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Background The relevance of context in implementation science is reflected in the numerous theories, frameworks, models and taxonomies that have been proposed to analyse determinants of implementation (in this paper referred to as determinant frameworks). This scoping review aimed to investigate and map how determinant frameworks used in implementation science were developed, what terms are used for contextual determinants for implementation, how the context is conceptualized, and which context dimensions that can be discerned. Methods A scoping review was conducted. MEDLINE and EMBASE were searched from inception to October 2017, and supplemented with implementation science text books and known published overviews. Publications in English that described a determinant framework (theory, model, taxonomy or checklist), of which context was one determinant, were eligible. Screening and inclusion were done in duplicate. Extracted data were analysed to address the study aims. A qualitative content analysis with an inductive approach was carried out concerning the development and core context dimensions of the frameworks. The review is reported according to the PRISMA guidelines. Results The database searches yielded a total of 1113 publications, of which 67 were considered potentially relevant based on the predetermined eligibility criteria, and retrieved in full text. Seventeen unique determinant frameworks were identified and included. Most were developed based on the literature and/or the developers’ implementation experiences. Six of the frameworks explicitly referred to “context”, but only four frameworks provided a specific definition of the concept. Instead, context was defined indirectly by description of various categories and sub-categories that together made up the context. Twelve context dimensions were identified, pertaining to different aggregation levels. The most widely addressed context dimensions were organizational support, financial resources, social relations and support, and leadership. Conclusions The findings suggest variation with regard to how the frameworks were developed and considerable inconsistency in terms used for contextual determinants, how context is conceptualized, and which contextual determinants are accounted for in frameworks used in implementation science. Common context dimensions were identified, which can facilitate research that incorporates a theory of context, i.e. assumptions about how different dimensions may influence each other and affect implementation outcomes. A thoughtful application of the concept and a more consistent terminology would enhance transparency, simplify communication among researchers, and facilitate comparison across studies.

Background Health care organizations are constantly changing as a result of technological advancements, ageing populations, changing disease patterns, new discoveries for the treatment of diseases and political reforms and policy initiatives. Changes can be challenging because they contradict humans’ basic need for a stable environment. The present study poses the question: what characterizes successful organizational changes in health care? The aim was to investigate the characteristics of changes of relevance for the work of health care professionals that they deemed successful. Methods The study was based on semi-structured interviews with 30 health care professionals: 11 physicians, 12 registered nurses and seven assistant nurses employed in the Swedish health care system. An inductive approach was applied using questions based on the existing literature on organizational change and change responses. The questions concerned the interviewees’ experiences and perceptions of any changes that they considered to have affected their work, regardless of whether these changes were “objectively” large or small changes. The interviewees’ responses were analysed using directed content analysis. Results The analysis yielded three categories concerning characteristics of successful changes: having the opportunity to influence the change; being prepared for the change; valuing the change. The interviewees emphasized the importance of having the opportunity to influence the organizational changes that are implemented. Changes that were initiated by the professionals themselves were considered the easiest and were rarely resisted. Changes that were clearly communicated to allow for preparation increased the chances for success. The interviewees did not support organizational changes that were perceived to be implemented unexpectedly and/or without prior communication. They conveyed that it was important for them to understand the need for and benefits of organizational changes. They particularly valued and perceived as successful organizational changes with a patient focus, with clear benefits to patients. Conclusions Organizational changes in health care are more likely to succeed when health care professionals have the opportunity to influence the change, feel prepared for the change and recognize the value of the change, including perceiving the benefit of the change for patients.

