
as an overarching framework for other tools to be utilised.
Change Concepts …
… can be defined as a “general idea, with proven merit and sound scientific or logical
foundation, that can stimulate specific ideas for changes that lead to improvement” (Nolan
& Schall 1996). They relate to the third question in the model – ‘what changes can we
make that will result in an improvement?’ and are generally good ideas rather than specific
ideas that are ready to be implemented, although there is a view that change concepts
“can be catalogued and made generally available to aid improvement work” (Plsek 1999).
A future development may be to grade the change concepts according to the evidence
that underpins them (Plsek 1999), and it is argued that this lack of evidence to date has
“unnecessarily allowed critics of rapid cycle improvement to label the entire effort as
unscientific (which it is not)” (Plsek 1999). (Langley et al. 1996) describe 70 change
concepts grouped into the categories of:
• eliminate waste
• improve work flow
• optimise inventory
• change the work environment
• enhance the product/customer relationship
• manage time
• manage variation
• design systems to avoid mistakes
• focus on a product/service

5.1.3 Where the approach has been used in healthcare:
the collaborative approach
The improvement collaborative methodology was developed by the Institute of Healthcare
Improvement in the US and is known as the ‘breakthrough’ model (Kilo 1998). This
approach has since been adopted by a number of different countries in Europe, including
England, Scotland, Wales, Sweden and France, to set up national system re-design initiatives
for services such as cancer and coronary heart disease. The breakthrough improvement
collaborative methodology derives from continuous quality improvement theories, combined
with more general organisational theories of initiating, implementing, monitoring and
evaluating change (i.e. the model for improvement). The approach involves a number of
teams with a common interest (e.g. improving cancer services) working together in a
structured way with a group of national experts for a period of around 12-18 months to
plan, implement and monitor improvements in care. The basic building blocks of the
approach include:
• generation of change concepts by an expert panel, based on existing evidence of best
practice
• rapid cycle improvement, using the plan-do-study-act cycle
• a series of national learning events, followed by periods of local action and
implementation
• ongoing communication and support from a team of national (and international) experts
through regular conference calls and e-mail discussion groups
• regular feedback and comparison of data at a local and national level

Cancer Services Collaborative in England
The National Health Service (NHS) in England established a Cancer Services Collaborative
in 1999, to improve the system of care delivery for patients with suspected or diagnosed
cancer. Based on the IHI methodology, the Cancer Services Collaborative was
underpinned by principles of system re-design and set out to challenge the way in which
cancer services were organised around discrete departments and a perceived lack of
awareness of the whole system of care. Since 1999, the initiative has progressed in three
distinct phases. In each phase, the focus has been on the process of patient care from
the point of referral through to diagnosis and treatment. The two key elements of
redesign that have been introduced through the Collaborative focus on mapping the
patient journey and addressing issues of capacity and demand.
Phase 1 ran from 1999 to 2001 and was set up as a pilot to identify what was actually
happening to patients and what might be possible in terms of service re-design. 9 pilots
in 8 of the 34 cancer networks3 received central funding (around £500,000 per pilot site)
to initiate improvements in one of five tumour group areas, namely, breast, lung, ovarian,
prostate and colorectal cancer. In total, 51 clinical project teams were set up. Phase I of
the Collaborative was evaluated by a research team from the University of Birmingham.
The results of this evaluation study are discussed in section 5.1.4.
Phase 2 of the Collaborative took place from 2001 to 2003. The aim of this phase was
to spread the Collaborative approach and methodology to all 34 of the cancer networks
in England in order to establish what was possible and to identify examples of good
practice. Further project teams were established and mandatory reporting of data on
waiting times was introduced (Department of Health 2000), as part of the overall NHS
performance management system. The establishment of the waiting time targets to be
monitored was itself influenced by the findings from phase 1 of the Collaborative
programme. By March 2003, the Modernisation Agency (MA) reported that through the
Collaborative, they had worked with half of the 1600 specialist cancer teams in England.
28,000 changes had been tested (using the PDSA cycle), resulting in at least 2,800
improvements for cancer patients across England, including improved patient experiences,
shorter waiting times, and more choice about treatment (NHS Modernisation
Agency 2003).
Phase 3 of the collaborative was launched in March 2003 as the Cancer Services
Collaborative – Improvement Partnership, again supported by central NHS funds
(guaranteed until 2006). This phase focused on implementation and took a wider focus
on all forms of cancer, alongside supporting services such as primary care, palliative care,
radiotherapy, radiology, chemotherapy, endoscopy services, and patient and care
experiences. As part of the developments, there was an explicit focus on integrating the
work of primary care in the redesign of services.
3. Following the publication of the Calman-Hine report on cancer services in 1995, 34 cancer networks were established throughout
England to facilitate service planning and co-ordination of care across institutional boundaries.

5.1.4 Outcomes that have been reported
Although the methodology of improvement collaboratives has been adopted on a wide scale
by health services across the world, there is little empirical evidence to suggest the approach
is more cost-effective than other quality improvement methods (Øvretveit, Bate & Cleary
2002). A number of formal evaluations of improvement collaboratives have been reported.
These demonstrate the impact of specific collaboratives on related outcomes such as:
• reduced infection rates in neonatal intensive care (Horbar, Rogowski & Plsek 2001)
• reduced caesarean section rates (Flamm, Berwick & Kabcenell 1998)
• reduced rates of adverse drug events (Leape, Kabcenell & Gandhi 2000).
However, questions have been raised at to whether the impact of collaboratives is as great as
expected and significant differences in outcomes have been observed between different
collaboratives and between different teams within the same collaborative (Bate, Robert &
McLeod 2002).
Use of the PDSA model with NHS collaboratives has been reported (Kerr, Bevan, Gowland et
al. 2002) to:
• facilitate the use of teamwork to make improvements
• provide a framework for the application of effective measurement and use of
improvement tools
• encourage planning to be based on evidence-based theory
• emphasise and encourage learning
• provide a way to empower people to take action
• continue to create the will for improvement as tests of change are completed
The main evaluation in relation to the Cancer Service Collaborative in England (Robert,
McLeod & Ham 2003) collected data from a wide range of sources, including collaborative
participants and stakeholders, observation of meetings and conference calls, documentary
evidence, cost data and patient level data on waiting times and booking. In terms of the
impact of the collaborative, the views of staff were positive, especially in relation to changes
in attitudes towards improvement, staff empowerment and the provision of time and training
opportunities. However, experiences were seen to be highly context specific, with notable
variations across and within programme sites. Most participants found the collaborative
methodology useful, although some aspects of the approach were preferred over others.
Participants were particularly negative about the volume of data monitoring and reporting
required and generally raised questions about the processes of data collection and
measurement, for example, in terms of the utility and validity of the measures used.

For some participants, the collaborative approach and the way it was presented through the
training workshops was seen to be too theoretical, with too much jargon. Others felt the
methodology was too prescriptive. This led the researchers to conclude that there was a very
difficult balancing act to perform to get the right mix between the top-down, centralised
structure of the programme and bottom up, local control of implementation (Robert et
al. 2003).
In attempting to explain the variation in findings, the researchers highlight a number of
process issues (defined as the key levers for change) that appeared to influence the outcome
of the collaborative at a project team level. These include:
• the adoption of a patient perspective
• the availability of dedicated time
• opportunities for training
• facilitation of multi-disciplinary working
• staff empowerment
• opportunities for networking (Robert et al. 2003)
In turn, these were dependent on local leadership, the presence of clinical champions and
wider organisational support for the collaborative. In their overall conclusions on the cancer
services collaborative, the researchers highlight the importance of the so-called levers for
change, alongside a receptive organisational context. Also the need to review measurement
and reporting mechanisms and requirements within the collaborative methodology and to
build in more preparatory work and the development of greater local ownership of
the collaborative.
Another study which examined the effectiveness of collaboratives and the factors influencing
this (Øvretveit et al. 2002) held structured discussions among researchers involved in
evaluating collaboratives to consider three questions of effectiveness:
• are collaboratives effective or cost-effective?
• are the results sustained?
• can they be made more effective?

In response to the first question, the researchers noted that individual collaboratives had
demonstrated an impact, but concluded that there is currently insufficient evidence to
determine whether collaboratives are more or less cost-effective in making and spreading
improvements than other approaches. By comparison to other approaches, collaboratives
were seen to be expensive, because of the costs involved in holding several large-scale
national meetings. Consequently, the issue of spread and sustainability was seen to be
particularly important to justify the costs associated with collaboratives. However, longer-term
evaluations to assess spread and sustainability are not yet available.
Features of collaboratives that were thought to be critical determinants of their effectiveness
were examined by drawing on expert opinion and experiences of collaborative leaders
(Wilson, Berwick & Cleary 2003). Seven key features were identified, and important
characteristics of each of these dimensions are summarised in Table 3.

Table 3 - Determinants of the effectiveness of improvement collaboratives
(Wilson et al. 2003)
Key Component Common variations Critical dimensions
Sponsorship • government
• professional organisations
• independent quality
organisations
• non-profit and for-profit
healthcare
• credibility of sponsor
• perceived alignment with
participants’ values and aims
• perceived gain for sponsors
Topic • broad or narrow
• complex or simple
• alignment with local and
national priorities
• consistency with local or
national priorities
• complexity
• practical relevance
• relative advantage
• compatibility with current
practices
Ideas for
improvements
• inclusion or exclusion of practical
knowledge
• national or local experts
• internal or external generation
of knowledge
• generic ideas for change or
specific changes
• perceived validity of knowledge
• applicability of knowledge
locally
• social distance between
collaborative leaders and
participants
• amount of practical knowledge
Participants • mandated or voluntary
• pay vs. no pay
• screening for previous
improvement experience and
readiness for change
• multidisciplinary
• inclusion of a medical clinician
• team size
• inclusion of team members
directly affected by the change
• readiness for change
• ability to work as a team
• team size
• heterogeneity of quality
improvement experience
Senior leadership
support
• variable support in form of
resources and mission
• praising and acknowledging
improvement work
• support and resources for
project
Preliminary work • developing understanding of
local system and its performance
• occasional addition of extra
learning sessions
• knowledge of local performance
Learning about and
making
improvements
• variable meetings for learning
• methods for sharing; strong vs.
weak sharing
• reporting
• rating system
• collaborative size
• use of improvement model
• variable social interaction
• different support mechanisms
• number of face-to-face
meetings
• total amount of inter-team
contact
• methods of information
sharing used
• improvement models/strategies
used
• ways of sharing good
performance
• strength of social and
information networks
• amount of central support

The findings from the research that have been reported to date highlight that collaboratives
are complex, multi-faceted interventions. As such, it is unsurprising that there does not seem
to be a right way of implementing a collaborative and that experience and outcomes vary
considerably both across and within collaboratives. The key point seems to be tailoring
implementation to match the specific healthcare, political or organisational context,
depending on the particular collaborative and the reasons for its implementation. This
requires some flexibility in the approach taken to designing and conducting improvement
collaboratives to enable them to be more context-specific. Of particular importance seems to
be an ability to get the right balance between top-down initiation and leadership of the
collaborative and bottom-up ownership and commitment to the collaborative process.
Several evaluations highlight useful pointers that seem to be important in terms of
maximising the effectiveness of collaboratives. These relate to the focus of the collaborative,
the participants and their host organisation and the style and method of implementing the
collaborative (Table 4).
Table 4 - Challenges for successful improvement collaboratives
(Øvretveit et al. 2002)
Key Area Challenge
Purpose and preparation Choosing the right subject
Ensuring participants define their objectives and
assess their capacity to benefit from the
collaborative
Defining roles and making clear what is expected
Ensuring team building and preparation by teams
for the collaborative
Collaborative organisation and
meetings
Enabling mutual learning rather than carrying out
teaching
Motivating and empowering teams
Ensuring teams have measurable and achievable
targets
Equipping teams to deal with data and change
challenges
Post-collaborative transition Learning and planning for sustaining improvements
Planning and learning for spread

Recent proposals and studies (Bate & Robert 2002) have suggested that rather than a
collaborative approach, a community approach which better enables knowledge transfer
would enable more effective learning and development, based around the concept of
communities of practice (Wenger & Snyder 2000). Improvement collaboratives are based on
many of the concepts of knowledge management (cross-boundary knowledge transfer,
communal exchange of knowledge etc.), but it is argued (Bate & Robert 2002) that their
impact could be strengthened if these concepts were developed further. In particular, they
propose a more organic model of collaboratives, with less emphasis on rules, regulations and
reporting relationships and a greater focus on people processes. In practice this would
involve a greater emphasis on sharing tacit knowledge (know-how) alongside explicit
knowledge (know-what), the creation, as well as the application, of knowledge, the
development of more effective networks and the establishment of communities of practice,
as opposed to time-limited project teams.
5.2 Statistical Process Control
The roots of Statistical Process Control (SPC) can be traced to work in the 1920s in Bell
Laboratories (Shewhart 1931), where Shewhart sought to identify the difference between
natural variation – termed ‘common cause’ - and that which could be controlled – ‘special’ or
‘assignable’ cause variation. Processes that exhibited only common cause variation were said
to be in statistical control. One of the many significant features of this work, which is still
used in basically the same form today, is “the management of quality acquired a scientific
and statistical foundation” (Kolesar 1993).
The central tool is the control chart, which adds process variation bounds (typically at ±2 or 3
standard deviations) to the simple time-sequence of a run chart. These bounds are referred to
as upper and lower control limits. Target or specification limits are usually not plotted when
the charts are used by process operators to avoid compromising achievable performance
(Pyzdek 2003a). As an approach, SPC uses control charts (typically in pairs recording the
evolution of both level and variation over time) to identify potential for process improvement
(eliminating special causes and reducing common cause variation) and to monitor a process
in real time in order to detect deteriorating performance (importantly seeking to identify
trends and so pre-empt unacceptable ‘out of control’ performance).
Are there areas where the PDSA approach could be used in your organisation?
Where might a collaborative approach be beneficial in improving healthcare?

Figure 3 - Example c-chart using number of emergency admissions on consecutive
Mondays (Mohammed, Worthington & Woodall 2008)
Aside from the use that was made of SPC by Deming etc, the 1980s saw a revival in its use
as TQM concepts developed from the work of the original quality gurus (Dale 2003). It is
usually regarded as a tool for measurement (Plsek 1999) within a wider approach, rather
than as an overall approach in it own right. For example:
• it is an important part of the final (control) stage of the Six Sigma Define-Measure-
Analyse-Improve-Control (DMAIC) roadmap (see section 5.3.1)
• it provides a key problem-identification tool at the start of the Decalogue approach to the
Theory of Constraints (ToC) (see section 5.5.1)
• it can also support the analysis and interpretation of data, for example as part of the check
or study stage of the PDSA cycle
Though use of SPC has grown at a relatively rapid rate, growth may have been even more
rapid if SPC did not challenge many of the fundamental assumptions in healthcare about
how to deliver improvement - in the same way that Deming’s approach does (Mohammed
2004) - in particular the focus on short-term cost reduction. In another paper the same
author suggests that SPC is superior to tools more commonly used to analyse variation in
healthcare because it provides guidance for action: “we should seriously question the role of
conventional statistical analysis in clinical governance” (Mohammed, Cheng, Rouse
et al. 2001).

5.2.3 Where the approach has been used in healthcare
The recognition of the importance of variation in healthcare (e.g. Haraden & Resar 2004,
Proudlove, Black & Fletcher 2007, Walley, Silvester, Steyn et al. 2006b), has naturally led to an
interest in SPC (Berwick 1991).
• a systematic review of the use of SPC in healthcare (Thor, Lundberg, Ask et al. 2007)
found a wide range of applications, from clinical and resource management through
biomedical variables (including by self-managing patients) to patient experience. The
earliest papers they identified were US applications in 1990 and from 1998 elsewhere
• clinical applications, including laboratory results, medication errors and application at
individual patient level are discussed by (Plsek 1999)
• a systematic review of the use of SPC in patient monitoring concluded that the four ‘gold
standard’ studies found showed “control charts to be simple, low-cost, effective tools with
good sensitivity and specificity characteristics” (Tennant, Mohammed, Coleman et al.
2007). The four case-study reports also reported positive impact on quality of care, patient
experience and carer experience
• the use of SPC is debated (Benneyan & Kaminsky 1995)
• some of the more methodologically robust papers about SPC application include
(Benneyan, Lloyd & Plsek 2003) and (Marshall, Mohammed & Rouse 2004)
• the profile of SPC amongst UK doctors was raised by the widely publicised application to
data about mortality in the light of the Shipman case and the Bristol enquiry (Mohammed
et al. 2001, Mohammed, Rathbone, Myers et al. 2004)
In the US the use of SPC has been encouraged by the IHI and other improvement specialists
(Carey 2002)4 and the NHS picked up on this (Balestracci 1998), as part of the Improvement
Partnership for Hospitals initiative (NHS Institute for Innovation and Improvement & Matrix
Research and Consultancy 2006).
As a result, an Excel-based SPC tool was widely distributed in the NHS and appears to be
used in places. In particular, control charts are used to display performance over time and
assess the impact of interventions, (e.g. Walley, Silvester & Mountford 2006a). Some NHS
trusts now use control or run chart format to present hospital-level activity reports and
courses have been run to help board-level managers interpret such charts. Guidance for
healthcare practitioners on how to use control charts has also been made generally available
(Mohammed et al. 2008).
4 SPC is not however featured as a discrete theme in the work of the IHI although control charts are widely used in a number of their
work areas

Lists of benefits, limitations, barriers and facilitating conditions for SPC in healthcare were
shown by a systematic review (Thor et al. 2007) and included:
• improving communication between clinicians, managers and patients by providing a
shared language
• describing and quantifying variation
• identifying areas for potential improvement
• assessing the impact of change interventions
A study of the effect of presenting data as league tables vs. control charts, for the purposes
of decision-making concluded that fewer outliers for further investigation are identified when
data is presented in control charts (Marshall et al. 2004).
Use of SPC to link performance information to physician compensation and practice
management has been shown to improve financial performance (Stewart, Greisler & Feldman
2002).
A series of examples presented which, though it is not clear how closely they are based on
real cases, show that using SPC enables teams to decide on the most appropriate
improvement strategy: searching for special causes or more fundamental process redesign
(Benneyan, Lloyd & Plsek 2004).
Issues in using SPC, and the thinking behind it, highlighted by applications in
healthcare include:
• the limitations to the objective being reduction of variation (McLaughlin 1996, Seddon
2005a)
• the complexity and appropriateness of data sets representing aggregations of different
types of patients or management units (Thor et al. 2007)
• the implications on the underlying statistics of having very small or very large data sets
(Mohammed & Laney 2006)
Where could SPC be used in your organisation for presenting and monitoring clinical and
non-clinical data?
What awareness of variation and its effects do you have within the organisation?

