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Week10--DOItheoryprinciplesandpractice.pdf

By James W. Dearing and Jeffrey G. Cox

Diffusion Of Innovations Theory, Principles, And Practice

ABSTRACT Aspects of the research and practice paradigm known as the diffusion of innovations are applicable to the complex context of health care, for both explanatory and interventionist purposes. This article answers the question, “What is diffusion?” by identifying the parameters of diffusion processes: what they are, how they operate, and why worthy innovations in health care do not spread more rapidly. We clarify how the diffusion of innovations is related to processes of dissemination and implementation, sustainability, improvement activity, and scale-up, and we suggest the diffusion principles that can be readily used in the design of interventions.

I n synthesizing many studies from differ- ent disciplines about how people re- spond to new ideas, Everett Rogers was answering a call set forth by the sociologist Robert K. Merton: theorize,

but in empirical ways and with practical impli- cations.1 Now, fifty-six years past the first publication of Rogers’s book Diffusion of Innova- tions, we briefly review this theory, its principles, and the implications for practice as a fifteen-year update to the book’s last edition in 2003. One of the best documented if frustrating prin-

ciples of diffusion is that it can take a long time. Consider the case of Project ECHO (Extension for Community Healthcare Outcomes), previ- ously reported in Health Affairs.2 This innovation in how academic medical centers partner with rural primary care clinicians to extend specialty care began at one site in New Mexico in 2003. By November 2017 Project ECHO reported 158 sites across the US, with sixty more sites in twen- ty-four other countries.3 The program has moved from hepatitis C care to include HIV/AIDS, geri- atrics, psychiatric medication management, and more.4 Or consider the Green House model of nursing home care, in which “house-like” facili- ties are built that emphasize an open kitchen, residents’ control in decision making, and em- powered nursing assistants.5 Underwritten by a

series of developmental, demonstration, and evaluation grants from the Robert Wood John- son Foundation beginning in 2003, more than 200 Green Houses were in operation across the US in2017 with300 expectedby theendof 2018.6

Project ECHO and the Green House model are evidence-based innovations that are spread- ing as new ways to deliver health care, but have they diffused? To assess the diffusion of an inno- vation, one must attend to its denominator. In these examples, the number of plausible and potential adopting sites for either of them is large, with 4,134 Medicare-certified rural health clinics in 2015 and 15,583 certified nursing facilities in the US in 2016.7 In diffusion terms, even after fourteen years and like many other health care innovations, impressive innovations such as Project ECHO and the Green House mod- el still have not reached “takeoff” or a tipping point in time on a national diffusion curve.8

What Is Diffusion? Diffusion is a social process that occurs among people in response to learning about an innova- tion such as a new evidence-based approach for extending or improving health care. In its classi- cal formulation, diffusion involves an innova- tion that is communicated through certain chan-

James W. Dearing (dearjim@ msu.edu) is a professor in the Department of Communication at Michigan State University, in East Lansing.

Jeffrey G. Cox is a research associate in the Department of Communication, Michigan State University.

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nels over time among the members of a social system.9 The typical dependent variable in diffusion research is time of adoption, though when complex organizations are the adopters, subsequent implementation is a more meaning- ful measure of change. Diffusion can be assessed among individuals such as members of Con- gress, organizations such as health care insur- ers, or larger collectivities such as cities and states. Exhibit 1 illustrates the relationships be- tween rates of adoption and how we characterize diffusion under different scenarios, including when innovations are introduced and do not dif- fuse. When time-of-adoption data are graphed cumulatively, an S-shaped curve is common, with an initial slow rate of adoption giving way to a rapidly accelerating rate, which then slows as fewer nonadopters remain within the social system in question. Not all instances of diffusion play out this way, especially in policy diffusion— where time to adoption can be shorter because of the occasional convergence of national attention to a problem, financial incentives, readiness for change among elected officials, motivated and organized groups, and an innovative solution that is perceived positively.10

