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 1 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 2 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. 3 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 4 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. 5 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 6 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 7 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, 8 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, 9 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 10 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 11 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. 13 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 15 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 18 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. 19 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. 41 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