Manon Roest

Healthcare systems in many western countries are confronted with intertwined pressures that collectively jeopardize their long-term sustainability. Population ageing, rising multimorbidity, increasing costs, and workforce constraints constitute a complex, interdependent set of challenges for which no single organization or policy instrument provides an adequate response. Sustaining the affordability, accessibility, and equity of healthcare systems requires fundamental change in the way that care is organized, delivered, and financed. This change extends beyond incremental efficiency gains as it requires a system-wide multi-level change process that, through innovation, affects multiple organizations and care providers with the aim of improving efficiency, care quality and patient outcomes. This process is commonly referred to as healthcare transformation. Because healthcare transformation is inherently a system-wide process, it cannot be achieved by individual organizations acting in isolation. It requires collaboration of multiple organizations that coordinate actions across organizational boundaries. Inter-organizational healthcare networks, in which multiple organizations collaborate towards a collective goal, have emerged as a vehicle to enable such coordination. In the Netherlands, these healthcare networks have been promoted through the Integral Care Act (Integraal Zorgakkoord). The Integral Care Act positions regional healthcare networks as an infrastructure for advancing transformation, emphasizing collaborative governance across hospitals, primary care providers, mental health services, and social welfare organizations. Healthcare networks hold significant potential: they provide platforms for the spread of innovations, facilitate knowledge exchange on best practices, support organizational learning, and build quality improvement capacity at the system level. However, they also face considerable challenges. Recurrent difficulties include sustaining active engagement over extended periods, managing tensions and competitive interests, ensuring sufficient resources and maintaining alignment among diverse stakeholders. These challenges underscore the importance of behavioral aspects of collaborating in healthcare networks. Networks are not merely governance arrangements or formal structures; at their core, they are constituted by actors (i.e. healthcare professionals and managers policymakers) who interact within and across organizational boundaries, thereby shaping whether collective objectives are ultimately achieved. While prior research has substantially advanced the understanding of the structural and governance dimensions of healthcare networks, it has offered comparatively limited insight into how the behaviors of actors shape network functioning and whether these behaviors can be actively supported to advance transformation objectives. It is precisely the behavioral dimension that remains underexplored, and which forms the central focus of this dissertation. This dissertation examines several behavioral aspects of actors collaborating in inter-organizational healthcare networks oriented toward system-level healthcare transformation. The overarching research question is: How do actors collaborate within healthcare networks aiming for healthcare transformation? This dissertation draws on qualitative empirical research conducted across Dutch healthcare networks. Because healthcare transformation unfolds across multiple levels (i.e., network, organization, and individual) and through the interactions between them, this dissertation addresses collaboration of multiple levels. The chapters provide insights into several behavioral aspects that shape whether and how healthcare networks collaborate towards their transformative goals. Chapter 2: Organizing telemonitoring This chapter addresses the organizational level of healthcare transformation, focusing on the decisions involved in organizing a digital health innovation: telemonitoring. Telemonitoring, defined as the use of technology to monitor patients remotely, restructures care delivery by shifting elements of care from hospital to home settings. As such, it addresses several of the systemic challenges described above, including unsustainable hospital capacity, rising costs and staff shortages. Understanding how organizations decide to implement telemonitoring is therefore directly relevant to healthcare transformation. Two principal organizational models were studied: a centralized model, in which patient monitoring is concentrated in a physical or virtual centralized monitoring center staffed predominantly by tele-nurses, and a distributed model, in which professionals monitor their own specific patient populations within existing workflows. This chapter applies the NASSS (Non-adoption, Abandonment, Scale-up, Spread, and Sustainability) framework to analyze decision-making across seven interconnected domains: condition, technology, value proposition, adopter system, organization, wider context and adaptation over time. The findings reveal that the behavior of actors determines which organizational model is pursued and which are not. This chapter illustrates that the choice between organizational models is profoundly shaped by the perceptions and value judgements of key decision makers, in particular, healthcare professionals. Decisions made in the early phases of implementation, often driven