As exhibit 1 suggests, several contextual as- pects of diffusion typically go unstudied. Com- peting orcomplementary innovations areimpor- tant, since potential adopters usually have a choice in what to adopt. Failures are important, since most innovations do not diffuse. Decelera- tion is important in two ways, since the decision to adopt an innovation often means abandoning a prior one,11 and nonadopters have their deci-

sion to reject an innovation socially confirmed.12

In the case of voluntary adoption decisions, acceleration in the rate of diffusion is usually the result of influential members of the social system making the decision to adopt and their decision being communicated to others, who then follow their lead. To use the example of efforts to reduce tobacco use, while a small sub- set of tobacco taxation policy experts, child wel- fare specialists, or mayors may make careful as- sessments of the evidence and other attributes of an innovation, most of their eventually adopting peers do not. When opinion-leading individuals and organizations adopt an innovation, social systems convert from one normative state (such as smoking in public being acceptable) to anoth- er (smoking being unacceptable).When opinion leaders do not adopt an innovation, systems do not change. Diffusion is an atypical outcome, since the vast majority of innovations fail to dif- fuse, never accelerating up an S-shaped curve.13,14

This can be a wholly warranted result, since an innovation is defined simply as that which is perceived to be new—not necessarily better— by potential adopters. Unworthy innovations sometimes diffuse, and effective innovations are often stymied. Over time through waves of innovations,

diffusion changes societies. Sometimes these changes manifest as differences in knowledge, disproportionate access to government and com- mercial services, and worsening inequality be- cause resource-rich communities tend to adopt innovations early relative to poor communities.15

In this special issue of Health Affairs, for exam-

Exhibit 1

The context of diffusion

SOURCE Authors’ analysis. NOTE Each curve represents a separate hypothetical innovation.

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ple, researchers report that rates of adoption of annual wellness visits were lower among prac- tices caring for poor communities.16 Resource- rich communities with greater concentrations of professionals exhibit greater capacity to acquire and make use of innovations.17 Even when low- income communities also benefit from innova- tion adoption, gaps between the haves and the have-nots can widen. A study of forty-four criminal justice policies and their diffusion from 1960 to 2008 shows that states are more likely to adopt policies that benefit privileged segments of the population and weaken marginalized seg- ments.18 Fortunately, diffusion principles can be used in ways that stimulate the spread of inno- vations specifically in low-resource settings,19 a strategy known as purposive dissemination or designing for diffusion.20

Factors That Affect Diffusion Diffusion or the lack thereof is often well ex- plained by three general sets of variables: each innovation’s set of pros and cons, or attributes; the characteristics of adopters, especially poten- tial adopters’ perceptions of opinion leaders’ re- actions, or social influence; and the larger social and political context, including the salience of issues related to the innovation, how proponents and opponents frame the meaning of the inno- vation, and the timing of its introduction. Per- haps unsurprisingly, given diffusion’s many con- cepts, diffusion studies have helped form the basis for a number of other areas of study,21 such as dissemination and implementation science in health.22

When a person learns about an innovation that they think may have important consequences for them or those they serve, uncertainty about how to respond typically leads to a search for further information, so the potential adopter can better assess whether the innovation’s attri- butes warrant further exploration. The following pros and cons are well codified: cost, or the per- ceived monetary, time, or other resource ex- pense of adopting and implementing an innova- tion; effectiveness, or the extent to which the innovation is perceived to work better than what it would displace; simplicity, or how easy the innovation is to understand and use; compatibil- ity, or how well the innovation fits with estab- lished ways of accomplishing the same goal; ob- servability, or the extent to which outcomes can be seen; and trialability, or the extent to which the adoption decision is reversible or can be managed in stages. Whether or not people engage in such a cost-

benefit assessment, if the innovation continues to seem promising and consequential to them,

they may engage in a secondary search for the evaluative judgments of trusted, expert, and ac- cessible others—that is, opinion leaders—who are more discriminating and less susceptible to influence.23 The seeking of advice or the model- ing of one’s behavior on what others do is a heuristic that often reflects an emotional desire for status and that allows the decision maker to save time while reducing uncertainty. Taken together, an innovation’s attributes and social influence can be thought of as psychological and sociological barriers that serve to protect the potential adopter from unworthy innova- tions. At the level of the social system, this man- ifests as no orpartial diffusion,or a veryslow rate of adoption. Needs and motivations differ among people