Background Artificial intelligence (AI) for healthcare presents potential solutions to some of the challenges faced by health systems around the world. However, it is well established in implementation and innovation research that novel technologies are often resisted by healthcare leaders, which contributes to their slow and variable uptake. Although research on various stakeholders’ perspectives on AI implementation has been undertaken, very few studies have investigated leaders’ perspectives on the issue of AI implementation in healthcare. It is essential to understand the perspectives of healthcare leaders, because they have a key role in the implementation process of new technologies in healthcare. The aim of this study was to explore challenges perceived by leaders in a regional Swedish healthcare setting concerning the implementation of AI in healthcare. Methods The study takes an explorative qualitative approach. Individual, semi-structured interviews were conducted from October 2020 to May 2021 with 26 healthcare leaders. The analysis was performed using qualitative content analysis, with an inductive approach. Results The analysis yielded three categories, representing three types of challenge perceived to be linked with the implementation of AI in healthcare: 1) Conditions external to the healthcare system; 2) Capacity for strategic change management; 3) Transformation of healthcare professions and healthcare practice. Conclusions In conclusion, healthcare leaders highlighted several implementation challenges in relation to AI within and beyond the healthcare system in general and their organisations in particular. The challenges comprised conditions external to the healthcare system, internal capacity for strategic change management, along with transformation of healthcare professions and healthcare practice. The results point to the need to develop implementation strategies across healthcare organisations to address challenges to AI-specific capacity building. Laws and policies are needed to regulate the design and execution of effective AI implementation strategies. There is a need to invest time and resources in implementation processes, with collaboration across healthcare, county councils, and industry partnerships.

Background A proliferation of theories, models, and frameworks (TMFs) have been developed in the implementation science field to facilitate the implementation process. The basic features of these TMFs have been identified by several reviews. However, systematic appraisals on the quality of these TMFs are inadequate. To fill this gap, this study aimed to assess the usability, applicability, and testability of the current TMFs in a structured way. Methods A scoping review method was employed. Electronic databases were searched to locate English and Chinese articles published between January 2000 and April 2022. Search terms were specific to implementation science. Additionally, hand searches were administered to identify articles from related reviews. Purpose and characteristics such as the type of TMF, analytical level, and observation unit were extracted. Structured appraisal criteria were adapted from Birken et al.’s Theory Comparison and Selection Tool (T-CaST) to conduct an in-depth analysis of the TMFs’ usability, applicability, and testability. Results A total of 143 TMFs were included in this analysis. Among them, the most common purpose was to identify barriers and facilitators. Most TMFs applied the descriptive method to summarize the included constructs or the prescriptive method to propose courses of implementation actions. TMFs were mainly mid-range theories built on existing conceptual frameworks or demonstrated grand theories. The usability of the TMFs needs to be improved in terms of the provision of conceptually matched strategies to barriers and facilitators and instructions on the TMFs usage. Regarding the applicability, little attention was paid to the constructs of macro-level context, stages of scale-up and sustainability, and implementation outcomes like feasibility, cost, and penetration. Also, fewer TMFs could propose recommended research and measurement methods to apply the TMFs. Lastly, explicit hypotheses or propositions were lacking in most of the TMFs, and empirical evidence was lacking to support the claimed mechanisms between framework elements in testability. Conclusions Common limitations were found in the usability, application, and testability of the current TMFs. The findings of this review could provide insights for developers of TMFs for future theoretical advancements.

Background The use of low-value care (LVC) is a persistent problem that calls for knowledge about strategies for de-implementation. However, studies are dispersed across many clinical fields, and there is no overview of strategies that can be used to support the de-implementation of LVC. The extent to which strategies used for implementation are also used in de-implementing LVC is unknown. The aim of this scoping review is to (1) identify strategies for the de-implementation of LVC described in the scientific literature and (2) compare de-implementation strategies to implementation strategies as specified in the Expert Recommendation for Implementing Change (ERIC) and strategies added by Perry et al. Method A scoping review was conducted according to recommendations outlined by Arksey and O’Malley. Four scientific databases were searched, relevant articles were snowball searched, and the journal Implementation Science was searched manually for peer-reviewed journal articles in English. Articles were included if they were empirical studies of strategies designed to reduce the use of LVC. Two reviewers conducted all abstract and full-text reviews, and conflicting decisions were discussed until consensus was reached. Data were charted using a piloted data-charting form. The strategies were first coded inductively and then mapped onto the ERIC compilation of implementation strategies. Results The scoping review identified a total of 71 unique de-implementation strategies described in the literature. Of these, 62 strategies could be mapped onto ERIC strategies, and four strategies onto one added category. Half (50%) of the 73 ERIC implementation strategies were used for de-implementation purposes. Five identified de-implementation strategies could not be mapped onto any of the existing strategies in ERIC. Conclusions Similar strategies are used for de-implementation and implementation. However, only a half of the implementation strategies included in the ERIC compilation were represented in the de-implementation studies, which may imply that some strategies are being underused or that they are not applicable for de-implementation purposes. The strategies assess and redesign workflow (a strategy previously suggested to be added to ERIC), accountability tool, and communication tool (unique new strategies for de-implementation) could complement the existing ERIC compilation when used for de-implementation purposes.

