CHAPTER 6
THE PATH TO SUSTAINABILITY IN HEALTHCARE: EXPLORING THE ROLE
OF LEARNING MICROSYSTEMS
Svante Lifvergren, M.D.
Development Director
Skaraborg Hospital Group
KSS, Skövde
Western Region
Sweden 54185
+46 70 6933081
Svante.lifvergren@vgregion.se
Ulla Andin, M. D.
Senior Physician
Skaraborg Hospital Group
Lidkopingsjukhus, Mellbyg. 11-15
Lidköping
Sweden 53185
+46 510 85000
Ulla.andin@vgregion.se
Tony Huzzard, Ph.D.
Professor
Lund University
School of Economics and Management
Box 7080
Lund, Sweden 22007
+46 46 222 3434
tony.huzzard@fek.lu.se
Andreas Hellström, Ph.D.
Senior Lecturer
Centre for Healthcare Improvement
Department of Technology Management and Economics
Chalmers University of Technology
Gothenburg, Sweden 41296
+46 31 772 8188
Andreas.hellstrom@chalmers.se
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ABSTRACT
Purpose
This chapter examines the developmental journey towards a sustainable healthcare system in
the West of Skaraborg County in Sweden from 2008 to the present by proposing and
illustrating the concept of a clinical microsystem to capture the work of a mobile team to care
for elderly people with multiple diseases in its embedded context.
Design
An action research approach was adopted that entailed four researchers, one of whom was
also a healthcare practitioner, engaging in iterative dialogues with the mobile team. This
aimed at catalysing joint learning in repeated action-reflection cycles at least three times a
year over a period of three years. Data from patient databases were also drawn upon as
additional resources for reflection.
Findings
The outcome of the initial periods of the team’s work in the microsystem dramatically
improved the care of these patients, significantly increasing quality of life and stabilising their
medical situation. It has also led to decreased resource utilization, not just by the team, but
elsewhere in the wider health system.
Originality/Value
We draw on and develop the concept of clinical microsystems to argue that such systems have
a team at their core, but their work practices and patient outcomes require us to look beyond
the team itself and take into account its interactions with patients and actors in the wider
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healthcare system. We also draw on the framework of Christensen et al. (2009) to propose
that each microsystem has three distinct value configurations, namely shops, a chain and a
network. In terms of design, we suggest that the clinical microsystem can be seen as a parallel
learning structure to that of the established healthcare bureaucracy.
Keywords: Sustainability, sustainable effectiveness, clinical microsystems, teams, learning,
sustainable healthcare system
Acknowledgments: We dedicate this chapter to the late Professor Peter Docherty of the
Centre for Healthcare Improvement (CHI) at the Chalmers University of Technology. Peter
played a central role and has been a major inspirational force throughout this project, sharing
his wisdom, kindness and vast experience. We will strive to continue our work in the spirit of
Peter to honor his memory. We would also like to thank Ulla Andin, Christina Pettersson and
Siv Jonsson, all members of the mobile team, for taking your time and sharing your insights
and reflections with us – this is your chapter. We would also like to thank Alexander
Chakhunashvili for excellent help with the statistical analysis. This chapter is founded on
research funded by Vinnova, the Swedish Governmental Agency for Innovation Systems.
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INTRODUCTION
The healthcare systems of today face extraordinary challenges, especially pertaining to the
care of elderly people. Life expectancy is increasing, and proportionately more people are
developing multiple and complex diseases (SALAR, 2005). Unfortunately, the current design
of healthcare systems lacks the integration and coordination critical for establishing a
coherent, sustainable care chain for multi-diseased, elderly people. New ways of organizing
healthcare are required, shifting the value configuration logic from traditional, vertical ways
of operating towards horizontal customer-, process- and network-centred organization logics
(Christensen, Grossman & Hwang, 2009). This approach to organising care has the ambition
of making much more effective links between care providers so that patients see healthcare as
being more coherent or “joined up” than has been the case hitherto. Traditionally,
bureaucracies in the sector have been poorly co-ordinated seen both from the perspective of
the patient and the healthcare system as a whole. Accordingly, many healthcare providers
have sought to make a transition to an alternative model – integrated care - that transgresses
organizational boundaries (Lifvergren, Docherty & Shani, 2011; Lifvergren, Huzzard &
Docherty, 2009).
This chapter examines the developmental journey towards a sustainable healthcare
system in the West of Skaraborg County in Sweden from 2008 to date. We aim to do this by
proposing and illustrating the concept of a clinical microsystem to capture the dynamic
practices of this team in its embedded context. Specifically, we describe the planning and
implementation of an integrated healthcare team dedicated to providing care for the elderly
with multiple illnesses – a critical capacity for a sustainable care system. We present and
discuss a case study of integrated care (Huzzard, Ahlberg & Ekman, 2010) from the region of
West Skaraborg in Sweden. Moreover, we focus on the establishment of the operational
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mobile team in West Skaraborg from 2008 to 2011; its background, its current modus
operandi and the results so far.
In attempting to fully understand the role of the mobile team, we argue that the team
concept, as it has broadly been treated in the literature, fails to fully appreciate the internal
and external interactions of the team in our empirical material. In our view, a rounded
understanding of the practices and processes we have observed in the case requires greater
attention to be paid to the embeddedness of the team in its broader context. The various
conceptualisations of teams in the literature, whilst helpful, tend to look at teams as discrete
entities. We could certainly detect instances of multidisciplinarity (Kim, Barnato, Angus,
Fleisher & Kahn, 2010; Mathieu, 2008; Solheim, 2007), role complementarity (Lind &
Rennstam, 2007) and self design (Kalliola, 2003) in the team, but propose the more
encompassing concept of clinical microsystem as a more helpful means to explore and shed
light on the wider embeddedness of the team. This concept has been proposed previously by
Mohr & Donaldson (2000; see also Batalden et al., 2002). What we aim to do in this chapter,
however, is to unpack this concept and arrive at a model for analysing our case study data.
Before giving an in-depth description of the actual case, we provide some important
background issues followed by a description of the theories underpinning the research. We
then move to a description of the action research approach used during the project, followed
by a more profound description of the context of the case. After the longitudinal casedescription including the results, we finally propose some lessons on what has been learned
from the case and areas where we believe more enquiry is needed to fully understand the
requirements for integrated care that can animate dialogue and inform the pursuit of
actionable knowledge on a more generalized level.
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BACKGROUND AND THEORETICAL INSPIRATION
In Sweden, healthcare needs for citizens are provided for by the state, at a moderate cost and
at a reasonable resource level. As of today, Sweden prides itself by having some of the best
medical outcomes in the world, with only 9.2% of the country’s gross domestic product being
allocated to healthcare (OECD, 2008). The accessibility to care has also improved during
recent years (SALAR, 2011). In the Swedish system, financed through individual and
corporate salary-based taxes, primary and hospital healthcare are organized at the regional
level, while after-care services are organized at the municipal level.
Still, even in Sweden healthcare stakeholders agree that business as usual is not an
option to meet future challenges. The Swedish system is not immune from the challenges
facing healthcare systems worldwide. Several reports from the Swedish Department of
Treasury and SALAR (Swedish Association of Local Counties and Regions) anticipate that
healthcare systems must be more sustainable (SALAR, 2005; Swedish Department of
Treasury, 2005). There is a need to transform their service delivery to balance available
resources to cope with future care needs (Mohrman & Shani, 2011). A critical question is how
these future challenges should be addressed, especially to meet the demands from an ageing
population, where patients with multiple diseases are abundant.
