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      SERIES: eHealth in primary care. Part 4: Addressing the challenges of implementation

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          Abstract

          Background

          The implementation of eHealth applications in primary care remains challenging. Enhancing knowledge and awareness of implementation determinants is critical to build evidence-based implementation strategies and optimise uptake and sustainability.

          Objectives

          We consider how evidence-based implementation strategies can be built to support eHealth implementation.

          Discussion

          What implementation strategies to consider depends on (potential) barriers and facilitators to eHealth implementation in a given situation. Therefore, we first discuss key barriers and facilitators following the five domains of the Consolidated Framework for Implementation Research (CFIR). Cost is identified as a critical barrier to eHealth implementation. Privacy, security problems, and a lack of recognised standards for eHealth applications also hinder implementation. Engagement of key stakeholders in the implementation process, planning the implementation of the intervention, and the availability of training and support are important facilitators. To support care professionals and researchers, we provide a stepwise approach to develop and apply evidence-based implementation strategies for eHealth in primary care. It includes the following steps: (1) specify the eHealth application, (2) define problem, (3) specify desired implementation behaviour, and (4) choose and (5) evaluate the implementation strategy. To improve the fit of the implementation strategy with the setting, the stepwise approach considers the phase of the implementation process and the specific context.

          Conclusion

          Applying an approach, as provided here, may help to improve the implementation of eHealth applications in primary care.

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          Most cited references24

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          Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science

          Background Many interventions found to be effective in health services research studies fail to translate into meaningful patient care outcomes across multiple contexts. Health services researchers recognize the need to evaluate not only summative outcomes but also formative outcomes to assess the extent to which implementation is effective in a specific setting, prolongs sustainability, and promotes dissemination into other settings. Many implementation theories have been published to help promote effective implementation. However, they overlap considerably in the constructs included in individual theories, and a comparison of theories reveals that each is missing important constructs included in other theories. In addition, terminology and definitions are not consistent across theories. We describe the Consolidated Framework For Implementation Research (CFIR) that offers an overarching typology to promote implementation theory development and verification about what works where and why across multiple contexts. Methods We used a snowball sampling approach to identify published theories that were evaluated to identify constructs based on strength of conceptual or empirical support for influence on implementation, consistency in definitions, alignment with our own findings, and potential for measurement. We combined constructs across published theories that had different labels but were redundant or overlapping in definition, and we parsed apart constructs that conflated underlying concepts. Results The CFIR is composed of five major domains: intervention characteristics, outer setting, inner setting, characteristics of the individuals involved, and the process of implementation. Eight constructs were identified related to the intervention (e.g., evidence strength and quality), four constructs were identified related to outer setting (e.g., patient needs and resources), 12 constructs were identified related to inner setting (e.g., culture, leadership engagement), five constructs were identified related to individual characteristics, and eight constructs were identified related to process (e.g., plan, evaluate, and reflect). We present explicit definitions for each construct. Conclusion The CFIR provides a pragmatic structure for approaching complex, interacting, multi-level, and transient states of constructs in the real world by embracing, consolidating, and unifying key constructs from published implementation theories. It can be used to guide formative evaluations and build the implementation knowledge base across multiple studies and settings.
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            A refined compilation of implementation strategies: results from the Expert Recommendations for Implementing Change (ERIC) project

            Background Identifying, developing, and testing implementation strategies are important goals of implementation science. However, these efforts have been complicated by the use of inconsistent language and inadequate descriptions of implementation strategies in the literature. The Expert Recommendations for Implementing Change (ERIC) study aimed to refine a published compilation of implementation strategy terms and definitions by systematically gathering input from a wide range of stakeholders with expertise in implementation science and clinical practice. Methods Purposive sampling was used to recruit a panel of experts in implementation and clinical practice who engaged in three rounds of a modified Delphi process to generate consensus on implementation strategies and definitions. The first and second rounds involved Web-based surveys soliciting comments on implementation strategy terms and definitions. After each round, iterative refinements were made based upon participant feedback. The third round involved a live polling and consensus process via a Web-based platform and conference call. Results Participants identified substantial concerns with 31% of the terms and/or definitions and suggested five additional strategies. Seventy-five percent of definitions from the originally published compilation of strategies were retained after voting. Ultimately, the expert panel reached consensus on a final compilation of 73 implementation strategies. Conclusions This research advances the field by improving the conceptual clarity, relevance, and comprehensiveness of implementation strategies that can be used in isolation or combination in implementation research and practice. Future phases of ERIC will focus on developing conceptually distinct categories of strategies as well as ratings for each strategy’s importance and feasibility. Next, the expert panel will recommend multifaceted strategies for hypothetical yet real-world scenarios that vary by sites’ endorsement of evidence-based programs and practices and the strength of contextual supports that surround the effort. Electronic supplementary material The online version of this article (doi:10.1186/s13012-015-0209-1) contains supplementary material, which is available to authorized users.
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              Beyond Adoption: A New Framework for Theorizing and Evaluating Nonadoption, Abandonment, and Challenges to the Scale-Up, Spread, and Sustainability of Health and Care Technologies