Background Implementation of evidence-based practices in health care implies change. Understanding health care professionals’ change responses may be critical for facilitating implementation to achieve an evidence-based practice in the rapidly changing health care environment. The aim of this study was to investigate health care professionals’ responses to organizational and workplace changes that have affected their work. Methods We conducted interviews with 30 health care professionals (physicians, registered nurses and assistant nurses) employed in the Swedish health care system. An inductive approach was applied, using a semi-structured interview guide developed by the authors. We used an analytical framework first published in 1999 to analyze the informants’ change responses in which change responses are perceived as a continuum ranging from a strong acceptance of change to strong resistance to change, describing seven forms of change responses along this continuum. Change response is conceptualized as a tridimensional attitude composed of three components: cognitive, affective and intentional/behavioral. Results Analysis of the data yielded 10 types of change responses, which could be mapped onto 5 of the 7 change response categories in the framework. Participants did not report change responses that corresponded with the two most extreme forms of responses in the framework, i.e., commitment and aggressive resistance. Most of the change responses were classified as either indifference or passive resistance to changes. Involvement in or support for changes occurred when the health care professionals initiated the changes themselves or when the changes featured their active input and when changes were seen as well founded and well communicated. We did not identify any change responses that could not be fitted into the framework. Conclusions We found the framework to be useful for a nuanced understanding of how people respond to changes. This knowledge of change responses is useful for the management of changes and for efforts to achieve more successful implementation of evidence-based practices in health care.

Background Recent reviews of the use and application of implementation frameworks in implementation efforts highlight the limited use of frameworks, despite the value in doing so. As such, this article aims to provide recommendations to enhance the application of implementation frameworks, for implementation researchers, intermediaries, and practitioners. Discussion Ideally, an implementation framework, or multiple frameworks should be used prior to and throughout an implementation effort. This includes both in implementation science research studies and in real-world implementation projects. To guide this application, outlined are ten recommendations for using implementation frameworks across the implementation process. The recommendations have been written in the rough chronological order of an implementation effort; however, we understand these may vary depending on the project or context: (1) select a suitable framework(s), (2) establish and maintain community stakeholder engagement and partnerships, (3) define issue and develop research or evaluation questions and hypotheses, (4) develop an implementation mechanistic process model or logic model, (5) select research and evaluation methods (6) determine implementation factors/determinants, (7) select and tailor, or develop, implementation strategy(s), (8) specify implementation outcomes and evaluate implementation, (9) use a framework(s) at micro level to conduct and tailor implementation, and (10) write the proposal and report. Ideally, a framework(s) would be applied to each of the recommendations. For this article, we begin by discussing each recommendation within the context of frameworks broadly, followed by specific examples using the Exploration, Preparation, Implementation, Sustainment (EPIS) framework. Summary The use of conceptual and theoretical frameworks provides a foundation from which generalizable implementation knowledge can be advanced. On the contrary, superficial use of frameworks hinders being able to use, learn from, and work sequentially to progress the field. Following the provided ten recommendations, we hope to assist researchers, intermediaries, and practitioners to improve the use of implementation science frameworks.