In this section, we apply theories of teams and clinical microsystems and the concept
of different value configuration logics to investigate how a mobile team enhances the adaptive
capacity of the system. We first provide some definitions of sustainability and adaptive
capacity in a healthcare context, moving on to describe different models that depict value
creation within healthcare. We then continue with a discussion of the team concept, the
limitations of its various treatments in the literature, and develop an argument for
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conceptualising the practices and interactions of teams in terms of clinical microsystems and
different team models.
Sustainable Healthcare Systems
According to Folke et al. (2002) a sustainable system is signified by adaptive capacities (p.
17):
Adaptive capacity is the ability of a social-ecological system to cope with novel
situations without losing options for the future, and resilience is key to
enhancing adaptive capacity.
A sustainable healthcare system is considered adaptive if it is able to fulfil the expectations of
its customers in ever changing situations, while simultaneously having a positive impact on
the various stakeholders and resources impacted upon by their operations. In this context we
define resources as entities that are either valuable as such or can be used in obtaining valued
ends (Hobfoll, 2002). A sustainable healthcare system is concerned with its human/social,
ecological and economic resources and their sustainable development and regeneration – a
combination that has been coined the triple bottom line (Elkington, 1999; Kira & Lifvergren,
2012). Moreover, sustainable healthcare systems must engage in ‘upstream thinking’, that is
seeking to detect and correct potential problems already ‘in the upstream’, or in the very
foundations of operations. Accordingly, sustainability from this perspective is about thinking
ahead; recognizing potential problems and pitfalls beforehand, thus reducing waste of
resources in the system ’downstream’ (Broman, Holmberg & Robert, 2000).
From these points of view, the organization of today’s healthcare seems to entail
resource degeneration rather than to regenerate resources from a human/social, economic and
ecological perspective (Christensen et al., 2009; Kira & Lifvergen 2012). This might be
explained by the fact that healthcare is deeply rooted in the epistemological traditions of the
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natural sciences and proven experience and evidence, which has been important for the
development of a safe and good care for patients. Consequently, healthcare has been
organized based on different medical disciplines and organs, which have led to a fragmented
and sometimes badly integrated system. A holistic view from the patient’s perspective is
lacking; care interventions along a patient’s journey often occur separated in time and space,
and an upstream perspective on the care provided is often missing. This is not least evident for
patients with multiple diseases who are passed around between different clinics and
physicians since no proper coordination takes place based on the patient’s needs.
Accordingly, it is important to consider how healthcare delivers value to its customers and
other stakeholders without wasting resources.
An increased focus on the customers’ real needs has in other industries changed how
products and services are produced. Stabell and Fjeldstad (1998) present a typology of three
generic value configurations, which later Christensen (2009) applied in a healthcare setting.
Translated to a healthcare context, we define value configuration logics as the way in which
different care activities are carried out, but also how competences, services, responsibilities
and level of standardization are organized to fulfil the needs of the customers, i.e. the patients
(see e.g. NUTEK, 2007). In their value configuration analysis, Stabell and Fjeldstad
distinguish between shops, chains, and networks. The shop configuration is characterized by
what relevant skills and resources are gathered so that they can collaborate based on patients'
various illnesses or life situations. It is an organization designed to solve customer problems.
The patient should in this case get smooth access to all relevant competencies to handle the
specific medical situation. The chain configuration, on the other hand, is probably the most
well-known value configuration of the three. The value chain concept (Porter, 1985) is a
generally accepted language for representing and analysing the logic of firm-level value
creation. Applying the configuration to a healthcare context, care chains (care processes,
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patient pathways) can be coordinated and integrated, thus linking various medical and care
resources to create value for the patient throughout the whole patient journey. Finally, we
have the network configuration where the organization or firm itself is not the network, but it
provides a network service. Often the patient can be seen as an active co-producer in the
value-creating network, supported by information technology, medical technology and mobile
care teams.
But how do we understand value configuration logics in the actual practices
undertaken in integrated care? Obviously, the construction and functioning of medical teams
is of utmost importance. For example, West et al. (2002) provide evidence that greater levels
of teamworking are associated with lower patient mortality (calculated using the Sunday
Times Mortality Index). The same study revealed other benefits of teamworking including
innovation, effectiveness in terms of patient mortality and low stress levels. Yet our basic
argument is that the team concept, as treated in the literature is insufficient to capture some of
the key elements of how a team functions in health care: we also need to embrace the broader
interactions in which the team is embedded. In order to shed light on this we draw on and
unpack the concept of clinical microsystems to illustrate recent developments in the labour
process of integrated care.
Clinical Microsystems and Teams in Healthcare
In order to provide a full appreciation and understanding of our case, we wish to underscore i)
a conceptualisation that takes into account not only the dynamic interactions within the team
itself but also the roles that the team members play to fulfil the aim of the team and, ii) the
embedded nature of the team in question – the team’s interactions with patients as well as
with other actors in the wider health care system. To this end we draw on two basic concepts:
Firstly, that of clinical microsystems (see e.g. Mohr, 2000; Nelson, Batalden & Godfrey,
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2007). Secondly, and to expand on clinical microsystem theory, we integrate with this the
concept of role complementarity in teams (Lind & Rennstam, 2007).
The theory of clinical microsystems originally stems from the industrial concept of
‘micro units’ (Quinn, 1992). Quinn described a micro unit as the smallest functional unit
within the organization. The unit has the resources it needs to solve its tasks including to
improve operations, reduce lead-times and increase customer satisfaction. Inspired by Quinn,
Batalden et al. (2002) and Mohr & Donaldsson (2000) put forward the following definition of
a clinical microsystem in a healthcare context (emphasis in original):
A clinical microsystem is a small group of people who work together on a
regular basis to provide care to discrete subpopulations of patients. It has
clinical and business aims, linked processes, and a shared information
environment, and it produces performance outcomes. Microsystems evolve over
time and are often embedded in larger organizations. They are complex
adaptive systems, and as such they must do the primary work associated with
core aims, meet the needs of internal staff, and maintain themselves over time as
clinical units.
According to this theory, the system’s quality of care can never exceed the synthesis
of care quality delivered by each individual microsystem (Batalden et al., 2002). Moreover,
successful microsystems often share a culture of respect and common values, providing an
inviting community to new co-workers. A patient focus is equally important, where the
patient and his/her relatives could be regarded as parts of the clinical microsystem (Batalden
et al., 2003). From studying 40 efficient microsystems in the US, Mohr & Donaldsson (2000)
could identify some common features. Successful microsystems have access to integrated
information of their operations and they also agree on sustainable long-term goals. The results
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of the microsystem are monitored in order to continuously improve the performance of the
microsystem. Support from and interaction with the wider health system as well as reciprocal
and cross-professional trust seem to be other important factors associated with the successful
establishment of clinical microsystems. Microsystem theory points to the importance of
studying how the mesosystem (major divisions of a healthcare system, e.g. a clinical
department or a women’s health program) and the macrosystem (the whole of the actual
healthcare organization) coordinate and collaborate to support the front-line microsystems. It
is also equally important to link and coordinate the microsystems along the patient process
(Nelson et al., 2007).
However, this theory implicitly assumes that teams are usually designed the same
way, not addressing the different roles that team-members might play depending on the
microsystems’ mission. Although Nelson et al. (2007) underscore that clinical microsystems
might be ‘tightly or loosely coupled’ (‘tightly’ signifying more permanent teams as opposed
to ‘loosely coupled’ teams that are more temporary), we believe that elaborating on the
composition of roles within a team might add to the understanding of clinical microsystems.