by clinical considerations and perceptions of added value, carry far-reaching organizational consequences: they determine task redistribution, influence workflows, and shape the scope and nature of inter-organizational partnerships at a regional level. Centralized monitoring centers, for example, require the establishment of a new professional role (i.e. the tele-nurse) and necessitate governance arrangements across multiple organizations, creating both coordination challenges and significant systemic potential. The chapter concludes that decision-makers must possess competencies that extend beyond clinical expertise; they must be equipped to assess organizational fit, anticipate inter-organizational implications, and evaluate contextual alignment across all relevant NASSS domains. Chapter 3: Sustaining Network Commitment In this chapter, the focus shifts from the organizational to the network level, examining the conditions under which sustained collaboration among network actors can be maintained over time. Since healthcare transformation is a gradual process, it often unfolds across multiple years and thus requires continuous engagement of diverse stakeholders. Yet, sustaining this engagement is a persistent challenge that healthcare networks face. Network commitment, which is the intention to remain in the network and actively contribute to its collective objectives, is widely recognized as an enabler of network effectiveness. However, the conditions under which commitment declines and the managerial approaches to address such decline, remain poorly understood. Through an exploratory qualitative study involving representatives from Dutch healthcare improvement networks, this chapter identifies reasons for declining network commitment: (1) rising discrepancies between network objectives and the evolving needs of participating organizations; (2) perceptions of slow progress; (3) a lack of reciprocal engagement; and (4) resistance to change at the organizational level. In response to each of these challenges, corresponding managerial approaches were identified: collaborative reassessment of goals and needs; expectation management and the celebration of incremental successes; the establishment of preconditions that foster equal contribution and build trust; and the engagement of senior leadership alongside deliberate cultivation of personal relationships. The findings are then synthesized into a dynamic model of network commitment, building on and extending Ring and Van de Ven's framework of developmental processes in cooperative inter-organizational relationships. The model emphasizes that managing network commitment is not a linear process but a cyclical one, requiring different behavioral responses at different stages of network development. Crucially, the model highlights the role of interpersonal relationships as both an outcome of sustained collaboration and a mitigating factor against commitment decline. The chapter contributes by providing empirical insight into the active management of network commitment and offers actionable guidance for network coordinators seeking to sustain collaboration toward healthcare transformation. Chapter 4: Brokerage Behavior Healthcare transformation is typically realized through innovations as they are widely recognized as essential drivers of system-level change. Yet despite the proliferation of innovations at the level of individual organizations and departments, healthcare systems continue to struggle with the same persistent challenges. A principal explanation lies in the predominantly local character of many innovations: developed within specific organizational contexts, they are rarely transferred successfully across institutional and professional boundaries. Without effective diffusion and dissemination, innovations remain isolated improvements rather than catalysts for system-wide change. The challenge of scaling innovations across organizational boundaries has brought attention to the role of intermediaries (e.g. individuals such as healthcare professionals, managers, and policy advisors) who function as bridges between disconnected actors and organizations. This act of bridging, often conceptualized as knowledge brokering, has been identified as a critical but underexplored mechanism in the dissemination of innovations within and across healthcare systems. This chapter argues that this is not only a structural problem but a behavioral one: whether and how innovations are shared, assessed, translated, and adopted depends on the behavior of the individuals who occupy key positions in the network. Drawing on a qualitative case study conducted within a Dutch nationwide network of 27 teaching hospitals, and building on the five brokerage roles conceptualized by Gould and Fernandez (1989), this chapter examines how actors enact specific brokerage behaviors to facilitate the dissemination of innovations across organizational boundaries. The five roles (i.e. coordinator, gatekeeper, representative, liaison, and cosmopolitan) each occupy a distinct structural position in the network and enact a characteristic set of activities. Beyond identifying the activities associated with each broker role, the chapter inductively identifies the competencies required to enact these roles effectively. The chapter concludes that brokerage in healthcare networks should be understood not as the activity of a single designated individual, but as