Background Implementation science in health is an interdisciplinary field with an emphasis on supporting behavior change required when clinicians and other actors implement evidence-based practices within organizational constraints. Behavioral economics has emerged in parallel and works towards developing realistic models of how humans behave and categorizes a wide range of features of choices that can influence behavior. We argue that implementation science can be enhanced by the incorporation of approaches from behavioral economics. Main body First, we provide a general overview of implementation science and ways in which implementation science has been limited to date. Second, we review principles of behavioral economics and describe how concepts from BE have been successfully applied to healthcare including nudges deployed in the electronic health record. For example, de-implementation of low-value prescribing has been supported by changing the default in the electronic health record. We then describe what a behavioral economics lens offers to existing implementation science theories, models and frameworks, including rich and realistic models of human behavior, additional research methods such as pre-mortems and behavioral design, and low-cost and scalable implementation strategies. We argue that insights from behavioral economics can guide the design of implementation strategies and the interpretation of implementation studies. Key objections to incorporating behavioral economics are addressed, including concerns about sustainment and at what level the strategies work. Conclusion Scholars should consider augmenting implementation science theories, models, and frameworks with relevant insights from behavioral economics. By drawing on these additional insights, implementation scientists have the potential to boost efforts to expand the provision and availability of high quality care.

ObjectiveThe aim of this study was to explore how the COVID-19 pandemic changed the working conditions of physicians in Swedish primary healthcare.DesignThis is a descriptive, qualitative study with individual semistructured interviews. Data were analysed using inductive content analysis.SettingSwedish primary healthcare units in both rural and urban areas.ParticipantsA total of 11 primary care physicians fulfilled participation.ResultsTwo main categories emerged: ‘work organisation and routines’ and ‘psychosocial work environment’, containing three and five subcategories, respectively. The pandemic enforced changes in work organisation and routines. Increased flexibility, including more patient-oriented delivery of care, and novel means of interorganisational and intraorganisational interactions were perceived as positive by physicians. The pandemic also caused several changes in physicians’ psychosocial work environment. Increased workload, information overload, as well as ethical considerations and feelings of uncertainty made the work environment stressful for physicians.ConclusionsThe COVID-19 pandemic affected the working conditions of physicians in Swedish primary healthcare in numerous ways. The pandemic enforced changes in work organisation and routines for physicians in primary healthcare. Further research is needed to investigate how the pandemic will affect primary healthcare in the longer term. Learning from the pandemic is important because this will not be the last crisis that primary care and its healthcare professionals will face.

Background Social cognitive theories on behaviour change are increasingly being used to understand and predict healthcare professionals’ intentions and clinical behaviours. Although these theories offer important insights into how new behaviours are initiated, they provide an incomplete account of how changes in clinical practice occur by failing to consider the role of cue-contingent habits. This article contributes to better understanding of the role of habits in clinical practice and how improved effectiveness of behavioural strategies in implementation research might be achieved. Discussion Habit is behaviour that has been repeated until it has become more or less automatic, enacted without purposeful thinking, largely without any sense of awareness. The process of forming habits occurs through a gradual shift in cognitive control from intentional to automatic processes. As behaviour is repeated in the same context, the control of behaviour gradually shifts from being internally guided ( e.g. , beliefs, attitudes, and intention) to being triggered by situational or contextual cues. Much clinical practice occurs in stable healthcare contexts and can be assumed to be habitual. Empirical findings in various fields suggest that behaviours that are repeated in constant contexts are difficult to change. Hence, interventions that focus on changing the context that maintains those habits have a greater probability of success. Some sort of contextual disturbance provides a window of opportunity in which a behaviour is more likely to be deliberately considered. Forming desired habits requires behaviour to be carried out repeatedly in the presence of the same contextual cues. Summary Social cognitive theories provide insight into how humans analytically process information and carefully plan actions, but their utility is more limited when it comes to explaining repeated behaviours that do not require such an ongoing contemplative decisional process. However, despite a growing interest in applying behavioural theory in interventions to change clinical practice, the potential importance of habit has not been explored in implementation research.