according to their degree of innovativeness (ex- hibit 2). Based on Everett Rogers’s meta-review of empirical studies,9 the first to adopt (innova- tors) tend to do so because of excitement over novelty and feeling unconstrained by social norms; the next to adopt (early adopters, some of whom are opinion leaders) do so because of a measured appraisal that an innovation’s advan- tages outweigh its disadvantages; and the subse- quent early and late majorities adopt because they feel social pressure to do so. Laggards are, like innovators, less susceptible to social pres- sure and feel free to take their time. Campaigns to spread evidence-based innovations often tar- get particular messages to the degree of innova- tiveness (or readiness to change) of potential adopters on the basis of data from formative evaluations. Innovativeness reflects individual thresholds for change: To adopt an innovation themselves, those who adopt early require few in their reference group to have already adopted;

Exhibit 2

Distribution of adopter innovativeness based on time of adoption

SOURCE Modified from Rogers EM, Diffusion of innovations (see note 9 in text). NOTES This exhibit is based on Everett Rogers’s meta-review of empirical diffusion studies. SD is standard deviation.

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those who wait need more of their contacts to have adopted. Motivations and time of adoption can be pre-

dicted by each adopter’s structural position in the network of advice-seeking and advice-giving relationships that tie a social system—an organi- zation, community, or virtual network—togeth- er. The pattern of diffusion often begins on the periphery of a relational network, as the first to try the innovation experiment with it. Central members of the network—the opinion leaders— observe the periphery and then adopt the inno- vation if they judge it to have important advan- tages over current practice. And the many others between thecenter and theperiphery then follow by paying attention to what highly connected opinion leaders do and advise.24 This form of social contagion, an outside-inside-outward pro- gression of adoption, when graphed cumulative- ly, reflects the S-shaped diffusion curve. Potential adopters also perceive the relevance

of innovations when others like themselves adopt, even if they are not relationally con- nected. This sort of imitative effect can result from having the same job title, same type of employer, common training, same hometown, or shared beliefs or practices—all of these can lead potential adopters to reject or adopt inno- vations since homophilous others have done so. Modelers, forecasters, and experimentalists have spent considerable time testing the effects of both heterogeneous differences among units of adoption and homophilous characteristics of social system members on the decision to adopt25,26 and have shown, for example, that laggedintroductions of innovations across coun- tries can actually accelerate diffusion by allowing potential adopters in later-adopting countries to better assess early adopters’ experiences with an innovation.27

Triggering Of Interest And Demand While easy to confuse, dissemination activity and diffusion processes are wholly distinct. Dissemination refers to activities by proponents or intermediaries to inform others of an innova- tion, often in terms of segmenting targeted audiences. Information about an innovation is transmitted or advertised in what is usually a one-to-many process using social, mass, or spe- cialty media channels—though simply making information available is probably more com- mon.With innovations that require complex im- plementation, dissemination of information is joined with the establishment of branch offices, in much the same way that health care providers open new clinics; licensing affiliate organiza- tions as franchises, much as the Center for Medi-

care and Medicaid Innovation established agree- ments with accountable care organizations to partner with hospitals and practices to spread the principle of rewarding value over volume; or partnering with distribution networks as a pathway to scale, in much the same way as the Agency for Healthcare Research and Quality uses health extension networks to help small primary care practices institute preventive cardiac care in the EvidenceNOW innovation.28 All of these pathways to scale still rely on the activation of demand from providers or patients as essential for sustained scale-up success.29

So diffusion is a form of social activation that may or may not occur after the dissemination of information or scaling up of services or products has occurred. Diffusion can also occur without organized, intentional dissemination.

Implementation Science And Diffusion Processes Implementation science is the study of what hap- pens before, during, and after an innovation’s adoption occurs, especially in organizational settings.30 Many studies of implementation fo- cus on the period before dissemination, on field- based tests of external validity to understand the extent to which an evidence-based innovation is effective under realistic practice conditions and thus a good candidate for dissemination. A smaller proportion of implementation research concerns postdissemination behavior, partly because of the oft-occurring lag for diffusion to occur. An implementer is someone who will change

their behavior to use an innovation in practice. Incomplexorganizations, theusers areoftennot the choosers of an innovation—which can make the study of implementation fascinating, since motivation to use an innovation in practice can be absent or can even contribute to sabotage. Historically, little attention to implementation has been a major limitation of diffusion re- search, most of which focused on physicians,

While easy to confuse, dissemination activity and diffusion processes are wholly distinct.

