- Top of page
- Key Research Areas
- A Model of Diffusion in Service Organizations
- Discussion and Recommendations for Further Research
This article summarizes an extensive literature review addressing the question, How can we spread and sustain innovations in health service delivery and organization? It considers both content (defining and measuring the diffusion of innovation in organizations) and process (reviewing the literature in a systematic and reproducible way). This article discusses (1) a parsimonious and evidence-based model for considering the diffusion of innovations in health service organizations, (2) clear knowledge gaps where further research should be focused, and (3) a robust and transferable methodology for systematically reviewing health service policy and management. Both the model and the method should be tested more widely in a range of contexts.
This article summarizes the findings of a systematic literature review of the diffusion of service innovations. The United Kingdom Department of Health explicitly commissioned this work, which was carried out between October 2002 and December 2003, for its National Health Service's extensive modernization agenda (UK Department of Health 2001). Our review, which supplements and extends previous overviews and meta-analyses (Damanpour 1991, 1992, 1996; Granados et al. 1997; Meyers, Sivakumar, and Nakata 1999; Rogers 1995; Tornatsky and Klein 1982; Wejnert 2002; Wolfe 1994), focuses primarily, but not exclusively, on research studies of health care. Because of the size and scope of our review, we cannot describe all our findings or discuss all our sources in this article. Instead, we encourage interested readers to read the complete project report (Greenhalgh et al. 2005a).
We defined a systematic review as a review of the literature according to an explicit, rigorous, and transparent methodology. We defined innovation in service delivery and organization as a novel set of behaviors, routines, and ways of working that are directed at improving health outcomes, administrative efficiency, cost effectiveness, or users' experience and that are implemented by planned and coordinated actions. We distinguished among diffusion (passive spread), dissemination (active and planned efforts to persuade target groups to adopt an innovation), implementation (active and planned efforts to mainstream an innovation within an organization), and sustainability (making an innovation routine until it reaches obsolescence). But we did note an ambiguity in the notion of sustainability (i.e., the longer an innovation is sustained, the less likely the organization will be open to additional innovations).
The breakdown of sources that contributed to the final report is shown in Figure 1. Because formal search techniques (e.g., entering index terms or key words in electronic databases) drew a poor yield, we relied mainly on “snowball” methods (pursuing references of references and using citation-tracking software) and sought advice on sources from experts in various fields. Our search strategy was designed to concentrate on the service sector, particularly health care. Our original inclusion criteria were (1) studies from the health care sector; (2) those that had addressed innovation in service delivery and organization; (3) those that had looked specifically at the diffusion, dissemination, implementation, and/or routinization of these innovations; and (4) those that met our stringent criteria for methodological quality. But as the review unfolded, two things became clear: first, in many areas, the evidence meeting all these criteria was sparse, and second, we could gain critical insights from beyond the parameters we had set. We therefore extended our criteria to a wider range of literature. In particular, we added both overview articles and “landmark” empirical studies from outside the health sector if they had important methodological or theoretical lessons for our research question. The literature on the sustainability of service innovations was, incidentally, very sparse, and so we did not include it in this article.
To help explore this large and heterogeneous literature, we developed a new technique, which we called meta-narrative review. It is summarized in Box 1 and explained in detail in a separate paper (Greenhalgh et al. 2005b). A meta-narrative is the unfolding “storyline” of research in a particular scientific tradition (defined as a coherent body of theoretical knowledge and a linked set of primary studies in which successive studies are influenced by the findings of previous studies; see Kuhn 1962). We mapped the meta-narratives (i.e., we traced the historical development of concepts, theory, and methods in each research tradition) by identifying the seminal theoretical and overview papers and books and analyzing the conceptual and theoretical models proposed by recognized experts in each field.