According to (Lind & Skärvad, 1997), a team is a group that consists of a small number of
individuals having different competences that work together or with integrated work tasks
with the aim of reaching a certain objective. Moreover, teams have the special characteristic
of having a specific raison d’être or purpose. A particularly significant dimension along which
teams may vary is the specific constellation of team member roles they presuppose and the
means through which they are co-ordinated. From this starting point Lind & Rennstam (2007)
have proposed three ways of organizing teams, namely as role-differentiated teams, roleintegrated teams and role complementary teams. The first entails sequential relations of
independent and differentiated tasks in the labour process; the second entails parallel and cooperative relations between partly dependent and integrated tasks, whereas the third entails
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mutual relations whereby tasks are parallel, tightly interdependent and complementary. In
healthcare contexts these can be illustrated by operating teams, emergency teams and outreach
psychiatric teams, or, as presented in this case, integrated mobile care teams respectively.
Surgical procedures are carried out by individuals working together in roledifferentiated teams, which tend to have distinct, specialist competences such that they cannot
undertake the tasks of others. These competences are standardised, based on explicit
knowledge and the work task is undertaken according to strict rules. Accordingly, the team
members need not have any previous experience of working together. The work norm is that
individuals aim to perform their individual tasks in an effective manner and rewards are
individually based. Emergency teams (role-integrated teams) also have a differentiation of
roles, also a need for working in parallel in a more integrated manner. Leadership by a given
team leader becomes more important as a means of securing effective communication, coordination and interaction. Here effectiveness is more dependent on social interaction than on
the performance of individuals as in an operating team. The greater social interaction calls for
a greater role for collective rewards but individual performances are still recognised. On the
other hand, our third example, outreach psychiatric teams or mobile care teams, presupposes a
much tighter degree of interdependency albeit within parallel processes (Sicotte, Pineault &
Lambert, 1993).
The modus operandi and rules of role complementary teams emerge from the team
itself as tacit knowledge. A premium is placed on effective communication and the genuinely
collective nature of the work effort in such teams makes individual rewards redundant. Such
teams are highly flexible, can adapt easily to the unexpected and pose high demands on the
personal chemistry between team members. Accordingly, the purpose of the clinical
microsystem has important implications for the constellation of team member roles. The case
presented in this chapter seeks to illustrate an integrated mobile care team, where the team
12
members complement one another in order to fulfil the needs of elderly patients with multiple
diseases.
Micro-, Meso- and Macrosystems in Healthcare
We also believe it is useful to conceive a clinical microsystem as a team embedded in a mesoand macrosystem that function as a shop, chain and network (Christensen et al., 2009). As a
shop, what the team delivers adds value to patients through care provision. As a chain, the
team adds value to its individual members through the internal learning processes in which it
engages along the patient pathway. Finally, as part of a network, the team adds value to the
wider health community by providing specialist resources including knowledge. The notion of
a shop depicts instances where patients seek and obtain care from and interact with the team
members. In integrated care these will include treatments offered at primary care outlets,
hospitals as well as aftercare provided by local authority social service departments. Together,
these instances of care provision can be seen as a chain along which the team will also interact
internally. In our case, as we shall see, the team is multidisciplinary (Kim et al., 2010;
Peterson, Albert, Amin, Patterson & Fonarow, 2008; Solheim, McElmurry & Kim, 2007) and
such interaction is characterised by role complementarity as well as the need for mobility as
the various shops are dispersed spatially. The team in question was also very much the author
of its own coming into being so the team also resembles what the literature has termed self
designed teams (Kalliola, 2003). Yet the third of the supportive logics specified by
Christensen et al. is also relevant as the clinical microsystem captures the interactions of the
team with actors in the wider health care system or network. Our respondents in the case
stressed the frequency and significance of knowledge sharing and learning processes in this
respect.
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Accordingly, we propose that integrated care needs to be understood in terms of how
medical teams interact not just internally, but also with patients and other actors in the wider
health care system in which the team is embedded. This broader conceptualization of a team
that we are suggesting here by drawing on the concept of a clinical microsystem is depicted
by the model set out in figure 1. Following a short discussion of our research methods, we
continue by presenting a specific example of such a clinical microsystem focused on elderly
patients with multiple illnesses that has entailed combining the shop, chain and network
logics.
-------------------------------------Insert figure 1 about here--------------------------------------------
METHODS
In this case the research strategy has been inspired by an action research approach. Action
research could be described as an orientation to inquiry where the intention to improve the
studied system is achieved by designing iterative action-reflection loops involving both the
researchers and the practitioners in the workplaces involved in the projects (Greenwood &
Levin, 2007). The purpose of action research projects is mainly twofold; to generate
actionable knowledge that helps to solve a specified local problem, and to contribute to the
body of generalized or scientific knowledge (Reason & Bradbury, 2008). In this particular
case, the actual project has sought to improve care provision for elderly people with multiple
diseases in West Skaraborg (see the Case section). From an action research perspective, there
has also been an ambition to explore how different strategies for improving elderly care might
be transferrable to other parts of Skaraborg, and, eventually, other parts of Sweden. In the
project, researchers and co-workers shared a participative community, in which all the
14
members were equally important in co-generating actionable knowledge. The core research
group consisted of team-members from the integrated mobile care team – the microsystem
(for a detailed description of the members, see the Case section), and four researchers (prof.
Docherty and the first, third and fourth author of the chapter). The first author is also a
healthcare practitioner and work part time as a development director at the Skaraborg Hospital
Group (SHG). Together with prof. Docherty, the first and fourth author engaged in iterative
dialogues with the mobile team, aimed at catalysing joint learning in repeated actionreflection cycles at least three times a year over a period of four years. Patients and their
relatives, as well as members of the actual microsystem and the surrounding systems have
been interviewed individually and in focus groups by prof. Docherty and the first author. The
experiences from interviews, focus groups and action-reflection cycles have also been shared
with external researchers, in particular with the third author of the article. Interpretations and
reflections from these meetings have been fed back to the actual micro-, meso- and
macrosystem for continued learning, validation and further action. Additionally, critical care
results of the clinical microsystem have been monitored throughout the project: All the
patients have continuously been registered in a database, covering basic medical data,
symptoms’ scores, reason for admittance and other critical data in the care process. The data
has also been used in the recurrent reflection – action dialogues. Finally, lessons learned have
been shared with the steering committee of the West Skaraborg development coalition (see
below) as well as with the top management team at SHG for further reflection and action
THE CASE - INTEGRATED CARE FOR ELDERLY PATIENTS WITH MULTIPLE
ILLNESSES
The Skaraborg Hospital Group
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The Skaraborg Hospital Group, (SHG), is situated in the Western Region of Sweden and
serves a population of 260,000 citizens. The group consists of the hospitals in four towns,
Lidköping, Skövde, Mariestad and Falköping. The services offered by SHG include acute and
planned care in a large number of specialties. In total there are more than 700 beds and around
4200 employees at SkaS. At SHG, sustainability is a prioritized strategic theme to meet the
future challenges facing healthcare systems. The long-term goals of SHG entail a focus on
continual process development from a patient’s perspective including high quality service
provision and patient safety. The long-term ambition of SHG is to continuously improve and
grow its value-adding activities in the care processes from a customer perspective, leading to
sustainable outcomes from clinical as well as social, ecological and economic perspectives.
The strategy requires full commitment from managers to support, develop, and empower
employees at all levels in the organization. Accordingly, in the past ten years a competence
structure for improvement has been established whereby many new working positions have
been created. A parallel, internal improvement organization has been developed, consisting of
30 full-time improvement facilitators connected to patient processes and key strategic
processes, but also 60 black belts, 300 green belts and more than 3000 white belts, 40 Lean
coaches and six part-time PhD students in technology management and economics –
competences that are all incorporated in the organization and that aim to lead and/or support
improvement efforts of various magnitudes (Hellström, Lifvergren & Quist, 2011; Lifvergren,
Gremyr, Chakhunashvili, Hellström & Bergman, 2010).