              Background Many promising technological innovations in health and social care are characterized by nonadoption or abandonment by individuals or by failed attempts to scale up locally, spread distantly, or sustain the innovation long term at the organization or system level. Objective Our objective was to produce an evidence-based, theory-informed, and pragmatic framework to help predict and evaluate the success of a technology-supported health or social care program. Methods The study had 2 parallel components: (1) secondary research (hermeneutic systematic review) to identify key domains, and (2) empirical case studies of technology implementation to explore, test, and refine these domains. We studied 6 technology-supported programs—video outpatient consultations, global positioning system tracking for cognitive impairment, pendant alarm services, remote biomarker monitoring for heart failure, care organizing software, and integrated case management via data sharing—using longitudinal ethnography and action research for up to 3 years across more than 20 organizations. Data were collected at micro level (individual technology users), meso level (organizational processes and systems), and macro level (national policy and wider context). Analysis and synthesis was aided by sociotechnically informed theories of individual, organizational, and system change. The draft framework was shared with colleagues who were introducing or evaluating other technology-supported health or care programs and refined in response to feedback. Results The literature review identified 28 previous technology implementation frameworks, of which 14 had taken a dynamic systems approach (including 2 integrative reviews of previous work). Our empirical dataset consisted of over 400 hours of ethnographic observation, 165 semistructured interviews, and 200 documents. The final nonadoption, abandonment, scale-up, spread, and sustainability (NASSS) framework included questions in 7 domains: the condition or illness, the technology, the value proposition, the adopter system (comprising professional staff, patient, and lay caregivers), the organization(s), the wider (institutional and societal) context, and the interaction and mutual adaptation between all these domains over time. Our empirical case studies raised a variety of challenges across all 7 domains, each classified as simple (straightforward, predictable, few components), complicated (multiple interacting components or issues), or complex (dynamic, unpredictable, not easily disaggregated into constituent components). Programs characterized by complicatedness proved difficult but not impossible to implement. Those characterized by complexity in multiple NASSS domains rarely, if ever, became mainstreamed. The framework showed promise when applied (both prospectively and retrospectively) to other programs. Conclusions Subject to further empirical testing, NASSS could be applied across a range of technological innovations in health and social care. It has several potential uses: (1) to inform the design of a new technology; (2) to identify technological solutions that (perhaps despite policy or industry enthusiasm) have a limited chance of achieving large-scale, sustained adoption; (3) to plan the implementation, scale-up, or rollout of a technology program; and (4) to explain and learn from program failures.
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                Author and article information

                Journal
                Eur J Gen Pract
                Eur J Gen Pract
                The European Journal of General Practice
                Taylor & Francis
                1381-4788
                1751-1402
                7 October 2020
                2020
                : 26
                : 1
                : 140-145
                Affiliations
                [a ]Department of Public Health and Primary Care, Leiden University Medical Centre , Leiden, the Netherlands
                [b ]National eHealth Living Lab (NeLL) , Leiden, the Netherlands
                [c ]Section of Clinical Psychology, Institute of Psychology, Faculty of Social and Behavioural Sciences, Leiden University , Leiden, the Netherlands
                [d ]Usher Institute, University of Edinburgh , Edinburgh, UK
                [e ]Center for Behavioral Intervention Technologies, Department of Preventive Medicine, Northwestern University , Chicago, IL, USA
                [f ]Institute of Global Health Innovation, Imperial College London , London, UK
                [g ]Center for Health Technology and Services Research (CINTESIS)/Department of Community Medicine, Health Information and Decision (MEDCIDS), Faculty of Medicine, University of Porto , Porto, Portugal
                Author notes
                [*]

                These authors contributed equally.

                Supplemental data for this article is available online at here .

                CONTACT Anke Versluis A.Versluis@ 123456lumc.nl Department of Public Health and Primary Care, Leiden University Medical Center , Hippocratespad 21, Postzone V0-P, PO Box 9600, RC Leiden, 2300, The Netherlands
                Author information
                https://orcid.org/0000-0002-9489-7925
                https://orcid.org/0000-0002-7871-5888
                https://orcid.org/0000-0003-2051-4183
                https://orcid.org/0000-0002-5976-8386
                https://orcid.org/0000-0002-3184-6338
                https://orcid.org/0000-0002-7107-7211
                https://orcid.org/0000-0002-8607-9199
                https://orcid.org/0000-0002-8638-4978
                Article
                1826431
                10.1080/13814788.2020.1826431
                7580793
                33025820
                9d2e7774-a41d-4a3d-812f-9a5bd7f39b92
                © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Page count
                Figures: 2, Tables: 1, Pages: 6, Words: 3104
                Categories
                Research Article
                Opinion Paper

                Medicine
                ehealth,primary care,implementation,barriers,facilitators
                Medicine
                ehealth, primary care, implementation, barriers, facilitators

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