Table BOX 1. Phases in Meta-Narrative Review
| a.Assemble a multidisciplinary research team whose background encompasses the relevant research traditions (an initial scoping phase may be needed before the definitive research team is appointed).|
| b.Outline the initial research question in a broad, open-ended format.|
| c.Define outputs in collaboration with funder or client.|
| d.Set up a series of regular, face-to-face review meetings, including planned input from external peers drawn from the intended audience for the review.|
| a.Lead the initial search by intuition, informal networking, and “browsing” in order to map the diversity of perspectives and approaches.|
| b.Search for seminal conceptual papers in each research tradition by tracking references of references. Evaluate these by the generic criteria of scholarship, comprehensiveness, and contribution to subsequent work within the tradition.|
| c.Search for empirical papers by electronically searching key databases, hand-searching key journals, and “snowballing” (references of references or electronic citation tracking).|
| Identify (separately for each research tradition):|
| a.The key elements of the research paradigm (conceptual, theoretical, methodological, and instrumental).|
| b.The key actors and events in the unfolding of the tradition (including the main findings and how they were discovered).|
| c.The prevailing language and imagery used by scientists to “tell the story” of their work.|
| Using appropriate critical appraisal techniques:|
| a.Evaluate each primary study for its validity and relevance to the review question.|
| b.Extract and collate the key results, grouping together comparable studies.|
| a.Identify all the key dimensions of the problem that have been researched.|
| b.For each dimension, give a narrative account of the contribution (if any) by each separate research tradition.|
| c.Treat conflicting findings as higher-order data, and explain them in terms of contestation among the different paradigms from which the data were generated.|
| Through reflection, multidisciplinary dialogue, and consultation with the intended users of the review:|
| a.Summarize the overall messages from the research literature along with other relevant evidence (budget, policymaking priorities, competing or aligning initiatives).|
| b.Distill and discuss recommendations for practice, policy, and further research.|
For each empirical study, we developed a data extraction form (available on request) to summarize the research question, study design, validity and robustness of methods, sample size and power, nature and strength of findings, and validity of conclusions. We modified published critical appraisal checklists to assess the quality of primary studies evaluating service interventions, qualitative research, mixed-methodology case studies, action research, and process. We then divided the primary studies' findings into six broad categories: (1) the innovation itself; (2) the adoption/assimilation process; (3) communication and influence (diffusion and dissemination, including social networks, opinion leadership, champions, and change agents); (4) the inner (organizational) context, including both antecedents for innovation in general and readiness for particular innovations; (5) the outer (interorganizational) context, including the impact of environmental variables, policy incentives and mandates, and interorganizational norms and networking; and (6) the implementation process. Within each category, we identified subtopics and painted a rich picture of each by grouping together the contributions from different research traditions.
Because different researchers in different traditions generally conceptualized their topic differently; used different language and metaphors for diffusion, dissemination, and implementation; asked different questions; privileged different methods; and used different criteria to judge “quality” and “success,” we used narrative, rather than statistical, synthesis techniques (Dixon-Woods et al. 2004). We highlighted the similarities and differences of the findings from different research traditions and considered the reasons for the differences. In this way, the heterogeneity of approaches and “contradictions” in findings could be turned into data and analyzed systematically. Based on the evidence from the primary studies, we developed a unifying conceptual model (Figure 3) and tested the model on four case studies (telemedicine, integrated care pathways, general practitioner fund holding, and the UK's electronic patient record), which are analyzed in detail in the full report (Greenhalgh et al. 2005a).
Figure 3. Conceptual Model for Considering the Determinants of Diffusion, Dissemination, and Implementation of Innovations in Health Service Delivery and Organization, Based on a Systematic Review of Empirical Research Studies
Download figure to PowerPoint
We graded the overall evidence supporting each of our conclusions using a modified version of the World Health Organization Health Evidence Network (WHO-HEN) criteria (Øvretveit 2003):
Strong direct evidence: consistent findings in two or more empirical studies of appropriate design and high scientific quality undertaken in health service organizations.
Strong indirect evidence: consistent findings in two or more empirical studies of appropriate design and high scientific quality, but not from a health service organization.
Moderate direct evidence: consistent findings in two or more empirical studies of less appropriate design and/or of acceptable scientific quality undertaken in health service organizations.