5.3 Six Sigma
Six Sigma is a process or product improvement or (re)design approach developed initially by
Motorola in the 1980s, then further by Allied Signal and General Electric. Having achieved
widespread acceptance in manufacturing, Six Sigma is becoming popular in the service sector
especially with US-owned firms (Schroeder, Linderman, Liedtke et al. 2007).
History of Six Sigma (developed from Laux 2008)
The roots of Six Sigma as a measurement standard can be traced back to Carl Frederick
Gauss (1777-1855) who introduced the concept of the normal curve. Six Sigma as a
measurement standard in product variation can be traced back to the 1920s when Walter
Shewhart showed that three sigma [three standard deviations (SDs)] from the mean is the
point where a process requires correction. Many measurement standards later came on
the scene but credit for coining the term Six Sigma goes to a Motorola engineer named
Bill Smith (Six Sigma is a federally registered trademark of Motorola).
In the late 1970s, Dr Mikel Harry, a senior staff engineer at Motorola’s Government
Electronics Group (GEG) began to experiment with problem solving through statistical
analysis. Using his methodology, GEG began to show dramatic results – GEG’s products
were being designed and produced faster and more cheaply. Subsequently, Dr. Harry
began to formulate a method for applying Six Sigma throughout Motorola. His work
culminated in a paper titled “The Strategic Vision for Accelerating Six Sigma within
Motorola.” He was later appointed head of the Motorola Six Sigma Research Institute and
became the driving force behind Six Sigma.
Dr Mikel Harry and Richard Schroeder, an ex-Motorola executive, were responsible for
creating the unique combination of change management and data-driven methodologies
that transformed Six Sigma from a simple quality measurement tool to the breakthrough
business excellence philosophy it is today. They had the charisma and the ability to
educate and engage business leaders such as Bob Galvin of Motorola, Larry Bossidy of
AlliedSignal (now Honeywell), and Jack Welch of GE. Together, Harry and Schroeder
elevated Six Sigma from the shop floor to the boardroom with their drive and innovative
ideas regarding entitlement, breakthrough strategy, sigma levels, and the roles for
deployment of Black Belts, Master Black Belts and Champions.

How is Six Sigma defined?
There are various understandings of what Six Sigma is (Proudlove and Boaden 2006b,
Schroeder, Linderman, Liedtke et al, 2007), though most authors agree it builds on the work
of Shewart and Deming and the Total Quality Management (TQM) approach. Six Sigma has
not been carefully defined in either the practitioner or academic literature but a
comprehensive definition which is well accepted is:
“Six Sigma is an organized and systematic method for strategic process
improvement and new product and service development that relies on statistical
methods and the scientific method to make dramatic reductions in customer
defined defect rates (Linderman, Schroeder, Zaheer et al. 2003 p.195)
This definition highlights the importance of improvements based on the customer’s definition
of a defect. A key step in any Six Sigma improvement effort is determining exactly what the
customer requires and then defining defects in terms of their ‘critical to quality’ parameters.
Many argue that Six Sigma is “a tactical methodology to determine the best approach for a
given situation/process” and that it “should not be considered just another initiative but
should integrate other programs … as part of an overall business strategy” (Breyfogle III,
Cupello & Meadows 2001).
What does the term ‘Six Sigma’ mean?
Six Sigma enabled Motorola to express its quality goal as 3.4 defects per million
opportunities (DPMO), where a defect opportunity is a process output that fails to meet
the customer’s critical requirements. Motorola set the goal to be reducing the SD of a
process so that the distance from the process target setting (mean) to the (nearest) defect
threshold would be 6 SDs (Breyfogle III et al. 2001). They further assumed that the process
was subject to disturbances that could cause the process mean to drift over time by as
much as 1.5 SD from the target setting (Montgomery 2001), which then results in the
distance being 4.5 SD and so (from the normal probability distribution) to the defect rate
being 3.4 DPMO. This goal was far beyond normal quality levels and required very
aggressive improvement efforts.

The full Six Sigma approach can be considered to consist of the following elements
(Proudlove & Boaden 2006b):
a. An underlying philosophy
This is to define acceptable process output according to the customer’s measure of quality,
then reduce process variation on this measure by establishing (statistically if possible) root
causes of variation.
b. Underpinning elements
These focus on deployment, support and training infrastructure (including ‘belt’ certification
structure: see Table 5). A major deployment of Six Sigma involves training and coaching by
very experienced Master Black Belts (MBBs) of practitioners (typically Green Belts (GBs)) and
expert practitioners (Black Belts (BBs)) who undertake improvement projects with the support
of Champions (leaders and senior managers who ensure that resources are available for
training and projects, and who are involved in project progress reviews).
Table 5 – Six sigma levels of certification5
Master Black Belts are Six Sigma quality experts who are responsible
for the strategic implementations within an organisation. Master
Black Belt’s main responsibilities include training and mentoring of
Black Belts and Green Belts; helping to prioritise, select and charter
high-impact projects; maintaining the integrity of the Six Sigma
measurements, improvements and tollgates; and developing,
maintaining and revising Six Sigma training materials.
Six Sigma team leaders are responsible for implementing process
improvement projects within the business — to increase customer
satisfaction levels and business productivity. Black Belts are
knowledgeable and skilled in the use of the Six Sigma methodology
and tools. Black Belts have typically completed four weeks of Six
Sigma training, and have demonstrated mastery of the subject
matter through the completion of project(s) and an examination.
Black Belts coach Green Belts and receive coaching and support
from Master Black Belts.
An employee of an organization who has been trained on the
improvement methodology of Six Sigma and will lead a process
improvement or quality improvement team as part of their full time
job. Their degree of knowledge and skills associated with Six Sigma
is less than that of a Black Belt or Master Black Belt. Extensive
product knowledge in their company is a must in their task of
process improvement. The Green Belt employee plays an important
role in executing the Six Sigma process at an organisation level.
5. http://www.isixsigma.com/dictionary
Master Black Belt
Black Belt
Green Belt

c. Methodologies or roadmaps
These guide practitioners through problem solving steps, providing structure for using tools.
Six Sigma uses a structured method, whether the task is process improvement or new
product design.
• In the case of process improvement, define, measure, analyze, improve and control
(DMAIC) are used as the five steps in process improvement.
• Somewhat different roadmaps called Design for Six Sigma (DFSS) are used for radical or
incremental product design (e.g. define, measure, analyse, design and verify (DMADV)).
These are less frequently used than DMAIC and use more complex statistical tools, so are
usually supported by more experienced practitioners.
The main steps in DMAIC are illustrated in Figure 4. Since the use of DMAIC is dominant it is
sometimes mistakenly taken to be synonymous with Six Sigma.
Figure 4 - The main steps in DMAIC (Brassard, Finn, Ginn et al. 2002).

d. A large toolkit
This includes process mapping and SPC – see (Pyzdek 2003b) for a comprehensive guide to
the tools. There is a careful integration of the tools with the overall method: “Whatever
method is chosen …it is important that the method be carefully followed and a solution not
offered until the problem is clearly defined. Data and objective measurement is critical at
each step of the method. The standard statistical quality tools are incorporated into the
structured method as needed … this careful integration of tools with the methods is unique
to Six Sigma.” (Linderman et al. 2003, p.195).
Is Six Sigma a new approach?
Debate about whether Six Sigma is really new, when it has been around since the mid-1980s
is in one sense irrelevant. However, there are clearly a variety of schools of thought about
what Six Sigma is, from “a set of historically known and used statistical techniques, in a new
package” (Breyfogle III et al. 2001, Klefsjö, Wiklund & Edgeman 2001) to “an effective
application of statistical techniques, delivered in an innovative manner that has achieved
acceptance, use and results by the management of many organisations” (Breyfogle III et al.
2001, Harry & Schroeder 1999).
Many authors claim that it is not new (Klefsjö et al. 2001), and justify their views by tracing
back the emphasis on process and variation to both Deming (Deming 1986) and Shewhart
(Shewhart 1931). Others claim (George & Rowlands 2003) that it has borrowed from the
best of Deming and adds features like a comprehensive training structure and a broad
definition of value from a customer perspective, which includes quality but also service
and delivery.
Perhaps what is new is the explicit linking of the tactical and the strategic – where statistical
techniques are “used in a systematic way … there is a focus on results, including customer-
related ones that lead to enhanced marketplace performance” (Klefsjö et al. 2001). It could
be suggested that it is therefore the use of Six Sigma as an overall approach rather than
simply the tools which is new.
The contribution of both the underpinnings (that support and drive change capability) and
the DMAIC methodology (which provides rigour and a logical structure to guide tool use) are
highlighted by some authors (Proudlove & Boaden 2006b). Others (Schroeder et al. 2007)
identify the key strength and differentiator of Six Sigma to be the underpinnings, which they
characterise as creating a very strong improvement structure (a ‘meso-structure’) in parallel
with the management hierarchy in an organisation. However they only examined
comprehensive deployments of Six Sigma in large organisations. Additional views come from
a review of Six Sigma, where two important features are described: “building and
maintaining management support and fostering use of methods among practitioners who
are not experts in statistics” (Brady & Allen 2006).

Many organisations claiming success in Six Sigma also have long-established TQM
programmes (McAdam & Lafferty 2004), and some appear to re-label their TQM
programmes as Six Sigma. Others do not view it as an alternative to TQM, but one approach
that supports the principles of TQM – in this case, a methodology within TQM, likened to
Business Process Reengineering (Klefsjö et al. 2001).
Others have claimed that Six Sigma is a more analytical and data-based approach than TQM,
or at least as it appeared to be practised, “little more than an ill-defined motivation or culture
change programme” (Bicheno 2002). A further comparison is made by (Lazarus 2003) –
see Table 6.
The comparison made more recently between Six Sigma and Lean will be covered in section
5.4.2, following the description of Lean.
A key early reference on Six Sigma in healthcare considered the implications of translating Six
Sigma (as an approach for reducing error and improving reliability) into healthcare from a
conceptual position (Chassin 1998), concluding that it is possible and the journey should
start. However, the reference is US-focused, as is a more recent overview, which includes a list
of examples and a case study (Sehwail & DeYong 2003).
TQM Six Sigma
Typically grass-roots driven Top-down implementation
Incremental improvement i.e. 10-15% Breakthrough improvement i.e. 50-100%
Focus is ongoing Focus is short-term projects
Goal is ‘more with more’ i.e. inspection Focus is ‘more with less’
Consensus driven Data driven, using statistical analysis
Table 6 - TQM and Six Sigma (Lazarus 2003)

A key US author is Revere (Black & Revere 2006, Revere & Black 2003, Revere, Black & Huq
2004) who looked at the implications of Six Sigma for patient care in a general sense, in
conjunction with Continuous Quality Improvement (CQI) approaches - including a review of
areas where it has been applied - and on use of Six Sigma in medication (Chaplin 2003).
Other areas which feature in the literature include radiology (Benedetto 2003a, Benedetto
2003b), nursing (Lanham & Maxson-Cooper 2003) and pharmacy (Johnstone, Hendrickson,
Derbach et al. 2003). Most of these appear to assume that Six Sigma can be applied in
healthcare and then simply go on to describe how.
Many other papers are essentially trade journal descriptions of the implementation of Six
Sigma with little real analysis of the problems/issues of translation (Anonymous 2000, 2003,
Brantes & Galvin 2001, Buck 1998, Grazier 2003, Grim 2001, Lazarus 2003, Lazarus &
Stamps 2002, Lucier & Seshadri 2001, Scalise 2003, Simmons 2002, Snee 2000, Thomerson
2001, 2002, Thomson & Lewis 2002). Others are merely proposals for use (Frings &
Grant 2005).
There are various books on Six Sigma in healthcare including:
• one described by the authors as ‘jargon free’ and without an academic focus (Barry,
Murcko & Brubaker 2002)
• one written by authors who wrote earlier papers and ‘how to’ books on the topic in
manufacturing, and who are both practitioners rather than academics (Snee & Hoerl 2004)
• one published by the American Society for Quality, intended for senior managers of
hospitals and medical clinics (Barry & Smith 2005)
A paper considering how to win the support of clinicians for Six Sigma postulates that the
fact that Six Sigma is quantitative, based on “solid data carefully validated for accuracy” and
able to achieve lasting results will attract clinicians to this method (Ettinger & Kooy 2003).
Their description of the process by which clinicians respond to Six Sigma is as follows
(Ettinger & Kooy 2003):
• they challenge the data as usual
• when their initial objections are addressed, they take a more focused approach to
questioning the quality of the data
• when the data stands up again, they sit up a bit and dust off their methodological
training. They ask a few more pointed questions about the methodology, see that it is
sound and then a transformation takes place
These accounts are overwhelmingly US-based, though some application has been made in at
least one Irish hospital (presented at practitioner conferences only) and major use at a
hospital in the Netherlands has been formally reported (van den Heuvel, Does &
Verver 2005).

Application within the NHS
In the NHS, reports of attempts to implement Six Sigma go back to the early 1990s (Merry &
Wing 1993). A recent paper claims that Six Sigma is the ’cure’ for the NHS and predicted
that use of Six Sigma “will continue to grow, especially here in the UK over the next five
years” although the paper makes no reference to any recent or current use within the NHS
(Antony, Downey-Ennis, Antony et al. 2007b). They further predict use of DFSS for designing
new processes and products in services.
Some training in Six Sigma was provided to the NHS in 2004-5, the details of which are given
below. The learning from this has also been published (Proudlove et al. 2008).
Separately, a Welsh multi-hospital trust has trained up some staff to be BBs and has been
using Six Sigma - alongside Lean tools (in particular value stream mapping (VSM)) - for many
years (Esain, Angel & Robertson 2006).
There are numerous accounts of positive business outcomes from the use of Six Sigma in
manufacturing (Hutchins 2000) but these have generally not been independently evaluated
(Ferlie, Aggarwal & McGivern 2002). In general, the academic literature on Six Sigma is
descriptive, with a “paucity of studies that fundamentally critique the phenomena of Six
Sigma in organisations from both people and process perspectives” (Erwin & Douglas 2000).
Training for Six Sigma in the NHS
The NHS Modernisation Agency (MA) ran a major experiment with Six Sigma in England
in 2004-05; the Green Belt programme, with over 50 staff participating in two four-day
periods of training, whilst working on projects in 14 teams. The training and project
coaching was led by Juran Institute MBBs with support from two NHS staff who had
previously achieved BB level. The projects involved both primary and secondary care, and
activities from A&E to outpatients. The programme was observed and evaluated for the
NHS MA by a team from Manchester Business School (MBS) (Proudlove et al. 2008).

A review of Six Sigma from an academic perspective (Antony 2004), highlights that the
academic perspective on Six Sigma is lagging behind the practice and that a theoretical
underpinning is currently lacking, something also supported by Linderman et al. 2003.
Another review notes a shifting interest from practitioners towards academics (Brady & Allen
2006). Comprehensive reviews of the general literature on Six Sigma (Hendry & Nonthaleerak
2005, Nonthaleerak & Hendry 2006) conclude that, despite the great claims made for it, so
far there is little rigorous empirical evidence for financial returns or on enablers and barriers
to success.
Success factors such as leadership and top management commitment are listed by many
authors (Antony, Antony, Kumar et al. 2007a, Banuelas & Antony 2002, Brady & Allen
2006), but not investigated using rigorous methodology.
Given the relatively unobjective accounts of Six Sigma in healthcare published to date it is not
possible to give independent views on the reported outcomes. However, it is worth listing
some of the outcomes described (Table 7). Many other examples of Six Sigma projects with
positive outcomes in US hospitals can also be found (Antony et al. 2007b). It is noted that
“Six Sigma has not been widely applied to patient care” (Revere et al. 2004), a conclusion
supported by the data in Table 7. There are undoubtedly other narrative examples of the
application of Six Sigma in healthcare, but no accounts of independent evaluation have been
found.
Examples of improvements from the application of Six Sigma
“Having begun, in late 1998, to coordinate Six Sigma strategies and measurements on a
worldwide basis, our experience clearly shows that the potential benefits are enormous in
terms of productivity improvement, product quality, customer satisfaction, more efficient
capital spending, and overall corporate profitability . . . Savings attributable to Six Sigma
were more than $30 million in 1999, and we expect to generate twice that amount in
2000 as we intensify our efforts.” Black and Decker Annual Report, 1999, quoted in
(Caulcutt 2001).
“. . . we plunged into Six Sigma with a company-consuming vengeance just over three
years ago. We have invested more than a billion dollars in the effort, and the financial
returns have now entered the exponential phase - more than three quarters of a billion
dollars saving beyond our investment in 1998, with a billion and a half in sight for 1999.”
GE Annual report 1998, quoted in (Caulcutt 2001).