The West Skaraborg Development Coalition
The set up of the initiative we focus on here can be traced back to a project initiated in 2001
with a view to strengthening collaboration between the hospital in Lidköping, its associated
primary care providers and the six municipalities in West Skaraborg, to ensure improvements
16
in care from a patient perspective. The Lidköping Hospital, one of the hospitals in SkaS,
serves a population of about 85,000 people in West Skaraborg. It is an acute care hospital
with complete departments and staff on call. It has about 160 beds and 700 employees. The
approach to the development of integrated care has explicitly had a long-term orientation. It
would combine existing and newly generated knowledge in both medicine and management
and would evolve continuously in small steps of experimentation, reflection and thereby
learning (Lifvergren et al., 2011; 2009). The organising model of integrated care in the project
has consisted of a political and an administrative team, the development coalition
management group (DCMG), as well as several project teams.
An Integrated Team Gets to Work
One of the most important outcomes from the previous West Skaraborg Collaboration project
was the institutionalization of the DCMG, a steering committee that includes the hospital
director, a senior civil servant from each of the six municipalities, and a senior management
representative from each of the six participating primary care centres. The DCMG group
shares a common vision as well as long-and short-term goals for the West Skaraborg,
formulated in a common balanced scorecard. The group meets every second week to lead and
support improvement activities pertaining to the integrated care within the area.
Drawing from an analysis in 2007, the DCMG concluded that although integrated care
within the area had improved significantly for the last five years (Lifvergren et al. 2011;
2009), it only really manifested itself in general networking terms, that is, as a set of arenas
for practitioners to discuss, across organizational and professional boundaries, ideas about
how care might be organized through more collaborative forms. Integrated practices that
involved direct everyday patient contact had not evolved.
Therefore, and as an initiative to catalyse the further development of integrated
17
practices in daily operations, DCMG decided to initiate and establish a mobile operational
team in late 2007, the purpose of which would be to provide care for elderly patients with
multiple illnesses. Three co-workers were recruited to form the team, which would budgetwise belong to the primary care organization but report directly to the DCMG. The first step
was taken in February 2008 when two nurses were hired: Siv, a former district nurse with
more than 20 years of experience from care of multiple-diseased elderly and; Christina, also
with many years’ experience from a haematological department at Lidköping Hospital but
also a former member of the local integrated care network (see Lifvergren et al., 2011; 2009).
During the autumn, Ulla, Senior Physician and specialist in geriatrics joined to complete the
team.
Towards a Working Model
The mission of the team, as expressed by the DMCG, was (and is) to improve healthcare for
elderly with multiple diseases within the area. However, no working model was established
then so the team members had to design the modus operandi themselves. During 2008, the
team started to analyse how they wanted to work: What evidence-based models could be
found in the literature? How were things organized in other healthcare systems? The team
members engaged in several field trips to other places in Sweden where integrated care teams
had been developed. But they didn’t find any team that worked the way they had envisioned:
Christina: …....we wanted to work in a more profound and embedded way. So
we also engaged in a deep analysis of our own area including the hospital and
the six surrounding municipalities. We pictured ourselves as a top of a triangle
and asked ourselves: from where will we get patients and where will they go
when we have stabilized their situation? It is obvious that these patients are
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everywhere in the system at the moment, in the primary care units, in the
municipalities and at the hospital.
It was decided that four of the following criteria should be met in order for a patient to
be treated within the integrated team model:
1 Have had at least 3 hospital admissions in the last 12 months
2 Have at least 3 chronic diseases
3 Have more than 6 standing medications
4 Require health care at home
5 Be at least 75 years of age
6 Be dependent on activities of daily life (ADL)
Moreover, the team explicitly stated that the model was designed to take care of
elderly people with multiple diseases as opposed to uni-diseased patients with late stage
tumour disease:
Ulla: Well, we are not a palliative care team. That is, we can’t handle unidiseased patients with severe cancer diagnoses. There are several experiences
from other parts of Sweden, e.g. Örebro, showing that this is an entirely other
group of patients in need of resources of a different kind including highspecialized palliative care. To mix the two patient categories often result in
poor outcomes and the tumour patients tend to attract all the resources. But still,
this isn’t to say that we don’t have a palliative approach when taking care of the
multi-diseased elderly.
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The team calculated on how large the actual population of West Skaraborg would be,
based on the inclusion criteria. To tackle this question, they began by considering the criteria
in all departments in the hospital an average day in April 2008. In the surgical departments
between 38% and 48% of patients fulfilled the criteria and in the medical clinics between 28%
and 67% of patients met them. The departments that had a high percentage were those that
were profiled against diseases that particularly affect the elderly patient.
The team then found that 0.2% of patients in the Lidköping hospital catchment area
had been hospitalized three times or more (i.e. the first of the inclusion criteria above) during
2007:
Christina: With this calculation we had seen the level of healthcare consumption
in its entirety. When we looked at the next criterion - having 3 or more chronic
diseases - the figure was about 0.2%, i.e. slightly less than 200 people per year.
Based on this factual information, the team went on to design the actual care model.
The overall population of elderly people in the actual area was conceptualized as a triangle,
see figure 2. At any moment, the team must have resources to handle 0.2% of the population.
The daily operations were visualized in terms of the “top of the triangle,” in which the team
planned to work with a limited number of patients at a time who were enrolled in the activities
of the integrated mobile care team. The team would take full responsibility for these patients.
-----------------------------------Insert Figure 2 about here-----------------------------------------------
The patient enters the "top of the triangle" through a referral that can come from the
hospital (emergency room, wards and clinics), primary care or the municipality, but not
directly from the patients themselves. Most often these patients, from having had a stable
20
condition that can be taken care of by the ordinary system (the 7% portion in the triangle), the
medical condition suddenly deteriorates and the patient tips over to the “top of the triangle.” If
a referral is affirmed, the patient is taken out of the ordinary ‘rat race’ for some time and the
team doctor would be their responsible doctor for about 4-8 weeks or, if needed, longer to
stabilize the situation in order to refer the patient back to the 7%-portion of the triangle. The
team estimated to handle up to 25 simultaneous patients, which later on appeared to be a
correct calculation (see the Results section). The team also envisaged an outflow from the
"top of the triangle" of two options – i) discharged as "healthy" to return to previous
healthcare providers, or with the right form of residence (the 7%-portion of the triangle, see
figure 1), or ii) discharged due to death. On the basis of additional calculations elsewhere,
they estimated that about half of the patients would die whilst still with the team and this has
also generally turned out to be correct.
Finally and before project start the team also worked on building an effective network
with all the involved stakeholders; the six municipalities, the primary care units and the focal
hospital. This was undertaken by systematically visiting workplaces in all organizations,
presenting the “triangle” approach as well as the inclusion criteria and how to refer a patient
to the team.
Ulla: We were met with great enthusiasm, but also some scepticism from some
quarters. We can however say that this scepticism, where it existed, has
gradually been replaced by more positive tones. For example, the municipal
nurses did not initially buy into our model as readily as the medical clinic's
physicians, but now we have developed a close and trustful relationship.
21
Testing the Model
The team started actual contact with patients on 15 November 2008. At this point, the
purposes and goals of the team had been agreed upon in a continuous dialogue with the
DCMG. The team’s vision was and still is to develop consensus with all the ordinary care
providers around the multi-ill patient irrespective of the principal care-providing organization.
The guiding principle is thus to focus on each individual patient to provide personalized,
secure, broad and coordinated care at home using a holistic and generalist perspective on the
care. Furthermore, the goal is also to reduce unplanned inpatient admissions.