Moderate indirect evidence: consistent findings in two or more empirical studies of less appropriate design and/or of acceptable scientific quality, but not from health service organizations.
Limited evidence: only one study of appropriate design and acceptable quality available, or inconsistent findings in several studies.
No evidence: no relevant study of acceptable scientific quality available.
Key Research Areas
- Top of page
- Key Research Areas
- A Model of Diffusion in Service Organizations
- Discussion and Recommendations for Further Research
Because of the very large number of empirical sources identified, we have cited in this article only illustrative studies and/or overviews, and we have not given citations for statements for which we had only limited evidence. For a full list of primary sources, please see our main report (Greenhalgh et al. 2005a). We identified 13 research areas that had, largely independently of one another, provided evidence relevant to the diffusion of innovations in health service organizations (Table 1). Four of these traditions can be classified as “early diffusion research”:
Table 1. Research Traditions Relevant to Diffusion of Innovations in Health Service Organizations
| Research Tradition|| Academic Discipline|| Definition and Scope||“Diffusion of Innovations” Conceptualized as|
|1. Rural sociology||Sociology||Study of rural society and the relationships among its members, especially the influence of social structures and norms on behaviors and practices.||Influence of social norms and values on adoption decisions; networks of social influence.|
|2. Medical sociology||Sociology||As above for medical society.||As above. Specifically, the norms, relationships, and shared values that drive clinician behavior (e.g., adoption of guidelines).|
|3. Communication studies||Psychology||Study of human communication, including both interpersonal and mass media.||Structure and operation of communication channels and networks. Interpersonal influence (e.g., impact of “experts” versus “peers” on decision making).|
|4. Marketing||Interdisciplinary (psychology and economics)||Study of the production, distribution, and consumption of goods and services.||Affordability, profitability, discretionary income, market penetration, media advertising, supply, and demand.|
|5. Development studies||Interdisciplinary (anthropology, sociology, economics, political science, information and communications technology)||Study of the adoption, adaptation, and use of technology, especially in development.||Barriers to the use of more advanced technologies (e.g., labor-saving machinery, computers).|
|6. Health promotion||Interdisciplinary (social psychology, epidemiology, marketing)||Study of strategies and practices to improve the health and well-being of populations (draws on and overlaps with communication studies).||“Reach” and “uptake” of positive lifestyle choices in populations targeted by health promotion campaigns.|
|7. Evidence-based medicine||Clinical epidemiology||Study of the spread of best (research) evidence on managing diseases and symptoms.||Filling a “knowledge gap” or “behavior gap” in targeted clinicians.|
|8. Structural determinants of organizational “innovativeness”||Organization and management||Study of how an organization's structure influences its function in relation to the use of new ideas and practices.||Organizational attributes influencing “innovativeness,” like size, slack resources, and hierarchical versus decentralized lines of management.|
|9. Studies of organizational process, context, and culture||Interdisciplinary (organization and management, sociology, anthropology)||Study of the development and impact of culture (meaning systems, language, traditions, accepted ways of doing things) in organizations and professional groups.||Changes in culture, values, and identities.|
|10. Interorganizational studies (networks and influence)||Interdisciplinary (organization and management, sociology)||Study of interorganizational norms, fashions, and influence.||Interorganizational fads and fashions, spread through social networks.|
|11. Knowledge utilization||Interdisciplinary (organization and management, information and communications technology, sociology)||Study of how individuals and teams acquire, construct, synthesize, share, and apply knowledge.||Transfer of knowledge, both explicit (formal and codified, as in a guideline) and tacit (informal and embodied, as in “knowing the ropes”).|
|12. Narrative studies||Interdisciplinary (literature, sociology, anthropology)||Study of stories (here, those told in and about organizations). Use of storytelling as a tool for dissemination and change in organizations.||The telling, retelling, and interpretation of stories. Innovators as characters (heroes, underdogs) in a story of change. Innovation as social drama.|
|13. Complexity studies||Interdisciplinary (ecology, social psychology, systems analysis)||Study of how individuals, groups, and organizations emerge, evolve, and adapt to their environment.||Creativity, emergence, and adaptation|
Rural sociology, for which Everett Rogers (1995) first developed the concept of diffusion of innovations: In this concept, innovations were defined as ideas or practices perceived as new by practitioners (in this case, farmers). Diffusion was seen as the spread of ideas among individuals, largely by imitation. Interventions aimed at spreading innovation harnessed the interpersonal influence of opinion leaders and change agents, and research mapped the social networks and adoption decisions of targeted individuals.
