The Assimilation of Evidence-Based Healthcare
Innovations: A Management-Based
Phyllis C. Panzano, PhD
Helen Anne Sweeney, MS
Beverly Seffrin, PhD
Richard Massatti, MSW
Kraig J. Knudsen, PhD
In order to reap the benefits of the nation’s vast investments in healthcare discoveries, evidence-
based healthcare innovations (EBHI) must be assimilated by the organizations that adopt them.
Data from a naturalistic field study are used to test a management-based model of implementation
success which hypothesizes strategic fit, climate for EBHI implementation, and fidelity will explain
variability in the assimilation of EBHIs by organizations that adopted them under ordinary
circumstances approximately 6 years earlier. Data gathered from top managers and external
consultants directly involved with these long-term EBHI implementation efforts provide
preliminary support for predicted positive linkages between strategic fit and climate; climate and
fidelity; and fidelity and assimilation. Mediated regression analyses also suggest that climate and
fidelity may be important mediators. Findings raise important questions about the meaning of
assimilation, top managers’ roles as agents of assimilation, and the extent to which results
represent real-world versus implicit models of assimilation.
Address correspondence to Phyllis C. Panzano, PhD, Decision Support Services, Inc, 4449 Easton Way Suite 2012,
Columbus, OH 43219, USA. Phone: +1-614-2211474; Email: firstname.lastname@example.org.
Helen Anne Sweeney, MS, Ohio Department of Mental Health, Office of Research and Evaluation, Columbus, OH, USA.
Phone: +1-614-4668651; Email: HelenAnne.Sweeney@mh.ohio.gov
Beverly Seffrin, PhD, Performance Evaluation Division, Franklin County Childrens’ Court, Columbus, OH, USA. Phone:
+1-614-5253429; Email: Bev_Seffrin@fccourts.org
Richard Massatti, MSW, Ohio Department of Alcohol and Drug Addiction Services, Columbus, OH, USA. Phone:
+1-43215-2256; Fax: +1-614-7528718; Email: Rick.Massatti@ada.ohio.gov
Kraig J. Knudsen, PhD, Office of Research and Evaluation, Ohio Department of Mental Health, Columbus, OH, USA.
Phone: +1-614-4668651; Email: Kraig.Knudsen@mh.ohio.gov
Journal of Behavioral Health Services & Research, 2012. 397–416. c) )2012 National Council for Community Behavioral
The Assimilation of Evidence-Based Healthcare InnovationsPANZANO et al.397
The dearth of knowledge about what accounts for evidence-based and promising health
and mental health innovations (EBHI) to endure in the organizations that adopt them has
been described as one of the most significant impediments to closing the gap between
intervention development and program use.1–11It prevents the nation from fully benefitting
from the billions of US tax dollars spent on developing EBHIs and, in mental health, it
unnecessarily prolongs the suffering of millions of Americans who live with mental
disorders.3While many barriers and complex challenges exist, long-term, longitudinal
investigations of public organizations’ efforts to implement EBHIs under naturalistic
conditions are needed to shed light on this important topic. This type of research is essential
to ensuring that all populations have the opportunity to benefit from the nation’s investments
in developing scientifically based healthcare innovations.9
A substantial body of theory and research from healthcare and organizational behavior identifies
factors and processes that account for the success of organizations’ efforts to implement
innovations. Much of this knowledge comes from studies which examine innovation implemen-
tation for relatively short time periods (e.g., 2 or 3 years), and which define success in a myriad of
ways.12–15In contrast, studies of long-term innovation-use are rare. Most of what is known about
implementation beyond initial use and early outcomes originates from in-depth case studies16
which tend to define implementation success in simplistic ways (e.g., continued use: yes or no).13
Even when EBHI implementation has been carried out on a broader scale and examined in the
context of large-scale field studies, the “primary focus has been on scaling up to insure that
implementation is successful during the course of the study rather than on addressing issues that
may facilitate continued use of innovations when formal investigations come to an end and/or
when extramural funding” or other forms of support are discontinued.17(p 135)Consequently, there
is much to be learned about the extent to which findings from short-term investigations of
innovation implementation explain enduring measures of implementation success, such as the
extent to which EBHIs become embedded in organizations that initially adopt them either as part of
research or demonstration projects18,19or under naturalistic conditions.1,2,10,11
This study advances a management-based model of implementation success which defines
success in terms of both fidelity and assimilation. The model is intended to apply to organizations
engaged in implementing EBHIs or other “fixed” innovations (i.e., innovations for which fidelity is
essential to effectiveness),15which are first adopted under naturalistic conditions rather than as part
of a research or demonstration project. Differences in the conditions under which innovations are
first adopted by organizations warrant independent research attention due to their likely important
implications for the course and outcomes of innovation implementation efforts. For example,
adoption decisions made in research versus real-world contexts may be associated with differences
in: adoption motives (e.g., relative interest in advancing science versus improving performance);
adoption intentions (e.g., trial versus permanent use); and consequential organizational attributes
(e.g., availability of slack resources—expertise, time, money).20,21Thus, while it is vital to
understand factors that prompt innovations to endure in organizations when research or
demonstration projects end, that context is not the focus of this analysis.18,19
Building on the innovation literature, including recent long-term investigations of the sustained
use of innovations by organizations, and on research regarding strategic cognition, the study
explores the premise that members of organizations’ top management teams (TMTs) (e.g., Chief
Executive Officer [CEO]/Agency Director) affect the success of efforts to implement EBHIs by
virtue of what they think (e.g., views held about strategic fit of innovations) and what they do (e.g.,
championship behavior displayed).16,22,23This idea is supported by management scholars who
contend that the success or failure of organizational innovation efforts may have more to do with
factors related to or under the control of top management than it has to do with exogenous
variables.24The proposed model and the methodological paradigm used to examine it reflect these
ideas as well.