After a year of using the model, the team convened together with the researchers to
reflect on the work model, results so far and how to improve the model. The team had then
handled around 60 patients. During the workshop, the team members all agreed that the model
was functioning well. The modelling of the team is based on a geriatric approach, that is, a
holistic approach around the patient and their relatives, in close collaboration with other
healthcare providers but with a clearly designated doctor responsible for the patient. The
approach is symptom-oriented rather than disease-oriented.
Siv: We get notified about a patient most often through the notification referral,
but sometimes also by a call from a nurse on a ward or from the municipalities.
In other cases Ulla also visits the different wards at the hospital to identify
patients that we then may take on the team. We then thoroughly gather every
piece of information, including the medical record, to get a comprehensive
picture of the patient’s status and current medical, social and psychological
problems. That way we can decide whether the patient really needs the team.
Usually, we can take on a patient within two weeks of notification.
22
Christina: The first thing we do if we decide to take care of a patient is to visit
the patient at home. The first visit is extremely important, not least to make the
patient and relatives feel safe and secure, being cared for, seen and listened to.
We usually spend around two hours on this first visit. It is important that the
patient and the relatives feel that there is no stress; that we take the time we
need. We are always two persons from the team, one physician and one nurse,
but we also make sure that a nurse from the municipality is present during the
visit.
Ulla: First, we sit together to talk about the current situation with the patient.
The dialogue is centred on the patient, his or her worst symptoms and what we
can do together to make the patient feel better and more secure at home. We also
go through the patient’s medication list to see if it fits with the pills that the
patient really uses.
Siv: This is quite scary. Not one out of 60 medication lists have been correct so
far!
Ulla: So it is extremely important that we get control of the patient’s
medication. During the second hour, we divide the work; I then spend an hour
with the relatives while Christina or Siv take care of the patient.
Christina: We have a very structured approach during the visit, where we
primarily focus on the patient’s symptoms and quality of life. We assess nine
23
different symptoms with visual analogue scales (see table 1). We also do a
regular medical check-up including pulse, saturation, blood pressure and routine
lab. In addition to symptoms we also evaluate risks, such as falls, pressure ulcers
and malnutrition, and not least the medication list, which is a big job particularly
when the existing drug lists around the patient are rarely consistent with each
other. This takes a lot of time and we then manage to establish a close contact
with the patient. Quite often the patient (him/) herself brings up questions about
death, fear of death and those sorts of issues.
Ulla: And that leaves me with plenty of time to talk to the relatives, most often a
husband or a wife. I then get a good picture of how they perceive the situation.
Fairly often we discuss how the patient feels about the disease, about death and
other questions like that. At the end of the visit we usually have a very good
picture of the situation and we can then create a care plan that aims at relieving
the most troublesome symptoms but also at making the patient feel secure and
safe.
Back at the office, the team then notifies all the involved actors in the surrounding
system – nurses and physicians in the municipalities, at the primary care centres and at the
hospital – about the plan and that the mobile team will take on the role as the spider in the
web until the situation is stabilized.
Christina: We put a lot of effort to integrate and coordinate the already existent
care resources around each patient. We try to involve them in the care, but we
24
also let them know of each other. The point is that we want the original care
system to function better so that we can eventually refer the patient back.
After the team has established the first contact with the patient, a lot of effort is put in
being there for the patient by phone. The team is available Monday to Friday during daytime.
They can be reached at all times during the day. Patients call when they have questions or if
anything happens at home. Should that be the case, two team members can visit the patient at
home to check the situation the same day. The team uses an “upstream approach” in the work
model.
Siv: All the time, we try to foresee potential problems to prevent deterioration of
the patient. That way, we avoid unnecessary admittances. We always prepare for
the weekends, when we are not available. We think of possible medical issues
that may emerge and prescribe drugs that can be administered by the
municipality nurse if needed. In other words, we contact the ordinary care
resources around each patient and prepare them for things that may surface. The
approach has been very successful, decreasing the number of readmissions
dramatically.
Christina: One of us always carries the phone and we complement each other
without any problems. I think that this is due to us being a small team; all of us
have a profound knowledge of what patients are in the ”top of the triangle”. We
work under the motto that something is never someone else's problem. We take
on problems where they are and solve them, sometimes in unconventional ways.
In collaboration with other healthcare providers, we work for the basic
25
technique of ‘backing off’ in confrontational contexts and thus gain confidence
in the long run.
The team has also access to two beds at the medical clinic where a patient could be
admitted should the situation be too unstable at home. However, due to the upstream
approach, these beds have rarely been needed.
RESULTS AND LESSONS LEARNED FROM THE FIRST THREE YEARS
After three years of experience, in December 2011, lessons learned and results were assessed
and reflected on together with the researchers and juxtaposed against the purpose and goals of
the team. The assessment included quantitative analysis of the database, interviews with the
surrounding meso- and macrosystem, reflections from the team, and interviews with patients
and their relatives.
The working model described above has turned out to be sustainable and the team still
uses the model, albeit with minor improvements. Moreover, the system seems to be stable
pertaining to the flow of patients moving through the top of the triangle, see figure 2. At any
given time, there are about 20 patients in the top and the team usually manage to take care of
these patients simultaneously. In December 2011 the team had handled 166 patients all in all.
Out of these, 55 had died during the time the team had been responsible for the care. Heart
failure is the most frequently represented diagnosis, affecting one-fourth of the patients. Other
common diagnoses are diabetes, ischemic heart disease and chronic obstructive pulmonary
disease. The most serious symptoms are fatigue, dyspnoea and unsteadiness.
The assessment showed that the team had been successful in its two initial goals: i) to
develop consensus in the surrounding meso- and macrosystem around the multi-ill patient
irrespective of the principal care-providing organization to improve security but also to reduce
26
care consumption and; ii) to focus on each individual patient to provide personalized, secure,
broad and coordinated care at home..
Consensus Around the Patient
The mobile team seems to play an important role in supporting the surrounding meso- and
macrosystem. In a focus group consisting of four nurses in the municipalities, two nurses
from the hospitals as well as physicians in the hospital, everyone appreciated the work of the
team:
Anna, municipality nurse: I feel really secure when they take over the patient,
you know yourself what do to and whom to contact when problems emerge. It’s
so much less work. Somehow you also get to know the system around the
patient, the team knows which care personnel are already involved around each
patient and how to contact them.
This quote was also concordant with reflections from the team. They try to act like a spider in
the web, teaching the already existing personnel in the meso- and macrosystem to integrate
and coordinate their efforts more efficiently so that the patient, when stabilized, eventually
can be handed over to the ordinary system, the 7% portion of the population triangle (see
figure 2).
Martin, senior physician at the hospital: I’ve been working with these types of
patients for a long time, but this is the first time I recognise a concrete
difference. Somehow the team manages to stabilize these fragile patients,
something that previous improvement efforts have failed to do. I think the team
does a tremendous job.
27
A clear effect of this was that the team members became more aware of each other’s
knowledge bases and became proficient at tapping into each other’s fields of expertise.
The care model also pointed to improved resource utilization. The care consumption
for the 166 patients was assessed; comparing six months prior to the patients’ inclusion in the
model with the consumption during the subsequent six months (counted from time of
admission to the mobile care program). The analysis showed an 80% reduction in emergency
visits by patients treated by the team. Likewise, a reduction of office visits by 89% was
observed, as was a reduction of hospital days by 92%. Moreover, all primary care physician
visits were eliminated in the municipality during the subsequent six months counting from the
time of admission of patients to the mobile care team. Thus, the analysis showed that the costs
for the actual clinical microsystem were more than made up for from savings in the
surrounding meso- and macrosystem. Although data is still under analysis, according to the
mobile care team, most of the stabilized patients that have been referred back to the ‘ordinary’
system have remained stable so far drawing from analyses of hospital re-admittances and
number of emergency visits.