Table 7 – Outcomes from applying Six Sigma in healthcare
Organisation (reference) Outcomes reported
Commonwealth Health Corporation
(CHC) (Simmons 2002)
• greater efficiency in radiology – cost per
procedure reduced by 21.5%
• throughput increased by 25%
• changing culture and understanding a
data approach also reported
Long Island Jewish (LIJ) Health System
(Cooper 2002, Scalise 2003, Simmons
2002)
• improved billing accuracy saved over a
quarter of a million dollars a year,
reduced bed turnaround time by 50%
and emergency wait time by 25%
Froedtert Memorial Lutheran Hospital
(Lanham & Maxson-Cooper 2003,
Simmons 2002)
• lab sample transport system speeded up
and errors reduced by 35%
Charleston Area Medical Center (CAMC)
(Revere et al. 2004, Simmons 2002)
• speeded up employee recruitment, saving
money on overtime
• improved supply chain for surgical
supplies, saving over half a million dollars
Virtual Health (Ettinger 2001, Scalise 2003,
Simmons 2002)
• did nine projects, saving over $4m on
an investment of $1.4m
McLeod Regional Medical Centre (Scalise
2003)
• reduced service time in registration by
25%, and reduced patient and
physician complaints
Mount Carmel Health (Revere et al. 2004) • refined patient coding and saved over
$800,000
Scottsdale Health Care (Revere et al. 2004) • reduced time to transfer emergency
patient to a bed, saved $600,000
Bon Secours Health System (Swayne 2003) • many examples, including reduction in
nurse overtime of 65% due to more
effective patient placement
Sentara Healthcare (Swayne 2003) • reduced ventilation stay of 25%, defects
per million reduced by 12%
Red Cross Hospital (the Netherlands) (van
den Heuvel et al. 2005)
• saved a1.2 million per year from 21
finished projects, expect to save a3
million per year from 23 running projects
Red Cross Hospital (the Netherlands) –
Lean Six Sigma (de Koning, Verver, van den
Heuvel et al. 2006)
• personnel hiring savings a36,000 (target);
OT reduced delayed starts; maintenance
savings a200,000 (achieved)

During use in Wales (Esain et al. 2006) it was noted that the customer focus tools in the
‘Define’ phase were considered stronger and more robust than others used, and that the
rigour of the DMAIC process was important. They also conclude that expressing project
outcome in terms of cost is “not a motivational concept for improvement”. In the NHS
context, greater throughput may often be more immediate to many staff than the cost
savings emphasised in US and Dutch deployments of Six Sigma.
Outcomes of the Six Sigma training in the NHS
The outcomes of the NHS Green Belt experiment (Proudlove et al. 2008) show that:
• Many processes were unready for Six Sigma, or at least for DMAIC process improvement
(being ill-defined or chaotic). This experience then contributed to subsequent NHS
interest in Lean Six Sigma and (pure) Lean approaches (see section 5.4.3)
• The DMAIC approach, and its associated tools, was very rigorous, and particularly
valuable at the Define and Measure phases in finding out the customer point of view,
thinking hard about what the process is, measuring how it is performing and obtaining
evidence for root causes
• However, rigour came at the cost of very considerable effort and (at the time)
frustration, and required considerable coaching to maintain both thoroughness and
project momentum.
More general findings, applicable to all improvement projects included:
• Project selection, and linking projects to important organisational goals is important
• Jargon can be off-putting
• In the NHS, identifying customers and processes can seem particularly difficult.
Does the fact that use of Six Sigma as an overall approach requires understanding of
statistical tools make it inappropriate for use in the NHS?
Are there areas where a structured approach to problem-solving would be beneficial - for
example, using the DMAIC roadmap without some or any of the recommended tools?
Is your process ready for improvement (is it stable and definable), or does it need
redesign first?
Do you have coaches available who can support the rigour of an improvement project and
advise on appropriate tools?

5.4 Lean
The term Lean has been developed in the context of manufacturing from the way in which
Toyota, and other Japanese motor manufacturers, organise their production processes. Much
of the original work with Toyota was carried out by Ohno (Ohno & (translator) Rosen 1995).
Recent authors have attempted to summarise how Toyota works although some argue
(Spear & Bowen 1999) that many of the practices used by Toyota have been studied but “the
essence of Toyota’s system consists of tacit knowledge, and is so woven into the culture, not
written down, and workers could not articulate it” (Jimmerson, Weber & Sobek 2005, p.5).
However, the two accounts of the Toyota Production System (TPS) most often used in the
West are:
The Machine that Changed the World
The term Lean production was coined by the authors of the book The Machine that
Changed the World in 1990 (Womack, Jones & Roos 1990). Lean production was then seen
to consist of Lean manufacturing, Lean product development, supply chain coordination,
customer distribution and Lean enterprise management (Womack et al. 1990).
Over the early 1990s these principles were gradually extended from the shop floor to other
areas and other industries, so that system design was described as based on “Lean principles”
(Womack & Jones 1996). It is argued that this may have happened as a reaction against a
‘one best way’ approach, “where advocates of Lean thinking started to re-position Lean
thinking as based on a set of five key principles that it was claimed could be applied across a
wide range of industrial settings” (Hines, Holweg & Rich 2004). Although many of the
examples were based on manufacturing industries and involved the common application of
kaikaku (improvement via breakthrough events, as opposed to kaizen,
continuous improvement).
The five Lean principles articulated by these authors are:
• the identification of customer value
• the management of the value stream
• developing the capability to flow production
• the use of ‘pull’ mechanisms to support material flow
• the pursuit of perfection through reducing all forms of waste in the system

These principles are also described as the “essential implementation sequence” for Lean 6 i.e.
the steps that organisations should follow in order to become Lean.
The Toyota Way
A series of books by Jeffrey Liker (Liker 2004) describe the way in which Toyota works as the
Toyota Production System (TPS). This is summarised in Figure 5:
Figure 5 – The Toyota Way
The problem-solving element of this is seen as key to success: “they tightly couple the process
of doing work with the process of learning to do it better as it’s being done. Operations are
expressly designed to reveal problems as they occur. When they arise, no matter how trivial
they are, they are addressed quickly, If the solution … generates new insights, these are
deployed systematically” (Spear 2005).
The TPS is summarised as “Toyota’s real achievement is not merely the creation and use of
the tools themselves; it is in making all its work a series of nested, on-going experiments”
(Spear 2004, p.79). The same author is clear that the TPS is about applying principles rather
than tools – which is why it is so difficult to emulate. This approach is summarised in Table 8
(Liker 2004).
6. http://www.lean.org/WhatsLean/CommonLeanQuestions.cfm

Table 8 – Delivering Operational Excellence: the Toyota Production System
Delivering Operational Excellence
Four basic organisational capabilities, if properly developed and nurtured, deliver the kind of
operational excellence exhibited at Toyota and companies like it:
The tools associated with a Lean approach
Like many other approaches Lean consists of a number of tools, some of which are also used
in other approaches to improvement. Some authors give more extensive lists of tools which
may be used within a Lean approach based on wider literature reviews (Bicheno 2000). A
comparison of the tools which might constitute Lean, with a focus on healthcare, from a
variety of sources is given in Table 9.
1. Work is designed as a series of ongoing experiments that immediately reveal problems,
in order to drive out any ambiguity, employees in industry-leading companies spell out
how work is expected to proceed in extraordinary detail, especially for highly complex
and idiosyncratic processes. This increases the chance that the employees will succeed
because it forces them to make their best understanding of a process explicit. If they
don’t succeed, spelling out what is expected increases the chance that problems will be
detected earlier rather than later, since people will be surprised by the unexpected
outcome. Such companies go even further by embedding tests into the work that
show when what is actually happening is contrary to what was expected.
2. Problems are addressed immediately through rapid experimentation. When something
does not go as expected, the problem is not worked around. Instead, it is addressed by
those most affected by its ramifications, contained and prevented from propagating
and corrupting someone else’s work. Causes are quickly investigated and
countermeasures rapidly tested to prevent the problem from recurring. When those
who first address a problem are flummoxed, the problem is quickly escalated up the
hierarchy so that broader perspectives and additional resources are brought to
its resolution.
3. Solutions are disseminated adaptively through collaborative experimentation. When an
effective countermeasure is developed, its use is not limited to where It has been
discovered. But that doesn’t mean the countermeasure is simply rolled out as a cookie
cutter solution. Rather, people build on local insights into reducing defects, improving
safety, enhancing responsiveness, and increasing efficiency by solving problems with
colleagues from other disciplines and areas so that the countermeasure, and the
process by which it was developed, is made explicit, can be emulated, and can be
critiqued.
4. People at all levels of the organization are taught to become experimentalists. Finally,
managers at companies like Toyota don’t pretend that the ability to design work
carefully, improve processes and transfer knowledge about those improvements
develops automatically or easily. Coaching, mentoring, training and assisting activities
constantly cascade down to ever more junior workers, thereby building exceptionally
adaptive and self-renewing organisations.

Table 9 – Tools associated with a Lean approach
Literature
review
(Bhasin &
Burcher 2006)
Empirical
Review of Lean
in the public
sector (Radnor,
Walley,
Stephens et al.
2006)
NHS Institute for
Innovation and
Improvement
(NHS Institute
for Innovation
and
Improvement
2007)
Lean tools in
the Virginia
Mason
Production
System
(Nelson-
Peterson &
Leppa 2007)
Lean tools in
healthcare
(Manos, Sattler
& Alukal 2006)
Continuous
improvement/
kaizen
Rapid
Improvement
Events (RIEs or
Kaizen Blitz)
RIEs
Cellular
manufacturing
Less commonly
used
U-shaped cells Cellular
Kanban (pull)
system
Pull signals Kanban Pull systems
JIT JIT JIT
Single piece
flow
One piece flow Batch size
reduction
Process
mapping
Process mapping
(sometimes as
Value Steam
Mapping, VSM)
VSM VSM
Single minute
exchange of
dies (SMED) i.e.
reduction of
changeover
time
Quick
changeover
Step
change/Kaikaku
Supplier
development
Supplier base
reduction
5S and general
visual
management
5S Visual
workplace/5S
Visual control 5S workplace
organisation
Visual workplace
systems
Total productive
maintenance
(TPM)
Less commonly
used
TPM
The seven
wastes
Identification and
eliminating of
waste

It should be noted that there is no definitive list of tools which comprise the Lean approach,
with some authors arguing (Hines et al. 2004) that “from a strategic point of view however,
you can integrate other approaches (particularly the tools they offer) without contradicting
the core objective of Lean – to provide customer value. In other words, any concept that
provides customer value can be in line with a Lean strategy, even if Lean production tools on
the shop-floor, such as Kanban, level scheduling, or take time, are not used” (p.1006).
Tools commonly used
Of the wide variety of tools available, the main ones used within the public sector appear to
be value stream mapping (VSM)/process mapping, 5S and kaizen blitz/rapid improvement
events (RIEs). Although there is little formal research to support this view, there is plenty of
informal and anecdotal evidence, not least the number of training programmes now
available for these approaches.
Market-based
demand analysis
Work
standardisation
(less commonly
used)
Work
standardisation
Standard work
and cycle times
Standardised
work
Staff involvement
Multi-functional
staff
Match resources
to demand
Point of use
storage
Poka-yoke
(mistake
proofing)
Self inspection
Autonomation
– automation
with a human
touch
Table 9 – Tools associated with a Lean approach - continued...
Literature
review
(Bhasin &
Burcher 2006)
Empirical
Review of Lean
in the public
sector (Radnor,
Walley,
Stephens et al.
2006)
NHS Institute for
Innovation and
Improvement
(NHS Institute
for Innovation
and
Improvement
2007)
Lean tools in
the Virginia
Mason
Production
System
(Nelson-
Peterson &
Leppa 2007)
Lean tools in
healthcare
(Manos, Sattler
& Alukal 2006)

Table 10 – The seven wastes
Some healthcare organisations extend this to 6S, explicitly adding safety (Fillingham, 2007).
Bicheno (2004) points out that safety should anyway be stressed in each of the five S. He
also comments that while the first two are the easiest and most widely adopted, the real
benefits arise from the later ones, especially standardise. An alternative is CANDO (Cleanup,
Arrange, Neatness, Discipline, Ongoing improvement.
Value Stream Mapping
VSM (Hines & Rich 1997) enables the seven common ‘wastes’ identified in the Toyota
Production system to then be addressed by some combination of other Lean tools. In
addition to the conventional mapping of activities, VSM adds an assessment of
whether each activity is value-adding or waste.
5S
5S “is the basic housekeeping discipline for Lean, quality and safety” Bicheno (2004:
p.52). There are various labels for each of the five S’s, but the thinking is the same:
1. Sort - classify equipment and supplies by frequency of use, remove what is not used
2. Simplify/Straighten/Set in order - allocate a place for equipment and supplies,
standardise locations with labelling, shadow boards, inventory footprints etc
3. Shine/Scrub - clean and check
4. Standardise/Stabilise - adopt standard work and standards for 5S
5. Sustain/Self Discipline - on-going 5S, housekeeping audits
Overproduction
Waiting
Transport
Inappropriate processing
Unnecessary inventory
Unnecessary motion
Defects

Many authors writing about the Lean approach believe that “you can integrate other
approaches (particularly the tools they offer) without contradicting the core objectives of
Lean – to improve customer value” (Hines et al. 2004, Kaplan & Rona 2004), and this is
demonstrated in Figure 6.
Figure 6 – Lean and its tools (Hines et al. 2004).
Rapid Improvement Events
The RIE process has been described as “the engine for implementing the changes
(physical and cultural) that a Lean approach requires” (Radnor et al 2006 p.77).
Preparation some weeks before an RIE includes data gathering and analysis, diagnosis,
agreeing measures, planning the event and (sometimes) training.
The event itself typically lasts for three to five days, centred on a series of facilitated PDSA
cycles or equivalent approach.
Over the subsequent weeks or months follow-up sessions target changes identified but
not implemented during the RIE, and on sustaining changes.
Bicheno (2004) suggests an organisation might focus early RIEs on issues such as layout,
5S or safety, with later ones targeting lead time, staffing etc.
RIEs are also known as kaizen blitz events, and are identified by Bicheno (2004) with the
description of kaikaku (breakthrough improvement) by Womack and Jones.

Key to Figure 6:
TQM Total Quality Management (see section 4.3)
TQC Total Quality Control
ToC Theory of Constraints (see section 5.5)
6σ Six Sigma (see section 5.3)
SPC Statistical Process Control (see section 5.2)
TPM Total Productive Maintenance
MRPI+II Materials Requirements Planning
ERP Enterprise Resource Planning
APS Advanced Planning and Scheduling
However some argue that there are fundamental differences, based on the experimental
approach used in the TPS: “The essential difference between TPS and traditional
improvement programs lie in who identifies a problem and how, by whom, when, and where
it is solved” (Thompson, Wolf & Spear 2003, p.587).
Lean and Six Sigma
Six Sigma and Lean are often compared because they are currently both popular with
industry, especially in the US (Arnheiter & Maleyeff 2005) and have both evolved from their
original routes to be comprehensive approaches to improvement. It is therefore important to
compare them directly.
Six Sigma’s rigorous, data-analytic search for root causes makes it well-suited for complex
‘cause-unknown’ problem situations. Meanwhile insights into situations where problems
involve cycle-time reduction and flow improvements have often been partitioned into
approaches often now labelled as Lean.
As many have tried both approaches separately, with initial success but then gradually
diminishing returns, there is a move to combine the two to form Lean Six Sigma (George &
Rowlands 2003). Efforts to bring Lean tools into Six Sigma, and attempt to exploit the
synergy of the two (Bossert 2003), have resulted in packages with names such as Lean Six
Sigma. Typically Lean tools such as value stream mapping are included in DMAIC, particularly
during Measure (e.g. value stream mapping) and Improve (e.g. including established pull
methods and 5S) (George, Rowlands, Price et al. 2005)).

If the two approaches are combined at a strategic level, rather than simply incorporating
tools, then a Lean Six Sigma organisation would include (from Lean principles)
(George 2003):
• an overriding philosophy that seeks to maximise the value-added content of all operations
• constant evaluation of incentive systems to ensure they result in global rather than local
optimisation
• a management decision-making process that bases every decision on its relative impact on
the customer
It would also include (from Six Sigma principles):
• a stress on data-driven methodologies in all decision-making
• methodologies that seek to minimise variation of quality
• a company-wide, highly structured, education and training programme
These proposals stem from the fact that (George 2003) Lean needs Six Sigma because:
• lean does not explicitly prescribe the culture and infrastructure needed to achieve and
sustain results
• customer needs are not at the centre
• lean does not recognise the impact of variation
• it misses out the define and measure aspects of a DMAIC process
Six Sigma needs Lean because:
• it identifies waste
• it improves process speed/cycle time
• it includes methods for rapid action (kaizen)
• six Sigma quality is approached faster if Lean eliminates non value-added steps
The differences between the two approaches are also summarised by (Nave 2002) who
argues that it is the organisational culture that makes the difference about which method is
appropriate and that many methods appear similar when their secondary effects are
considered.

