Diffusion Of Innovations Theory, Principles, And Practice

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DOI: 10.1377/hlthaff.2017.1104
Cite this publication
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.
By James W. Dearing and Jeffrey G. Cox
Diffusion Of Innovations Theory,
Principles, And Practice
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.
In 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.1Now, fifty-six years past the first
publication of Rogerss book Diffusion of Innova-
tions, we briefly review this theory, its principles,
and the implications for practice as a fifteen-year
update to the books 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.2This 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.3The program has moved
from hepatitis C care to include HIV/AIDS, geri-
atrics, psychiatric medication management, and
more.4Or consider the Green House model of
nursing home care, in which house-likefacili-
ties are built that emphasize an open kitchen,
residentscontrol in decision making, and em-
powered nursing assistants.5Underwritten 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 in 2017 with 300 expected by the end of 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 thediffusion 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 2016.7In 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 takeoffor 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-
doi: 10.1377/hlthaff.2017.1104
NO. 2 (2018): 183190
©2018 Project HOPE
The People-to-People Health
Foundation, Inc.
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.
February 2018 37:2 Health Affairs 183
Diffusion Of Innovation
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nels over time among the members of a social
system.9The 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 or complementary innovations are impor-
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 newnot 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 Authorsanalysis. 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
innovations set of pros and cons, or attributes;
the characteristics of adopters, especially poten-
tial adoptersperceptions of opinion leadersre-
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 diffusions 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
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 innovations 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 othersthat is, opinion leaderswho
are more discriminating and less susceptible to
influence.23 The seeking of advice or the model-
ing of ones 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 innovations 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 or partial diffusion, or a very slow rate
of adoption.
Needs and motivations differ among people
according to their degree of innovativeness (ex-
hibit 2). Based on Everett Rogerss meta-review
of empirical studies,9the 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 innovations 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 Rogerss 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 adopters structural position in
the network of advice-seeking and advice-giving
relationships that tie a social systeman organi-
zation, community, or virtual networktogeth-
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 networkthe 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 the center and the periphery 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 practicesall 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
lagged introductions of innovations across coun-
tries can actually accelerate diffusion by allowing
potential adopters in later-adopting countries to
better assess early adoptersexperiences with an
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 channelsthough 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 innovations
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.
In complex organizations, the users are often not
the choosers of an innovationwhich 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,
dissemination activity
and diffusion
processes are wholly
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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
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
adoptionas 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 innovations 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
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
changesknowingly or notto 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-
vations 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 perfectbut 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
personnelwhich lowered the programs 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 developerswilling-
ness to cede control. This resultthat degrees of
decentralized control can increase the rate and
reach of innovation diffusionis 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 Innovations 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-
holdersperspectives 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
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 implementedand, 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 validitythe in-
novations ability to achieve positive outcomes
across a diversity of sitesneeds 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 Canadas 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 adoptionfor 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
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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 highthus contributing to a climate for
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.
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  • ... Theories of innovative development, in particular the diffuse orientation of innovations, have become widespread in European and American research practice [14]. The American sociologist Everett Rogers studied how, why, and at what frequency new ideas and technologies disseminate across different cultures; defined "diffusion" as a process, which implements the innovation through specific channels among members of social systems [15]. ...
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    This article considers the opportunities of using Moodle LMS (learning management system) tools to ensure the effective implementation of an innovative policy of the higher educational institution. In the framework of digital transformation of social space an important and relevant topic for higher educational institutions is the creation of high-quality information and communication environment, which shall correspond to the contemporary state of science and technology development, global educational standards and information society needs. The advantages of the Moodle system are studied. Moodle system provides for a comprehensive educational process through its extensive educational content, a system for control, monitoring and evaluating the knowledge quality. The authors compare the four-phased model of knowledge management with the capacities of LMS Moodle educational environment. The latter is capable of simulating professional actions in a virtual educational space that allows the university to train advanced specialists and ensure a high level of their professional skills based on hard and soft skills. The perceptive and cognitive attitude of university students and teachers towards the implementation of the LMS Moodle educational platform was researched. The research has brought out the subjective assessment model of the innovative process with clear meaningful factors of changes’ perception. Such a model allows understanding the collective attitude to the university’s policy and highlighting mental settings necessary for working with human resources within the social adaptation and diffusion of innovation. The synergy of technological and managerial innovations has been updated to ensure completeness and efficiency in presenting a professional educational product based on the LMS Moodle platform.