, in which similar concepts and theoretical explanations were applied to doctors' clinical behavior (most notably, the 1966 study by Coleman, Katz, and Menzel on the spread of prescribing of newly introduced antibiotics): Early studies in medical sociology set the foundations for network analysis—the systematic study of “who knows whom” and “who copies whom”—and led to the finding that well-networked individuals are generally better educated, have a higher social status, and are earlier adopters of innovations (Burt 1973
, in which innovations were conceptualized as new information (often “news”), and spread was seen as the transmission of this information by either mass media or interpersonal communication: Research measured the speed and direction of the message's transmission and studied the impact of altering key variables such as the style of message, the communication channel (spoken, written, etc.), and the nature of exposure (Rogers and Kincaid 1981
, in which innovations were conceptualized as products or services, and the adoption decision was seen as a rational (quasi-economic) analysis of costs and benefits: Research measured the success of efforts to increase the perceived benefits or reduce the perceived costs of an innovation in the eyes of potential adopters. An important stream of research in this area centered on developing mathematical models to predict adoption behavior (Bass 1969
These early studies produced some robust empirical findings (discussed later) on the attributes of innovations, the characteristics and behavior of adopters, and the nature and extent of interpersonal and mass media influence on adoption decisions. But the work had a number of theoretical limitations, notably the erroneous assumptions that (1) the only relevant unit of analysis is the individual innovation and/or the individual adopter; (2) an innovation is necessarily better than what has gone before and adoption is more worthy of study than is nonadoption or rejection; (3) patterns of adoption reflect fixed personality traits; and (4) the findings of diffusion research are invariably transferable to new contexts and settings. Research areas that emerged as developments—and sometimes as breakaways—from such conceptual models include
, in which research on the spread of innovations was explicitly broadened to include an exploration of the political, technological, and ideological context of the innovation and any dissemination program, and of particular innovations' different meaning and social value in different societies: Diffusion of innovations was reframed as centrally pertaining to the appropriateness of particular technologies and ideas for particular situations at particular stages in development. Two important contributions from this tradition have been (1) that the meaning of an innovation for the agency that introduces it may be very different from that held by the intended adopters and (2) that “innovation-system fit” (related to the interaction between the innovation and its potential context) is generally a more valid and useful construct than “innovation attributes” (often assumed to be fixed properties of the innovation in any context) (Bourdenave 1976
, in which innovations were defined as good ideas for healthy behaviors and lifestyles, and the spread of such innovations was expressed as the reach and uptake of health promotion programs in defined target groups: Health promotion research has traditionally used social marketing, developed from marketing theory, as its theoretical basis. More recently, a more radical “developmental” agenda has emerged in health promotion, with parallels to development studies, in which a one-way transmission of advice from the change agency to the target group has been replaced with various models of partnership and community development (Potvin, Haddad, and Frohlich 2001
, in which innovations were defined as health technologies and practices supported by sound research evidence: Until recently, the spread of innovation in this tradition was seen as a linear and technical process at the level of the individual and hence was described as changes in clinicians' behavior in line with evidence-based guidelines (Granados et al. 1997
). Many evidence-based medicine researchers subsequently (and perhaps somewhat belatedly) recognized that the implementation of most clinical guidelines requires changing the system and, hence, organizational as well as individual change (Grimshaw et al. 2004
). A more recent conceptual development is the notion that the evidence base for particular technologies and practices is often ambiguous and contested and must be continually interpreted and reframed in accordance with the local context and priorities, a process that often involves power struggles among various professional groups (Ferlie et al. 2001
In the organization and management literature, we found the following areas that were relevant to our review:
Studies of the structural determinants of organizational innovativeness
, in which innovation was seen as a product or process likely to make an organization more profitable: Organizational innovativeness was regarded as primarily influenced by structural determinants, especially size, functional differentiation (an internal division of labor), slack resources, and specialization (the organization has a clear “niche” in which it offers expertise and specialist resources). In this area, research focuses on collecting quantitative data about the formal structures of organizations, usually by sending questionnaires to the chief executive. Such studies were among the few in our review that were amenable to meta-analysis (Damanpour 1991, 1992, 1996
Studies of organizational process, context, and culture
, whose research focus was the adoption, assimilation, and routinization of an innovation: Here, the exploration of an organization's innovativeness concentrated on the “softer,” nonstructural aspects of its makeup, especially the prevailing culture and climate, notably in relation to leadership style, power balances, social relations, and attitudes toward risk taking. This area used mainly qualitative (often ethnographic) methods and centered on people and their relationships and behavior. This research often overlapped with the mainstream change management literature, in addition to a distinct innovation subarea (Kanter 1988
; Van de Ven et al. 1999
, which examine an organization's innovativeness in relation to the influence of other organizations, particularly interorganizational communication, collaboration, competition, and norm setting: This area applied social network theory (the notion that people are “networked” to friends and colleagues and that these networks form channels of communication and influence [Granovetter and Soong 1983]) to the level of the organization (e.g., the concept of the opinion-leading organization was introduced and explored). Interorganizational norms (“fads and fashions”) were seen as a key mechanism for spreading ideas among organizations (Abrahamson 1991
; Abrahamson and Fairchild 1999
Knowledge-based approaches to innovation in organizations
, in which both innovation and diffusion were radically redefined as the construction and distribution of knowledge (Nonaka and Takeuchi 1995
): A critical new concept was the organization's absorptive capacity for new knowledge. Absorptive capacity
is a complex construct incorporating the organization's existing knowledge base, “learning organization” values and goals (i.e., those that are explicitly directed to capturing, sharing, and creating new knowledge), technological infrastructure, leadership and knowledge sharing, and effective boundary-spanning roles with other organizations (Zahra and George 2002
Narrative organizational studies
, in which one important dimension of organizational innovativeness—the generation of ideas—was viewed as the creative imagination of individuals in the organization: In this field, an innovative organization
is one in which new stories can be told and that has the capacity to capture and circulate these stories (Czarniawska 1998
; Gabriel 2000
). This research area emphasizes the rule-bound, inherently conservative nature of large professional bureaucracies and celebrates stories for their inherent subversiveness. Because the principal constructions in stories are surprise, tension, dissent, and “twists in the plot,” and because characters can be assigned positive virtues such as honesty, courage, or determination, stories can offer “permission to break the rules” (Buckler and Zein 1996
). In the narrative tradition, the diffusion of innovations within organizations gives a shared story a new ending. Hence, interventions to support innovation are directed toward supporting “communities of practice” with a positive story to tell (Bate 2004
are derived from general systems theory and regard innovation as the emergent continuity and transformation of patterns of interaction, understood as complex responses of humans relating to one another in local situations: The diffusion of innovations is seen as a highly organic and adaptive process in which the organization adapts to the innovation and the innovation is adapted to the organization (Fonseca 2001
). As Figure 2
shows, this organic, adaptive process is not easily—and perhaps not at all—controlled by external change agencies (Plsek 2003
One other relevant area in the organization and management literature is organizational psychology, in which innovativeness is seen as dependent on good leadership, sound decision making, and effective human resource management (especially the motivation, training, and support of staff ). We did not explore this literature in detail, as it was the subject of several other projects funded by the UK Department of Health Service Delivery and Organization Programme (see http://www.sdo.lshtm.ac.uk/changemanagement.htm).