Table 11 – Six Sigma and Lean
Other approaches to using Lean and Six Sigma include parallel roadmaps, an approach
proposed by the NHS (see Figure 7).
Figure 7 – Lean Six Sigma (NHS Institute for Innovation and Improvement 2006)
Program
Theory
Application
guidelines
Focus
Assumptions
Primary effect
Secondary effects
Six Sigma
Reduce variation
Define
Measure
Analyse
Improve
Control
Problem
A problem exists
Figures and numbers are valued
System output improves if
variation in all processes is
reduced
Uniform process output
Less waster
Fast throughput
Less inventory
Fluctuation – performance
measures for managers
Improved quality
Lean
Reduce waste
Identify value
Identify value stream
Flow
Pull
Perfection
Flow
Waste removal will improve
performance
Many small improvements are better
than systems analysis
Reduced flow time
Less variation
Uniform output
Less inventory
New accounting system
Flow - performance measures for
managers
Improved quality
Criticisms System interaction not
considered
Processes improved
independently
Statistical or system analysis not
valued

Some have also proposed new hybrid roadmaps (Rath & Strong Management Consultants
2005), or recommend applying Lean first to redesign or stabilise a process, then Six Sigma to
improve it (see section 5.3.4).
The principles on which a Lean approach is based can be viewed as generic (Jones & Mitchell
2006) and therefore potentially applicable outside of manufacturing – to other service
organisations and to healthcare. “Lean thinking is … a management strategy that is
applicable to all organisations because it is to do with improving processes” (Miller 2005) p.2.
Particular features of Lean which may indicate that it is applicable to healthcare include:
• it has an overall philosophy and a way of setting priorities
• it builds on improvement that has already been carried out e.g. clearing bottlenecks in the
patient journey, identifying the causes of variation, by adding “some more tolls and
providing more of a framework” (Jones & Mitchell 2006 p.3). It can be argued that “There
are still considerable gains to be made in terms of efficiency and effective use of resources
to be achieved in public services” (Radnor & Boaden 2008) p.6
• it has a body of evidence-based tools and approaches already tested within the public
sector (Radnor & Boaden 2008)
• there is a community of those trying Lean to support implementation
In addition there are features of healthcare which may make it amenable to Lean (Table 12).
Table 12 – Characteristics of healthcare that might imply that Lean is applicable
Characteristics of
healthcare that make
it amenable to Lean
(Jones & Mitchell
2006):
How Lean can help A Lean culture
(Miller 2005)
Change in
mindset that
leaders need to
achieve
(Westwood &
Silvester 2007)
things are hard to see
e.g. relating to errors
Defining the problem (cf the
diagnosis) is the first step
(Thompson et al. 2003)
Share information Understand
demand and plan
based on this
responsibilities are not
clear – often made worse
by patients being in
various places and lack of
communication between
staff caring for the
patient
Interdisciplinary
teams
Team organised by
flow – based on
value stream
unnecessary work keeps
being created
Its principles and tools
enable the various forms of
waste to be identified and
their root causes tackled
(Jones & Mitchell 2006)
Reduce waste

processes are not joined
up – especially common
where there are various
departments involved in
a process
It emphasises the whole
system (Jones & Mitchell
2006)
Process driven Systems thinking
inappropriate measures
and targets – accounting
measures in particular
focus only on a single
element
It highlights that “many
traditional approaches to
efficiency improvement are
futile and focus on the
wrong thing” (Jones &
Mitchell 2006 p.2)
Managers focus on
delivering value to
the patients
problems are not
resolved – because the
root cause is not
identified
“How work is expected to
proceed is specified before it
is performed. This applies to
delegation of responsibility
(who will do what task for
whom), coordination of
delegated tasks and
execution of delegated tasks.
Work is designed so that
when it proceeds contrary to
expectations, this becomes
immediately evident”
(Thompson et al. 2003 p.
587). Therefore, when
someone experiences a
problem they should not
seek a ‘work around’ but
identify the problem and call
for assistance in developing a
counter measure that
removes the root cause that
created the problem
Root cause analysis
things get compounded
because of the large
number of steps in the
process
It distinguishes between
waste and value by not
viewing all costs as the
same – some costs do
deliver value
Removing waste
lowers cost
No delays are
experienced
Minimise cost of
capacity
frustration dissipates
energy – staff may want
to do a good job but the
system doesn’t let them
Its focus on the things that
“matter to patients and
clinicians, and on the things
that cause them stress and
get in the way of care”
(Jones & Mitchell 2006 p.2)
The problems
generating the
waste are
understood, so
exiting resources are
more productive
Table 12 – Characteristics of healthcare that might imply that Lean is applicable - continued...
Characteristics of
healthcare that make
it amenable to Lean
(Jones & Mitchell
2006):
How Lean can help A Lean culture
(Miller 2005)
Change in
mindset that
leaders need to
achieve
(Westwood &
Silvester 2007)

Adapting Lean thinking for services
A vociferous critic of the way Lean has been applied to services is John Seddon (Seddon
2005a) who argues:
• the focus of Lean on standardisation of processes is inappropriate in services, where the
time taken to perform a task can vary and standardisation may cause costs to rise, because
the system cannot absorb variety, and morale may fall
• value stream mapping is of little value as it does not take account of flows being dictated
by external factors i.e. the customer. It also is not primarily focused on levels of inventory
but on information fit for purpose being supplied by preceding steps in the process.
Recent research has also shown that the Lean approach may need to be adapted for public
services, with evidence suggesting that public services should first engage with the principles
of customer and process view, flow, and reduction of waste through the use of simple tools
rather than embarking on the implementation of more complex tools used in manufacturing
(for example line balancing). The authors argue that “the issues and context of the public
sector means that the approach could only ever be piecemeal due to the need of service
processes being able to cope with variety, uncertainty and so not being over-standardized
and inflexible.” (Radnor & Boaden 2008, p.5).
Recent research has shown that there is “relatively little evidence of the complete Lean
philosophy being applied in the public sector” (Radnor et al. 2006). There is also evidence to
suggest that it is applied within the public sector without a full understanding of the
underlying principles, so it is seen as another policy or set of tools, which leads to Lean being
applied to processes that are not suited to it, and considered as a set of tools rather than a
fundamental shift in culture and approach (Radnor & Boaden 2008).
Current guidance on implementing Lean in healthcare
Within the UK there is a developing body of guidance, being led primarily by both the NHS
Institute for Innovation and Improvement and the Lean Institute. Within the US, the Lean
Institute is also a major provider of training, and the Institute for Health Improvement (IHI)
has also produced guidance. The main sources of information are shown in Table 13.
Table 13 – Guidance on Lean in healthcare
Institution Key documents Information available at
NHS Institute for
Innovation and
Improvement
Going Lean in the NHS (Westwood,
James-Moore & Cooke 2007)
http://www.institute.nhs.uk/quality_
and_value/Lean_thinking/Lean_
thinking.html/
UK Lean Enterprise
Academy
Presentations from the 4 UK Lean
Healthcare Forums
http://www.Leanuk.org/pages/Lean_h
ealthcare.htm
Institute for
Health
Improvement
Going Lean in Health Care
(Miller 2005)
http://www.ihi.org
Lean Enterprise
Institute
Range of articles and training
programmes
http://www.Lean.org/

Although the IHI site does have cross-links to academic papers, the others in general do not
(unless they are papers written by staff from those organisations). The source of information
for the guidance produced – which is extensive and prescriptive – is therefore often unclear;
in particular the extent to which it is based on existing evidence. Reference to key texts
about Lean and the TPS (Womack & Jones 1996) does not of itself constitute an evidence-
based approach since these books are themselves accounts of activity rather than research-
based analyses.
How to implement Lean in healthcare
Many publications now suggest a series of steps that should be followed in order for
organisations to become Lean; examples (Table 14) are all based around the five Lean
principles (Womack & Jones 1996).
Table 14 – Implementing Lean
However, many authors also urge caution in the implementation of Lean in healthcare for a
variety of reasons:
Integration with organisation strategy and structure
• lean has to be locally led and part of the organisation’s strategy: it cannot be imposed
from outside (Jones & Mitchell 2006)
Original Lean
principles
(Womack &
Jones 1996)
NHS Institute/University of
Warwick guidance for Lean
(Westwood et al. 2007)
NHS Confederation (Lean
Institute) Lean guidance
(Jones & Mitchell 2006)
The identification
of customer
value
Specify value – this can only be
defined by the customer. Value is any
activity which improves the patient’s
health, well-being and experience
Identify value streams
The
management of
the value stream
Identify the value stream or patient
journey – the core set of actions
required to deliver value for patients
Map value streams – which usually
shows immediate waste
Developing the
capability to flow
production
Make the process and value flow –
align healthcare processes to facilitate
the smooth flow of patients and
information
The use of pull
mechanisms to
support material
flow
Let the customer pull – the customer
should pull products and services as
needed. We should deliver care on
demand, with the resources needed
for it
Identify and implement immediate
medium-term and long-term
improvements. RIEs may be used
initially which will show and
enable immediate improvements,
but there has to be responsibility
for also making the medium and
longer-term improvements that
will also be identified
The pursuit of
perfection
through
reducing all
forms of waste
in the system
Pursue perfection – develop and
amend processes continually in pursuit
of the ideal

• a strategic approach to improvement, as well as supportive organisational culture and
ownership are some of the factors described as related to successful Lean implementation
in the public sector (Radnor et al. 2006)
• activities must be organised by flow of patients and information rather than by functional
departments. Accounting structures and reports also need to be organised in this way
(Westwood & Silvester 2007)
• leaders must “create a clear vision statement that guides people to make the right choices
… evaluate the organisational structure and work to flatten it, eliminating hierarchical
layers and organising staff into operational teams based on products and services” (Miller
2005, p.5)
Leadership and management
• executive support is essential for success – leaders must “create the environment where
applying Lean thinking can deliver results” (Westwood et al. 2007, p.20). This will then
enable frontline staff to implement the solutions to the problems they have identified
• to realise the full potential executives will “need to do more than provide support for pilot
projects … they will need to embrace and embody TPS in their own work” (Spear 2005,
p.91)
• management commitment and capability is one of the factors described as related to
successful Lean implementation in the public sector (Radnor et al. 2006). However, for
Lean to work staff need to support and cooperate; it cannot be imposed by managers
Time taken to achieve benefits
• Lean is not a quick-fix and although there may be immediate improvements, the principles
take time to embed. Because its application relies on the “positive commitment and
support of staff in their day-to-day work” linking it to short-term cost-cutting measures will
not lead to long-term success in its application (Jones & Mitchell 2006)
• however there may be short-term gains too: small changes make a big difference – staff
often “merely need permission to improve” (Westwood et al. 2007, p.19)
• timing to set realistic timescales for change and to make effective use of commitments and
enthusiasm for change are some of the factors described as related to successful Lean
implementation in the public sector (Radnor et al. 2006)
Support and education needed
• there is debate about the extent to which external or expert support is required to
implement Lean. However, some do propose a dedicated team to support the process
(Thompson et al. 2003) and recommend active administrative support. Others say that
dedicated improvement expertise is essential (Westwood & Silvester 2007)
• external support from consultants in the first instance, as well as provision of adequate
resources to support change are some of the factors described as related to successful

Lean implementation in the public sector (Radnor et al. 2006). The same authors cite poor
selection of improvement team members as a barrier to change
• some initial education is needed for all (Thompson et al. 2003)
Involvement and communication
• all levels and types of staff need to be involved: “You need to create a shared, joint view of
what is going on … in hospitals doctors find it hard to listen to anyone else” (Jones &
Mitchell 2006, p.21)
• effective communication and engagement through the organisation, as well as teamwork
and joined-up whole systems thinking are some of the factors described as related to
successful Lean implementation in the public sector (Radnor et al. 2006)
In manufacturing, there is a considerable body of research (Oliver, Delbridge, Jones et al.
1994) exploring the impact of what were termed ‘world class manufacturing’ approaches, of
which Lean is considered to be one. However, one of the few reviews of its effects focuses
on just-in-time (JIT) (White, Pearson & Wilson 1999).
Where studies have considered the impact of Lean they have focused on a single aspect of
Lean and its performance implications (Hackman & Wageman 1995, Samson & Terziovski
1999), or the implementation and performance relationship with two aspects of Lean (Flynn,
Sakakibara & Schroeder 1995, McKone, Schroeder & Cua 2001).
Many of the findings support the general assertion that there is “unambiguous evidence that
the synergistic effects of all Lean practices are associated with better manufacturing
performance. The implication for managers of plants that are not implementing Lean
practices is also fairly clear. To not implement Lean bundles is likely to put plants at a
performance disadvantage compared to plants that do implement, regardless of size, age or
level of unionization of the plant in question” (White et al. 1999).
Methodologically these studies are both comparative and quantitative, which may lead to less
emphasis on the ‘softer’ benefits but would generally be regarded as more rigorous than
single case studies.
Theoretically, benefits from Lean may be in ‘waves’ (Jones & Mitchell 2006):
• improved quality and safety – fewer mistakes
• improved delivery – better work gets done sooner
• improved throughput – same people and equipment capable of achieving more
• accelerating momentum – stable working environment with clear standardised procedures
• staff morale improves.
Places where Lean implementation in healthcare and its benefits have been reported in
reports or papers include (Table 15) but the authors recognise that due to the current
popularity of Lean in healthcare, such reports are being published at an increasing rate.

Table 15 – Reported outcomes from the application of Lean
Place Source of
information
Area of
application
Reported benefits
(examples)
UK
Bolton Hospitals
NHS Trust
Has own
website with
information and
links to other
Lean sites 7
Hereford
Hospital
Jones & Mitchell 2006 Pathology department • steps in blood sample
process reduced from
309 to 57
• distance walked by staff
reduced by 80%
• time taken to process
endocrinology and
haematinics samples cut
from 24-30 hrs to 2-3 hrs
• same amount of work
done with fewer staff
• space needed by
department reduced
by 50%
Westwood et
al. 2007
Non-elective trauma
patient pathway
• 50% reduction in
hospital mortality for
older patients with
fractured neck of femur
• 37% reduction in overall
mortality for adult
trauma patients
• 32% shorter length
of stay
Fillingham 2007 Bolton Improving
Care System
• 42% reduction in
paperwork associated
with trauma cases
• 38% decrease in time
taken to get patients
with fractured hip to
theatre
Westwood & Silvester
2007
Pathology
turnaround times
• productivity improved by
252%
• £365K annual savings
through earlier patient
discharge
• delays in specimen
reception reduced from
13 mins to 1 min
Mayday
Healthcare NHS
Trust
Westwood et al.
2007
Sterile services (RIE) • flow improved, giving
more consistent
turnaround time
• less time lost preparing
theatre lists
• demand smoothed
throughout the day
7. http://www.boltonhospitals.nhs.uk/publications/bics/default.htm

Medway Trust Mathieson 2006 Audiology • reduced time taken to
issue hearing aids from 2
years to 101 days by
allowing direct GP
referral to audiologists
Wirral Hospital Mathieson 2006;
Jones & Mitchell
2006
Day surgery • doubled day surgery
capacity at elective
surgery site
US
Thedacare,
Wisconsin
Miller 2005 Various. Details of
approach are in paper
• 3.3m$ savings in 2004
• reduced accounts
receivable from 56 to 44
days in 2204, equating
to about 12m$ in
cash flow.
Western
Pennsylvania
Hospital,
Pittsburgh
Spear 2005 Pre-surgery unit • reliability of work
improved: 54 problems
identified and worked
around e.g. time
between patient signing
in and registering
reduced from 2hrs to 0,
unnecessary blood bank
reports reduced from 7
to 0 per day
Hospitals in the
Pittsburgh
Regional
Healthcare
Initiative:
Lifecare Hospitals
Monongahela
Valley Hospital
UPMS Health
System
Allegheny
General Hospital
Spear 2005 Central line-
associated
bloodstream (CLAB)
infections
• 87% reduction in CLAB
infections, down to 0 in
some places
University of
Pittsburgh
Medical Center
(UPMC) Health
System
Thompson et al.
2003
Use of IV push
method
• preparation time for
antibiotics reduced by 4
mins per dose, nurse
savings of over 5000 hrs
per year, patient does not
experience discomfort
before dose is changed
Table 15 – Reported outcomes from the application of Lean - continued...
Place Source of
information
Area of
application
Reported benefits
(examples)

Virginia Mason
Medical Centre,
Seattle
Reinertsen 2006 Various areas • no of patients
contracting pneumonia
while on ventilator
reduced from 40 to 2 per
year, and costs dropped
from 1.6$m to 0.1$m
Progressive
Healthcare
Bushell, Mobley &
Shelest 2002
Primary care delivery
processes
• none reported in this
paper – about process
only
Miller 2005 Various. Details of
their approach given
in this paper
• inventory down 53%
• floor space down 41%
• distance travelled by
people down 44%
• setup time down 82%
Bush 2007 Various. Examples
given from each of
Ohno’s seven wastes
(Ohno & (translator)
Rosen 1995)
• waiting time from breast
cancer diagnosis to
initiation of treatment
down from 21 to 11
days
Nelson-Peterson &
Leppa 2007
Various but focuses
on nursing and
includes details of
how the approach is
applied.
• staff walking distance
down from 240 to 126
min per workflow cycle
• % of nurse time spent in
non value-adding activity
down from 68% to 10%
Intermountain
Healthcare
Jimmerson et al.
2005
Various • new medication orders
lead time reduced from 4
hrs to 12 mins
Park Nicollet
Health Services
(PNHS),
Minneapolis
Kim, Spahlinger, Kin
et al. 2006
Patient access • number of MRI and CT
scans performed each
day increased
• urgent care wait clinical
reduced from 122 to 52
minutes
Community
Medical Center,
Montana
Kim et al. 2006 Pathology • report turnaround time
reduced from 5 to 2 days
Place Source of
information
Area of
application
Reported benefits
(examples)

There are case studies of North American organisations available from a variety of sources,
the main one being the web site of the Lean Enterprise Institute8 (the US version of the UK
Lean Enterprise Academy which runs the Lean Healthcare Forums). Cases include the Mayo
Clinic, HôtelDieu Grace Hospital in Windsor, Ontario, and Massachusetts General Hospital.
NHS organisations reported as undertaking Lean initiatives9 not covered above include
(Table 16):
Table 16 – Reported applications of Lean in the NHS
In addition, a number or organisations are undertaking The Productive Ward/Community
Hospital/Leader/Operating Theatre initiatives within the NHS10 although the impact of these
has yet to be formally evaluated.
Australia
Flinders Medical
Centre,
Adelaide, South
Australia
Jones & Mitchell
2006,
Ben-Tovim, Bassham,
Bennett et al. 2008a,
Ben-Tovim, Bassham,
Bolch et al. 2007
Redesigning Care
Program:
emergency
department flows,
medical flows,
surgical flows,
now also extended to
support services,
mental health and
transition to
community care
• rates of serious adverse
events reported to
insurers halved since
programme began
• average emergency
waiting time fell by 25%
• increase in capacity led to
full functioning of
elective surgery
programme
• costs now below budget
Jones & Mitchell
2006
Ward ‘pull’
programme
• 20% increase in patient
turnover, median length
of stay in general medical
service by one day
Organisation Area of application
Gwent NHS Trust Various within overall improvement framework
Wirral NHS Trust Cardiology RIE
Salisbury NHS Trust Radiology
Wirral NHS Trust Pre-operative assessment/elective surgery
Mayday Hospital NHS Trust Sterile services
Kings College Hospital Various within overall improvement framework
George Eliot Hospital NHS Trust Diabetes
East Devon PCT Failure demand for emergency care
8. www.lean.org
9. www.leanhealthcare.org.uk - Presentations from the 4 Lean Healthcare Forums that have happened to date
10. www.institute.nhs.uk
Place Source of
information
Area of
application
Reported benefits
(examples)

Lean Six Sigma
It is claimed that Lean Six Sigma “holds great promise for optimizing the delivery of health
services because it maximises stakeholder value by achieving the fastest rate of improvement
in customer satisfaction, quality, cost, process speed and invested capital” (Forthman,
Wooster, Hill et al. 2003).
Lean Six Sigma in healthcare has been investigated in the context of its application in clinical
trials, in order to better understand customer requirements (Marti 2005) and in the context
of reducing medication errors (Esimai 2005). It is also included in a review of service
applications of Lean Six Sigma (George 2003). Outside the US, it has been applied in the
same Dutch hospital at which extensive Six Sigma use was previously noted (de Koning et
al. 2006).
To what extent does your organisation need to adapt the original principles of Lean
if it is to be successfully implemented?
Why is the Lean approach currently so attractive to healthcare organisations?
Are there areas where Lean tools would be beneficial, without requiring a full
organisational implementation of Lean thinking?
Lean Six Sigma in the NHS
Following the NHS Green Belt programme (section 5.3.3), the Juran Institute also delivered
a three-day Lean Six Sigma course, based on their own suggestion for how to combine Six
Sigma and Lean “to integrate the power of Six Sigma tools and Lean tools which can be
applied within an organisation to create the fastest rate of improvement, maximise
shareholder value and increase customer delight” (Juran Institute 2005). The NHS Institute
then compiled a document on its view of the potential for Lean Six Sigma (NHS Institute
for Innovation and Improvement 2006) and NHS change agents continue to advocate that
the NHS should create its own version of Lean Six Sigma (Westwood & Silvester 2007).
However, there seems to be no evidence of significant use of this approach in the English
NHS, beyond a brief report of work at Hereford Hospital (Westwood & Silvester 2007)
which identifies the use of some measurement techniques (e.g. to quantify variation in
demand) and analysis techniques (to understand root causes).
To what extent does your organisation understand the difference in focus
between Lean and Six Sigma?
Why might Lean Six Sigma be attractive to healthcare organisations?