Personalized Care at Home
Some citations from interviews with relatives might elucidate the importance of the role that
the mobile team played when taking full care of the patient. As expressed by Dagmar, the
wife of one of the patients, now diseased:
I remember the first visit; they asked me if I thought he was afraid of dying. I
don’t know what it was – they were so sweet. I could tell that they had real
sympathy for us. We felt taken care of, really…If you had any worries you
could just call them….. //…….Lars really liked them (the mobile care team)
28
tremendously. They just made such a good contact immediately. Doesn’t it
always feel good when you’re not just a number? When someone really cares
for you.
Or, listening to the voice of Gunnar’s wife (Gunnar is now deceased):
All these ambulance travels…. When he was in pain the district nurse gave him
morphine. If he was still in pain, we had to go the hospital. This happened in
February, and again in March and in April, it was really exhausting. During the
last fourteen days, however, we were taken care of by the mobile team. It was
just wonderful, we got help at home and we could stay at home. Gunnar didn’t
seem to suffer and he gently fell asleep. We should have gotten this help earlier.
The quantitative analysis showed improved quality of life. The relief of symptoms was
directly measured in the patients who were discharged and still alive (n=23), and compared
with symptoms assessments at referral, see table 1. As illustrated in the table, there has been
an improvement in nearly all of the symptoms, whereas eight of them showed statistically
significant improvements.
------------------------------Insert table 1 about here-----------------------------------------------
Spreading the Concept: Further and Future Developments in Skaraborg
Accordingly, the establishment of the clinical microsystem in West Skaraborg has so far been
successful from many perspectives. However, during 2011 DCMG has taken further steps to
tie the actual microsystem tighter to the surrounding meso- and macrosystem. The steering
committee realized that a sustainable healthcare system demands a strategy that entails an
29
upstream approach to manage the entire elderly population. Subsequently, different strategies
have been articulated in West Skaraborg by the DCMG, the purposes of which are to
constantly seek ways to shift the centre of gravity of the elderly population triangle to its base
(see figure 2). Keeping elderly people healthy or preventing disease is hence of utmost
importance (the two base portions of the triangle), preventing them from developing and/or
reducing the impact of chronic diseases.
In 2008, the three care providing organizations –the hospital, the municipalities and
the primary care organization – agreed on common goals to promote health and prevent
disease (Lifvergren et al., 2011). The goals were formulated in a shared balanced scorecard
and are now continuously being implemented in the three organizations. In addition, when
elderly patients have developed multiple diseases, the goal is to stabilize the condition, thus
preventing the patients from deteriorating to an unstable situation (the top of the triangle).
Using this model, during 2010 a senior physician belonging to the primary care organisation
was assigned to take on responsibility for the coordination and integration of care pertaining
to the 7% proportion of the elderly population, see figure 2. The physician also reports to the
DCMG and has meetings once a month with the integrated mobile care team. The ambition of
the meetings is to constantly identify risk patients within the 7% proportion of the population
to prevent them from becoming unstable – an upstream perspective, but also to prepare for a
safe re-remittal of stabilized patients to the ordinary system.
Moreover, the DCMG has established another clinical microsystem in the area with
the mission to take care of uni-diseased cancer patients in palliative or terminal states. This
team also consists of several nurses and one senior physician, all of them with long-term
experiences from hospital cancer care. The team is mobile, but has also access to beds in a
palliative care home nearby. The cancer care microsystem shares office with the integrated
30
care microsystem, which facilitates collaboration and care coordination between the teams. As
stated by the physician in the cancer care team:
We meet on a daily bases, why it is really easy to share information about
common patients. I also think the vulnerability of the both systems diminishes –
we can always help each other when needed.
In 2011, SHG took over the economic responsibility for the integrated mobile care
team in West Skaraborg, although the team still reports to the DCMG as well. Moreover, the
SHG has decided to implement the entire West Skaraborg care model for elderly people and
patients with cancer disease throughout the Skaraborg county. For instance, during 2012,
three more integrated mobile teams for multi-ill elderly patients will be established to cover
the remaining northern-, eastern- and southern parts of Skaraborg.
DISCUSSION
In the context of the West Skaraborg case the challenge has been to establish new forms of
working that integrate thinking and actions along patient pathways. We propose the concept
of a clinical microsystem to capture how this might be understood. We argue that whilst the
various conceptualisations of teams in the literature are helpful, something more is needed to
fully capture not just the dynamics of the team but also the broader interactions in which it is
embedded. Our case illustrates a team in its embedded context – what we call a clinical
microsystem - whose members mutually support each other as a role complementary team.
The members of the team at the core of the microsystem set out its criteria for defining
which patients its work would encompass, then designed a working model and thereafter
tested this. Each of these activities fed into the next following periods of reflection on the
31
outcomes of the various actions undertaken by the team collectively. In other words, we can
see the emergence and evolution of the microsystem as a learning process. The design of the
model entailed the visualisation of daily care activities in terms of a triangle which specified
which patients they would work with, and who would have responsibility for their care. The
subsequent testing of the model designed by the team members entailed a process of
collective reflection (Boud et al., 2005) on their actual work practices within the value
configuration of the chain (Christensen et al., 2009). Indeed, we can also understand that such
practices characterise the everyday social interaction within the mobile team at various
junctures along patient pathways. In the case the particular challenge faced by the mobile
team was that of delivering integrated care to a particular group of patients who had serious
difficulties in gaining access to the normal care delivery points in primary, secondary and
tertiary care. To rectify this, the team took the care to the patient instead. However, this idea is
easier said than done. It requires not only the actual care provision arising, now, from the new
practices of the mobile team, at the home of the patient, but also knowledge sharing within the
team along the various points of the patient pathway as well as interaction and knowledge
sharing with other actors – external to the team – within the broader healthcare system.
The work of the team obviously also entailed the provision of care to patients in what
Christensen et al. (2009) call a shop logic. This is clear, for example, in Christina’s account of
visiting patients at home for dialogues about symptoms and regular check ups. The access of
the team to beds at the medical clinic of the local hospital can also be seen as “shops”. The
team has similar access to primary care facilities and local authority social services
departments as potential shops if necessary, but these are rarely used because the team
prioritises an upstream approach. An emphasis on symptoms rather than diseases together
with the prioritization of preventing deterioration at an early stage means that most of the
32
“shopping” activity takes place at the patient’s home rather than on the premises of the care
providers.
A key idea is to combine as far as possible the various treatments and consultations
with patients, simultaneously in time and space. An upstream approach implies that this
occurs as far as possible at the home of the patient. This can be seen as “one-stop shopping”
whereby a role-complementary team is able to undertake as many if not all of the required
care practices on one visit. This inevitably requires such a team to be geographically flexible
or mobile in that patients may not necessarily have easy access to the everyday premises of
the healthcare providers. The patients concerned (”the top of the triangle”) might find
themselves at home or in care residencies and unable to travel to either the hospital or primary
care units. This mobility of the team, together with its role complementarity, exemplify well
the notion of adaptive capacities that we have argued previously are a core feature of a
sustainable health care system (Folke et al, 2002).
