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There are no measures of clear goals and priorities and high-quality data capture. We constructed our own items to represent these constructs. Similarly, no tools were available to capture system readiness for innovation. Many of these constructs are not easily assessed in simple survey items and were therefore included in the interview. System readiness for innovation includes tension for change, innovation-system fit, power balances support versus advocacy , assessment of implications, dedicated time and resources e.


We were only able to locate one relevant measure of tension for change[ 91 ], a rating system developed through interviews with organizational experts to identify factors that influence health system change. Unfortunately, the authors did not provide the specific items utilized, and thus we captured the tension for change in the interview by asking providers about their existing work climate and the perceived need for new treatments.

The constructs of innovation-system fit, power balances, assessment of implications, dedicated time and resources, and monitoring and feedback also did not have standardized measures and thus we devised our own questions. Outer context constructs include socio-political climate, incentives and mandates, interorganizational norm-setting and networks, and environmental stability. There are no standard tools to assess these domains. There are limited measures of sociopolitical climate[ 8 ].

Because there were no identified existing measures for incentives and mandates, secondary data sources were used, such as a review of national mandates in provider handbooks from VA Central Office and discussions with one of the co-authors JR , who is in charge of one of the national evidence-based roll-outs. Likewise for interorganizational norm setting and networks, the team devised items to assess these constructs because no reliable existing measures were available. Environmental stability was derived from interview questions asking if staffing changes had occurred and perceived reasons for changes e.

This construct clearly overlaps with inner context e. Thus, our group devised survey items and interview questions and used administrative data to represent outer context constructs. While organizational written policies and procedures are likely accessible to most researchers, changes in budgets and funding may not be, particularly for researchers studying implementation from outside an organization.

When possible, this type of information should be sought to support the understanding of outer context. Consistent with Greenhalgh et al. Decision-making was assessed through questions regarding decentralization described above. Because there are no established measures to assess hands-on approach by leader, or human resources issues and dedicated resources, these were developed by group consensus.

For internal communication, we asked a question in the interview about whether a provider sought consultation from someone inside their setting regarding the innovation and its implementation. For external collaboration, we also asked a specific question regarding outside formal consultation.

Because no formal measure for feedback existed, we utilized interview questions from monitoring feedback to capture both constructs. Even though Greenhalgh et al. Despite numerous strengths of the model, there had been no explicit recommendations for operational definitions or measurement for most of the six identified constructs. Through a systematic literature review of measures for associated constructs and an iterative process of team consensus, our group has taken a first step at operationalizing, and thus testing this model.

We are presently using a mixed-method approach of measurement using quantitative data through survey and administrative data and qualitative data through semi-structured interviews and other artifacts e. Information from that study should provide knowledge to assist in the refinement of the measures, such as examination of psychometric properties and identifying changes needed to better operationalize the constructs.

It will be essential, of course, to test the Greenhalgh et al. Given the challenge to operationalize such a saturated model, this work should be considered a first step in the advancement of a testable theory.

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A contextual approach should be taken to strategically determine which constructs are most applicable to the individual study or evaluation. Also, a more in-depth examination of several constructs may be a needed next step. Some variables potentially important in the process of implementation are not addressed in the Greenhalgh model.

For example, there are several adopter characteristics and social cognition constructs that are not included e. Further, in times of increasing fiscal constraint, it is important to note that the model does not consider cost of the innovation itself or costs associated with its implementation, including investment, supply, and opportunity costs as opposed to available resources from the inner setting [ 7 ].

Other constructs receive mention in the model but likely warrant further refinement and elaboration. For example, while several constructs are similar to organizational culture and climate, concurrent use of other measurement tools may be warranted e. Similarly, the concept of leadership received only minimal attention in the Greenhalgh model, even though mental health researchers[ 10 ] have found this construct to be influential in implementation.

Because the validity of the transtheoretical stages of change model has been questioned[ 95 ], alternatives may be needed to capture this important construct. Other constructs are complicated by overlap e. One example is feedback on progress, which is listed under the domain implementation process, but the very similar construct monitoring and feedback is listed under the domain system readiness for innovation.

Likewise, social networks are captured under both adopter and communication and influence domains. Our measurement process attempted to streamline questioning both in the survey and interview by crafting questions to account for redundancy in constructs e. We also chose not to include every construct and sub-construct in the model because their assessment would be burdensome for providers.

Like most measures based on participant responses, our survey and interview may be influenced by intentional false reporting, inattentive responding or memory limitations, or participant fatigue. It is possible that our search terms may not have identified all the relevant measures. In addition, searching for the specific construct labels from this model assumes that there is consensus in the research community about the meaning of these terms and that no other terms are ever used to label these constructs. Of course, operationalizing constructs is only one aspect of making a model testable.

It also requires information about construct validity, a clear statement of the proposed relationships between elements in the model that would inform an analysis strategy, and a transparent articulation about the generalizability of the model and which contexts or factors might limit its applicability. In sum, our work here represents a significant step toward measuring Greenhalgh et al. This conceptual and measurement development now provides for a more explicit, transparent, and testable theory. Despite limitations, the survey and interview measures as well as our use of administrative data described here can enhance research on implementation by providing investigators with a broad measurement tool that includes, in a single questionnaire and interview, most of the many factors affecting implementation that are included in the Greenhalgh model and other overarching theoretical formulations.

Empirical grounding of the process of implementation remains a work in progress. Milbank Quart. Rogers EM: Diffusion of innovations.

Conducting a Systematic Literature Review

J Prim Prev. Am J Com Psychol. Implement Sci.

Diffusion of innovations in service organizations: systematic review and recommendations.

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Measurement of a model of implementation for health care: toward a testable theory

Dec Sci. Dec Supp Syst. Vishwanath A, Goldhaber GM: An examination of the factors contributing to adoption decisions among late-diffused technology products. New Media Soc. Health Pol Plan. J Nursing Admin. Blancquaert I: Managing partnerships and impact on decision-making: the example of health technology assessment in genetics. Community Genet. Cyber Psychol Behav. Davis F: Perceived usefulness, perceived ease of use and user acceptance of technology.

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    Qual Saf Health Care. Download references. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Mental Health or the National Institutes of Health. Correspondence to Joan M Cook. JMC, CO and SD conducted a systematic review of articles for possible inclusion and identification of key measurement constructs captured. All authors contributed to the drafting, editing and final approval of the manuscript. This article is published under license to BioMed Central Ltd.

    Reprints and Permissions. Search all BMC articles Search. Abstract Background Greenhalgh et al. Results The review and iterative process of team consensus identified three types of data that can been used to operationalize the constructs in the model: survey items, interview questions, and administrative data. Conclusion Despite limitations, the mixed-methods approach to measurement using the survey, interview measure, and administrative data can facilitate research on implementation by providing investigators with a measurement tool that captures most of the constructs identified by the Greenhalgh model.

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