Discussion and Recommendations for Further Research
- Top of page
- Key Research Areas
- A Model of Diffusion in Service Organizations
- Discussion and Recommendations for Further Research
This study has attempted to combine a large and diverse literature into a unifying model of the diffusion of innovations in health care organizations. Our methods were systematic and independently verifiable. However, the literature was vast and complex, our approach was emergent and somewhat unconventional, and many subjective judgments and serendipitous discoveries were involved. A different group of researchers setting out to answer the same research question would inevitably have identified a different set of primary sources and made different judgments about their quality and relevance. Their synthesis might have produced a different unifying model. This is, arguably, an inherent characteristic of any systematic review that addresses complex interventions and seeks to unpack the nuances of their implementation in different social, organizational, or environmental contexts. In this respect, a meta-narrative review can be thought of as a particular application of a realist review, in which the reviewer's interpretive judgments are integral to the synthesis process and can never be fully rationalized or standardized (Greenhalgh et al. 2005b; Pawson et al. 2005). The findings presented here, and especially the model in Figure 3, should therefore be seen as “illuminating the problem and raising areas to consider” rather than “providing the definitive answers.” A recently published review of diffusion of innovations aimed at changing individual clinician behavior, not available when we were developing our model, was consistent with our own conclusions (Fleuren, Wiefferink, and Paulussen 2004).
Our review affirmed many well-described themes in the literature, such as the useful list of innovation attributes that predict (but do not guarantee) successful adoption; the importance of social influence and the networks through which it operates; the complex and contingent nature of the adoption process; the characteristics (both “hard” and “soft”) of organizations that encourage and inhibit innovation; and the messy, stop-start, and difficult-to-research process of assimilation and routinization. We also exposed some demons in this literature, such as the lack of empirical evidence for the widely cited “adopter traits”; the focus on innovations that arise centrally and are disseminated through official channels at the expense of those that arise peripherally and spread informally; the limited generalizability of the empirical work on product-based innovation in companies to process innovation in service organizations; and the near absence of studies focusing primarily on the sustainability of complex service innovations.
The components of this model do not, of course, represent a comprehensive list of the determinants of organizational innovativeness and successful assimilation. They are simply the areas on which research has been undertaken and findings have been published. Conspicuously absent from most empirical work in the service sector, for example, is the important issue of internal politics (e.g., doctor-manager power balances), which was identified in a single qualitative study as one of several critical influences (Champagne et al. 1991). In an evaluation of five projects to implement complex service innovations in primary health care, our own team found that power relations (especially between a project steering group and the main project worker) were critical to successful implementation but that they were extremely difficult to explore systematically and raised ethical issues for the research team (Hughes et al. 2002).
A striking finding of this extensive review was the tiny proportion of empirical studies that acknowledged, let alone explicitly set out to study, the complexities of spreading and sustaining innovation in service organizations. Most studies concentrated on a few of the components depicted in our model and failed to take account of their different interactions and contextual and contingent features. This, of course, is an inherent limitation of any experimental or quasi-experimental research: The shifting baseline of context and the multiplicity of confounding variables must be stripped away (“controlled for”) to make the research objective (Pawson et al. 2005).
But herein lies a paradox. Context and “confounders” lie at the very heart of the diffusion, dissemination, and implementation of complex innovations. They are not extraneous to the object of study; they are an integral part of it. The multiple (and often unpredictable) interactions that arise in particular contexts and settings are precisely what determine the success or failure of a dissemination initiative. Champions, for example, emerged in our review as a key determinant of organizational innovation, but no amount of empirical research will provide a simple recipe for how champions should behave that is independent of the nature of the innovation, the organizational setting, the sociopolitical context, and so on.
Based on the findings of this review, on some of the methodological recommendations made by others (Green 2001; Pawson et al. 2005; Rootman et al. 2001), and on feedback from policymakers who read drafts of this review, we suggest that the next generation of research on diffusion of health service innovations should be
Theory-driven: Empirical studies should explore an explicit hypothecated link between an intervention or program and a defined outcome. Specifically, researchers should refine their understanding of the mechanism by which the determinants produce (or fail to produce) the outcome of interest in a particular context.