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farmers, consumers, and other autonomous de- cision makers for whom adoption served as a reasonable proxy for use. In clinics and other types of organizations, the extent and quality of implementation and the responses of clients and constituents are outcomes at least as impor- tant as initial adoption. The same can be said about the sustained use of innovations after implementation and continued outcomes for patients or other end beneficiaries. Sustainabili- ty is the subject of increasing study by implemen- tation science and organizational change scholars.31

Government Policies As Innovations Policies have been long studied as innovations in the diffusion tradition, starting with a seminal US study about the spread of traffic-safety legislation among the states32 to hundreds of diffusion studies about policies concerning edu- cation, health, civil rights, and lotteries.33 While studies about policy diffusion among the states suggest rapid imitation once diffusion begins, the diffusion of policies sometimes demon- strates the same S-shaped curve as do other types of innovations in their cumulative distribution over time,34 with long latency periods before me- dia and public attention are able to propel policy adoption—as was the case with the issue of HIV/ AIDS in the 1980s.35 Researchers often concep- tualize more or less time-ordered stages of policy consideration, adoption, and growth or scale-up,36 though such stages have become com- pressed over the past century as communication technology has enabled faster and faster aware- ness of innovations.10

Policy diffusion researchers have found that beliefs about an innovation’s effectiveness can be more important than knowledge of actual out- comes, again suggesting that who has previously adopted an innovation can be more important for decision makers than what was previously adopted and what effects it had.37 This type of result echoes the importance of imitation and mimicry in studies of other types of innovations in other eras and in other countries.38 Policy diffusion studies show that national policy and media attention can drive policy consideration at the state level,39 as a contextual effect,18 though there is evidence that policy attention and enact- ment in neighboring states and gubernatorial agenda-setting can be stronger predictors of state policy adoption.40 There is also consider- able evidence that local successes in cities and states can become noticed and highlighted at the federal level and then diffuse back out broadly to the states as new programs and policies, often with the incentive of funding mechanisms.33,41

Policy diffusion among the states accelerates with more federal attention to a problem area and its policy alternatives.42

Policy diffusion studies have also shown the importance of types of intermediary actors, such as professional associations, in diffusion proc- esses.43 Policy entrepreneurs are a particularly notable type of actor with the ability to pollinate political jurisdictions with innovations.44 A poli- cy entrepreneur combines the functions of a bridge who ties together disparate groups with that of a champion who represents an innovation from one city or state to high-level decision mak- ers in other jurisdictions. Effective policy entre- preneurs are able to talk about innovations as solutions to public policy problems in ways that are politically palatable.45 Policy entrepreneurs have been state representatives, leaders of nonprofit community organizations, and well- known experts within a profession. They work to exploit political windows of opportunity; frame solutions to problems in politically palat- able ways; and join together disparate individu- als, groups, and networks to diffuse policies.

Fidelity, Reinvention, And Adaptation Fidelity is the extent to which an innovation is implemented by others in the way intended by its developers. Fidelity is often measured as the correspondence between how a program is delivered in tests before scale-up and how the program is later offered by implementing part- ners in the field.46 Innovation developers differ in the degree to which they modify innovations before dissemination, and how much they seek to maintain control over potential modifications by practice-based implementers. Although a strict adherence to the original procedures may be desirable to maximize effectiveness in the new setting, implementers often make changes—knowingly or not—to better fit an in- novation to their organization and clients. Fidelity can be affected in the process of diffu-

sion in two ways: reinvention and adaptation. Reinvention refers to changes made by an inno- vation’s developer to an innovation before its dissemination or scale-up to increase its likeli- hood of being adopted and effectively imple- mented. These changes often take the form of lessening a “perfect” but costly innovation so that it produces enough benefit to justify its dis- semination to more beneficiaries. For example, the YMCA of the USA reinvented its Diabetes Prevention Program from a one-on-one counsel- ing intervention led by a medical professional to a group intervention facilitated by YMCA personnel—which lowered the program’s cost