The team, in its endeavours to provide a seamless process of care provision for the
patient, necessarily also draws on broader resources, for example knowledge, through
developing relationships with key stakeholders beyond the team that reside in the broader
healthcare macrosystem or network. This is well illustrated by Ulla’s account of the team’s
visits to various workplaces within the broader macrosystem for exchanges of experience and
dialogues to gain better understandings of each other’s role in the system. This is a good
example of what Christensen et al. (2009) call a network logic that entails knowledge sharing
and the mobilisation of resources from beyond the team. The importance of the broader
network in the daily activities of the team is also underscored by Christina who stresses that
the team members put a great deal of effort into coordinating the already existent care
resources (from the network) around the patient. Accordingly, knowledge is transferred both
from the broader system to the team and vice versa.
33
A further aspect of the case is that the team state they have increasingly broadened
their competences beyond their own individual fields of expertise. To be more precise, this
has necessarily entailed the team members having hooks to each other’s knowledge bases so
that they can work out their knowledge interdependencies. In this sense the team has evolved
to resemble what researchers have identified as role complementary teams (Lind & Rennstam,
2007). Interestingly, this runs counter to tradition within medicine whereby professional
specialisation has been the prevailing norm and ideal. Moreover, the mobile team can be seen
as embodying or symbolising key features that can be drawn upon by actors elsewhere in the
broader system of integrated care as “good practice.” Accordingly, the team has not only
drawn on the wider system in terms of securing resources including knowledge, it has also
played a pedagogical role of its own in terms of transferring knowledge on each patient to
actors in the broader system, for example nurses and physicians in the municipalities, primary
care centres and the hospital.
Finally, we believe that the team, through its continuous dialogue with critical
stakeholders in the surrounding meso-and macrosystem, e.g. the DCMG, encouraged a
broader system’s understanding, eventually catalysing an improvement strategy entailing the
entire population of elderly people within the area, see figure 2.
What, then, are the design implications for our conceptualisation of clinical
microsystems? We should be wary about making sweeping claims from a single case. But it
seems to us that clinical microsystems do share many of the characteristics of parallel learning
systems (Bushe and Shani, 1991). Although not strictly speaking a part of the formal health
care organization, clinical microsystems do entail interaction between professionals
encompassed by the microsystem and their colleagues in the formal health care bureaucracy.
As such, the knowledge sharing in which the team is engaged both internally and externally
with actors in the clinical microsystem needs to be made transparent.
34
On the other hand, the self-design element we detected in the emergence of the team
suggests that the scope for conscious design and implementation may have its limitations. It is
fruitful to understand the mobile team at the core of the clinical microsystem as focused on
the delivery of care processes, whereas the formal bureaucracy is focused on the securing and
distribution of resources. The relation between these two is one of loose coupling. However,
our findings challenge the view of Nelson et al (2007) who argue that loose coupling is likely
to characterise temporary rather than permanent teams. In the case of our clinical microsystem
this is not the case: Within the overall ambition of sustainability the intention is for the mobile
team to become an enduring feature. However, more research is needed to specify the precise
mechanisms that link the process and resource organizations more clearly.
CONCLUSION
This chapter has reported on the background, implementation and outcomes of a mobile
integrated care team that has been set up with a view to improving care to elderly patients
with multiple illnesses. The team has drawn on three quite distinct logics functioning
simultaneously as a shop for care provision on discrete medical conditions, as a chain for
ensuring that these are coherently integrated and consistent with patient needs as well as
working within the broader network that comprises the healthcare system of the area as a
whole. We have argued in the chapter that this team can be seen as an instructive illustration
of a clinical microsystem (Batalden et al., 2003).
A sustainable health system has to be built on alternative principles to those of the
traditional functional bureaucracy, which has been the standard template in healthcare
organisations across the globe for many decades. However, whilst bureaucracy certainly has
its defenders (see e.g. Adler and Borys, 1996; du Gay, 2000), it has also been argued that it
cannot deliver the triple bottom line (Kira & Lifvergren, 2012). The demand to conform to
35
centrally determined budgets entails a one-dimensional organising logic that conflicts with a
logic that prioritises the provision of services in line with customer (i.e. patient) needs.
Accordingly, we also argue in the chapter that a clinical microsystem with adaptive capacities
can form the cornerstone of a broader system of sustainable health care (Lifvergren et al.,
2009).
However, we still know very little about how such a sustainable health system might
be designed. We have thus sought in this chapter to advance our understanding of
sustainability in healthcare by eliciting and illustrating the concept of a clinical microsystem
and linking it to the existing literature on teamwork. It is perhaps premature to claim that a
mobile team with its specific characteristics of embeddedness can be generalised into other
contexts. However, on the basis that we have unpacked and illustrated the concept of a
clinical microsystem in this chapter we are at the very least confident that the concept has
analytical purchase beyond the single case.
A number of issues, however, remain unexplored here suggesting the need for further
research on the role and implications of clinical microsystems in the context of integrated
care. For example, our grasp of the learning dynamics between the micro- and macro systems
remains undeveloped. We have suggested here, on the basis of interview data with team
members, that knowledge has been transferred or shared between the systems in both
directions. Further work is needed, however, to shed light on the learning mechanisms and
processes in play here (Shani & Docherty, 2008). Who, precisely, learns, and what is it that
they learn? How do we conceive of learning at the team level? And can we talk about learning
at the system level (Lifvergren et al., 2009)?
36
REFERENCES
Adler, P., & Borys, B. (1996). Two types of bureaucracy: Enabling and coercive.
Administrative Science Quarterly, 41, 61-89.
Batalden, P. B., Nelson, E. C., Huber, T. P., Mohr, J. J., Godfrey, M. M., Headrick, M. A. &
Wasson, J. H. (2002). Microsystems in Health Care: Part 1. Learning from HighPerforming Front-Line Clinical Units. Journal on Quality Improvement, 28(9), 472-93.
Batalden, P. B., Nelson, E. C., Huber, T. P., Mohr, J. J., Godfrey, M. M., Headrick, M. A.,
Wasson, J. H., Campbell, C. & Homa, K. (2003). Microsystems in Health Care: Part 2.
Creating a Rich Information Environment. Joint Commission Journal on Quality and
Safety, 29 (1); 5-15.
Boud, D., Cressey, P. & Docherty, P. (eds) (2005). Productive Reflection at Work. London:
Routledge.
Broman, G., Holmberg, J., Robèrt, K.H. (2000). Simplicity without reduction – Thinking
upstream towards the sustainable society. Interfaces: International Journal of the
Institute for Operations Research and the Management Sciences, 30(3).
Bushe, G. and Shani, A. B. (1991) Parallel Learning Structures. Reading MA: AddisonWesley.
Cederquist, J. & Hjortendal Hellman, E. (2005). Iakttagelser om Landsting [Observations on
County Councils]. Stockholm: Rapport från KOMSAM, Swedish Ministry of Finance.
Christensen, C., Grossman, J. & Hwang, J. (2009). The Innovator's Prescription: A Disruptive
Solution for Health Care. New York: McGraw-Hill.
37
Clark, P. G. & Drinka, T. J. K. (2000). Healthcare Teamwork: Interdisciplinary Practice and
Teaching. Westport, CT: Auburn House.
Du Gay, P. (2000). In Praise of Bureaucracy. London: Sage.
Elkington, J. (1999). Triple bottom-line reporting: Looking for balance. Australian CPA,
69(2), 18-22.
Folke, C. et al. (2002). Resilience and sustainable development: Building adaptive capacity in
a world of transformations. Scientific background paper on resilience for the process of
The World Summit on Sustainable Development on behalf of The Environmental
Advisory Council to the Swedish Government. Stockholm: Environmental Advisory
Council, Ministry of the Environment.
Greenwood ,D . & Lewin, M. (2007). Introduction to Action Research: Social Research for
Social Change (2nd edn). Thousand Oaks: Sage.
Hobfoll, S.E. (2002). Social and psychological resources and adaptation. Review of General
Psychology, 6(4), 307-324.