  • ... ACT launch and dissemination strategies were based on the PCORI Dissemination and Implementation Framework (11) and systematic application of Diffusion of Innovation Theory for accelerating the adoption of biomedical interventions and technologies by individuals and institutions (12)(13)(14)(15)(16). Diffusion theory rests on the established fact that people typically learn of innovations through mediated channels of communication but then turn to trusted or expert interpersonal sources for advice about whether to adopt or not. ...
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    We conducted a multi-study, mixed-methods, longitudinal investigation to examine how mobile technology diffuses across the lifespan, in real time, within a multi-generational population, while seeking local knowledge through community-based participatory research. Using qualitative methods (QUAL), we examined technology adoption within and across three iterations (16 weeks) of a nine-wave longitudinal community technology-training workshop, situated within a 15-wave study. In parallel, we interrogated existing conceptualization and operationalization of diffusion of technology variables, then deductively evaluated the dominant DOI-related variables re-conceptualized through the community study in a large cross-sectional quantitative (QUAN) investigation. We interpreted our results consistently and iteratively with a mixed-methods approach that included conceptualization, operationalization, and empirical testing. We discovered that oft-conflated concepts of knowledge, use, and ownership represent distinct stages of adoption. Our findings suggest constant feedback/permeable boundaries between these stages, and that DOI attributes may influence mobile technology adoption stages differentially. We suggest that innovators seeking to facilitate mobile technology adoption should focus on reducing complexity, and establishing calibration of complexity perceptions. We propose a lifespan mobile technology diffusion model, and call to question the language used in investigations related to the digital divide. We strive to clarify labels that may stereotype vulnerable populations, such as older adults. Our research contributes to theories of technology adoption – particularly after the introduction of digital communication - the diffusion of innovations in the community over time, and technology adoption process as affected by interpersonal communication and relationships, including among the technologically undercapitalized and the digitally privileged.
  • ... Late majority are those who are inescapable of adopting the technology otherwise there would be risks and additional cost to be incurred in the absence of adoption. Laggards are those who are struggling to adopt the new technology and sceptics are those who are suspicious always for adoption of new technology [18]. ...
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    The US health care system has recently begun to account for patients' unmet social needs in care delivery and payment reform. This article presents a twenty-year qualitative case study of five stages of diffusion-testing and learning, standardization, replication, shifting from doing to enabling, and catalyzing broad adoption-of a practical approach for integrating social needs into clinical care. This case study of Health Leads and its funders confirms the importance of focusing on a clear aim, investing in model testing and standardization to enable subsequent responsiveness to the market, and the willingness of innovators and their investors to cede control of a model to allow local adaption and accelerate broad adoption.
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    In 2011 Medicare introduced the annual wellness visit to help address the health risks of aging adults. The visit also offers primary care practices an opportunity to generate revenue, and may allow practices in accountable care organizations to attract healthier patients while stabilizing patient-practitioner assignments. However, uptake of the visit has been uneven. Using national Medicare data for the period 2008-15, we assessed practices' ability and motivation to adopt the visit. In 2015, 51.2 percent of practices provided no annual wellness visits (nonadopters), while 23.1 percent provided visits to at least a quarter of their eligible beneficiaries (adopters). Adopters replaced problem-based visits with annual wellness visits and saw increases in primary care revenue. Compared to nonadopters, adopters had more stable patient assignment and a slightly healthier patient mix. At the same time, visit rates were lower among practices caring for underserved populations (for example, racial minorities and those dually enrolled in Medicaid), potentially worsening disparities. Policy makers should consider ways to encourage uptake of the visit or other mechanisms to promote preventive care in underserved populations and the practices that serve them.
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    Congress established the Center for Medicare and Medicaid Innovation (CMMI) to design, test, and spread innovative payment and service delivery models that either reduce spending without reducing the quality of care or improve the quality of care without increasing spending. CMMI sought to leverage these models to foster market innovation and accelerate the transformation of payment and care delivery to achieve the Triple Aim of better health, better care, and lower cost. This article provides a perspective on the design and execution of CMMI's five initial models, the resulting outcomes and lessons, and how their core concepts evolved within and spread beyond CMMI. This experience yields three key insights that could inform future efforts by CMMI and public and private payers, including model designs and policy decisions. These insights center on the need for iterative testing and learning guided by market feedback, more realistic time frames to demonstrate impact on cost and quality, and greater integration of models.