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and broadened its reach.47

Adaptation refers to changes made to an inno- vation by implementers who serve intended ben- eficiaries. Adaptations are made by staff in re- sponse both to the immediate context of a health care or public health organizational setting and to changes in the external environment that can make or break the sustained applicability of an innovation for improving health and health care. Developers who share or cede control of the im- plementation of an innovation, sometimes in- sisting on fidelity to its core components while encouraging customization of peripheral com- ponents, can achieve diffusion through ongoing course corrections and allowing the implemen- tation strategy to evolve, as exhibited in the twenty-year history of Health Leads reported in this issue of Health Affairs.48 Health Leads has successfully integrated social needs into clin- ical care partly as a result of developers’ willing- ness to cede control. This result—that degrees of decentralized control can increase the rate and reach of innovation diffusion—is found in stud- ies of educational and public health innova- tions, too. Feedback from field-based implementers so

that ongoing results can contribute to an evolv- ing implementation strategy need not end with developers. The sharing of real-time insights from implementers to other implementers is a key takeaway lesson from the Center for Medi- care and Medicaid Innovation’s experience, as reported in this special issue.49 Performance im- provement methodology does not suit all inno- vations, but health care services in particular seem well suited to the incorporation of stake- holders’ perspectives into service redesign.50 En- abling and supporting adaptation by stakehold- ers can produce sustained use of innovations because of a stronger sense of ownership by im- plementers,51 as long as adaptations are fidelity consistent.52

Using Diffusion Concepts To Affect Rate And Reach Purposive dissemination, or designing for diffu- sion, means taking additional steps early in the process of creating an innovation to increase its chances of being noticed, positively perceived, adopted, adapted, and implemented—and, thus, successfully crossing the research-to-practice chasm.53 First of all, one wants to be certain that an innovation should be diffused and that, in so doing, its reach is extended to those communi- ties and population segments where need is greatest and capacity is sufficient to adopt and implement the innovation to good effect. In pur- posive dissemination, external validity—the in-

novation’s ability to achieve positive outcomes across a diversity of sites—needs to be assessed (ideally on the basis of theory as well as data) from the vantage points of stakeholders who will implement the innovation.54 Other measures of readiness also should be assessed, including how potential adopters perceive the attributes of the innovation and the availability of implementa- tion support in anticipation of demand from providers and patients.55

Formative assessment of advice-seeking net- works among potential adopters of an innova- tion is an important key to the stimulation of diffusion. Such data can statistically and visually identify which few potential adopters are partic- ularly influential when the vast majority of others are deciding whether or not to adopt, as illustrated in the work of the Translating Research in Elder Care group, based at the Uni- versity of Alberta. A recent formative study by this group assessed advice-seeking ties across 958 nursing homes in nine of Canada’s eleven provinces and territories. The results identified opinion leaders within each jurisdiction, as well as advice-seeking ties across provinces, so that future resources can be focused on intervention with small proportions of influential individuals and organizations for eventual system change.56

Getting off on the right foot in the stimulation of a diffusion process is important. Diffusion processes often exhibit path dependence, where- by initial conditions determine how rapidly and to what extent an innovation will spread.57 Relat- edly, the timing of dissemination can be critical to diffusion.58 If potential adopters are attending to a different type of problem than the innova- tion addresses, waiting to disseminate can be the right decision. Learning about and addressing barriers to dif-

fusion for both end beneficiaries and the health care practitioners who serve them is important. Many health care innovations require multiple levels of adoption—for example, by a chief medi- cal officer and organizational sponsors, clinical chiefs, head nurses, and patients and families.

Getting off on the right foot in the stimulation of a diffusion process is important.

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Formative evaluation along the entire supply chain that needs to coordinate for the dissemi- nation, supply, delivery, and support of an inno- vation can reduce barriers before launch.59 This includes attention to perceived incentives, both monetary and intrinsic, which can be tailored to address types of stakeholders where formative evaluation suggests that barriers to adoption are high—thus contributing to a climate for change.60

Conclusion The research and practice paradigm known as the diffusion of innovations offers a ready set of concepts and approaches that can be used to explain receptivity to health care policies and practices by individuals and organizations. Diffusion principles can also be operationalized to accelerate the rate of adoption and broaden the reach of health innovations. ▪

NOTES

1 Dearing JW, Singhal A. Communi- cation of innovations: a journey with Ev Rogers. In: Singhal A, Dearing JW, editors. Communication of innovations. Thousand Oaks (CA): Sage; 2006. p. 15–28.