398 The Journal of Behavioral Health Services & Research39:4October 2012
This investigation draws on data gathered from a 7-year observational field study of the
adoption, implementation and de-adoption of two evidence-based and two promising mental health
innovations (EBHI) within one state mental health system.25The analysis is concerned with
explaining the degree to which these EBHIs are assimilated into routine practice and the extent to
which they are implemented with fidelity by the behavioral healthcare organizations (BHO) that
adopted them roughly 6 years earlier. Following Yin’s work, assimilation is defined as an
organizational process that (1) begins when organizational decision-makers first become aware of
an EBHI, (2) can lead to the adoption of the EBHI, and (3) which may culminate in the EBHI’s
routinization or institutionalization by adopter organizations.26,27This analysis is concerned with
the latter phase of this process and seeks to explain the degree to which innovations become
embedded into organizational operations. And, as with other investigations of innovation
implementation, the EBHI implementation effort rather than the organization is the unit of
analysis for hypothesis testing.12,13,16,22,27,28
Conceptual and Methodological Issues
Implementation success: assimilation and fidelity
Business and healthcare scholars have identified numerous categories of outcome variables that
may be useful for gauging the success of organizations’ efforts to implement innovations.14,15,29,30
The category of indicators labeled by O’Connor and colleagues “measures of implementation,
integration, and institutionalization” is especially relevant to this study because it includes
variables which are useful for understanding the extent to which innovations have taken hold in the
organizations that adopt them.14(p74)For example, measures include: the degree of implementation
(e.g., the extent of use among intended users such as targeted staff); the extent of assimilation or
institutionalization (e.g., the degree to which the innovation is embedded in regular organizational
operations); integration (e.g., the extent to which the innovation is interconnected with other core
organizational processes and structures); fidelity of implementation (e.g., the extent to which the
innovation as deployed mirrors the innovation as designed); and the sustained or continued use of
innovations (e.g., duration of use; whether or not the innovation is still being used at a given point
in time). Fidelity of implementation and assimilation are the success measures most relevant to this
The assimilation of EBHIs into routine practice by the organizations targeted to adopt them is
essential to fully realizing the benefits these innovations have to offer. The idea that assimilation is
important to the success of public-sector program and practice innovations is not new. Over three
public organizations and ensuring that innovations endure under real-world circumstances,26concerns
that continue to be echoed by scholars interested in program sustainability.8,17–19,31,32Yin cautioned
researchers and policymakers against making premature judgments about the success of implemen-
tation efforts. He explained “…the implementation problem extends well beyond the adoption and
early use of innovations” and argued that assimilation is the ultimate indicator of implementation
success because the incorporation of innovations into routine operations reflects their true value to the
organizations that adopt them.26(p 383)
Since that time, organizational behavior13,16,33and healthcare1,17,32experts have continued to
view assimilation as essential to reaping the benefits of the investments made in developing EBHIs.
Assimilation is an important behavioral indicator of an organization’s commitment to an innovation
and of the likelihood that innovation implementation will endure for the foreseeable future. In
addition, full incorporation of an innovation into organizational operations theoretically signals the
“disappearance stage” of assimilation, the phase when innovations such as EBHIs presumably
become part of the status quo and, therefore, are no longer prime targets for elimination.27These
The Assimilation of Evidence-Based Healthcare InnovationsPANZANO et al.399
claims are less likely to apply to some of the other success measures noted above. For example,
“continued use” may not be a reliable predictor of the likelihood an innovation will endure because
continued use may hinge on the availability of external resources,34,35or be motivated by other
concerns (e.g., organizational image management).36As a result, the degree to which EBHIs are
assimilated into routine operations is the key implementation success measure used, and the major
dependent variable for this analysis.
An organization’s failure to achieve the intended benefits of an innovation may be a function of
implementation failure or a failure of the innovation itself.12The latter explanation, a failure of the
innovation itself, is less likely to apply to EBHIs and to other fixed innovations which are
supported by effectiveness research. In contrast, implementation failure is the more likely
explanation and, for EBHIs, it may take the form of inadequate fidelity. This is especially true for
service innovations such as EBHIs for which maintaining fidelity tends to be far more challenging
than it is for product innovations.15Consequently, fidelity is the second key measure of
implementation success used in this analysis, and it is expected to be linked to assimilation in
potentially interesting ways with regard to EBHIs. For example, fidelity may be a prime factor
considered in assessing the extent to which EBHI assimilation has occurred.
Factors affecting implementation success
Three important themes are apparent in the large, multidisciplinary body of research regarding
factors and processes that affect the success of organizations’ efforts to implement innovations.
First, implementation success is contingent on a multitude of factors, which span multiple levels of
analysis28,36,37from the individual level (e.g., attitudes, championship behavior),33,38to the
program level (e.g., implementation climate),12,29,39to the organization level (e.g., organization
size, slack resources),34,36,40and to the system-level (e.g., innovation policy).41–43Second,
implementation success begins with first events which often occur well before formal
implementation efforts get underway.13,16,17,22For example, success has been tied to the readiness
of organizations to deliver innovations;44,45to the ‘readiness’ of state systems40and broader
systems41to support the uptake of innovations; to attributes of innovation decision-making,
planning, and prioritization processes;16and, also to the tactics and strategies used by
organizational leaders to engage stakeholders and to build buy-in.13,42Third, as with other
strategic issues and decisions, top management makes a difference: the cognitions and actions of
members of organizations’ TMTs affect implementation success in pivotal ways.12–14,16,22,27,33
This third theme is prominent in the strategic decision-making and planning literatures, as well.13,22,23
This investigation is mostly concerned with the third theme: the role of top management. It
advances and provides a preliminary test of a management-based model of implementation success
which defines success in terms of fidelity and assimilation. The proposed framework is intended to
apply to organizations which adopt EBHIs or other fixed innovations under ordinary circum-
stances, rather than as part of a research or demonstration project.
