Network-based modes of organization have emerged in many public services. In the healthcare sector, they are considered useful tools to define patients’ care pathways and to help knowledge and practice sharing among organizations and professionals. In the case of cancer services the reconfiguration to network organizational forms has become the rule rather than the exception.
Even though the first instances of networks were mainly voluntary groups of professionals, they have since been regulated, structured, and institutionalized by governing bodies to pursue central targets and concentrate healthcare services. These networks, referred to as mandated networks, can be seen as a completion of the institutional structure of a healthcare system, increasing its complexity by adding a horizontal dimension to the vertical hierarchy.
The governance structure is crucial for network functioning and it includes both formal and informal aspects. As pointed out by Iedema et al. (2017), the governance of clinical networks has to be studied according to the dynamics and equilibria of healthcare systems. In fact, the creation of networks typically entails reconfiguring healthcare services to a network-based perspective while preserving the autonomy of the participant organizations. However, the reverse effect, i.e.,the effect of healthcare reconfigurations, such as merger processes, on networks, should also be taken into consideration.
Italian regional health systems are interesting cases for understanding and interpreting the position and role of clinical networks in changing healthcare systems. In fact, as every region has its own structure of healthcare system, different examples of clinical networks have emerged. The geographical, demographic, political, and healthcare system context in which clinical networks developed, also influenced their evolution in terms of governance structure. Moreover, it is possible to explore the influence that healthcare organizations’ reconfigurations, especially merger processes, have on pre-existing clinical networks.
Literature on network governance has provided indications of governance characteristics that are preferable in certain contexts or that fit better together, but has provided little empirical evidence[6–8]. The main aspect of this article is the application of the Provan and Kenis (2008) model of the governance mode of networks to the specific field of healthcare networks and its extension to include the analysis of systems in which mandated networks are involved.
The aim of this study is thus to analyze and compare the governance of two cancer networks in two Italian regions that underwent system reconfiguration processes. Our research questions are: a) how Italian regional healthcare systems, which have recently gone through reorganization processes, such as merger processes, influenced governance structures for cancer networks; and b) which contextual factors (internal and external to the networks) affect the possibility that different modes of network find a positive balance between the competing needs identified by Provan and Kenis (2008) (efficiency and inclusivity, internal and external legitimacy, flexibility and stability).
This paper is structured as follows. First, we review the literature on networks, with a focus on mandated networks and clinical networks. We then define the methodology of our study, followed by the description and comparison of our two cases based on a theoretical framework obtained from literature on mandated networks. We conclude by summarizing and discussing our key findings.
In the public organization domain, Provan and Kenis (2008) [6, p. 236]defined a network as “groups of three or more legally autonomous organizations that work together to achieve not only their own goals but also collective goals.” According to the authors, organizations join networks to gain legitimacy, enhance their effectiveness, attract resources, and address complex problems.
Collaboration may start from network members themselves (voluntary networks) but it can also be imposed by a third party, such as an institutional authority (mandated networks). In mandated networks this third mandating party, often referred as the regulator, has a key role in specifying the scope of the network, the financing framework and the distribution of resources and benefits, the eligibility or mandate to participate, the rules for relationships among members, the timing of actions, and the control mechanisms[10,11]. In highly institutionalized systems, such as public healthcare systems, voluntary networks frequently evolve into mandated networks through institutionalization and these mandated networks often need to achieve commitment of and legitimacy from members to reach their goals. According to Rodríguez et al. (2007), relationships among organizations in highly institutionalized systems are similar to relationships among business units within the same firm. This is true for Italian regional healthcare systems, where the regional authority can be considered as a single entity and the local health organizations (LHOs) as the business units.
Literature on networks developed many branches, among which are those on networks’ structural characteristics, networks’ formation processes and network effectiveness or performance. A different branch treats networks as mechanisms of coordination, often referred to as network governance. In this article, we will refer to the latter branch of literature, focusing on mandated networks in the public healthcare sector. We will refer to the framework developed by Provan and Kenis (2008), who identified three governance models:
a) the shared organization model where governance is accomplished informally (i.e., in the absence of hierarchy), through the uncoordinated efforts of stakeholders, or formally, through regular meetings of designated organizational representatives;
b) the lead organization (LO) model where one of the organizations of the network, chosen by members or mandated, assumes the responsibility for administration, receives resources from members, or intermediates the access to external funds. To set up such a model, one organization needs to have sufficient resources, legitimacy, and/or central position in the flow of clients/patients to play a lead role;
c) the network administrative organization (NAO) model, which occurs when a single individual (network facilitator or broker) or a formal organization consisting of an executive director, staff, and board including all or a subset of network members is set up for network governance and does not provide its own set of services. The administrative organization may be a government entity or a nonprofit organization.