2 Arora S, Kalishman S, Dion D, Som D, Thornton K, Bankhurst A, et al. Partnering urban academic medical centers and rural primary care clinicians to provide complex chronic disease care. Health Aff (Millwood). 2011;30(6):1176–84.

3 Project ECHO: the global ECHO network [Internet]. Albuquerque (NM): University of New Mexico School of Medicine, Project ECHO; 2017 Nov 9 [cited 2018 Jan 16]. Available from: https://echo.unm .edu/wp-content/uploads/2017/11/ ECHOSuperHubs_and_Hubs_2017 1109.pdf

4 Madore A, Rosenberg J, Weintrab R. Project ECHO: expanding the ca- pacity of primary care providers to address complex conditions [Inter- net]. Cambridge (MA): President and Fellows of Harvard College; 2017 Mar [cited 2017 Dec 12]. (Cases in Global Health Delivery). Available from: http://www.globalhealth delivery.org/files/ghd/files/ghd- 036_project_echo_case.pdf

5 Zimmerman S, Bowers BJ, Cohen LW, Grabowski DC, Horn SD, Kemper P. New evidence on the Green House model of nursing home care: synthesis of findings and im- plications for policy, practice, and research. Health Serv Res. 2016; 51(Suppl 1):475–96.

6 Baker B. Rebooting the nursing home. Politico [serial on the Inter- net]. 2017 Jan 11 [cited 2017 Dec 21]. Available from: https://www .politico.com/agenda/story/2017/ 01/nursing-homes-of-the-future- 000269

7 Henry J. Kaiser Family Foundation. State health facts [Internet]. Menlo Park (CA): KFF; 2017 [cited 2017 Dec 5]. Available for download from: https://www.kff.org/other/state- indicator/total-rural-health-clinics/ ?currentTimeframe=0&sortModel= %7B%22colId%22:%22Location %22,%22sort%22:%22asc %22%7D

8 Morris ZS, Wooding S, Grant J. The answer is 17 years, what is the question: understanding time lags in translational research. J R Soc Med. 2011;104(12):510–20.

9 Rogers EM. Diffusion of innova- tions. 5th ed. New York (NY): Free Press; 2003.

10 Boushey GT. Policy diffusion dy- namics in America. New York (NY): Cambridge University Press; 2010.

11 Greve HR. Fast and expensive: the diffusion of a disappointing inno- vation. Strateg Manage J. 2011; 32(9):949–68.

12 Miner AS, Kim JY, Holzinger IW, Haunschild PR. Fruits of failure: organizational failure and popula- tion-level learning. In: Baum JAC, Miner AS, Anderson P, editors. Advances in strategic management, volume 16. Greenwich (CT): JAI Press; 1999. p. 187–220.

13 Lomas J. Words without action? The production, dissemination, and im- pact of consensus recommenda- tions. Annu Rev Public Health. 1991;12:41–65.

14 Berwick DM. Disseminating inno- vations in health care. JAMA. 2003; 289(15):1969–75.

15 Buchanan A, Cole T, Keohane RO. Justice in the diffusion of innova- tion. J Polit Philos. 2011;19(3): 306–32.

16 Ganguli I, Souza J, McWilliams MJ, Mehrotra A. Practices caring for underserved less likely to adopt Medicare’s annual wellness visit. Health Aff (Millwood). 2018;37 (2):283–91.

17 Bhatti Y, Olsen AL, Pederson LH. Administrative professionals and the diffusion of innovations: the case of citizen service centres. Public Adm. 2011;89(2):577–94.

18 Boushey G. Targeted for diffusion? How the use and acceptance of stereotypes shape the diffusion of criminal justice policy innovations in the American states. Am Polit Sci Rev. 2016;110(1):198–214.