Top management and implementation success
As stewards of organizations’ interests, CEOs and TMT members engage in ongoing processes
of interpreting strategic developments, making strategic decisions, and taking action in response to
a wide array of issues that have implications for organizational performance, such as issues
concerning organizational innovation, in general, and specific innovation initiatives, as well.23,46–49
With regard to the latter, senior managers’ strategic cognitions (SC) about specific innovation
initiatives are bound to affect the stances organizations take toward them and the actions,
responses, and outcomes that follow.22,23
400 The Journal of Behavioral Health Services & Research39:4 October 2012
Top management cognition and implementation success
Decisions regarding innovation are strategic decisions which typically are made by senior
organizational managers.12They are organizationally important, complex, non-routine, and
tend to be made in the face of ambiguous or incomplete information and in a context of risk and
uncertainty.50Examples of major decisions regarding innovation that warrant the attention of
senior management include: decisions to adopt,51disengage from,34,35sustain, or embed
innovations into routine practice.13,16,19,27,52
Theory and research from managerial and organizational cognition, and the innovation literature
about the risks involved with adopting EBHIs explained significant variability in EBHI adoption
decisions51just as top managers’ perceptions about risk have been useful for understanding
organizations’ responses to a host of other strategic issues.50,54,55Similarly, the SCs of CEOs about
the likelihood that particular innovations present opportunities versus threats to organizational interests
explained significant variability in the success of innovation implementation efforts measured years
later according to a recent longitudinal analysis.22This finding is consistent with research grounded in
the strategic issue diagnosis paradigm which examines linkages between how TMT members frame
important developments and issues in terms of widely studied categories and dimensions (e.g., threat
versus opportunity; gain versus loss)56,57and organizations’ responses to those issues.
Strategic cognitions regarding the fit or compatibility of particular innovations to organizational
priorities are likely to be important as well. In fact, an exploratory study of the de-adoption of
EBHIs revealed that TMT member cognitions about the extent to which EBHIs fit organizational
needs discriminated between organizations that sustained EBHIs and those that decided to de-
adopt them.34This finding is consistent with research which suggests compatible innovations are
more likely to be adopted, and to be easier to implement with success by organizational and
These findings support the idea that information about top manager cognitions is of value for
understanding implementation success. In other words, if innovation implementation is a process
that involves the use of strategies to adopt and integrate EBHIs and to change practice patterns
within specific settings,60the strategic cognitions of senior management are likely to affect this
process in noteworthy ways.
Top manager cognitions about the strategic fit of EBHIs are of central interest to this
investigation. Strategic fit is defined here as the extent to which the implementation of a particular
EBHI is compatible with organizational goals, interests, and/or values.
Top management action and implementation success
The actions taken by or under the direction of senior management also are expected to affect the
success of organizations’ effort to implement innovations in both the short29and long term.16TMT
member actions have both symbolic and instrumental value and can speak volumes about the extent to
which organizations prioritize and support specific innovations and efforts to implement them.29,41–45,52
However, innovation-specific support from top management must be consistent, strong and
visible in order to send an unequivocal message that a specific innovation is highly valued by the
organization, and in order to effectively facilitate efforts to implement particular innova-
tions.12,13,16,30,33,34Supportive actions that may be taken by TMT members, or by others with
top management support or approval, include but are not limited to: dedicating adequate resources
and setting policy to favor the implementation of specific innovations;29,44setting goals and
priorities that support the use of specific innovations;13,16implementing performance monitoring
systems, and establishing reward and reinforcement criteria that support effective use of particular
The Assimilation of Evidence-Based Healthcare Innovations PANZANO et al.401
innovations;52intervening to reduce obstacles to effective implementation;39serving as innovation
champions;22,27,33demonstrating a hands-on approach to innovation implementation efforts;30
demonstrating leadership behavior that fosters rather than dampens a spirit of innovation;12,13,38
and actively advocating for changes to be made in external systems in order to increase the
feasibility of implementing particular innovations.52
Actions such as those listed above have been consistently linked to the success of organizations’
effort to implement innovations, including EBHIs.16,20,27,29,39In theory, this is because these
actions are likely to foster a “climate for innovation implementation”12,39,61and lay the
groundwork for the implementation of particular innovations to be successful. In fact, Klein and
colleagues, who coined the term, define an organization’s climate for innovation implementation as
the extent to which the use of a specific innovation is perceived to be rewarded, supported, and
expected within a given organization.12Empirical evidence supporting the idea that climate for
implementation is key to implementation success is available from varied contexts such as
education,62healthcare,61manufacturing,29and mental health.39
However, views about climate strength may vary from employee to employee for a variety of
reasons. For example, views may vary if TMT actions in support of particular innovations are not
strong, consistent and visible. They may also vary as a result of the extent to which employees are
directly involved in delivering service innovations such as EBHIs. For instance, many EBHIs are
delivered by small teams of employees and climate perceptions of team members may be very
different from employees not directly involved with EBHI delivery.