These governance models, again according to Provan and Kenis (2008), are permeate by three basic contradictory logics: inclusiveness vs efficiency, internal vs external legitimacy, and flexibility vs stability.
First, networks must reach a dynamic balance between efficiency and inclusiveness of members. Shared-governance systems, mostly relying on a clan governance mode to enhance coordination, i.e., on shared values, trust and reputation, may be enthusiastic and inclusive, but may lack efficiency, especially if members become numerous and are spread out geographically, or they may suffer from collaborative inertia. To increase efficiency, networks tend to shift to lead organization models, where direct involvement––but consequently inclusiveness––are significantly reduced. An NAO could balance these tensions, as its board includes members of organizations in a set of formal rules and structure, but it may be seen as bureaucratic and less efficient and members may not feel accountable for network choices. Moreover, ideally, network involvement should occur at several hierarchical levels in the organization, thereby gaining the participation, commitment, and engagement of all (multiplexity). In more complex governance models, such as NAO and lead organization models, interactions may only occur at higher hierarchical levels, reducing the commitment of the base. In NAO models, if all organizations participate to every decision, the network efficiency may suffer from overembeddedness.
A second tension between internal and external legitimacy needs to be accounted for.
Internal legitimacy is based on shared values and knowledge, trust, reputation, goal consensus. This is the results of different dimensions:
a) The commitment of members to the network’s goals; this can depend also on the competitive patterns among organizations and the potential benefits that members have from the interactions (i.e., for example, an organization may send patients to another network organization on the basis of its specialization);
b) The active role of a network broker. Some authors noted that the abilities, management style, and leadership[22, 23] of the network manager, also called the facilitator or broker, are key factors in solving tensions, building and maintaining commitment (what Agranoff and McGuire (2001) call mobilizing). To do this, in clinical networks, the broker needs to have robust legitimation from the professionals.
External legitimacy is the value of the network for external stakeholders, such as local or national government, or eminent public or private bodies.
Shared organization models, which seem suitable to address internal legitimacy even though clan mechanisms may result in divisions and distrust, are less easily recognized and legitimated by external stakeholders. On the contrary, the lead organizations in particular but also the NAOs appear more suited to represent networks externally as unique structures, but they may encounter further issues with internal legitimacy.
Third, a balance between flexibility and stability has to be found. Through networks, organizations can work with one another to achieve specific goals that require flexibility in order to share resources, knowledge, and expertise. Hierarchies alone could not readily accomplish such a degree of flexibility. At the same time, however, high flexibility and adaptability, also typical of shared governance, are likely to be difficult to sustain in terms of legitimacy. Networks must then focus on stability––which can be intended both as stability over time, i.e., sustainability, and stability of mechanisms––to maintain legitimacy, for which the most obvious way is building a formal hierarchy, although this may end up destroying the original intent of the network, as well as alienating most participants. The regulator could actually over-formalize and constrain roles and relationships at the expense of flexibility. Stability is also related to and influenced by goal consensus on long-term outcomes or process-oriented objectives and by stakeholders’ perceived effectiveness of the network.
Developing a governance structure requires frequent reassessment of the balance of the aforementioned tensions and how these are managed is critical for network performance. The theme of how network governance relates to network performance is still under debate, in particular for networks in public and nonprofit contexts, even when limiting network performance to network effectiveness, defined as reaching network goals. The issue remains because network goals are often unclearly stated or non-uniformly perceived by the members of the network and because a large and mostly undefined number of network characteristics are involved in network effectiveness. However, perceived effectiveness by stakeholders (i.e.,regional authority and/or network members), to which we will refer in our study, can be used as a proxy for a minimum level of network effectiveness.