19 Green LW, Gottlieb NH, Parcel GS. Diffusion theory extended and ap- plied. In: Ward WB, Lewis FM, edi- tors. Advances in health education and promotion. Vol. 3. London: Jessica Kingsley Publishers; 1991.

p. 91–117. 20 Dearing JW, Smith DK, Larson RS,

Estabrooks CA. Designing for diffu- sion of a biomedical intervention. Am J Prev Med. 2013;44(1 Suppl 2): S70–6.

21 Estabrooks CA, Derksen L, Winther C, Lavis JN, Scott SD, Wallin L, et al. The intellectual structure and sub- stance of the knowledge utilization field: a longitudinal author co-cita- tion analysis, 1945 to 2004. Imple- ment Sci. 2008;3:49.

22 Norton WE, Lungeanu A, Chambers DA, Contractor N. Mapping the growing discipline of dissemination and implementation science in health. Scientometrics. 2017;112(3): 1367–90.

23 Aral S, Walker D. Identifying influ- ential and susceptible members of social networks. Science. 2012; 337(6092):337–41.

24 Kerckhoff AC, Back KW, Miller N. Sociometric patterns in hysterical contagion. Sociometry. 1965; 28(1):2–15.

25 Meade N, Islam T. Modeling and forecasting the diffusion of innovation—a 25-year review. Int J Forecast. 2006;22(3):519–45.

26 Centola D. An experimental study of homophily in the adoption of health behavior. Science. 2011;334(6060): 1269–72.

27 Kumar V, Krishnan TV. Multina- tional diffusion models: an alterna- tive framework. Mark Sci. 2002;21: 318–30.

28 Larson RS, Dearing JW, Backer TE. Strategies to scale up social pro- grams: pathways, partnerships and fidelity [Internet]. East Lansing (MI): Diffusion Associates; 2017 Sep [cited 2017 Dec 12]. Available from: http://www.wallacefoundation.org/ knowledge-center/Documents/ Strategies-to-Scale-Up-Social- Programs.pdf

29 Simmons R, Fajans P, Ghiron L. Scaling up health service delivery: from pilot innovations to policies and programmes [Internet]. Geneva: World Health Organization; 2007 [cited 2017 Dec 12]. Available from: http://www.who.int/immunization/ hpv/deliver/scalingup_health_ service_delivery_who_2007.pdf

February 2018 37:2 Health Affairs 189 Downloaded from HealthAffairs.org on October 21, 2021.

30 Brownson RC, Colditz GA, Proctor EK editors. Dissemination and im- plementation research in health: translating science to practice. 2nd ed. New York (NY): Oxford Univer- sity Press; 2018.

31 Wiltsey Stirman S, Kimberly J, Cook N, Calloway A, Castro F, Charns M. The sustainability of new programs and innovations: a review of the empirical literature and recommen- dations for future research. Imple- ment Sci. 2012;7:17.

32 Walker JL. The diffusion of innova- tions among the American states. Am Polit Sci Rev. 1969;63(3): 880–99.

33 Karch A. Democratic laboratories: policy diffusion among the American states. Ann Arbor (MI): University of Michigan Press; 2007.

34 Baumgartner FR, Jones BD. Agendas and instability in American politics. 2nd ed. Chicago (IL): University of Chicago Press; 2009.

35 Rogers EM, Dearing JW, Chang S. AIDS in the 1980s: the agenda- setting process for a public issue. Journalism Monographs [serial on the Internet]. Available from: https://www.researchgate.net/ profile/James_Dearing2/ publication/263807905_AIDS_ in_the_1980s_The_Agenda- setting_Process_for_a_Public_ Issue/links/5825d2b908ae7ea5 be7b623a/AIDS-in-the-1980s-The- Agenda-setting-Process-for-a-Public- Issue.pdf.

36 Mangham LJ, Hanson K. Scaling up in international health: what are the key issues? Health Policy Plan. 2010; 25(2):85–96.

37 May PJ. Policy learning and failure. J Public Policy. 1992;12(4):331–54.

38 Conell C, Cohn S. Learning from other people’s actions: environmen- tal variation and diffusion in French coal mining strikes, 1890–1935. Am J Sociol. 1995;101(2):366–403.

39 Karch A. Vertical diffusion and the policy-making process: the politics of embryonic stem cell research. Polit Res Q. 2010;65(1):48–61.