This investigation is concerned with climate perceptions of individuals most involved with or
knowledgeable about the delivery of EBHIs, including top managers and EBHI implementation
leaders. Their perceptions are expected to provide the most meaningful indicators of climate for
innovationimplementationinthisresearchcontext because climate isexpectedtohavea visible impact
on the ease with which these individuals carry out their daily work. The majority of the EBHI
implementation efforts targeted for this analysis involve EBHIs delivered by a small team of
employees. The remaining efforts involve an EBHI which is delivered by individuals who are part of a
selectgroup.Inlight ofthese issues andinordertomaintainuniformityinsources ofinformationabout
climate across EBHI implementation effort, information to assess climate for innovation implemen-
tation will be sought from the TMT member most involved with the implementation effort and the
EBHI implementation manager. Climate information also will be sought from external EBHI
consultants, in cases in which consultants are both available and knowledgeable about EBHI
Cognition, action, and implementation success: the assimilation framework
Senior managers in organizations are agents of implementation success by virtue of what they
think and what they do. As with other strategic issues and developments, their cognitions
pertaining to organizational innovation, such as organizations’ efforts to implement particular
innovations, are important to consider because strategic cognitions are likely to influence
organizational actions and responses to innovations in noteworthy ways.23,27These ideas are
buttressed by empirical findings in the innovation literature, including recent long-term
investigations of implementation success,16,22and are reflected in the model guiding this
investigation which is shown in Figure 1.
The model in Figure 1 suggests cognitions about the strategic fit of an innovation to an
organization’s goals and interests will affect the strength of the climate for innovation
implementation that develops. Stronger fit is likely to yield stronger climates because innovations
that are well-suited to organizations’ interests are likely to be valued and prioritized. Thus, Figure 1
suggests that the effects of strategic fit on implementation success will work through the climate for
innovation implementation for a specific innovation. Climate is conceptualized to be a composite
402 The Journal of Behavioral Health Services & Research39:4 October 2012
construct which consists of several dimensions (e.g., dedicated resources: the extent to which resources
are earmarked to support a specific innovation implementation effort)39that contribute to the strength of
the climate in an additive way.12Stronger climates are expected to provide greater support for
organizations’ efforts to implement specific innovations and to result in more successful innovation
implementation efforts. Thus, the framework also suggests that a positive association will exist between
climate for innovation implementation and the two implementation success measures: fidelity and
assimilation of EBHIs, fidelity is expected to mediate the link between climate and assimilation.
The following five hypotheses capture these ideas, represented by Figure 1:
Hypothesis 1: Top management cognitions about the strategic fit of an EBHI will be positively
related to the strength of the climate for innovation implementation.
Hypothesis 2: Climate for innovation implementation will be positively related to fidelity of
Hypothesis 3: Fidelity of implementation will be positively related to assimilation.
Hypothesis 4: Climate for innovation implementation will mediate the effects of strategic fit on
fidelity of implementation.
Hypothesis 5: Implementation fidelity will mediate the effects of climate for innovation
implementation on assimilation.
Research context and larger study
This investigation utilizes data from a mixed-methods, naturalistic field study of the adoption,29
implementation,39and de-adoption34of four evidence-based and promising mental health practices
of EBHI with
Implementation success: Factors explaining the assimilation of evidence-based healthcare
The Assimilation of Evidence-Based Healthcare Innovations PANZANO et al.403
(EBHIs) conducted over a 7-year period from 2001 to 2008 in one state mental health system. The
EBHIs that were the focus of implementation efforts included two evidence-based, team-delivered
practices (i.e., multi-systemic therapy [MST])63and integrated dual disorder treatment [IDDT]);64
one promising, psychiatrist-delivered practice (i.e., the Ohio medication algorithms (OMA) based
on the Texas medication algorithm);65and one promising practice delivered by qualified clinicians
(e.g., Cluster-based Outcomes Management [CBOM]).66Thus, the delivery of focal EBHIs directly
involved only a limited number of employees within adopting organizations. Most often, EBHI
implementation efforts were carried out under the direction of a TMT member and an EBHI
implementation leader. In many cases, an external EBHI consultant assisted with some aspects of
EBHI implementation (e.g., fidelity monitoring).
Targeted EBHI implementation efforts
Just before the larger study (of which this investigation is part) got underway, statewide technical
assistance centers (i.e., Coordinating Centers of Excellence or CCOEs) received start-up funding
from the state mental health authority to market and educate behavioral healthcare organizations
(BHO) about these EBHIs and their benefits. However, decisions to contact CCOEs, contract for
CCOE services (e.g., training), and/or adopt EBHIs were left entirely up to BHOs.
BHOs that contacted CCOEs subsequently were approached about participating in the
larger observational field study of which this investigation is part. Participation was entirely
voluntary but 84 of the 89 initial contacts resulted in decisions to participate in the broader
study.25Approximately 60% or 50 of the 84 EBHI adoption decision processes that took
place resulted in a decision to adopt an EBHI.51An earlier analysis suggests, on average,
EBHI “adopters” saw the risks of adopting as lesser and more manageable than non-
adopters.51Those 50 EBHI adoption decision processes which resulted in a decision to adopt
subsequently proceeded with efforts to implement them.39These 50 cases were of potential
interest to this study of EBHI assimilation.
Prior to the start of this investigation, data for the larger study had been gathered over the course
of three rounds, separated from one another by approximately 2 years. Forty-four of the 50 EBHI
implementation efforts were still underway as of the third round of data gathering. Those 44 efforts
were targeted for participation in this investigation. Participation entailed taking part in a fourth
round of data-gathering, conducted roughly 2 years after round three.
For each of the 44 targeted EBHI implementation efforts, participation in telephone interviews
and surveys was sought from the TMT member or members (e.g., CEO/Agency Director; Chief
Clinical Office) most involved with the EBHI implementation effort and from the EBHI project
implementation manager. In other words, consistent with other innovation implementation studies
that are grounded in strategic cognition and/or planning paradigms,13,16,22two upper-level
management informants who were most knowledgeable and/or involved with a given EBHI
implementation effort typically were approached to participate in a fourth round of data gathering.
The three Coordinating Centers of Excellence (CCOE) associated with the 44 targeted EBHI
implementation efforts also were contacted to identify staff members most knowledgeable about
each EBHI implementation effort for potential participation in a brief, fourth-round survey. All
CCOEs were receptive and provided names and contact information for these individuals.