5.5 Theory of Constraints
Theory of Constraints (ToC) developed from the Optimised Production Technology (OPT)
system first proposed by Goldratt in the early 1980s (Goldratt & Cox 1984). Goldratt believed
that ToC represented “an overall theory for running an organisation” (Goldratt 1988) and
although it had evolved from factory-floor concepts, it was applicable to the whole
organisation; constraints might be managerial-policy related rather than related to physical
things. The basic concepts of ToC are:
• every system has at least one constraint. If this were not so “a real system such as a profit-
making organisation would make unlimited profit” (Rahman 1998). A constraint is
anything that limits the system from achieving higher performance
• the existence of constraints represents opportunities for improvement. Constraints are not
viewed as negative, but as opportunities to improve
There are three components to ToC:
a. Prerequisites:
1. establish the goal of the organisation
2. establish what performance measurement system will support achievement of the goal
b. The Thinking Processes (TPs)
A set of tools, basically cause-effect diagrams, that help managers to think through answers
to three generic questions that arise when identifying constraints:
1. decide what to change
2. decide what to change to
3. decide how to cause the change
This can be characterised as a generic approach to “address policy constraints and create
breakthrough situations for them using common sense, intuitive knowledge and logic”
(Rahman 1998).
Tools include the Current and Future Reality Trees
c. The working principles, the Five Focusing Steps:
1. Identify the system’s constraints - physical, managerial or policy.
2. Decide how to exploit the system’s constraints - if physical; make it as effective as possible.
If managerial, eliminate it and replace with a policy that will support increased throughput.
3. Subordinate everything to the above decision - every other part of the system should be
adjusted to support the maximum effectiveness of the constraint.

4. Elevate the system’s constraints - if existing constraints are still the most critical, improve
them until the system encounters a new constraint.
5. If in any of the previous steps a constraint is broken, go back to step 1. Do not let inertia
become the next constraint - this shows that it is a continual process, and that no solution
is appropriate for all time, since the system itself is dynamic.
The best-publicised result of this approach is the drum-buffer-rope (DBR) approach to
managing constraints in process flow (see box). Time or stock buffers protect the constraint
from starvation, with visual buffer management using a traffic-light system.
Goldratt’s application of the ToC philosophy to project management has produced the
Critical Chain approach (Goldratt 1997, Rand 2000) in which time buffers are used to protect
the constraint of the completion date. A variation on the ToC approach is The Decalogue
(Lepore & Cohen 1999) which uses SPC control charts as a ‘front end’ to find and diagnose
problems to then address with ToC and stresses the links between ToC and
Deming’s thinking.
To a greater extent than in any of the other philosophies, ToC tends to be regarded as an
exclusive approach, being principally the creation of a one person, Goldratt, with training and
qualifications centrally-controlled.
There are relatively few published papers on the application of the approach, despite a large
number of theoretical papers. This may be because it has not been applied to any great
extent, or because the applications hove not been reported.
Drum-Buffer-Rope
• As the throughput-rate limiting step, the rate of work of the constraint should set the
rate for the whole process – it provides the ‘drumbeat’.
• Lost throughput opportunity at the constraint is capacity irretrievably lost to the whole
system, so the constraint is protected from starvation by a buffer. This can be a resource
buffer (containing physical items) or, in the project management (critical chain)
implementation of ToC, a time buffer. The state of this protective buffer must be
monitored very closely; often a traffic-light buffer-status system is used.
• To prevent unnecessary build up of inventory upstream of the constraint, work is only
admitted to the process upon receipt of a pull signal from the buffer – conceptually the
buffer status pulls a rope connected to the entry point to the system.

Where it has been reported, the research is “anecdotal and fragmented” (Lubitsh, Doyle and
Valentine 2005) and mainly from the US. Certainly this indicates a lack of substantial
academic research into its application, which it is expected would have yielded papers, had it
taken place. There are even fewer examples of its application in the service sector.
• Three descriptive articles of applying ToC in healthcare settings were located, one of which
is also military (Breen, Burton-Houle & Aron 2002, Kershaw 2000, Womack &
Flowers 1999).
• The Thinking Processes have also been used to argue that faster and sustained progress in
patient safety systems will only be achieved when sufficient attention is given to root
causes (Pauker, Zane & Salem 2005).
ToC in the NHS
In the UK there are two approaches to using TOC ideas in the NHS: using the Thinking
Processes and the Five Focusing Steps (see section 5.5.1) routinely in tactical and operational
management; and implementing constraint management software tools.
1. The concept-driven approach has been used in a limited number of hospital trusts and
health boards in England, Scotland and Northern Ireland, one of which has also been
using the Decalogue variant. Real application to the NHS, including cross-organisational
work in mental health has been described (Ritson & O’Neill 2006, Ritson &
Waterfield 2005).
• Applications in surgery have been tested as part of two doctoral theses (Lubitsh et al 2005)
and (Nuttall 2005).
• Nottingham Trent University has started an MSc for NHS employees teaching a ToC
approach to operations management.
• We All Fall Down (Wright & King 2006) is a ‘business novel’ in the style of The Goal, which
gives illustrations of the application of the ToC approach (including the Thinking Processes)
to improving patient flow management in the NHS.
2. The software-driven approach developed from work by Ashridge Consulting (Knight
2000/1). The key people involved from Ashridge Consulting (now working as Goldratt
Consulting or QFI Consulting) decided that the most promising approach was to
incorporate the drum-buffer-rope ideas in software tools at critical constraint points in
patient flows, and it is this approach which now dominates UK ToC application.
• Simple time-buffer coordination and management ideas have been used to develop a set
of IT tools (‘Jonahs’), initially in Oxfordshire (Goldratt Group and Oxford Radcliffe Hospitals
NHS Trust 2003). These help manage individual patients through database-driven traffic-
light buffer management. The main three Jonahs are:
a. monitor waiting times against the 4-hour A&E target
b. schedule discharge arrangements to hit predicted discharge dates
c. schedule key resources to protect operating theatre utilisation

• recording and audit of reasons for breaches of the buffers is encouraged, and can provide
powerful quantitative data to support cases for more resource to protect key constraints.
They are very much practical, operational reactions to current problems, rather than
promoting fundamental rethinking
• the Accident and Emergency department (A&E) wait and discharge planning Jonahs have
been adopted by many hospitals in England and a few in Scotland and Wales through
QFI Consulting
• the discharge tool has been compared with other hospital-flow software tools (Proudlove
& Boaden 2006a)
ToC is not an approach that has even been promoted on a national basis within the NHS,
beyond the inclusion of The Goal on reading lists associated with various improvement
training programmes. There are a number of reasons for this:
• ToC is quite complex when all the parts are considered:
• ToC is closely associated with one commercial umbrella organisation, the Goldratt Group,
so there are potential issues about provision of and capacity for training and consulting. In
the NHS, ToC/Goldratt is becoming identified with the software and associated
implementation consulting. We have been unable to identify anyone who led
improvement at a national level within the NHS who is formally trained in ToC, unlike
Lean, Six Sigma etc
• there appears to a perception of arrogance about the way it is promoted as the
only solution
A review of ToC across all sectors (Mabin & Balderstone 2003) states that over 400 articles
and 45 books have been published on the subject since 1993, but without much systematic
assessment of its impact. This review showed that those manufacturing organisations
employing ToC did report it to be a substantial source of competitive advantage, but that
many did not use the thinking process aspects of ToC.
The lack of rigour in reported research means that there is little evidence that has been
independently assessed.
• analysis of the use of drum-buffer-rope management (Lubitsh et al. 2005) found some,
though not dramatic, improvement in two of three surgical specialties and noted the
impact of organisational complexity and culture, and the importance of tailoring
implementation to local circumstances
• similarly, (Nuttall 2005) achieved modest improvements in performance and noted
fundamental cultural barriers in the organisation such as the absence of consensus on the
‘goal’ of the organisation and externally and internally imposed performance measures
• the Thinking Processes are claimed to have fitted well with NHS culture and facilitated
negotiation between professionals (Ritson & O’Neill 2006, Ritson & Waterfield 2005)

• the Ashridge work (Knight 2000/1) claims a variety of outcomes, summarised as the ability
to “simultaneously increase the number of patients treated and improve the quality of care
and without extra resources” (Knight 2000/1)
• subsequently (Umble & Umble 2006) reproduced Goldratt Consulting/QFI data that
illustrates considerable improvement in A&E four-hour performance in the period following
A&E Jonah implementation. No formal evidence of the effects of using the other Jonah
tools has been published, beyond anecdotes and internal results presented at conferences
5.6 Mass Customisation
5.6.1 Outline of what the approach is
Mass customisation is generally defined as “the ability to produce products or services in high
volume, yet vary their specification to the needs of individual customers or type of customer”
(Slack, Chambers & Johnston 2007, p.47). It is intrinsically linked to the variability of the
process and the resultant service provided (see section 6.1.5).
Customising each product or service for each customer can mean high costs, and has been
described a “both an imperative and a potential curse” (Gilmore & Pine II 1997, p.91).
Warnings that “any operations wishing to push their processes in this direction need to think
very carefully about the technology and skills required to operate effectively, and profitably, in
this area.” (Johnston & Clark 2005, p.191) abound, yet interest in this approach continues to
increase. One way of addressing the cost and complexity challenges may be to be clear
about the type of customisation to be pursued (Gilmore & Pine II 1997):
• collaborative: dialogue with individual customers to help them identify their needs and
then to produce customised products or services for them
• adaptive: a standardised product is offered, that can be customised
• cosmetic: presenting a standard product differently to different customers, usually through
packaging
• transparent: providing customers with unique goods and services without letting them
know that they have been customised for them. Appropriate when customer needs are
predictable or can be easily deduced
What is the goal of your organisation?
What are your system's constraints - physical, behavioural or policy?
How might the principles of ToC be used?
What is the ‘drum’ driving the pace of flow in your processes?

These approaches can be combined but may have implications for the way in which the
organisation operates. It has also been suggested that various principles of operation may
apply to any type of customisation, again to minimise cost and complexity:
• Develop standard modules. ‘Menus’ of standard services can be developed, which can
then be arranged in appropriate combinations to provide a degree of customisation for
individual customers. The achievement of customisation is therefore contingent on the
management of the combination of services rather than the development of new services.
(Johnston & Clark 2005)
• Postpone customisation until the latest possible stage. In this approach the delivery process
is standardised for all stages until the last possible moment. This allows the service to gain
the benefits of efficiency and consistency that are found in high volume/low variety
processes (McLaughlin & Kaluzny 2000, p.77)
• Understand the process by which customisation takes place (McLaughlin 1996).
In pursuing mass customisation, when the number of service delivery processes increases
significantly, a major transition can occur. In such circumstances it is recommended:
• flexibility of the parts of the organisation dealing directly with customers is increased
• customer-facing staff are required to give informed advice as to the best service for an
individual customer
• customer-facing staff are ‘upskilled’ through a combination of greater staff training and
supportive information systems
• processes are designed to be more flexible and allow greater discretion on the part of the
employee (Johnston & Clark 2005)
However, an alternative view of mass customisation (Boynton, Victor & Pine 1993) describes
it as a strategy to be adopted by organisations where process change is stable but
product/service change is dynamic. Other strategy options in this model are mass production
(for stable process and product change), innovation (where both process and product change
is dynamic) and continuous improvement (where process change is dynamic but
product/service change is stable).
A theoretical assessment of the application of this model within healthcare (McLaughlin &
Kaluzny 2000) highlights that the path to mass customisation as a strategy is different in
healthcare from other industries. Healthcare is traditionally a ‘craft’ industry, characterised by
process innovation and product variety. Following a move to more emphasis on process
improvement, healthcare may then develop into mass production, but only if “the approach
is sufficiently cut and dried, the volume is high and the patient will accept this impersonal
mode of delivery” (McLaughlin & Kaluzny 2000, p.77). These authors then see mass
customisation as the strategy “that will satisfy health care customers at low or reasonable
relative costs” (McLaughlin & Kaluzny 2000, p.77), although it will involve less stability in
healthcare processes as effectiveness improves (McLaughlin 1996).

5.6.2 How the approach fits with other approaches
This approach is different in that it is not an approach to improvement, but rather one
focusing on process and system design (see section 6.1.3).
It is increasingly argued by some authors that mass customisation is the next stage after
process improvement activities, which are “simply stopping points on the way to the efficient
and effective health care system that consumers desire” (McLaughlin & Kaluzny 2000, p.82).
However, there is no empirical evidence presented to support this assertion.
Despite a large number of research papers detailing mass customisation in a manufacturing
environment, there is a paucity of literature that describes the application of the approach to
healthcare, or even to other types of service organisation. Reasons for this may include:
• the natural process variability and the high degree of autonomy in healthcare systems
(McLaughlin & Kaluzny 1997)
• the fact that a change to more customisation is required, but has not yet been; “We
should be able to coach organisations to implement … models that we will change as we
learn, so as to achieve that other industries call ‘mass customisation’” (Berwick 2005,
p.325)
• the technology is not readily available. The US-based Center for the Health Professions
advocates the use of mass customisation in healthcare but believes that the ‘high tech and
high touch’ (Naisbitt 2001) approach that is required ‘is well beyond where health care is
today’11
However, some authors have described the potential of mass customisation to improve
healthcare as:
• a mechanism for creating more effective health professional teams that can measure
results and systematically improve clinical outcomes while reducing costs (James 2005)
• a means of maintaining system performance as processes change. NHS hospitals have
been viewed as the service equivalent of a batch manufacturing system (Silvestro 1999) as
patients are moved from one department to another in complex, long distance stop-start
flow patterns. However, it widely recognised that processes must move from batch to
mass production as their output volume increases or the performance of the system can
be seriously affected (Walley et al. 2006a)
• a benefit for disease management as it permits patient subcategories that are large
enough to warrant separate contact but not so small that they present an administrative
burden (Miller 2003)

• a mechanism for better meeting the needs of patients. A study that examined the
potential of mass customisation (Thompson & Nussbaum 2000) concluded that there are
“practice opportunities and the need for further research in order to implement mass
customisation in healthcare” (Thompson & Nussbaum 2000 p.19). The notion of improving
flexibility in systems is also described as important here: “It is the waste and inflexibility of
our own work system that forces us into uniformity towards patients when more agile
systems would respect their diversity” (Berwick 1997)
Other examples of applications include:
There are no independently evaluated examples of outcomes of mass customisation in
healthcare that have been reported to date.
Are there any processes in your organisation for which mass customisation could
be appropriate?
How will you identify the needs of your customers?
11. http://futurehealth.ucsf.edu/from_the_director_0105.html.
Custom printed information materials that are built for each individual patient and are
termed ‘snowflake technology’ as no two patients receive exactly the same information
(Miller 2003 p.47)
Clinical pathways that integrate information systems to provide highly specific
information about each patient-background, preferences, health status and the optimal
co-ordination of services (Fitzgerald & McLaughlin 2001)
It is argued the NHS Direct telephone service follows a “hybrid mass customisation
model” (Goode & Greatbatch 2005, p.316). As the service is purely an advice line its
impact on healthcare, and the value of taking a mass customisation approach, has been
difficult to ascertain (Florin & Rosen 1999).