Process rather than “package” oriented: Researchers should avoid questions framed in terms of causal inferences, such as “Does program X work?” or “Does strategy Y have this effect?” Rather, research questions should be framed so as to illuminate a process; for example, “What features account for the success of program X in this context and the failure of a comparable program in a different context?”
Ecological: Research should recognize the reciprocal interaction between the program that is the explicit focus of research and the wider setting in which it takes place. The latter provides a dynamic, shifting baseline against which any program-related activity will occur; each influences the other. Program-setting interactions form an important element of data and are a particularly rich source of new hypotheses about mechanisms of success or failure.
Addressed using common definitions, measures, and tools: Empirical work should adopt standardized approaches to measuring key variables and confounders (e.g., quality of life, implementation success) to enable valid comparisons across studies.
Collaborative and coordinated: Research teams should prioritize and study research questions across multiple programs in a variety of contexts, rather than small isolated teams “doing their own thing.” In this way, the impact of place, setting, and context can be systematically studied.
Multidisciplinary and multimethod: Research should recognize the inherent limitations of experimental approaches to researching open systems and embrace a broad range of research methods emphasizing interpretive approaches.
Meticulously detailed: Studies should document the unique aspects of different programs and their respective contexts and settings to allow for meaningful comparisons across programs. Such detailed descriptions, perhaps stored centrally as electronic appendices to published papers and reports, could be used by future research teams to interpret idiosyncratic findings and test rival hypotheses about mechanisms.
Participatory: Because of the reciprocal interactions between context and program success, researchers should engage “on-the-ground” service practitioners as partners in the research process. Locally owned and driven programs produce more useful research questions and data that are more valid for practitioners and policymakers.
When carrying out this review, we were struck by the duplication of empirical studies and also by the number of studies that had been undertaken without a comprehensive review of the existing relevant research, many of which asked what appeared to be obsolete questions. Bearing in mind our general recommendation for a more “whole-systems” approach to researching organizational innovation, we next highlight specific areas in which we believe further empirical research is—and, equally important, is not—needed.
Further research into the attributes of innovations that promote their adoption is probably not needed. Instead, research in this area should be directed at the following questions:
How do innovations in health service organizations arise, and in what circumstances? What mix of what factors tends to produce “adoptable” innovations (e.g., ones that have clear advantages beyond their source organization and low implementation complexity and are readily adaptable to new contexts)?
How can innovations in health service organizations be adapted to be perceived as more advantageous, more compatible with prevailing norms and values, less complex, more trialable, with more observable results, and with greater scope for local reinvention? Is there a role for a central agency, resource center, or officially sanctioned demonstration programs in this?
How are innovations arising as “good ideas” in local health care systems reinvented as they are transmitted through individual and organizational networks, and how can this process be supported or enhanced?
How can we identify “bad ideas” likely to spread so that we can intervene to prevent this?
Adopters and Adoption
We do not recommend further descriptive studies of patterns of adoption by individuals. We believe the main unanswered questions are the following:
Why and how do people (and organizations) reject an innovation after adopting it? (In the more than 200 empirical research studies covered in our review, only one explicitly and prospectively studied discontinuance; see Riemer-Reiss 1999).
What are the transferable lessons from cognitive and social psychology about the ability and tendency of individuals to adopt particular innovations in particular circumstances? For example, what can we glean from the mainstream literature about how individuals process information, make decisions, apply heuristics, and so on? A particularly fruitful area is likely to be the psychological literature on the interaction between humans and computers as it applies to the adoption and assimilation of information and communications technology (ICT) innovations in the service sector.
Dissemination and Social Influence
We do not recommend further “intervention” trials of the use of opinion leaders to change the behavior of potential adopters. We already know from published research that opinion leadership is a complex and delicate process, and research that fails to capture these process elements is unlikely to add to what we already know. We recommend that research into dissemination address the following questions:
What is the nature of interpersonal influence and opinion leadership in the range of different professional and managerial groups in the health service, especially in relation to organizational innovations? In particular, how are key players identified and influenced?