However, there were 8 EBHI implementation efforts (of the 44) for which no CCOE experts could
be identified due to limited contact or no recent contact between the CCOE and those 8 EBHI
implementation sites. As with the previous 3 rounds, participation in round 4 was voluntary and
confidentiality was guaranteed to all participants.
404 The Journal of Behavioral Health Services & Research39:4 October 2012
Archival data set
Table 1 provides an overview of the archival data set for the larger study from which data for this
analysis is drawn. Column headings indicate the round in which data were gathered and row
headings indicate the method used and source of those data. As noted in the footnotes to Table 1,
data gathered during rounds one, two, and three of the larger study have been used in other
analyses. To date, data from round four has been used only for this investigation.
As shown under the column labeled “4th Contact” in Table 1, information about all 44 targeted
EBHI implementation efforts was gathered during round four. Surveys were completed by 70
targeted BHO staff members and 34 targeted CCOE external consultants. Together, these surveys
addressed all 44 of the targeted EBHI implementation efforts. Those 44 efforts included: 27 (61%)
pertaining to IDDT, 7 (16%) pertaining to MST, and 10 (23 %) dealing with CPOM. No OMA
implementation efforts were targeted for participation in round four because there were no OMA
efforts still underway as of the third round of data-gathering.
Surveys and Measures
Multi-item measures included in round four BHO and CCOE surveys were adapted from
prior analyses34,39,51and were used to operationalize the concepts shown in Figure 1: strategic
fit, climate for innovation implementation, fidelity, and assimilation. The focal entity for all
relevant survey items was either the EBHI or the EBHI implementation effort.28Operational
measures for the four concepts made up a small portion of the items in the BHO versions of
the survey but nearly all of the items included in the CCOE version of the survey.
Focal EBHI efforts, and data sources reflected in the archival data set, by contact period
Data collection round
Focal EBHI effortsa
Total data sourcesf(average
data sources per effort)
845044 44 222e
1360 (6.1)594 (7.1)316 (6.3) 282 (6.4)168 (3.8)
aEBHI efforts represent EBHI adoption decision-making processes for the first contact period (n=84) and
EBHI implementation efforts for the second, third, and fourth contact periods
bSource of data for an earlier test of an adoption decision-making model51and an implementation framework39
cSource of data for an exploratory analysis of EBHI de-adoption16
dOrganization/BHO and Consultant/CCOE Survey data from contact period four are used for this investigation
eThis is a duplicated count of EBHI efforts; most EBHI efforts were represented in multiple rounds of data
fAdditional data regarding organizational and community characteristics were acquired from other archival
data sets to augment interview and survey data
The Assimilation of Evidence-Based Healthcare InnovationsPANZANO et al. 405
Versions of the survey
The CCOE version of the survey included far fewer items than the BHO versions because some
CCOE consultants were required to complete multiple surveys. This was because a single
individual often was identified as the most knowledgeable external consultant for several EPHI
implementation efforts. In an effort to minimize burden and increase the likelihood that external
consultants would complete multiple surveys, CCOE surveys were kept as brief as possible.
Information provided by CCOE staff was expected to provide important comparative data for the
The BHO surveys were designed to minimize burden as well, and to reduce concerns arising
from common method variance. A decision-maker version of the survey was designed to be
combined with an implementer version of the survey for each EBHI implementation effort. An
abbreviated version of the combined surveys also was developed to accommodate BHOs for which
only one knowledgeable informant was available to participate in the investigation.
Strategic fit was measured with eight items on the CCOE version of the survey and four items on
the BHO version. Respondents were asked to indicate the extent to which they agreed, on a seven-
point scale where 7 = “strongly agree” and 1 = “strongly disagree”, with statements such as: “EBHI
Name fits well with the mission and overall goals of this organization” and “EBHI Name is
compatible with the treatment philosophy at this organization”. A “Don’t Know” option also was
available. Higher scale scores indicate better strategic fit.
Climate for innovation implementation was measured with nine items on the CCOE version of
the survey and 25 items on the BHO version. Respondents were asked to indicate the extent to
which they agreed, on a seven-point scale where 7 = “strongly agree” and 1 = “strongly disagree”,
with statements such as: “Top administrators strongly support the implementation of EBHI Name at
this organization” and “Adequate resources are available for implementing EBHI Name”. A “Don’t
Know” option also was available. Higher scale scores indicate a stronger, more favorable climate.
Fidelity of implementation was measured with four items on both the CCOE and BHO versions
of the survey. Respondents were asked to indicate the extent to which they agreed on a seven-point
scale where 7 = “strongly agree” and 1 = “strongly disagree” with statements such as “EBHI Name
is being implemented at this organization as prescribed by experts” and “EBHI Name is being
implemented ‘to the letter’ as prescribed by its developers”. A “Don’t Know” option also was
available. Higher scale score indicate better fidelity.
Assimilation was measured with five items on the CCOE survey and four items on the BHO
survey. Respondents were asked to indicate the extent to which they agreed on a seven-point scale
where 7 = “strongly agree” and 1 = “strongly disagree” with statements such as “EBHI Name is
seen as a regular part of programming at this organization” and “EBHI Name will be part of the
way this organization does business for the foreseeable future”. A ‘Don’t Know” option also was
available. Higher scale scores indicate greater assimilation.
Participants and EBHI implementation efforts
A total of 104 surveys were completed by BHO management (n=70) and CCOE external
consultants (n=34). Combined, these surveys address all 44 implementation efforts. Seventy BHO
management informants involved with 35 (of the 44) implementation efforts completed round-four
surveys. The distribution of EBHIs represented by BHO surveys (i.e., 66% IDDT; 17% MST;
17% CBOM) parallels the distribution of the full group of 44 efforts reported above. On average,
406 The Journal of Behavioral Health Services & Research39:4 October 2012
two BHO surveys were completed per effort, most typically by the CEO and the EBHI project
manager. This rate of participation is typical of strategic decision-making studies, including studies
of innovation adoption and implementation.13,16,22
CCOE consultants completed surveys pertaining to 34 of the 44 EBHI implementation efforts.