The approaches to quality improvement detailed in this report are all based on a series of
underlying concepts, with different emphasis on each one depending on the approach
concerned. The purpose of this section is to outline these concepts and to show how they
support the various approaches to quality improvement, as well as to demonstrate the
implications for using the approaches in practice. Their application to the healthcare context
will also be explored.
These concepts might be described as underlying operations management, a well-established
academic discipline (Voss 1995); although the concepts are described in different ways by
differing authors (Slack et al. 2007).
Every organisation has a function that can be described as operations because every
organisation produces products, services or a combination of the two. Operations
management focuses on examining the processes that are used to produce these goods and
services. Effective operations management has the potential to keep costs down, improve
revenue, appropriately allocate resources and develop future competitive advantage (Slack et
al. 2007). It has been argued that modern operations management principles are supportive
of what many clinicians have been suggesting for a long time (Walley 2003a) but it is argued
that research in healthcare rarely take an operations management perspective (Davies &
Walley 2000).
The concepts described here are:
• systems and processes
o systems thinking in healthcare
o the process view
o process design in healthcare
o managing flow
o variation
• the role of the customer
• balancing supply and demand:
o capacity management
o demand management
o inventory management
In each section, the link between the concepts and the approaches to improvement (see
section 5) is described, along with any evidence of the use of these concepts within
healthcare.
6. UNDERLYING CONCEPTS

6.1 Systems and processes
Systems thinking has been an approach to viewing organisations for many years, with the
divergence between hard systems and soft systems being made later in its development
(Checkland 1981). Systems thinking is also the basis of recent emphasis on organisational
learning (Senge 1990). It can be described as exploration of “the properties which exist once
the parts [of the system] have been combined into a whole” (Iles & Sutherland 2001).
This systems view is claimed by operations management academics as the key to their
approach (Slack, Chambers, Johnston et al. 2006), and it described as one of the “persistent
themes” in a recent review of the development of the operations management field
(Sprague 2007)
The systems view is fundamental to a lot of the thinking in improvement, perhaps particularly
to Deming’s insights, and is inherent in many of the approaches discussed in section 4. This
has been appreciated to be a strength in the healthcare context, e.g. “healthcare is taught to
look at the system – that’s exactly what Six Sigma does” (Scalise 2003). Other authors argue
that an operations management approach based on systems can be applied to hospitals
(Mango & Shapiro 2001)
A current proponent of systems thinking in the public sector and healthcare context is John
Seddon, whose approach is built on interpreting and applying the fundamental principles of
Deming and the TPS in the context of service organisations; a Lean approach but with few
tools (Seddon 2005a). It emphasises understanding demand and the capability of the system,
introducing appropriate measures, introducing ‘cLean’ flow, reducing failure demand and
designing a system to absorb variation. Seddon has adopted the label ‘systems thinking’ for
these principles, and claims that this is “diametrically opposed to command and control
thinking” (Table 17).
Table 17 – Command and control versus systems thinking (Seddon 2005a)
COMMAND AND
CONTROL THINKING
SYSTEMS THINKING
Top-down, hierarchy Perspective Outside-in, system
Functional Design Demand, value and flow
Separated from work Decision-making Integrated with work
Output, targets, standards:
related to budget
Measurement Capability, variation: related
to purpose
Contractual Attitude to customers What matters?
Contractual Attitude to suppliers Cooperative
Manage people and budgets Role of management Act on the system
Control Ethos Learning
Reactive, projects Change Adaptive, integral
Extrinsic Motivation Intrinsic

A full systems view of improvement should avoid the risk of local improvement resulting in
sub-optimisation of the wider system. Of the approaches discussed in section 4, TOC is most
explicit in emphasising looking upwards to appreciating the overall goal of the system and
using performance measurement systems that support this goal.
6.1.1 Systems thinking in healthcare
Systems thinking has also been proposed as a means of understanding medical systems
(Nolan 1998), based on the following principles:
• a system needs a purpose to aid people in managing interdependencies
• the structure of a system significantly determines the performance of the system
• changes in the structure of a system have the potential for generating unintended
consequences
• the structure of a system dictates the benefits that accrue to various people working in the
system
• the size and scope of a system influence the potential for improvement
• the need for co-operation is a logical extension of interdependencies within systems
• systems must be managed
• improvements in systems must be led
Design of healthcare systems has focused in more recent years on hospitals forming health
service partnership based networks aimed to provide the public with access to a broad
spectrum of services and seamless coordinated care (Addicott & Ferlie 2007, Li, Benton &
Keong Leong 2002). Cancer services are an early example of this practice. Managed
Clinical Networks (MCNs) have been established by the NHS “as a means to streamlining
patient pathways and fostering the flow of knowledge and good practice between the
many different professions and organisations involved in care” (Addicott & Ferlie 2007
p.393). The aim is that all providers of cancer care for a defined population work together
to deliver high quality care (Leese, Heywood, Allgar et al. 2006). The evidence of their
effectiveness to date is developing quickly (Addicott, McGivern & Ferlie 2006, Robert et al.
2003) and the transfer of knowledge between practitioners as part of network activity has
been shown to be substantial (Nicolini, Powell, Conville et al. 2007).
6.1.2 The process view
A consequence of viewing organisation and networks, as systems is an increased focus on
the processes which comprise such systems. Academics from many fields have recognised the
importance of the process view, where process management is defined as entailing three
practices: mapping processes, improving processes and adhering to systems of improved
processes (Benner & Tushman 2003) – an approach that is reflected in much study of both
quality improvement and patient safety.

Clinical and managerial processes have sometimes been interpreted as discrete and a largely
unconnected set of activities within the delivery of healthcare (Sorensen & Ledema 2008),
with the subsequent effect of producing misaligned objectives and a lack of strategic focus
on the most important areas for improvement. The conflict between clinical and managerial
priorities is often most apparent when defining quality, especially when performance metrics
are associated with tangible aspects of process quality (e.g. waiting times) rather than patient
experience or clinical outcomes.
It is argued that taking a process view is one of the key characteristics of organisations who
are successful in improvement, along with adopting evidence-based practice, learning
collaboratively and being ready and able to change (Plsek 1999). This process view is not only
about changing organisations but also examining and improving the interaction between
elements of the organisation, including the individuals who work within them.
It is interesting that the approach which has probably had the biggest impact in the NHS to
date (PDSA) does not explicitly refer to processes (Langley et al. 1996), although the
approach appears to be based on the assumption that work is or can be organised into
processes. Given the origin of this, and many other quality improvement approaches, in the
manufacturing sector it was perhaps seen to be obvious that work was organised in this way.
A key principle of operations management relates to processes and their design. This includes
physical layout, but is not limited to this, as the increased emphasis on services and their
organisation means that processing information is vital to the effective operation
of organisations.
The Lean and TOC approaches focus on flow, so have tools in their toolkits to design flow
systems according to their philosophies. Other improvement approaches focus more on the
analysis of existing process design, rather than providing guidance on how to design
a process.
6.1.3 Process design in healthcare
Designing care processes is cited as a key decision area within healthcare delivery systems
(Roth 1993). As the outcomes of the healthcare delivery process include the patients’ health
status and their perceptions of their care experience, Roth (1993) suggests four factors that
play a role in designing healthcare processes:
1. Explicit healthcare services: these are the service processes that satisfy the basic healthcare
needs of patients.
2. Implicit benefits: these include psychological or ‘implied’ benefits derived from the service
encounter, such as relief or delight.
3. Delivery channels: this factor includes the patient interface with the organisation and the
availability of relevant information regarding this interface.

4. Facilitating materials: these are the support tools, techniques, services, supplies and
goods used in providing care.
The principles of process design have been used in a variety of situations within healthcare:
• some success in using operations management approaches in redesigning process layouts
has been described (Walley et al. 2006a), albeit not known to be operations management
by the hospitals involved, based on volume variation analysis in A&E departments
• the NHS Institute for Innovation and Improvement has champion process redesign as an
effective way to achieve the target of an 18-week patient pathway through its ‘No Delays’
programme12
• experience based design (EBD) as a way of capturing and understanding how patients’
and carers’ experience healthcare in order to improve services13
• various experiences of process redesign in Australia have been reported (MacLellan,
Cregan, McCaughan et al. 2008, McGrath, Bennett, Ben-Tovim et al. 2008, O’Connell,
Ben-Tovim, McCaughan et al. 2008). The stages that may be involved in a redesign
programme are shown in Figure 8
Some change initiatives within healthcare have been labelled as process redesign (Locock
2003) although these have tended to be focused on single processes rather than whole
organisations. There appears to be an interest in the term ‘process redesign’ (Ben-Tovim et al.
2008b), as shown in Figure 8, although closer examination shows that these initiatives are
also labelled as Lean.
Figure 8 – The phases of clinical process redesign (Ben-Tovim et al. 2008b)
12. http://www.institute.nhs.uk/no_delays/introduction/no_delays.html
13. http://www.institute.nhs.uk/quality_and_value/introduction/experience_based_design.html

6.1.4 Managing flow
Flow through a process is a key concept in operations management, largely derived from the
manufacturing experience. While this draws on the concepts of capacity, demand and
inventory (see section 6.3), it merits separate consideration because of its current popularity
in healthcare.
The Lean approach focuses on elements of processes, to operationalise its principles of
smooth pull-based flow. Similarly ToC leads to the design of a process with the focus on a
critical buffer which protects the key constraint to maximising the system’s goal, with a rope
pull mechanism.
The importance of flow is increasingly emphasised within healthcare (Brideau 2004), with
work by IHI in the IMPACT network in the US (Haraden & Resar 2004). These authors
maintain that understanding variation (see section 6.1.5) is essential to improving flow.
The basis of the IHI approach is summarised in Table 18.
Table 18 - IHI approach to improving flow (Institute for Healthcare Improvement
2003)
Understanding and evaluating flow requires more detailed understanding of demand and
capacity than has often been the case in healthcare organisations (Horton 2004).
One author (Zimmerman 2004) proposes that studying and improving flow leads to a need
to consider alignment – within the whole healthcare system, within pre-hospital care, of
goals within the system, especially between healthcare organisations and clinicians. This will
inevitably lead to whole-systems approaches to improvement (see section 6.1.1).
6.1.5 Variation
The emphasis on variation in the improvement approaches discussed in section 4 differs.
Approaches based on statistical thinking (SPC, Six Sigma) are based on the principles that
(Antony 2004):
• all work occurs in a system of interconnected processes
• variation exists in all processes
• understanding and analysing the variation are keys to success (Snee 1990).
Step 1: Evaluate flow: how much of the time do you get it right?
Step 2: Measure and understand flow variation
Step 3: Test changes to improve flow
changes within the hospital
changes that result in cooperative relationships with other healthcare providers outside
the hospital

Lean also suggests reducing process variation (in the interests of making flow as smooth
as possible).
These principles are also in line with Deming’s view (Deming 1986) that as variation is
reduced, quality is improved. The way in which these principles may fit with an overall quality
improvement approach is shown in Figure 9.
Figure 9 - Statistical Thinking in Quality Improvement (Snee 1990)
In contrast, ToC stresses the design of processes to absorb the inevitable variation in demand
volume and the variability in its content through buffer management. A realisation of the
importance of absorbing variation and variety, including the use of mass customisation (see
section 5.6) in attempts to use Lean in UK public services has been observed (Radnor &
Walley 2006).
Variation is argued to be inherent in healthcare (Haraden & Resar 2004), and the result of
clinical (patient) flow, and professional variability (Institute for Healthcare Improvement 2003).
Patient variability is random and cannot be eliminated or reduced, but must be managed,
whereas non-random variability should be eliminated. This links with the concepts of causes
of variation which are the basis of SPC (see section 5.2). It is argued (Institute for Healthcare
Improvement 2003) that “it is variation … that causes most of the flow problems in our
hospital systems”.
6.2 The role of the customer
Another concept which underpins most of the approaches in this review is that of identifying
the customer, who may be internal or external to the organisation, and subsequently the
needs of the customer. Whether the customer is explicitly identified, or whether their
requirements are translated into a clear objective for a process (the first principle of medical
systems identified by (Nolan 1998)), the purpose of the process has to be clear before
improvement can take place. All industrial approaches to quality improvement involve the

identification of the customer, who may be internal or external to the organisation and,
subsequently, their needs.
• in Six Sigma what is ‘critical to quality’ as far as the customer is concerned is used to
define the measures used to determine the ‘defects’ to be reduced
• similarly, in Lean the customer’s conception of value (which might be thought of as the
ratio of benefits to costs) defines which bits of processes are useful (value-adding), the rest
being waste (steps or components the customer would not wish to pay for)
• interestingly, while Six Sigma and Lean are predicated on the principle that the system
should seek to provide more quality or benefit to the customer and/or at lower cost, ToC
does not automatically assume this is the way to maximise the goal of the organisation
6.2.1 Who is the customer in healthcare?
The concept of customer needs driving improvement was developed in manufacturing where
the ‘customers‘ of a process are usually easy to identify. Usually they are those receiving the
product of the process and – critically – the ones to make the judgement on whether they
wish to pay for that product at that level of quality at that cost.
However, this is more complex in healthcare systems and whether the ‘customer’ can be
defined as the patient is open to question. This issue has been debated especially in the
context of Lean implementation, where the customer is the driver of value and questions
have been asked about “the extent to which patients, service providers, or even taxpayers
equate to customers in the commercial setting and the way in which health outcomes,
patient satisfaction, or even cost can be legitimately used to define value.” (Young et al.
2004, p.162). Views on this include:
• the customer “will generally be the patient” (Jones & Mitchell 2006, p.16)
• “An “obvious” customer in healthcare is the patient. However, other customers exist. A
customer is someone who uses something that it made or was provided by a previous
process step” (Westwood et al. 2007, p.5)
• the patient may be seen as the primary customer, but the patient does not pay directly for
services where they are publicly funded – other customers may include the patient’s family,
and society in general, as well as commissioners. “Depending on the perspective, the
definition of value will hence differ. However, because the main mission of healthcare is to
treat and cure patients … it is argued that the patient should define what creates value in
healthcare” (Kollberg, Dahlgaard & Brehmer 2007, p.12)
• in the public sector the processes by which decisions are made could themselves be
regarded as the customers. The principle of due process (Scorsone 2008) may determine
the steps in the process and the pace at which they are carried out, whether or not they
are perceived as adding value

It is clear that to date patient involvement in quality improvement has been limited (Silvester
et al. 2004) with lack of attention to the presence of the patient in processes (Shortell, Levin,
O’Brien et al. 1995) and lack of consumer power also being cited as important (Zbabada,
Rivers & Munchus 1998). It is also argued that the market structure of healthcare in the UK
at least does not enable ‘consumers’ to alter the behaviour of healthcare providers as there is
no effective choice (Zbabada et al. 1998).
6.3 Balancing supply and demand
Balancing the supply of services with the demand for them is often referred to as planning
and control and is perhaps the more traditional territory of operations management. As a
result this is the area where there has perhaps been most application of operations
management principles within healthcare. There are several aspects to this:
6.3.1 Capacity management
Capacity management is the ability to balance demand from customers (or patients) with the
capability of the service delivery system to satisfy the demand (Armistead & Clarke 1994).
In examining the use of capacity management in four NHS trusts one study concluded that
“there appeared to be little correlation between approaches to capacity management from
clinical perspectives, and those which appear in the service management literature”’ (Davies
& Walley 2000, p.24). It is argued that capacity management proves difficult in hospitals due
to the scheduling and processing of patients and the difficulty in consistently gaining high
utilisation of resources because capacity bottlenecks move within the healthcare system
(Walley et al. 2006a). There is evidence that the focus of most hospitals is on long-term
aggregate capacity due to demand trends and budgetary requirements. As a result,
healthcare managers do not respond to incremental changes in volume or variety, leading to
a mismatch between skill mixes, staff grading and job design compared to ideal process
requirements (Davies & Walley 2000).
Bed management has been described as a component of healthcare capacity management
(National Audit Office 2000), with the purpose of bed management being defined in the
following terms: “hospitals have to balance, ensuring the availability of beds against the
efficient utilisation of an expensive hospital resource” management (National Audit Office
2000, p.33). However, research shows that in practice bed managers are rarely consulted
about capacity planning issues (Boaden, Proudlove & Wilson 1999, Gemmel & Van
Dierdonck 1999).
Like all operations, healthcare systems have to cope with varying demand and supply and will
need to consider adjusting capacity accordingly. Operations management theory details
various plans for treating such variation (Slack et al. 2007):

Level capacity plan
This ignores demand fluctuations and keeps nominal capacity levels constant. A level capacity
strategy elevates the cost objective for hospitals seeking to maximise the utilisation of scarce
resources, such as those tied to acute inpatient beds, under the premise that patients are
willing to wait for services they highly value.
Chase demand plan
This adjusts capacity to reflect fluctuations in demand. A chase demand strategy recognises
the pre-eminence of service quality, particularly in relation to waiting times for patient access.
The initiation of ‘winter plans’ starting in 1996, where NHS hospitals and wider social and
healthcare service capacities were increased, arguably demonstrates that chase demand
strategies have been increasingly adopted as service quality has become less negotiable
(Department of Health 2004).
Coping
A further capacity management strategy has been termed as ‘coping’ (Johnston & Clark
2005) - when operations are too busy and perceived quality begins to decline (Armistead &
Clarke 1994). Hospital coping strategies noted in the literature include:
• a practice termed as outlying, where patients are placed into beds from alternate bed
pools that are capable of meeting minimum medical needs. Although this practice usually
involves putting an emergency medical patient (a medical outlier) into a surgical bed, the
reverse is possible. Such approaches are believed to decrease productivity (National Audit
Office 2000), and any subsequent repatriation transfers are anecdotally said to increase the
length of stay by one day per move, thus increasing costs whilst reducing the capacity
available (Proudlove, Gordon & Boaden 2003)
• re-designating beds to meet patient needs. Examples include switching male wards to
female wards or vice versa. It is reported that 87% of NHS trusts use this approach
(National Audit Office 2000)
• load sharing, where emergency patients are admitted in one hospital’s A&E department
and transferred for placement in another hospital’s beds (Boaden et al. 1999)
• expediting inpatient discharges from acute beds. It is reported that 98% of acute trusts
used this approach (National Audit Office 2000)
• cancellations of elective patients. This practice has been described as an important ‘safety
valve’ for coping with bed crises wherein the needs of one customer group are traded
against another (Jones, Joy & Pearson 2002)
Armistead and Clark (1994) highlight that although coping practices are in common use by a
variety of frontline staff in service industries, most managers are unaware of entering coping
zones and what the trigger points are. Such findings suggest that coping is a tactic rather
than a strategy as its implementation is uncontrolled, unplanned and lacking objective
measures to ascertain whether the operation is about to enter or leave the ‘coping zone’

(Conyon 2006). For example research in healthcare has shown that:
• 25% of hospitals do not make short-term forecasts about likely bed availability (National
Audit Office 2000)
• limited used is made of demand pattern data and information systems are poor (Boaden
et al. 1999)
• bed managers have been described as being permanently engaged in ‘firefighting’ with
‘no beginning and end’ (Morell, Green & Armstrong 1994), indicating that coping is the
norm and not a distinct strategy
6.3.2 Demand management
An alternative to managing capacity is to attempt to alter the demand for the service:
demand management. Services have different characteristics from products and unused
production (lost service potential) cannot be stored for sale (use) later. Research shows a
limited understanding of the nature of demand in hospitals, the implications of which are
delays for patients (Davies & Walley 2000).
Examples of demand management in healthcare include:
• in a study of US obstetrics (Heineke 1995) demand for hospital services was shown to
depend on many unpredictable factors, such as the time that services are needed and the
type of professional skill that is required. Better performance was associated with clear
policies regarding access and the use of very structured procedures for patient admissions
• a survey conducted in US community hospitals found that an emphasis on demand
management contributed to more desirable cost and quality performance, which lead to a
better financial performance (Li et al. 2002). The use of guidelines has been advocated to
manage the issues of hospital inpatient admission and inpatient and output surgical
schedules based on expected length of stay
Failure demand
Demand for services can also be created as a result of not satisfying the customer the first
time. This is sometimes labelled failure demand (Seddon 2005a), and can result from a
number of system failures: part of the system having earlier failed to satisfactorily provide the
service; a customer failing to understand the system’s expectations of them or being unaware
of an alternative, more-appropriate system; or the organisation not having such an
alternative. This is a major waste of capacity in systems such as call centres. Failure demand
has a huge impact on NHS capacity, for example A&E attendances or GP referrals leading to
inappropriate emergency admissions (of patients who don’t need inpatient treatment) and
inadvertent admissions (of patients needing treatment of a type for which a more
appropriate pathway is not available).

