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      Towards a measurement instrument for determinants of innovations

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          Abstract

          Objective

          To develop a short instrument to measure determinants of innovations that may affect its implementation.

          Design

          We pooled the original data from eight empirical studies of the implementation of evidence-based innovations. The studies used a list of 60 potentially relevant determinants based on a systematic review of empirical studies and a Delphi study among implementation experts. Each study used similar methods to measure both the implementation of the innovation and determinants. Missing values in the final data set were replaced by plausible values using multiple imputation. We assessed which determinants predicted completeness of use of the innovation (% of recommendations applied). In addition, 22 implementation experts were consulted about the results and about implications for designing a short instrument.

          Setting

          Eight innovations introduced in Preventive Child Health Care or schools in the Netherlands.

          Participants

          Doctors, nurses, doctor's assistants and teachers; 1977 respondents in total.

          Results

          The initial list of 60 determinants could be reduced to 29. Twenty-one determinants were based on the pooled analysis of the eight studies, seven on the theoretical expectations of the experts consulted and one new determinant was added on the basis of the experts' practical experience.

          Conclusions

          The instrument is promising and should be further validated. We invite researchers to use and explore the instrument in multiple settings. The instrument describes how each determinant should preferably be measured (questions and response scales). It can be used both before and after the introduction of an innovation to gain an understanding of the critical change objectives.

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          Most cited references18

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          A comparison of inclusive and restrictive strategies in modern missing data procedures.

          Two classes of modern missing data procedures, maximum likelihood (ML) and multiple imputation (MI), tend to yield similar results when implemented in comparable ways. In either approach, it is possible to include auxiliary variables solely for the purpose of improving the missing data procedure. A simulation was presented to assess the potential costs and benefits of a restrictive strategy, which makes minimal use of auxiliary variables, versus an inclusive strategy, which makes liberal use of such variables. The simulation showed that the inclusive strategy is to be greatly preferred. With an inclusive strategy not only is there a reduced chance of inadvertently omitting an important cause of missingness, there is also the possibility of noticeable gains in terms of increased efficiency and reduced bias, with only minor costs. As implemented in currently available software, the ML approach tends to encourage the use of a restrictive strategy, whereas the MI approach makes it relatively simple to use an inclusive strategy.
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            Diffusion of Innovations.

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              Toward evidence-based quality improvement. Evidence (and its limitations) of the effectiveness of guideline dissemination and implementation strategies 1966-1998.

              To determine effectiveness and costs of different guideline dissemination and implementation strategies. MEDLINE (1966 to 1998), HEALTHSTAR (1975 to 1998), Cochrane Controlled Trial Register (4th edn 1998), EMBASE (1980 to 1998), SIGLE (1980 to 1988), and the specialized register of the Cochrane Effective Practice and Organisation of Care group. Randomized-controlled trials, controlled clinical trials, controlled before and after studies, and interrupted time series evaluating guideline dissemination and implementation strategies targeting medically qualified health care professionals that reported objective measures of provider behavior and/or patient outcome. Two reviewers independently abstracted data on the methodologic quality of the studies, characteristics of study setting, participants, targeted behaviors, and interventions. We derived single estimates of dichotomous process variables (e.g., proportion of patients receiving appropriate treatment) for each study comparison and reported the median and range of effect sizes observed by study group and other quality criteria. We included 309 comparisons derived from 235 studies. The overall quality of the studies was poor. Seventy-three percent of comparisons evaluated multifaceted interventions. Overall, the majority of comparisons (86.6%) observed improvements in care; for example, the median absolute improvement in performance across interventions ranged from 14.1% in 14 cluster-randomized comparisons of reminders, 8.1% in 4 cluster-randomized comparisons of dissemination of educational materials, 7.0% in 5 cluster-randomized comparisons of audit and feedback, and 6.0% in 13 cluster-randomized comparisons of multifaceted interventions involving educational outreach. We found no relationship between the number of components and the effects of multifaceted interventions. Only 29.4% of comparisons reported any economic data. Current guideline dissemination and implementation strategies can lead to improvements in care within the context of rigorous evaluative studies. However, there is an imperfect evidence base to support decisions about which guideline dissemination and implementation strategies are likely to be efficient under different circumstances. Decision makers need to use considerable judgment about how best to use the limited resources they have for quality improvement activities.
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                Author and article information

                Journal
                Int J Qual Health Care
                Int J Qual Health Care
                intqhc
                intqhc
                International Journal for Quality in Health Care
                Oxford University Press
                1353-4505
                1464-3677
                October 2014
                20 June 2014
                20 June 2014
                : 26
                : 5
                : 501-510
                Affiliations
                [1 ]TNO , PO Box 2215, 2301 CE Leiden, TheNetherlands
                [2 ]FSS, University of Utrecht , Utrecht, TheNetherlands
                Author notes
                Address reprint requests to: Margot Fleuren, TNO, PO Box 2215, 2301 CE Leiden, The Netherlands. Tel: +31-88-866-6276; Fax: +31-88-866-0613, E-mail: margot.fleuren@ 123456tno.nl
                Article
                mzu060
                10.1093/intqhc/mzu060
                4195468
                24951511
                0e72bec4-317b-42f9-a52a-ca8b78b0741d
                © The Author 2014. Published by Oxford University Press in association with the International Society for Quality in Health Care

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence ( http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 15 May 2014
                Categories
                Papers

                Medicine
                implementation,preventive child healthcare,school-based health promotion
                Medicine
                implementation, preventive child healthcare, school-based health promotion

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