As noted, knowledgeable external consultants were not available for 8 of the 44 efforts. The
distribution of EBHI efforts addressed by CCOE surveys (i.e., 50% IDDT; 21% MST; 29%
CBOM) is similar to that for the 44 efforts. Consultants were encouraged to respond “Don’t Know”
to survey items for which they lacked current knowledge.
There were only 25 EBHI implementation efforts for which both BHO and CCOE survey data
were available (i.e., ‘common EBHI efforts’). The EBHIs addressed by these common EBHI
efforts is similar to the full distribution (i.e., 52% IDDT; 24% MST; 24% CBOM).
As suggested in Table 2, the internal consistency reliability of the four scales based on CCOE
survey data as assessed with Cronbach’s alpha is quite strong, ranging from .81 to .90. Table 2 also
suggests there is substantial variability on scale scores from the 34 CCOE surveys. Mean scale
scores tend to be slightly above the seven-point scale midpoint (e.g., mean=4.6/7.0) and the range
of scores within scale is between 4.1 and 6.0 points.
As shown in Table 2, Cronbach alphas for scales based on BHO survey data are strong as well
and range from .80 to .91. Table 2 also indicates there is reasonable variability in response on the
four scales based on the 70 BHO surveys. Mean scale scores tend to be slightly above the seven-
point scale midpoint (i.e., 5.0/7.0), and the range of responses on each of the four scales also is
satisfactory (i.e., between 3.5 and 5.0 points).
Test of hypotheses
According to both CCOE and BHO informants, the vast majority of the 44 EBHI
implementation efforts targeted for this investigation were described as actively implementing
the focal EBHI as of round-four data gathering. Exceptions to this description were as follows: two
efforts were described as recent de-adopters of EBHIs, and one was described as a recent re-
adopter. Even so, all 44 efforts were included in hypothesis testing.
Simple bi-variate correlations were computed to test the first three study hypotheses which
predict positive associations between major linkages shown in Figure 1: the association between
strategic fit and climate for implementation (Hypothesis 1: H1); the association between climate for
implementation and fidelity (Hypothesis: H2); and the link between fidelity and assimilation
(Hypothesis 3: H3). Findings are displayed in Table 3.
As noted in Table 3, scale inter-correlations pertaining to BHO surveys are displayed above the
main diagonal; scale inter-correlations based on CCOE surveys are displayed below the main
diagonal, and scale inter-correlations pertaining to the 25 “common EBHI efforts” for which both
CCOE and BHO surveys were completed are shown on the main diagonal. In other words,
coefficients displayed on the main diagonal represent correlations between CCOE and BHO scores
on the same scale (e.g., r=.346, pG.05 is the correlation between strategic fit as assessed on the
CCOE survey and fit as assessed on the BHO survey).
Findings in Table 3 lend support for Hypotheses 1, 2, and 3. They suggest a positive relationship
exists between strategic fit and climate (H1); between climate and fidelity (H2); and between fidelity
and assimilation (H3). All three hypotheses were supported by data pertaining to the 35
implementation efforts assessed by BHO surveys (i.e., Pearson r ranges in value from .62 to .79,
pG.01), and by data pertaining to the 34 efforts assessed by CCOE surveys (i.e., Pearson r ranges
in value from .54 to .74, pG.01).
The Assimilation of Evidence-Based Healthcare InnovationsPANZANO et al. 407
The Pearson correlation coefficients shown on the main diagonal of Table 3 pertain to the 25
“common EBHI efforts.” They represent correlations between BHO informant ratings and CCOE
informant ratings for a given scale (e.g., strategic fit). Only two of the four coefficients based on the
25 common EBHI efforts were significant: strategic fit (r=.346, pG.05, n=25), and climate for
innovation implementation (r=.375, pG.05, n=25). Further, as shown in Table 4, the results of
paired T tests comparing scale score ratings between the CCOE and BHO surveys revealed that
BHO informants, on average, present a rosier view of strategic fit (paired T=6.78 (24), two-tailed
pG.01), climate (paired T=2.65 (24), two-tailed pG.01) and assimilation (paired T=2.65 (24), two-
tailed pG.01) compared to CCOE external consultants. Although not significant, this trend holds
for assessments about implementation fidelity as well.
Strategic fit, climate, fidelity, and assimilation scales: Scale reliability and scale descriptive statistics
Scale Sample items Sourcea
1. EBHI (name) fits well with the
mission and overall goals of
2. EBHI is compatible with the
treatment philosophy at the
1. Top administrators strongly
support the implementation of
EBHI at this organization.
2. Adequate resources are
available for implementing
1. EBHI is being implemented at
this organization as prescribed
2. EBHI is being implemented
‘to the letter’ as prescribed
by its developers.
1. EBHI is seen as a regular
part of programming at this
2. EBHI will be part of the
way this organization does
business for the foreseeable
8 .87 4.2/7 1.0/6.0
9 .87 5.1/7 1.0/4.1
25 .91 5.4/7.84/4.0
4 .90 4.6/71.5/4.7
4 .83 5.0/71.2/5.0
5 .815.0/7 1.5/5.0
4 .83 5.4/7 1.1/4.4
aCCOE survey information is based on data regarding 34 of the 44 targeted EBHI implementation efforts;
BHO survey information is based on data regarding 35 of the 44 targeted efforts
bAll survey items utilized a seven-point, Likert-type scale and response options ranged from “1” = strongly
disagree to “7” = strongly agree. A “Don’t Know” option also was available. Higher scale scores are more
positive (e.g., higher score on fidelity means better fidelity)
408The Journal of Behavioral Health Services & Research 39:4October 2012
Hypothesis 4 (H4) predicts that climate for implementation mediates the effects of strategic fit on
fidelity. Hypothesis 5 (H5) predicts that fidelity mediates the effects of climate for implementation
on assimilation. Overall mediation is tested for each hypothesis using Baron and Kenny’s67four-
step approach in which several regression analyses are conducted and significance of the
coefficients are examined in each step.