40 Pacheco J, Boushey G. Public health and agenda setting: determinants of

state attention to tobacco and vac- cines. J Health Polit Policy Law. 2014;39(3):565–89.

41 Shipan CR, Volden C. Bottom-up federalism: the diffusion of anti- smoking policies from U.S. cities to states. Am J Pol Sci. 2006;50(4): 825–43.

42 Boushey G. Punctuated equilibrium theory and the diffusion of innova- tions. Policy Stud J. 2012;40(1): 127–46.

43 Douglas JW, Raudla R, Hartley RE. Shifting constellations of actors and their influence on policy diffusion: a study of the diffusion of drug courts. Policy Stud J. 2015;43(4):484–511.

44 Mintrom M, Norman P. Policy en- trepreneurship and policy change. Policy Stud J. 2009;37(4):649–67.

45 Keck ME, Sikkink K. Activists be- yond borders: advocacy networks in international politics. Ithaca (NY): Cornell University Press; 1998.

46 Pérez D, Van der Stuyft P, Zabala MC, Castro M, Lefèvre P. A modified theoretical framework to assess im- plementation fidelity of adaptive public health interventions. Imple- ment Sci. 2016;11(1):91.

47 Alva ML, Hoerger TJ, Jeyaraman R, Amico P, Rojas-Smith L. Impact of the YMCA of the USA diabetes pre- vention program on Medicare spending and utilization. Health Aff (Millwood). 2017;36(3):417–24.

48 Onie RD, Lavizzo-Mourey R, Lee TH, Marks J, Perla RJ. Integrating social needs into health care: a twenty-year case study of adaptation and diffu- sion. Health Aff (Millwood). 2018; 37(2):240–47.

49 Perla RJ, Pham H, Gilfillan R, Berwick DM, Baron RJ, Lee P, et al. Government as innovation catalyst: lessons from the early Center for Medicare and Medicaid Innovation models. Health Aff (Millwood). 2018;37(2):213–21.

50 Batalden M, Batalden P, Margolis P, Seid M, Armstrong G, Opipari- Arrigan L, et al. Coproduction of healthcare service. BMJ Qual Saf. 2016;25(7):509–17.

51 Scheirer MA, Dearing JW. An agenda for research on the sustainability of

public health programs. Am J Public Health. 2011;101(11):2059–67.

52 Wiltsey Stirman S, Gutner CA, Crits-Christoph P, Edmunds J, Evans AC, Beidas RS. Relationships be- tween clinician-level attributes and fidelity-consistent and fidelity- inconsistent modifications to an evidence-based psychotherapy. Implement Sci. 2015;10:115.

53 Dearing JW, Kreuter MW. Designing for diffusion: how can we increase uptake of cancer communication innovations? Patient Educ Couns. 2010;81(Suppl):S100–10.

54 Leviton LC. Generalizing about public health interventions: a mixed- methods approach to external va- lidity. Annu Rev Public Health. 2017; 38:371–91.

55 Flay BR, Biglan A, Boruch RF, Castro FG, Gottfredson D, Kellam S, et al. Standards of evidence: criteria for efficacy, effectiveness and dissemi- nation. Prev Sci. 2005;6(3):151–75.

56 Dearing JW, Beacom AM, Chamberlain SA, Meng J, Berta WB, Keefe JM, et al. Pathways for best practice diffusion: the structure of informal relationships in Canada’s long-term care sector. Implement Sci. 2017;12(1):11.

57 Greve HR, Seidel M-DL. The thin red line between success and failure: path dependence in the diffusion of innovative production technologies. Strateg Manage J. 2015;36(4): 475–96.

58 Calantone R, Di Benedetto CA, Rubera G. Launch timing and launch activities proficiency as antecedents to new product performance. J Global Scholars Market Sci: Bridging Asia World. 2012;22(4):290–309.

59 Talke K, Hultink EJ. Managing dif- fusion barriers when launching new products. J Prod Innov Manage. 2010;27(4):537–53.

60 Parston G, McQueen J, Patel H, Keown OP, Fontana G, Al Kuwari H, et al. The science and art of delivery: accelerating the diffusion of health care innovation. Health Aff (Mill- wood). 2015;34(12):2160–6.

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