The Greenhalgh model:

Based on the work of Rogers (1995) (see DOI) and a systematic review of more than 6000 empirical research studies, Greenhalgh et al. (2004) developed a conceptual model for considering the determinants of diffusion, dissemination, and

implementation of innovations in health service delivery and organisation. This model of innovation aims to identify various factors that either hinder or facilitate the diffusion of CIS as an innovation in health care organisations. The barriers identified include a lack of systems’ thinking, complexity of innovations, and a lack of

understanding about the benefits that can be provided by innovations (Carayon, 2010).

Greenhalgh et al. (2004) developed their model (figure 7) and tested its explanatory power in four case studies of complex innovations (integrated care pathways, a GP fund holding in the UK, an electronic health record, and telemedicine). The authors concluded that the model provided a helpful framework for explaining the spread and sustainability of the innovations in the historical case studies, as well as for

constructing hypotheses about the success of one initiative in the early stages of the dissemination and implementation.

Other studies (Damschroder et al., 2009; Keller, Gare, Edenius, & Lindblad, 2010; Newhouse, 2007) utilised the Greenhalgh et al. (2004) conceptual model for considering the determinants of diffusion, dissemination, and implementation of innovations in health service delivery and organisation as a framework model. For example, Newhouse (2007) used their conceptual model for considering the determinants of diffusion, dissemination, and implementation of innovations in

health service delivery and organisation to indicate the organisational infrastructure that enables evidence-based nursing practice and strategies for leaders to enhance evidence-based practice. Also, when considering the potential barriers and enablers of building an infrastructure for the implementation of a program, and the

infrastructure that supports evidence-based practice as innovations within that context, the system antecedents for innovation, system readiness for innovation, attributes of the adopter (nurse), the assimilation of the innovation, the

implementation process, the linkages, the outer context, communication, influence, and the innovation itself are important factors.

Recently, Carayon (2010) conducted a study regarding the use of Human Factors and Ergonomics (HFE) tools, methods, concepts, and theories in health care and patient safety. To facilitate and support the spread of HFE knowledge and skills in health care and patient safety, they conceptualised HFE as innovations. They also

determined that its diffusion, dissemination, implementation and sustainability could be understood and specified using the Greenhalgh et al. (2004) model of innovation to examine the potential challenges related to the use of HFE innovations in health care and patient safety. Greenhalgh’s model provided Carayon (2010) with a map to follow in order to examine the organisational characteristics (antecedents) that favour innovations. It also included the extent to which the organisation is ready to adopt the innovation HFE application to be implemented in a health care organisation. Carayon formulated the recommendations for HFE professionals, researchers, and educators for improving the spread of HFE innovations for patient safety in health care organisations.

Greenhalgh’s work appears comprehensive and relevant when considering the determinants of diffusion, dissemination, and the implementation of innovations in health service organisations.

Figure 7: Conceptual Model for Considering the Determinants of Diffusion, Dissemination, and Implementation of Innovations in Health Service Delivery and Organisation (adapted from

Greenhalgh et al., 2004).

Greenhalgh et al. (2004) identified innovations in health service delivery and organisation as:

“…a set of behaviours, routines and ways of working, along with any associated administrative technologies and systems, which are:

(a) perceived as new by a proportion of key stakeholders (b) linked to the provision or support of health care (c) discontinuous with previous practice

(d) directed at improving health outcomes, administrative efficiency, cost effectiveness, or the user experience, and

(e) implemented by means of planned and co-ordinated action by individuals, teams or organisations.” (2004, p. 40)

The characteristics of innovations, as perceived by intended adopters, can influence the adoption rate of innovations. Thus, these characteristics are necessary to

consider; but they do not adequately explain the adoption and assimilation of the complex innovations within complex organisations, such as health care organisations (Greenhalgh, Robert, Macfarlane, et al., 2004). Greenhalgh et al. (2004) identified the key attributes that influence the spread and sustainability of innovation in health care settings. These attributes include fuzzy boundaries, minimal risk, relevance, the nature of knowledge required, and technical support. They are considered

complementary to each other attribute. For instance, fuzzy boundaries provide the innovation with the elasticity required to accommodate the required knowledge from different organisational structures and systems (Denis, Hébert, Langley, Lozeau, & Trottier, 2002). Following on from this, if an innovation appears to fit and, as such, involves minimal risk, it is more likely to be adopted. However, if the innovation does not make a positive impact on task performance, and if the knowledge and skills that are required to operate innovations do not easily systematise and transfer to the end users of innovation, the implementation of innovation (e.g. CIS) may not be successful (Greenhalgh et al., 2004).

Importantly, Greenhalgh et al. (2004) emphasises that categories, such as ‘early adopter’, are mathematically defined. However, they have not been investigated in relation to service sector innovation. Nevertheless, individual adoption decisions are influenced by needs, motivations, values and goals, skills, learning styles, and social networks. Greenhalgh’s systematic review found that the psychological antecedents (capacity of end users, in terms of intellectual ability, tolerance of ambiguity, and motivation) are important determinants of an individual’s adoption decision, while

those antecedents have an attitude towards different adoption decisions within different contexts.