Tables 5 and 6 display results of the four-step regression approach used to test Hypothesis 4.
Table 5 displays results using data from organization/BHO surveys. Table 6 displays results using
data from CCOE surveys. Overall findings reported in these tables are quite similar and provide
Inter-correlations among fit, climate, fidelity and assimilation scale scores derived from
organization/BHO surveys and consultant/CCOE surveysa
ScaleFit ClimateFidelity Assimilation
aPearson product-moment correlation coefficients displayed above the main diagonal are based on BHO
survey data whereas coefficients displayed below the main diagonal are based on CCOE survey data.
Coefficients displayed on the main diagonal are correlations between CCOE and BHO scale scores for those
25 common EBHI efforts that were assessed on both the CCOE and BHO surveys
*pG.05, one-tailed; **pG.01, one-tailed
Paired-sample T tests between consultant/CCOE survey scale scores and organization/BHO survey
scale scores for twenty-five (25) EBHI implementation efforts assessed on both surveys
statistic (df )
Pair 1 Assimilation_BHO Survey
Strategic Fit_BHO Survey
Strategic Fit_CCOE Survey
Pair 3 2.653* (24)
Pair 46.780* (24)
The Assimilation of Evidence-Based Healthcare InnovationsPANZANO et al. 409
support for the notion that climate for implementation mediates the effects of strategic fit on
fidelity. However, regression results based on BHO survey data suggest full mediation (i.e., beta for
fit is no longer significant at step 4, Table 5) compared to results from CCOE survey data which
suggest partial mediation (i.e., beta for fit remains significant at Step 4, Table 6).
Tables 7 and 8 display results of Baron and Kenny’s four step regression approach used to test
Hypothesis 5. Table 7 displays results using data from organization/BHO surveys. Table 8 displays
results using data from CCOE surveys. Overall findings reported in these tables are quite similar
and provide support for the notion that fidelity mediates the effects of climate for implementation
on assimilation. Regression results for both analyses suggest that mediation is partial (i.e., beta for
climate remains significant at Step 4, Tables 7 and 8).
Organization1survey mediated regression: Does climate mediate the effect of strategic fit on fidelity?
6.8* 1,29 .19
41.7** 1,29 .55
1Organization/BHO survey data (N=31)
aNon-significant Beta suggests full mediation
Consultant1survey mediated regression: Does climate mediate the effect of strategic fit on fidelity?
1Consultant (CCOE) survey data (N=34)
aBeta for “Fit” suggests partial mediation
410 The Journal of Behavioral Health Services & Research39:4 October 2012
Scales used in the analysis were internally consistent and demonstrated reasonable variability
based on data from the BHO and CCOE surveys. For the BHO survey, average scale scores for the
strategic fit, climate, fidelity and assimilation scales tended to be slightly above the midpoint on a
seven-point scale (e.g., 5 = “somewhat agree” resources are adequate to support implementation).
In all cases, higher scale scores indicate more favorable ratings.
Scale scores based on the CCOE survey were a bit less rosy compared to scores from the BHO
survey. In fact, when considering data pertaining to the 25 common EBHI implementation efforts,
Organization1survey mediated regression: Does fidelity mediate the effect of climate on assimilation?
45.8** 2,28 .76
1Organization/BHO survey data (N=31)
aBeta for “Climate” suggests partial mediation
Consultant1survey mediated regression: Does fidelity mediate the effect of climate on assimilation?
1Consultant (CCOE) survey data (N=34)
aBeta for “Climate” suggests partial mediation
The Assimilation of Evidence-Based Healthcare Innovations PANZANO et al.411
BHO scale scores were significantly higher for three of the four scales. Although differences were
not significant, the trend also held for the fidelity scale.
Study findings also provide preliminary support for major hypotheses and the underlying
management-based model of implementation success. Data from both the CCOE and BHO surveys
revealed significant positive associations between strategic fit and climate (Hypothesis 1); between
climate and fidelity (Hypothesis); and between fidelity and assimilation (Hypothesis 3). In other
words, survey data from BHO top managers and EBHI program leaders, and survey data from
knowledgeable and involved CCOE external consultants suggest these concepts co-vary as
predicted. In addition, the similarity in the magnitude and patterns of bi-variate associations
between the two surveys is noteworthy.
Support was found for Hypotheses 4 and 5 which predicted mediation effects. More specifically,
Hypothesis 4, which predicted that climate for innovation implementation would mediate the
effects of strategic fit on fidelity, was supported by both BHO and CCOE survey data. Hypothesis
5, which predicted that fidelity of implementation would mediate the effects of climate for
implementation on assimilation, was supported by data from both surveys as well.
The investigation has many noteworthy and apparent weaknesses. The design is observational
and cross-sectional rather than experimental and longitudinal. Findings are correlational and little
can be said about causality. Findings may be more useful for generating questions than for testing
theory. Statistical power and variability is limited, small sample sizes raise questions about the
validity of findings pertaining to mediational analyses,68and operational measures of concepts are
not identical for the BHO and CCOE surveys. Common method variance is a concern, and
attributes of the context (e.g., a system with CCOEs) and of EBHIs (e.g., team-based) may limit the
generalizability of findings to other EBHIs and settings.