a collective process enacted through configurations of complementary broker roles. Formalizing and deliberately cultivating these roles through role clarity, training, and governance holds significant potential for strengthening the capacity of networks to disseminate innovations at scale. Chapter 5: A Serious Game “Care to Collab?” The fifth chapter translates the theoretical and empirical insights of Chapter 4 into a practice-oriented, experiential learning intervention: a serious game specifically designed to enable healthcare professionals and managers to recognize, experience, and reflect upon brokerage behavior within a simulated inter-organizational collaboration. The game, titled “Care to Collab?”, structures a simulated regional healthcare network comprising three organizations (a hospital, a midwifery practice, and a general practice), with a minimum of six players. Through a combination of constrained communication pathways, individually assigned goals, and deliberately distributed information cards, the game places each player in a distinct position and challenges them to collaborate across organizational boundaries to resolve a shared crisis scenario. The game was tested across a range of settings. The results demonstrate in this chapter that the game elicited diverse brokerage behaviors, surfaced tensions arising from competing individual and collective goals, and prompted recognition of counterproductive behaviors including organizational siloing, non-reciprocity, and inside-out framing. Through gameplay and guided reflection, players not only enacted different broker roles but also developed greater awareness of the dynamics that undermine collaborative efforts. The chapter concludes that the serious game offers a promising and accessible tool for bridging the research-to-practice gap, facilitating both experiential learning and reflective insight into the conditions that enable or constrain collaboration in healthcare networks. Discussion The four empirical chapters are not to be seen as isolated studies but as interconnected inquiries into behavioral aspects of actors collaborating in healthcare networks aiming for healthcare transformation. Taken together, these findings advance a consistent argument: the functioning of inter-organizational healthcare networks is ultimately shaped by the actions and interactions of the actors within them. Decision-making at the organizational level carries organizational and inter-organizational consequences, underscoring the need for well-informed decision-making. Network commitment is not a given but will be challenged over the time, requiring continuous management and anticipation. Brokerage behavior determines whether innovations disseminate across the network and must therefore be recognized, formalized and supported. Moreover, counterproductive behaviors must be identified and addressed before they undermine collective efforts. Since healthcare transformation is a gradual process, time emerged as a theme throughout this dissertation. This chapter argues that adopting a temporal perspective is indispensable for understanding how behaviors, roles, and managerial needs change as networks mature and as the nature of knowledge demands shifts across phases. In the early phases of a network’s lifecycle for example, actors are primarily engaged in forming relationships, identifying where expertise resides, and accessing knowledge that would otherwise be unavailable. This initial exposure to new knowledge generates immediate value, which motivates commitment and fuels engagement. As networks mature and move toward implementation phases, knowledge demands become more specific and context-sensitive, requiring practical guidance on the organizational implications of innovation choices. Simultaneously the prominence of broker roles shifts and the reasons for decline in network commitment, as discussed in Chapter 3. Concluding This dissertation advances understanding of how actors collaborate within inter-organizational healthcare networks aiming for healthcare transformation. Through four empirical studies, it demonstrates that behavioral aspects of network collaboration are not secondary to structural conditions. Behavior of actors shape healthcare network functioning and whether they reach their transformation objectives. Healthcare transformation requires more than establishing networks and formulating collective objectives; it depends on the ongoing, well-supported, and collaborative behavior of the actors within them. Decision-making on innovation carries (inter-) organizational consequences; networks commitment is challenged by the behavior of network members and requires continuous management; brokerage behavior determines whether innovations cross organizational boundaries; Counterproductive behaviors, if left unaddressed, risk undermining collective efforts. The dissertation offers contributions to both academia and practice. For researchers, it advances theoretical frameworks of network commitment, brokerage, and innovation dissemination, and calls for a more explicitly temporal approach to network research. For practitioners (e.g., network managers, healthcare professionals, and policymakers alike) it provides actionable insights into how collaborative behaviors can be supported, counterproductive dynamics can be mitigated, and healthcare networks can be sustained in their pursuit of system-level transformation.