What is the nature and extent of the social networks of different players in the health service (both clinical and nonclinical)? How do these networks serve as channels for social influence and the reinvention and embedding of complex service innovations?
Who are the individuals who act as champions for organizational innovations in health services? What is the nature of their role, and how might it be enabled and enhanced?
Who are the individuals who act as boundary spanners among health service organizations, especially in relation to complex service innovations? What is the nature of their role, and how might it be enabled and enhanced?
The Organizational Context
We do not recommend further survey-based research to identify structural determinants of innovativeness in health care organizations, since the small but significant effect of structural determinants is well established. We suggest the following questions as possible directions for further research:
To what extent do “restructuring” initiatives (popular in health service organizations) improve their ability to adopt, implement, and sustain innovations? In particular, will a planned move from a traditional hierarchical structure to one based on semiautonomous teams with independent decision-making power improve innovativeness?
How can we improve the absorptive capacity of service organizations for new knowledge? In particular, what is the detailed process by which ideas are captured from outside, circulated internally, adapted, reframed, implemented, and routinized in a service organization, and how might this process be systematically enhanced?
How can leaders of service organizations set about achieving a receptive context for change; that is, the kind of culture and climate that supports and enables change in general? A systematic review centering on the mainstream change management literature (which we explicitly excluded from this review) is probably the most appropriate first step for this question.
What is the process leading to long-term routinization (with appropriate adaptation and development) of innovations in health service delivery and organization?
System Readiness for Innovation
There is relatively little systematic research on the development of system readiness (i.e., the steps that organizations can take to assess and anticipate the impact of an innovation). The following questions should be addressed:
What steps must be taken by service organizations when moving toward a state of “readiness” (i.e., with all players on board and with protected time and funding), and how can this overall process be supported and enhanced? In particular, (1) How can tension for change be engendered? (2) How can innovation-system fit best be assessed? (3) How can the implications of the innovation be assessed and fed into the decision-making process? (4) What measures enhance the success of efforts to secure funding for the innovation in the resource allocation cycle? and (5) How can the organization's capacity to evaluate the impact of the innovation be enhanced?
What are the characteristics of organizations that successfully avoid taking up “bad ideas”? Are they just lucky, or do they have better mechanisms for evaluating the ideas and anticipating the subsequent effects?
The Outer Context
Aside from questions in the fields of political science and macroeconomics, the main research questions on the environmental context are the following:
What is the nature of informal interorganizational networking in different areas of activity, and how can this be enhanced through explicit knowledge management activities (such as the appointment and support of knowledge workers and boundary spanners)?
What is (or could be) the role of professional organizations and informal interprofessional networks in spreading innovation among health care organizations?
What is the cost-effectiveness of structured health care quality collaboratives and comparable models of quality improvement, and how can this be enhanced? To what sort of projects in what sort of contexts should resources for such interorganizational collaboratives be allocated?
What are the harmful effects of an external “push” (such as a policy directive or incentive) for a particular innovation when the system is not ready? What are the characteristics of more successful external pushes promoting the assimilation and implementation of innovations by health service organizations?
Overall, we found that empirical studies of implementing and maintaining innovations in service organizations (1) had been undertaken from a pragmatic rather than an academic perspective and been presented as “gray literature” reports (which for practical reasons we did not include in this review); (2) were difficult to disentangle from the literature on change management in general; and (3) were impoverished by lack of process information. We recommend that further research focus on the following two questions:
By what processes are particular innovations in health service delivery and organization implemented and sustained (or not) in particular contexts and settings, and can these processes be enhanced? This question, which was probably the most serious gap in the literature we uncovered for this review, would benefit from in-depth mixed-methodology studies aimed at building up a rich picture of process and impact.
Are there any additional lessons from the mainstream change management literature (to add to the diffusion of innovations literature reviewed here) for implementing and sustaining innovations in health care organizations?