Huzzard, T., Ahlberg, B. M. & Ekman, M. (2010). Constructing Interorganisational
Collaboration: The Action Researcher as Boundary Subject. Action Research Journal
8(3), 293-314.
Kalliola, S. (2003). Self-designed teams in improving public sector performance and quality
of working life. Public Performance Management Review, 27(2), 110-122.
Kim, M.M., Barnato, A.E., Angus, D.C., Fleisher, L.F. & Kahn, J.M. (2010). The Effect of
Multidisciplinary Care Teams on Intensive Care Unit Mortality. Archives of Internal
Medicine 170(4), 369-376.
Kira, M., & Lifvergren, S. (2012). Sowing seeds for sustainability in work systems.
Forthcoming chapter in: Ehnert, I. (editor) In: I. Ehnert, W. Harry and K. Zink (Eds),
Handbook of Sustainability and Human Resource Management.
38
Lifvergren, S., Docherty, P., & Shani, A.B. (Rami). (2011). Toward a sustainable healthcare
system: Transformation through participation. In: S. Moreman & A.B. Shani,
Sustainability Effectiveness. Emerald, MA.
Lifvergren, S., Gremyr, I., Hellström, A., Chakhunashvili, A., & Bergman, B. (2010). Lessons
from Sweden’s first large-scale implementation of Six Sigma in healthcare. Operations
Management Research, 3, 117–128, DOI 10.1007/s12063-010-0038-y.
Lifvergren, S., Huzzard, T., & Docherty, P. (2009). A development coalition for sustainability
in healthcare. In: P. Docherty, M. Kira & AB. Shani (Eds), Creating sustainable work
systems (2nd ed, pp. 167–185). London: Routledge.
Lind. J-I., & Rennstam, J. (2007). Team – Typer och Myter. [Teams – Types and Myths]. In
Alvesson, M. & Sveningsson, S. (Eds), Organisation och Ledning. Lund:
Studentlitteratur.
Lind, J-I., & Skärvad, P-H. (1997). Nya Team i Organisationernas Värld. [New teams in the
world of organizations]. Malmö: Liber.
Mathieu, J.E., Maynard, M.T., Rapp, T., & Gilson, L. (2008). Team Effectiveness 1997-2007:
a review of recent advancements and a glimpse into the future. Journal of Management,
34(3), 410-476.
NHS (2012) ‘Improving Patient Pathways’
http://www.institute.nhs.uk/care_outside_hospital/care/care_outside_hospital.html
(accessed on 17th January 2012).
Mohr, J. J., & Donaldson, M. S. (2000). Exploring Innovation and Quality Improvement in
Health Care Micro-Systems - A Cross-Case Analysis. A Technical Report for the
Institute of Medicine Committee on the Quality of Health Care in America. Washington;
Institute of Medicine.
39
Mohrman, S. & Shani, A.B. (Rami) (2011) Organizing for Sustainable Effectiveness: Taking
Stock and Moving Forward. In: Mohrman, S. & Shani, A.B. (Rami) (Eds.),
Organizing for Sustainability. Bingley, UK: Emerald.
Nelson, E. C., Batalden, P. B. & Godfrey, M. M. (2007). Quality by design – a clinical
microsystems approach. Josey Bass: San Fransisco.
NUTEK. (2007). Effektivare vård med patienten i focus. [More efficient care focusing the
patient]. New facts and statistics, no 6, July.
Peterson, E.D., Albert, N.M., Amin, A., Patterson, J.H. & Fonarow, G.C. (2008).
Implementing Critical Pathway and a Multidisciplinary Team Approach to
Cardiovascular Disease Management. The American Journal of Cardiology 102(5A),
47G-56G.
Porter, M. (1985). Competitive Advantage: Creating and Sustaining Superior Performance.
Free Press: New York.
Procter, S., & Mueller, F (2000) Teamworking: strategy, structure, systems and culture. In:
Procter, S. & Mueller, F (Eds) Teamworking. Basingstoke: Palgrave MacMillan.
Quinn, J. B. (1992). Intelligent Enterprise. New York: Free Press.
Reason, P., & Bradbury, H. (Eds) (2008). The Sage Handbook of Action Research:
Participative Inquiry and Practice (2nd edn). Thousand Oaks: Sage.
Sicotte, C., Pineault, R., & Lambert, J. (1993). Medical team interdependence as a
determinant of use of clinical resources. Health Services Research, 28(5), 599-621.
Solheim, K., McElmurry, B. J., & Kim, M. J. (2007). Multidisciplinary teamwork in US
primary health care. Social Science & Medicine, 65(3): 622-634.
Stabell, C., & Fjeldstad, Ø. (1998) Configuring Value for Competitive Advantage: On Chains,
Shops, and Networks. Strategic Management Journal, 19(5), 413-437.
40
Swedish Association of Local Authorities and Regions, SALAR (2005). Hälso- och
sjukvården till 2030. [Healthcare from now to 2030]. Borås: SKL.
Swedish Association of Local Authorities and Regions, SALAR (2011). Öppna jämförelser.
[Open Comparisons]. Borås: SKL.
Swedish Department of Treasury (2005) Iaktagelser om landsting [Observations on counties]
DS 2005:7 (online http://www.sweden.gov.se/sb/d/108/a/41627).
West, M.A., Borrill C., Dawson, J, Scully, J., Carter, M., Anelay, S., Patterson, M., &
Waring, J. (2002). The link between the management of employees and patient
mortality in acute hospitals. The International Journal of Human Resource
Management, 13(8), 1299-1310.
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Table 1. Wilcoxon's signed ranks test has been used to compare the patient symptoms before (at
admission) and after/at discharge (n=23). The symptoms have been measured subjectively by patients
on a scale 1-10, where 10 is the worst condition and 1 is the best condition. An exception is
sleeplessness, satisfaction and quality of life, where the scale has been reversed. Significant
differences bolded.
Symptoms
Dizziness
Unsteadiness
Pain
Nausea
Poor appetite
Difficulty of swallowing
Thirst
Obstipation
Leakage of urine
Peripheral oedema
Dyspnoea
Chest pain
Sleeplessness
Fatigue
Loneliness
Depression
Meaninglessness
Uneasiness
Anxiety
Satisfaction
Quality of Life
Walking range
Z
-2,862a
-,601a
-1,857a
-,368a
-1,442a
-1,000a
-1,342b
-1,069a
-,071a
-2,542a
-2,060a
-2,673b
-2,269a
-1,874a
-,422a
-2,056a
-1,912a
-2,670a
-2,032a
-1,335b
-1,608b
-1,362b
Asymp. Sig. (2-tailed
,004*
,548
,063
,713
,149
,317
,180
,285
,577
,943
,039*
,008*
,023*
,061
,673
,040*
,056
,008*
,042*
,182
,108
,173
42
Figure 1: A clinical microsystem – a model
Shop:
Home
Shop:
Primary
care
care
provision
Patient
symptoms
Shop:
Hospital
care
provision
Shop: Local
authority
(aftercare)
care
provision
Chain: multidisciplinarity, role complementarity, mobility, self design
knowledge
sharing ,resource
mobilization
Network ( wider health system)
43
Patient
discharge
Figure 2
Conceptual figure developed by the team together with the researchers that illustrates the different proportions of elderly people with different
care needs in the actual area
Elderly people with multiple chronic diseases
in unstable condition and taken care of by the
integrated mobile care team
0.2%
7% of elderly
population
Elderly people with
one or two stable chronic
diseases and taken care of by the
’ordinary’ care system
Healthy elderly people
44
Elderly people with multiple chronic
diseases but in stable condition and taken
care of by the ’ordinary’ care system