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    Scaling what works is a crucial component of systems change. The 45 education, youth development and health programs in this study have scaled to varying degrees using different pathways, but all involve some type of collaboration or partnership and all must address issues of program fidelity. Though our study is exploratory and not representative of all social program scale up activity, we hope that the present report can help move the field of scale up studies and practice forward.
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    Background: The field of dissemination and implementation (D&I) research in health has grown considerably in the past decade. Despite the potential for advancing the science, limited research has focused on mapping the field. Methods: We administered an online survey to individuals in the D&I field to assess participants' demographics and expertise, as well as engagement with journals and conferences, publications, and grants. A combined roster-nomination method was used to collect data on participants' advice networks and collaboration networks; participants' motivations for choosing collaborators was also assessed. Frequency and descriptive statistics were used to characterize the overall sample; network metrics were used to characterize both networks. Among a sub-sample of respondents who were researchers, regression analyses identified predictors of two metrics of academic performance (i.e., publications and funded grants). Results: A total of 421 individuals completed the survey, representing a 30.75% response rate of eligible individuals. Most participants were White (n = 343), female (n = 284, 67.4%), and identified as a researcher (n = 340, 81%). Both the advice and the collaboration networks displayed characteristics of a small world network. The most important motivations for selecting collaborators were aligned with advancing the science (i.e., prior collaborators, strong reputation, and good collaborators) rather than relying on human proclivities for homophily, proximity, and friendship. Among a sub-sample of 295 researchers, expertise (individual predictor), status (advice network), and connectedness (collaboration network) were significant predictors of both metrics of academic performance. Conclusions: Network-based interventions can enhance collaboration and productivity; future research is needed to leverage these data to advance the field.
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    The YMCA of the USA received a Health Care Innovation Award from the Centers for Medicare and Medicaid Services to provide a diabetes prevention program to Medicare beneficiaries with prediabetes in seventeen regional networks of participating YMCAs nationwide. The goal of the program is to help participants lose weight and increase physical activity. We tested whether the program reduced medical spending and utilization in the Medicare population. Using claims data to compute total medical costs for fee-for-service Medicare participants and a matched comparison group of nonparticipants, we found that the overall weighted average savings per member per quarter during the first three years of the intervention period was $278. Total decreases in inpatient admissions and emergency department (ED) visits were significant, with nine fewer inpatient stays and nine fewer ED visits per 1,000 participants per quarter. These results justify continued support of the model.
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    Background Initiatives to accelerate the adoption and implementation of evidence-based practices benefit from an association with influential individuals and organizations. When opinion leaders advocate or adopt a best practice, others adopt too, resulting in diffusion. We sought to identify existing influence throughout Canada’s long-term care sector and the extent to which informal advice-seeking relationships tie the sector together as a network. Methods We conducted a sociometric survey of senior leaders in 958 long-term care facilities operating in 11 of Canada’s 13 provinces and territories. We used an integrated knowledge translation approach to involve knowledge users in planning and administering the survey and in analyzing and interpreting the results. Responses from 482 senior leaders generated the names of 794 individuals and 587 organizations as sources of advice for improving resident care in long-term care facilities. ResultsA single advice-seeking network appears to span the nation. Proximity exhibits a strong effect on network structure, with provincial inter-organizational networks having more connections and thus a denser structure than interpersonal networks. We found credible individuals and organizations within groups (opinion leaders and opinion-leading organizations) and individuals and organizations that function as weak ties across groups (boundary spanners and bridges) for all studied provinces and territories. A good deal of influence in the Canadian long-term care sector rests with professionals such as provincial health administrators not employed in long-term care facilities. Conclusions The Canadian long-term care sector is tied together through informal advice-seeking relationships that have given rise to an emergent network structure. Knowledge of this structure and engagement with its opinion leaders and boundary spanners may provide a route for stimulating the adoption and effective implementation of best practices, improving resident care and strengthening the long-term care advice network. We conclude that informal relational pathways hold promise for helping to transform the Canadian long-term care sector.