6.3.3 Inventory management
Inventory can be used to maintain operational performance by providing a buffer against
uncertainty and variation of demand and supply (Slack et al. 2007). There is a performance
trade-off associated with keeping inventories; although process utilisation is increased,
inventories can adversely affect the time a job has to wait in queues and increase the storage
costs. There is a view that reducing inventory will lead to the exposure of other systems issues
which are otherwise hidden (see Figure 10).
Figure 10 – Reducing the level of inventory enables management to see the
problems (Slack et al. 2006).
Inventory in service organisations can be interpreted as people (customers) waiting in a
queue. Waiting time in the queue is a function of:
• V (the variability in the queuing system)
• U (the utilisation of the queuing system, that is, demand versus capacity)
• T (the processing times at the station).
This leads to the VUT formula (Slack, Chambers & Johnston 2004) in operations
management: queuing time will increase as variability, utilisation or processing time increases.
This was illustrated in the NHS by an analysis of the impact of bed utilisation on length of
wait for admission (Bagust, Place & Posnett 1999). This influential work led to the DH
recommending a bed utilisation target for hospitals. However, the differing VUT trade-off
resulting from different contexts (e.g. emergency medical vs. elective surgical units) was
misunderstood by some leading improvement in hospitals (Proudlove et al. 2007).

It is reported that many patient ‘inventories’ remain hidden, only being identified through ad
hoc manually collated surveys (Audit Commission 2003, National Audit Office 2000) since
they do not always constitute physical queues. Even where the patients were physically
present, pressure to meet NHS A&E waiting time targets is reported to have led to patients
being ‘stored’ as inventory (Walley et al. 2006a), unnoticed in a bed not a trolley, instead of
being observed carefully by the right people and equipment.
Queuing is also about the experience of those in the queue, and in parallel with more
general findings in operations management findings about the subjective experience being in
a queue (Slack et al. 2004), it has been found that simple steps can improve patients queuing
experiences. Efforts to keep patients informed of the likely length of wait improve
perceptions of service quality (Lovelock 1992). Patients were found to be happier to queue if
(Green & Armstrong 1994):
• they believed that hospital staff were aware of them
• they believed that something was happening
• they knew what to expect
Moreover, patient perceptions of what was most medically urgent also influenced their
readiness to wait for admission, with cases described where patients actually believed that
others should go before them in the queue (Green & Armstrong 1994).
Differences between the perceived wait of emergency patients waiting in A&E for a bed and
recorded lengths of waits on hospital information systems have also been published and
show that patients perceived their waits to be longer than the hospital reports indicated
(Healthcare Commission 2006a). This may be attributed to:
• inaccuracies in hospital reporting systems (Conyon 2006)
• the patient experience making waiting time seem longer than it was (Lovelock 1992)
• escalating customer expectations despite reductions in customer waiting times (Healthcare
Commission 2006a)

6.4 Underlying concepts and approaches to
improvement
The concepts described in the previous sections are all used in the approaches to
improvement, but the emphasis varies.
Table 19 summarises the key foci of each approach in relation to the concepts of process,
customer focus, variation and flow.
Table 19 – The relationship of the approaches to the main concepts
It could be argued that only Lean and TOC are overall approaches to improvement with the
other approaches described here being tools that can be applied in various approaches.
However, the development of PDSA into the model for improvement and the extension of Six
Sigma from a statistical analysis tool to an overall approach mean that many would now
consider these to be overall improvement approaches with their own underlying
philosophies. SPC is however a tool, albeit one which can be utilised in all the approaches
described here.
Process view Variation Flow Customer focus
All approaches
assume there is
a process focus,
although some
regard it as
more
fundamental
than others
All these themes may be important, depending on the
answer to the first question from the model for improvement
and the change concepts derived as a result of
considering thethird question
Main focus
Leads to definition of
control limits for process
Main focus
Main focus
The driver for definition of
what needs to be improved
Reducing waste, which may be
related to variation and/or flow, is
the focus. Flow tends to be
emphasised more (Seddon 2005b)
Leads to the definition of
value which determines
where improvement is
focused
Leads to the definition of
performance measures and
targets for improvement
PDSA
SPC
Six
Sigma
Lean
ToC
Do you know who your customers are?
How do you balance the competing needs and wants of different customer groups?
What techniques do you use to balance the supply of your services with
the demand for them?
What is your predominant approach to quality improvement? How do you know whether
it is the most appropriate?
In what situations, and when, might it matter which approach to improvement you are
using, and how rigorously you are using it?

Many of the issues about translation stem from the exploration of the extent to which
healthcare may be different from other industries, and the implications this may have for the
application of quality improvement approaches in this sector. Other translation issues focus
on the success (or otherwise) of these approaches in other sectors and how research in this
area may be judged.
7.1 The difference between healthcare and other
sectors
Even within the public sector, an argument can be made that the healthcare sector is
different; an argument that does not simply apply to healthcare in the UK, with healthcare
organisations described as showing “striking fragmentation and turbulence that impede their
capacity to provide quality care …” (Ramanujam & Rousseau 2006, p.811).
Compared to the private sector, the NHS can be characterised by (Pollitt 1993):
• the range and diversity of stakeholders
• tts complex ownership and resourcing arrangements
• the professional autonomy of many of its staff
Healthcare may be simply different in emphasis from other public services, rather than
fundamentally different from other service organisations (Radnor & Boaden 2008).
7.1.1 Healthcare is a professional service
Like accountancy and law, healthcare organisations are ‘professional’ (Mintzberg 1979) and
characterised by high levels of professional autonomy. Details of the implications of this are
well summarised elsewhere (Buchanan, Fitzgerald & Ketley 2007) but some of the elements
are shown below:
7. TRANSLATING IMPROVEMENT
APPROACHES TO THE HEALTHCARE
CONTEXT
Features of the professional organisation
• Professionals have considerable autonomy and discretion, as their work involves the
application of knowledge and expertise to complex problems
• Professionals are loyal to their profession and committed to their clients rather than to
their employing organisation
• Professionals work independently, without reference to each other or to management
• Managers cannot develop strategy independently, but must persuade professionals to
support and champion initiatives
• High-quality work is based on internalised values, beliefs and aspirations, developed
through training, rather than on formal bureaucratic controls
(Buchanan et al. 2007, p.253), based on (Brock, Powell & Hinings 1999)

Other authors refer to the craft nature of clinical work and how this differs from a focus on
systems: “the hospital doctor acting as a skilled craftsperson … managing their own waiting
list of patients, clinics and operations inside some else’s mass production general hospital”
(Jones 2006), although some would view this now as an outdated model.
The dominance of the medical profession is especially seen when quality improvement is
considered – “quality has become a battleground on which professions compete for
ownership and definition of quality” (Øvretveit 1997). It is also argued that for health
professionals, translation starts from their own world and although the change concepts (see
section 5.1) may be the same for different clinical areas, success in translation only comes
from promotion by other peers in the same field. Differences of span of managerial control
and the relative dominance of rational decision-making processes were also cited as key
issues (Arndt & Bigelow 1995). Some of these issues are summarised as clinician lack of
perception of the applicability of quality improvement, and the fact that many improvement
initiatives in the NHS have been led by managers, often excluding clinicians (Silvester et
al. 2004).
The professional culture and the way in which it may compare with the type of
organisational culture generally considered appropriate for quality improvement is described
by a number of authors (Short & Rahmin 1995). Table 20 refers to TQM specifically, although
the principles are common to most quality improvement initiatives.
Table 20 – Comparison of hospital professional and TQM models (Short & Rahmin
1995)
PROFESSIONAL TQM
Individual responsibilities Collective responsibilities
Professional leadership Managerial leadership
Autonomy Accountability
Administrative authority Participation
Goal expectations Performance and process expectations
Rigid planning Flexible planning
Responses to complaints Benchmarking
Retrospective performance appraisal Concurrent performance appraisal
Quality assurance Continuous improvement

7.1.2 Healthcare has a complex structure
Healthcare is arguably more complex than many of the industries that pioneered the use of
these approaches, although many would argue that this should not mean that these
approaches are not useful (Walley 2003b). Issues described by others (Benneyan & Kaminsky
1995) include the fact that healthcare practitioners believe healthcare systems are ‘uniquely
complex’, and the process of transfer requires validation and refinement.
Juran argues that “in the minds of many, the health industry is different. This is certainly true
as to its history, technology and culture. However, the decisive factors in what works and
what does not are the managerial processes, which are alike for all industries” (Berwick,
Godfrey & Roessner 1990/2002)
The complexity of ownership also leads to the lack of a top-down, or whole-system view.
Any analysis incorporating a process model of inputs being transformed into outputs is
complex to apply in healthcare because both the output and the customer are difficult
to define.
“the product here is ‘care’ in both the physical and emotional senses, not a tangible physical
object … the service is delivered, or possibly co-produced, through a series of interactions
between worker and patients, but the ‘payer’ is often far away … leaving unclear the
question of who the true customer is. Increasing productivity requires orchestrating complex
interactions between professionals, service staff, agencies and clients” (Eaton 2000, p.607).
This leads to a complex performance measure system.
“Conceptually complex outputs are delivered utilising a wide variety of inputs. The
measurement methodologies used are often complicated … the output of a health system
must be measured in a number of dimensions for any measurement to give a balanced and
comprehensive view. These may include health outcomes, social outcomes, quality of life,
and social equality as well as financial measures” (Micheli et al. 2005, p.69).
7.1.3 Healthcare is difficult and complex to change
The motivation for using these approaches in industry – primarily competition – is not present
to the same degree within the NHS although it is more so in other types of healthcare system
(e.g. the US). It is argued that this therefore makes sustainable change difficult to achieve.
There may also be internal cultural factors: “In healthcare, we’re not that way, so you’ve got
to be willing to change the culture. It’s a bit tricky to know how hard to push… if you fail to
push enough, nothing happens. If you push too hard, people will ignore what is trying to be
achieved” (Simmons 2002).

Evidence about the extent to which knowledge, theories and models from the private sector
can be transferred to healthcare/public sector organisations can be found in the meta
analyses reported by Golembiewski, Proehl & Sink 1982 and Robertson & Seneviratne 1995.
They showed that public and private sector interventions showed similar patterns of results.
However, their findings should be interpreted with care, especially given the professional
nature of healthcare and the scale of the change intervention (Iles & Sutherland 2001).
However, IHI is clear that “in matters of quality improvement, healthcare can indeed learn
from industry – and perhaps, equally important, industry can also learn from healthcare. The
fundamental principles of quality improvement apply to both” (Berwick et al. 1990/2002).
The issues of translation are not covered in any detail in its published work. In considering the
translation of SPC (Mohammed 2004) he proposes that the fact that SPC was first used in
manufacturing makes translation difficult: “there is a reluctance, despite evidence to the
contrary, to accept that an approach for improving the quality of ‘widgets’ can be
legitimately applied to healthcare”.
Why is it difficult to resolve organisational problems in healthcare?
• The missions of the organisation are multiple and potentially conflicting – being
developed from the demands of clinical need, community services, staff, research and
financial viability. Assessing these multiple missions then requires multiple dimensions,
which generates additional challenges.
• The workforce is comprised of “multiple professions socialized elsewhere” (Ramanujam
and Rousseau, 2006, p814) – professional groups influenced by their professional
training and identity which results in strong professional identification and weak
organisational identification (Meyer, Allen & Smith 1993).
• The external environment is complex, with multiple stakeholders – these include
healthcare commissioners (who are not the patients who receive the service), the
patients themselves and their families, as well as government and professional
associations (e.g. the British Medical Association representing doctors).
• The environment within which healthcare is provided is complex, ambiguous, dynamic
and local – with increasing professional specialisation, demands for standardisation of
clinical work as well as flexibility, the continuous emergence of new evidence to support
or discredit existing ways of working and variation in performance between individual
units within a single organisation.
Developed from (Ramanujam & Rousseau 2006)

7.2 The implications for people
7.2.1 Culture
Most perspectives on improvement focus on the motivation and beliefs of individuals in the
organisation, which contribute to defining the culture as well as the behaviour that results
from them. Approaches to culture in the literature are ambiguous. On the one hand, some
authors describe a ‘quality culture’ as one “whereby everyone in the organisation shares a
commitment to continuous improvement aimed at customer satisfaction” (Wilkinson &
Brown 2003, p.184). Others believe that culture cannot be ‘managed’ (Schein 1985) despite
many policy innovations intended to achieve exactly this (Mannion, Davies & Marshall 2005).
In one study a participative, flexible, risk-taking culture was strongly associated with the
implementation of quality improvement (Shortell, O’Brien, Carman et al. 1995).
7.2.2 Leadership
There are an increasing number of documents describing what leaders should do in terms of
leading improvement within their organisations (Bibby & Reinertsen undated, Reinertsen,
Pugh & Bisognano 2005). Many include exhortations to leaders to change the culture of their
organisations (e.g. Table 21).
Table 21 – What leaders should do to change culture (Bibby & Reinertsen undated)
Guidance from IHI states that it is based on complex system theory, observed performance of
leadership and health systems as well as hunches, intuition and collective experience. It
contains seven “leadership leverage points” (Reinertsen et al. 2005):
From To
Unrelated pockets of improvement activity Improvement activity aligned with
measurable goals
Improvement being an add-on for enthusiasts Improvement as a function of service delivery
Improvement stopping at organisational
boundaries
Collaboration across organisations to deliver
seamless care
Improvement gains confined within
individual projects
Learning transferred throughout the system
Leadership of improvement as a positional
responsibility
Leadership of improvement at every level of
the system

1. Establish and oversee system-level aims for improvement at the highest board and
leadership level
2. Aligning system measures, strategy and projects in a leadership learning system
3. Channel leadership attention to system-level improvement
4. Get the right team on the bus
5. Make the chief financial officer a quality champion
6. Engage physicians
7. Build improvement capability.
The guidance also includes a tool for assessing performance against these points and
developing desired behaviours.
A literature review of the role of managers and leaders in quality improvement (Ovretveit
2005) concluded that despite the range of literature available and the limitations of the
research, there was a pattern of similar findings focused around:
• preparation – of the current state of the organisation and its improvement expertise
• vision and strategy – a vision of what the organisation should look like and an agreed and
achievable strategy for reaching it
• structural and line management process changes – responsibility for quality improvement
needs to be specified in job descriptions and line management processes changed to
include regular reporting of quality progress
• system changes – development of data collection and reporting systems, as well as
appropriate reward and incentive systems
• human resources, people and team development – training and development to support
the changes required
• communication, commitment and motivation – understanding what motivates individuals,
and rewards
Their guidance is summarised as:
1. Assess the situation
2. Assess your influence
3. Translate, don’t transfer
4. Balance attention between the seven areas

The involvement of top management, use of teamwork and the ability to foster innovation
were shown to be important in quality improvement (Parker, Wubbenhorst, Young et al.
1999). In fact, quality improvement can be seen to be dependent on leaders, both in relation
to clarifying the overall mission and strategy and creating a commitment to change (Berwick
et al. 1990/2002). Leaders have a key role to play in planning for quality, creating the right
cultural conditions and setting organisational structures that empower staff to become
actively involved in improvement (Juran 1989).
In terms of research evidence that leadership makes a difference, there is an increasing body
of literature to show that it does. In terms of both clinical (outcomes) and process quality,
Marley, Collier & Goldstein 2004 show that leadership is a significant influence, supporting
earlier work on quality management in general (Collier, Goldstein & Wilson 2002, Flynn,
Schroeder & Sakakibara 1994) as well as that specific to healthcare (Goldstein & Schweikhart
2002, Institute of Medicine & Committee on Quality Health Care in America 2001, Meyer &
Collier 2001).
7.2.3 The healthcare workforce
The people implications are broader than organisational culture, relating to individual
employment arrangements, professional motivation and the need to take into account both
individuals and systems and the way they interact.
Concern about the impact of quality improvement initiatives on the workforce is not
something unique to healthcare, nor is it an area which has received relatively much attention
when compared to the details of the tools which can be used. However, it is an increasing
concern, not least because “prevailing strategies [for developing the workforce] rely largely
on outmoded theories of control and standardisation of work” (Berwick 2003 p.448). It is
argued that a change in attitude is needed so that responsibility for quality is seen as
something for everyone, not someone else’s problem. This will then enable the workforce to
“set aims, measure and interpret results, search for unfamiliar and promising alternatives to
the status quo and test those alternatives rapidly, carefully, and constantly” (Berwick 2003
p.451) – something which is very similar to the TPS model promoted by others (Spear 2005).
However, some of the contradictions in organisational approaches to quality improvement in
terms of their assumptions about the individuals who work in the organisations include
(Wilkinson & Willmott 1995):
• the assumption that staff will welcome approaches which improve the
effectiveness of the organisation: it appears to be taken for granted by the quality
gurus and their approaches that employees will welcome, and be committed to,
approaches that minimise unproductive activity and enable them to take a pride in what is
produced by the organisation. However, while these approaches are employed within the
context of a hierarchical relationship between management and employees, the benefits
from quality improvement will be limited.