The adoption of innovation is complex at an organisational level. The assimilation (adoption) of an innovation in an organisation means complex changes that need to take place in an organisational setting. These changes involve innovation attributes (the degree of the risk produced from associated procedure, the level of skills needed to operate the equipment, and the degree of how the results of using innovation are visible to the users), inner context size, organisation external environment, and interaction between innovation and organisation in terms of its compatibility with organisational values, goals, resources, and ways of working (Greenhalgh, Robert, Bate, Macfarlane, & Kyriakidou, 2005). Furthermore, organisations need to consider the innovation assimilation process as complex, iterative, organic, and messy, rather being comprised of rational decision-making machines that move sequentially through an ordered process of awareness–evaluation– adoption–implementation (Greenhalgh et al., 2005).

Greenhalgh et al. (2005) differentiated between diffusion in which the spread of innovation is unplanned, informal, decentralised, and often spreads horizontally through peers, and dissemination that is planned, formal, usually centralised, and more likely to move through vertical hierarchies. Based on Rogers’ (2003) work, Greenhalgh et al. (2004) listed a number of elements that could be considered key contextual facilitators of the adoption and the diffusion of the innovation process within the organisations. These elements, for example, included network structure, which is the structure and quality of channels that powerfully influence the rate

adoption of innovation. There are two types of networks: horizontal and vertical. Horizontal networks are more effective for spreading peer influence and supporting the construction and reframing of meaning (e.g., doctors tend to operate in informal); vertical networks are more effective for cascading codified information and passing on authoritative decisions (e.g., nurses more often have formal).

In addition, Greenhalgh et al. (2005) argued the importance of the opinion leaders as an expert in the innovation implementation process. Opinion leaders exert their influence on status, while peer opinion leaders exert their authority through their representatives and credibility (Greenhalgh et al., 2005). Further, opinion leaders can have a positive or negative influence, depending on their perception of the innovation (Urquhart, Sargeant, & Grunfeld, 2013).

Champions, as active actors in the implementation process, were discussed by Greenhalgh et al. (2005) in relation to the use of key individuals, in social networks, who are willing to support the innovation. Four types of champions were identified: 1) the organisational maverick, who lends autonomy to innovators; 2) the

transformational leader, who harnesses support for other members; 3) the

organisational buffer, who creates loose monitoring systems for the innovators; and 4) the network facilitator, who develops cross-functional partnership within the organisation.

Greenhalgh et al. (2005) acknowledged that the structure and culture of an

organisation provides an important contextual environment. Such an environment can influence the probability of innovation assimilation. Hence, it was argued that it

was important to consider the structural determinants of innovativeness, the absorptive capacity for new knowledge and a receptive context for change.

Added to this background, Greenhalgh et al. (2005) recognised that an organisation may be structurally and socially configured to support innovation adoption and assimilation, but the decision to adopt, or not adopt, may depend on its willingness or readiness to make the change. According to the author, there were elements that may affect the decision of change, such as the tension for change, which depends on the users’ judgement of the innovation in terms of its ease of use and usefulness. Further, it depends on the current situation being intolerable, especially if the innovation can provide a better working environment or not. If the innovation-system fits, it means a compatibility of the innovation with the organisation’s values, norms, goals,

strategies, skill mix, and workflow. An assessment of the implications, support and advocacy, dedicated time and resources, and capacity to evaluate the innovation were significant factors that might influence the innovation integration assimilation within the organisation.

Further, Greenhalgh et al. (2005) observed that an organisation exists within a social and administrative context. Moreover, the decision to adopt an innovation, and the resources required to implement and sustain such a change, are dependent on this wider context, which includes informal inter-organisational networks that promote the adoption of an innovation. The integrative organisational forms that are linked by common management and governance structures help spread innovations across member organisations. Additionally, intentional spread strategies, wider

environment, and political directives are critical elements that need to be addressed when the organisation tends to implement change. For example the political

directives can have an equivocal effect on the adoption of innovation. A policy push in the early stages of implementation can provide the confidence that resources will be made available for the initiative to succeed. But these days, the ‘one size fits all’ approach is no more applicable and appropriate to be used to implement change (Dunham, Owen, & Heta-Lensen, 2015). The anticipation of a policy directive, however, can restrain local innovation activity by attempting to second guess what the policy directive will be (Dunham et al., 2015; Greenhalgh et al., 2005).

Finally, the success of implementation depends on many of the aforementioned attributes being provided or managed appropriately (Van de Ven, Angle, & Poole, 2000). Greenhalgh et al. (2005) also characterises the move from considering innovation to routinisation as a non-linear process that involves multiple shocks, setbacks, and unanticipated events, such as organisational structure, leadership and management, human resource and funding issues, and inter-organisational networks.