The investigation also has noteworthy strengths. The framework is theory-based and focuses on
understanding the assimilation of fixed innovations, such as EBHIs adopted under naturalistic
conditions. Assimilation is examined several years post-adoption, which provided time for EBHIs
to become embedded in organizational operations. Scale reliability is strong, methods are grounded
in the managerial and organization cognition literature, and perspectives of internal and external
subject matter experts are compared.
Implications for Behavioral Health
The issues of assimilation and sustainability as they pertain to evidence-based and promising
healthcare innovations (EBHI) will continue to gain momentum and currency in the public
healthcare sector as fiscal constraints drive policymakers to demand evidence about the likelihood
EBHIs will be adopted under naturalistic conditions by the organizations they are intended for, and
the likelihood EBHIs will become embedded in regular operations among organizations that
choose to adopt them. Healthcare experts contend that we don’t really know what becomes of
organizations’ efforts to implement healthcare innovations,1but there seems to be general
recognition that an “assimilation gap”69exists between rates of initial adoption and rates of
continued use. Clearly, a lot needs to be learned about the assimilation of EBHIs, so, it’s important
to seek-out real-world opportunities to gain insight about this important phenomenon.
This naturalistic case study was conducted with that spirit in mind. It focuses on key
management-related factors that account for variability in assimilation. At the outset of the larger
project of which this investigation is part, there was no intention to explore questions about factors
that explain the extent to which EBHIs get embedded into organizational operations among a group
of long-term implementers of EBHIs. In fact, there was no expectation that there would be long-
412 The Journal of Behavioral Health Services & Research39:4 October 2012
term implementers of EBHIs to study. The realization that a sizeable group of organizations was still
implementing EBHIs roughly 4-years post-adoption presented an unexpected opportunity to
begin to explore this question by implementing a fourth-round of data-gathering roughly 2 years later
(i.e., 6 years post-adoption). This investigation was designed to take advantage of that opportunity.
An important premise guiding the investigation is that members of organizations’ TMTs are
agents of EBHI assimilation by virtue of what they think and what they do. Yet, theory and
research from managerial and organizational cognition suggest it may be particularly important to
pay attention to what TMT members think because their cognitions are likely to significantly affect
the stances taken by organizations toward innovations and the actions and responses that follow.
Moreover, because innovation decisions (e.g., decisions to adopt, sustain, de-adopt and embed
innovations) are strategic decisions typically made by senior management, it’s imperative to
understand top managers views about the extent to which innovations fit with changing
organizational needs and priorities, and the extent to which efforts to implement particular
innovations are seen as viable and valuable to the organization. This information is likely to
provide important insights about the likelihood of assimilation.
Yet, findings also raise questions about whose point of view matters most when it comes to
understanding the assimilation of fixed innovations. As noted, this investigation assumes TMT
perceptions are pivotal because they are likely to drive organizational response and action. Even so,
it is important to examine the extent to which TMTs cognitions mesh with or are influenced by the
perceptions of others, such as external consultants and front-line EBHI implementers. In other
words, if TMT perceptions matter most, it’s essential to get a better understanding of the extent to
which strategic cognitions are shaped by social information.
Patterns of findings based on those 25 common EBHI efforts assessed on both the CCOE and
BHO surveys suggest knowledgeable informants may not see eye-to-eye on important matters
related to innovation assimilation, such as the extent to which climate for innovation implementation is
strong. Differences in perspectives may simply be a function of differences in exposure and access to
information. On the other hand, differences in perspectives may be a function of differences in the
frames of reference considered in arriving at ratings. For example, for those CCOE external
consultants who completed surveys about multiple EBHI implementation efforts, ratings provided
about a particular EBHI effort may have been made by drawing comparisons with the other EBHI
efforts to be rated. It’s important to understand the extent to which differences in frames of reference or
other factors account for why internal and external expert informants may not see eye-to-eye on the
progress and outcomes of particular EBHI implementation efforts.
The highly similar pattern of co-variation observed among major model variables (e.g.,
climate and fidelity) based on CCOE and BHO survey data raises a very intriguing question.
Do these findings represent true co-variation among study variables or the implicit models
held by top managers and external consultants about how these variables should be inter-
related in a rational world? The answer to this question has significant implications for the
management of innovation in real-world settings, and for the paradigms and methods used to
study implementation as well.
Finally, the study raises important questions about the nomological network surrounding
the concept of assimilation. While major model concepts are grounded in theory and
research, more thought needs to be given to the meaning of these concepts as they pertain to
assimilation. Are they antecedents, aspects or indicators of assimilation? For example, is a
strong climate for implementation an indication that an EBHI has become embedded in
organizational operations? Or, is a strong climate an antecedent to assimilation? Is fidelity a
prerequisite for assimilation to occur when it comes to EBHIs and other fixed innovations?
Does assimilation mean something different for fixed versus adaptive innovations?15These
are important conceptual questions with practical and scientific implications for policymakers,
practitioners and researchers to consider.
The Assimilation of Evidence-Based Healthcare InnovationsPANZANO et al.413
This research was funded by grant 1168 from the Ohio Department of Mental Health (ODMH)
and by grant 00-65717-HCD from the John D. and Catherine T. MacArthur Foundation Network
on Mental Health Policy Research. The authors gratefully acknowledge the leadership and support
of former ODMH Director Michael F. Hogan, former Chief of the ODMH Office of Program
Evaluation and Research, Dee Roth, and key contributions made by Dushka-Crane Ross and
Vandana Vaidyanathan, to the larger study of which this investigation is part. Finally, the authors are
also indebted to the Center for Evidence Based Practices and the Center of Innovative Practice at Case
Western Reserve University, Synthesis, Inc. and the many organizational participants in the research
who gave generously of their time over several years to make this project possible.
Conflicts of Interest The authors declare having no conflicts of interest.
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