• the ownership of the organisation: employees or managers who do not own or
control the organisation that employs them are likely, according to employment research,
to be concerned primarily with their own rewards and conditions of employment.
However, these structures of ownership and control will also limit the extent to which
employees can be involved and empowered (two aspects seen to be key to
quality improvement).
• viewing employees as internal customers: which is a fundamental assumption of
quality improvement. This is argued to be difficult to reconcile with the
teamwork/empowerment approaches, which imply that individuals gain more control over
their own work. The internal customer approach implies that what you produce is dictated
by the requirements of your customer rather than being primarily controlled by the
individual performing the work.
The Lean approach and people
A variety of authors describe in detail the implications of a Lean approach for staff within the
organisation, both from Lean in general and specifically in healthcare. Early criticism of Lean
production was concerned with the effect it had on the worker, arguing that Lean
production meant “a loss of autonomy and further intensification of work” (Skorstad 1994).
Other writers described Lean production as ‘mean production’ or ‘management by stress’
(Berggren 1993, Delbridge & Turnball 1992). Further work produced clearer definitions of
Lean work practices (Kinnie, Hutchinson, Purcell et al. 1996, Syrett & Lammiman 1997) and
defined Lean “not as a homogeneous or invariable state but a context-dependent process”
(Kinnie et al. 1996).
However, some argue that “Lean is not mean” (Jones & Mitchell 2006 p.6) but it is about
being able to do more with existing resources – if less people are needed they can be
redeployed to create more value.
Many authors from the healthcare perspective do however highlight that job security is an
issue: “The lesson from long experience is that Lean initiatives rarely succeed unless continuity
of staff employment is guaranteed in advance” (Jones & Mitchell 2006 p.21, Thompson et
al. 2003).
Many also argue that Lean will help to motivate staff and save time and money – it is
“inclusive and motivational because it encourages a problem-solving culture” (Westwood et
al. 2007 p.19) with anecdotal evidence that staff in healthcare do like the approach. The
CEO of Bolton Hospitals NHS Trust suggests that Lean redesign processes have strengthened
team working in those areas where relationships were already sound and helped tackle
problems in areas where team working was not well established (Fillingham 2008).

7.3 Does quality improvement work?
Many earlier publications demonstrated the extent of the issue rather than prescribing what
could be done to improve quality, although these did lead to change.
Two reports on the evidence for quality failures (Hurtado et al. 2001, Kohn, Corrigan &
Donaldson 1999) were catalysts for changes and improvements internationally. A book
examining the ‘improvement journeys’ of medical organisations that have earned reputations
for sustained achievement of quality improvement (Bate, Mendel & Robert 2008).
Apart from the studies on particular approaches, which are detailed earlier in this report,
there are also some studies which have taken a wider remit. It is acknowledged that there is
a limited number of studies, but a useful summary of “the relatively few well-conducted
empirical studies” (Iles & Sutherland 2001) of change management within the NHS is
provided in (Iles & Sutherland 2001). They cite in particular a few evaluation studies on TQM
and BPR (Joss & Kogan 1995, McNulty & Ferlie 2002, Packwood, Pollitt & Roberts 1998) but
reiterate the lack of research that considers the factors that shape organisational change in
the NHS.
The studies that do exist have demonstrated a number of issues:
7.3.1 Methodology
In a review of reported studies evaluating the clinical application of continuous quality
improvement (CQI), (Shortell, Bennett & Byck 1998) conclude that studies are limited both in
terms of quantity and methodological quality. Other authors report that most studies have
severe methodological limitations and that few studies describe or compare different types of
programmes (Øvretveit & Gustafson 2004). This is also an issue with management research in
general (Lilford, Dobbie, Warren et al. 2003) although there is acknowledgement that the
speed of implementation of process redesign does hamper both longitudinal and
independent research: “the speed of implementation and the rapid proliferation of different
variants…make a dispassionate assessment of its effectiveness hard to achieve” (Locock
2003, p.122).
Do you know what motivates the different staff groups within your organisation?
What assumptions have you made about the motivation of people
within your organisation to improve?
How can you link measures of performance to the motivating factors of
the different staff groups in the organisation?
What is likely to be the impact of short-term cost cutting and/or job security
on the success of quality improvement?

7.3.2 Definition
There has been such a variety of approaches to improving quality used, as well as varying
understanding of what healthcare quality is that this has hampered the progress of quality
improvement initiatives (Øvretveit 1997). Because of the lack of a “unified approach or
common language of quality” (Øvretveit 1997), professions and departments are unable to
put into practice the exhortations to work using a “systems approach”. It has also been
noted that the label given to a programme (for example “TQM”) is no guide to the activities
which are actually carried out – programmes with the same name are implemented
differently at different rates, coverage and depth in the organisation (Øvretveit &
Gustafson 2004)
7.3.3 Critical success factors
Those studies that have been reported provide generally favourable results in relation to the
impact of CQI on clinical processes and outcomes. Critical success factors include:
• the participation of a nucleus of physicians,
• feedback to individual practitioners,
• a supportive organisational culture
• a conducive external environment (for example, alignment of policy, regulatory and
incentive related factors) (Shortell et al. 1998)
• a “phased coordinated spreading” approach where top management monitored progress,
coordinated efforts and allocated resources (Øvretveit 1997)
• although improvement activity may be bottom-up, it must be supported by “top-down
policies that are consistent with the improvement objectives” as well as the relinquishing of
some control by senior managers (Silvester et al. 2004)
Core challenges in organising for quality have been identified as shown in Table 22.

Table 22 – Core challenges to organising for quality (Bate et al. 2008)
7.3.4 The process of implementation is more important than
the approach
All the approaches examined are underpinned by a philosophy that quality improvement is
an important value (as opposed to e.g. cost reduction) but the way in which they are
implemented is vital in their success or otherwise, and should therefore be evaluated
(Hackman & Wageman 1995). This view is supported by a number of other authors:
“Most importantly, our research suggests that the inability of most organizations to
reap the full benefit of these innovations has little to do with the specific
improvement tool they select. Instead, the problem has its roots in how the
introduction of a new improvement program Interacts with the physical, economic,
social, and psychological structures in which implementation takes place. In other
words, it’s not just a tool problem, any more than it’s a human resources problem
or a leadership problem. Instead it is a systemic problem, one that is created by the
interaction of tools, equipment, workers, and managers.” (Repenning & Sterman
2001, p.66
Challenge Lack of this can lead to …
Structural – organising, planning and
coordinating quality efforts
Fragmentation and a general lack of synergy
between the different parts of the organisation
doing quality improvement
Political – addressing and dealing with the
politics of change surrounding any quality
improvement effort
Disillusionment and inertia because quality
improvement is not happening on the ground,
and certain groups or individuals are blocking
and resisting change
Cultural – giving quality a shared, collective
meaning, value and significance within the
organisation
Evaporation because the change has not been
properly anchored or become rooted in
everyday thinking and behavioural routines
Educational – creating a learning process that
supports improvement
Amnesia and frustration as lessons and
knowledge are forgotten or fail to accumulate,
and improvement capabilities and skills fail to
keep abreast of growing aspirations
Emotional – engaging and motivating people
by linking quality improvement efforts to
inner sentiments and deeper commitments
and beliefs
Loss of interest and fade-out as the change
effort runs out of momentum due to a failure
to engage front-line staff
Physical and technological – the designing of
physical systems and technological
infrastructure that supports and sustains
quality efforts
Exhaustion as people try to make change
happen informally, without a system or
standardised set of routines to take the weight
of necessary everyday activities

“As important as the method is seriously adopting and committing to a method …
all too often the tendency has been to dabble in different methods … whatever the
flavour of the month might be” Gary Kaplan, CEO of Virginia Mason Medical
Center, quoted in (Reinertsen 2006)
A recent study of a range of quality improvement programmes (Bate et al. 2008) started
from the premise that there had been little research into how to set quality improvement
processes in motion, or into how they interrelate, leading to a focus on organising for quality.
The main conclusions of the study were that:
“There are many different paths to successful, sustained quality improvement.
However the unifying features … are an ability to address multiple challenges
simultaneously and to adapt solutions and strategies to the organisation’s own
context” (Bate et al. 2008).
How will you implement quality improvement so as to maximise the likelihood of success?
How much do you understand the system and its influence on organisational change?
Can your organisation address multiple challenges at the same time?

8.1 Quality improvement: the theory
8.1.1 The applicability of quality improvement approaches
There are many approaches taken, both in healthcare and industry. There is now some
integration of these approaches, with a particular focus on the application of industrial
approaches in healthcare. However, this raises questions about the way in which the
approaches may need to be adapted for the healthcare context, and the nature of healthcare
as a sector.
8.1.2 Are the approaches really different?
The various approaches appear to be different because of their historical development and
labelling, although the differentiating factors are actually a matter of emphasis on the core
concepts of variation, flow and customer focus. The apparent contradictions between
approaches are also due to the differing assumptions about value and its definition.
All approaches are based on same principles by which organisations operate. The approaches
all also draw on a fairly common body of tools for improvement, with some labelled by one
approach as being an essential element. Many of these tools may be more appropriate
starting points for improvement than the overall ‘package’.
8.1.3 So which approach should be used?
A key challenge for organisations is to know which approach is right for them at any
one point in time. To address this, organisations must define and assess the
characteristics of their processes.
There is some evidence of a body of knowledge which is being built on, especially with the
longer-established approaches, and many of the more recent approaches have as their
foundation the statistical analysis of quality or a model of continuous and incremental
improvement. However, it is difficult to argue that there is a definitive body of knowledge
about any single approach and where an approach does not appear to work there are often
methodological issues about the evidence to support the assertion, or concerns about
whether it is too soon to assess the impact of the improvement.
8.1.4 How do we know what works?
The methods most appropriate to assess the effectiveness of quality improvement approaches
is still a matter of debate, and this is likely to continue given the fundamental differences
between a scientific and a social science research paradigm around the nature of proof that
something works. However, key commentators are increasingly calling for more use of
approaches which take into account the context for implementation; what is important is not
what works, but where and why it works. Similarly, it is unlikely that there will be definitive
8. CONCLUSIONS

evidence to show the optimum context for successful implementation, but as the body of
evidence continues to grow the issues will become clearer.
8.1.5 Is it what works or why?
There is little guidance or evidence in the literature about practical implementation issues and
in particular, the readiness of the organisation for change is rarely considered. Despite a huge
amount of evidence and research on organisational change, leadership and organisational
culture from the social sciences, to date this has not been incorporated to any large extent
into the evidence for quality improvement.
8.2 Quality improvement: the practice
Whilst the evidence about what works, where and when with regard to any one approach is
limited, there are a number of common implications for practice that can be drawn out.
8.2.1 Define quality first
Attempts to improve quality often fail to address clearly how quality is defined before starting
to change organisations and processes. It is important to explore what is meant by quality
before attempting to improve it – but care must also be taken to ensure that this step does
not take too long.
8.2.2 Identify the process
It is clear that whatever approach is taken to improve quality, the identification of the process
is a vital first step. Processes will have both clinical and organisational elements and should
not be separated but integrated. Clinical processes in particular must take account of the
organisational resources necessary for them to function effectively. However organisational
processes must also recognise the clinical decisions which are necessary as patients go
through the process. Processes are key determinants of outcomes, and their position as part
of wider system must be recognised. Recognise that work is a series of processes and that
organisations are part of systems – and then do something about it.
8.2.3 Beware of exclusive promotion of one approach
Whilst literature suggests that implementation is more important than the actual tool or
approach chosen, this is not put across in how techniques are promoted where there is often
an exclusivity about which one can or should be used. It is not clear to what extent this is the
result of the people or organisations promoting particular approaches, but clearly the
business mindset of consultancies that provide support for implementation to many
healthcare organisations is one factor. It may be argued that there are also some academics
that appear wedded to one approach/mindset and appear to show more interest in

promoting pre-determined tools/approaches than solving organisational problems in the long
term. The problems of the process and system should be identified before systematic change,
using any approach, is undertaken. The common elements of the various approaches should
also be recognised, especially at the level of tools for improvement.
8.2.4 Think about who the customer is
It must not be assumed that an individual patient is the only customer where healthcare is
provided within the public sector: this is an over-simplistic approach. Other important
customers include those who commission healthcare, as well as the wider public and perhaps
those with political interests.
8.2.5 Understand the people
Quality will only improve where the behaviour of individuals within the system changes and
this has to date often been ignored or underplayed in quality improvement efforts.
Understanding what motivates the individuals within the healthcare system, especially those
with a clinical professional background, is vital. A programmatic approach to improvement
(e.g. we have now ‘done’ Lean) is not supported by the evidence: sustained improvement is
about a different way of doing things, following from a changed culture and way of
thinking, resulting from changes in people as well as their capability.
8.2.6 Get data about quality before you start
Data about performance and quality is needed – it should be appropriate and enable
improvement action. Improvement based on gut feelings about what is wrong is not likely to
be effective or sustainable. Evidence of success will not be obtained without a baseline
against which to assess progress. For this reason, the define or plan stage of any approach is
important so that there a basis for change.
8.2.7 Recognise the importance of whole system leadership
Organisations and whole health systems need to be effectively led and staff empowered to
improve quality. Quality will not improve throughout the system when the actions or words
of those at the top do not support quality improvement. Effective change will only be
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All the authors are members of staff at Manchester Business School. Full details of their work
and publications can be found by searching for their name at www.mbs.ac.uk
Ruth Boaden Ruth is Professor of Service Operations Management and Deputy Director
of the Greater Manchester Collaboration for Leadership in Applied Health
Research and Care (CLAHRC). Her research interests cover a wide range of
areas within health services management and include work in electronic
health records, re-engineering, operating theatre management and
scheduling, patient safety, the management of Emergency Admissions,
bed management and chronic disease management. Her main areas of
interest are in quality and improvement and the use of industrial methods
within the NHS, as well as the implementation of new approaches. She
has a focus on knowledge transfer arising from high quality research, to
ensure that the findings are accessible and applicable to practice. She has
published widely in these areas as well as in the areas of IT
implementation and quality management. She set up and directed the
Leadership through Effective People Management programme for the
NHS, which was run in partnership with PricewaterhouseCoopers from
2001-2006 and provided for directors and deputies from across the NHS.
Gill Harvey Gill is a senior lecturer in healthcare and public sector management.
She has a professional background in nursing and prior to taking up
post at MBS (in August 2003), Gill had worked for nine years as the
director of the Royal College of Nursing's Quality Improvement
Programme. In this post, she was responsible for leading the RCN's
work on clinical guidelines, audit, clinical governance and healthcare
quality improvement and was involved in a wide range of educational,
research, development and policy-focused activities. Gill's own
research interests are particularly focused on evaluative research
around issues of implementation and facilitating quality improvement
in practice. Current research activities include projects on
organisational failure and turnaround, knowledge translation and
utilisation and evaluating improvement initiatives in the NHS.
Whilst working at the RCN, Gill was responsible for establishing and
leading the NICE funded National Collaborating Centre for Nursing and
Supportive Care. She is a past Co-Chair of the European Forum for Quality
Improvement in Health Care and for several years was an associate editor
of the Quality and Safety in Healthcare journal.
APPENDIX 1 - The authors of the report

Nathan Nathan is a senior lecturer in operational research. He has worked on
Proudlove health management issues since the mid-1990s. Nathan's particular
interests are operation management and flow issues such as capacity and
demand, forecasting, bed management, and process improvement. He
has worked with many hospital trusts and with the NHS Modernisation
Agency, in particular Intensive Support Teams, the Innovation and
Knowledge Group, and the Emergency Care Strategy Team. He also has
links with the NHS in Wales and Northern Ireland. He has published in a
range of academic and practitioner journals in the healthcare field,
including the Health Service Journal, the International Journal of
Healthcare Technology and Management, the Emergency Medicine
Journal, the British Journal of Healthcare Computing and Information
Management, and the Journal of Health Organisation and Management.
He has also contributed guidance to the National Electronic Library for
Health, and advice on healthcare issues to the National Audit Office and
Prime Minister's Delivery Unit.
Claire Moxham Claire is a lecturer in the decision sciences and operations management
group. Her background is in process improvement and she has held
managerial positions in the textile and caravan manufacturing industries.
Prior to her appointment at MBS Claire spent three years as a Voluntary
Service Overseas volunteer lecturing in operations management in
Ethiopia. Claire joined MBS in September 2003 and teaches operations
and quality management at undergraduate, postgraduate and post-
experience levels. Her areas of expertise include performance
measurement, process improvement, and the application of industrial
management techniques to the public and voluntary sectors.

Quality improvement theory and practice in healthcare

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Quality improvement theory and practice in healthcare