Perceptions and values of care professionals are critical in successfully implementing technology in health care. The aim of this study was threefold: (1) to explore the main values of health care professionals, (2) to investigate the perceived influence of the technologies regarding these values, and (3) the accumulated views of care professionals with respect to the use of technology in the future. In total, 51 professionals were interviewed. Interpretative phenomenological analysis was applied. All care professionals highly valued being able to satisfy the needs of their care recipients. Mutual inter-collegial respect and appreciation of supervisors was also highly cherished. The opportunity to work in a careful manner was another important value. Conditions for the successful implementation of technology involved reliability of the technology at hand, training with team members in the practical use of new technology, and the availability of a help desk. Views regarding the future of health care were mainly related to financial cut backs and with a lower availability of staff. Interestingly, no spontaneous thoughts about the role of new technology were part of these views. It can be concluded that professionals need support in relating technological solutions to care recipients' needs. The role of health care organisations, including technological expertise, can be crucial here.
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Abstract: This case study examines the use of an eHealth application for improving preoperative rehabilitation (prehabilitation). We have analysed healthcare professionals' motivators and drivers for adopting eHealth for a surgical procedure at academic medical facilities. The research focused on when and why healthcare professionals are inclined to adopt eHealth applications in their way of working? For this qualitative study, we selected 12 professionals involved in all levels of the organisation and stages of the medical process and conducted semi-structured interviews. Kotter’s transformational change model and the Technology Acceptance Model were used as analytical frameworks for the identification of the motivation of eHealth adoption. The findings suggest that contrary to Kotter’s change model, which argues that adoption of change is based on perceptions and feelings, the healthcare drivers are rational when it comes to deciding whether or not to adopt eHealth apps. This study further elaborates the observation made by the Dutch expertise centre on eHealth, Nictiz, that when the value of an eHealth pplication is clear for a stakeholder, the adoption process accelerates. Analysis of the motivations and drivers of the healthcare professionals show a strong relationship with an evidence-based grounding of usefulness and the responsibility these professionals have towards their patients. We found that healthcare professionals respond to the primary goal of improving healthcare. This is true if the eHealth application will innovate their work, but mainly when the application will improve the patient care they are responsible for. When eHealth applications are implemented, rational facts need to be collected in a study before deployment of eHealth applications on how these applications will improve the patient's health or wellbeing throughout their so-called medical journey for their treatment. Furthermore, the preference to learn about new eHealth applications from someone who speaks from authority through expertise on the subject matter, suggests adoption by healthcare professionals may be accelerated through peers. The result of this study may provide healthcare management with a different approach to their eHealth strategy. Future research is needed to validate the findings in different medical organisational settings such as regional healthcare facilities or for-profit centers which do not necessarily have an innovation focus but are driven by other strategic drivers.
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Transitions in health care and the increasing pace at which technological innovations emerge, have led to new professional approach at the crossroads of health care and technology. In order to adequately deal with these transition processes and challenges before future professionals access the labour market, Fontys University of Applied Sciences is in a transition to combining education with interdisciplinary practice-based research. Fontys UAS is launching a new centre of expertise in Health Care and Technology, which is a new approach compared to existing educational structures. The new centre is presented as an example of how new initiatives in the field of education and research at the intersection of care and technology can be shaped.
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BackgroundThe world’s population is aging, and with aging population comes an increase of chronic diseases and multimorbidity. At the same time a shortfall of trained health care professionals is anticipated. This raises questions on how to provide the best possible care. The use of Information and communication technology (ICT) and e-health has the potential to address the challenges that healthcare is facing. ICT applications and e-health, such as videophones, telemedicine and mobile devices, can benefit the healthcare system. Nonetheless, ICT is not used to its full potential. One of the key factors is the low adoption rate by nursing professionals. The nursing profession is characterized by teamwork and interdisciplinary collaboration. Nurses often work in nursing teams and collaboration between different disciplines is necessary for providing health care. Thus, collaboration is necessary when implementing ICT innovations.MethodsA systematic literature review was conducted in online databases PubMEd, CINAHL and IEEE, using key words related to innovation, nursing teams and adoption.ResultsThe result of the systematic review is that little is known about the relation between ICT adoption by nurses and the nature of collaboration by nurses in teams and in interdisciplinary networks. This leads to further research questions and a need for further research in this subject.
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The aim of this review was to explore which factors influence nurses' adoption of information and communication technology. A systematic review was conducted using qualitative and quantitative studies. The authors performed the search strategy in the databases of PubMed, CINAHL, and IEEE and included articles published between January 2011 and July 2021. This review explores the following factors: collaboration, leadership, and individual and team factors—that, according to qualitative and quantitative research, seem to influence nurses' adoption of information and communication technology. A gradual implementation process of the information and communication technology, involvement from care professionals in the implementation process, and team functioning are important factors to consider when adopting information and communication technology. In addition to these, individual factors such as age, experience, attitude, and knowledge are also influencing factors. The review suggests that collaboration is important within the implementation of information and communication technology in care and that it positively influences nurses' adoption of it. Individual factors are researched more extensively than collaboration, leadership, and team factors. Although they also appear to influence the adoption of information and communication technology, there is insufficient evidence to convincingly substantiate this.
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Despite the promises of learning analytics and the existence of several learning analytics implementation frameworks, the large-scale adoption of learning analytics within higher educational institutions remains low. Extant frameworks either focus on a specific element of learning analytics implementation, for example, policy or privacy, or lack operationalization of the organizational capabilities necessary for successful deployment. Therefore, this literature review addresses the research question “What capabilities for the successful adoption of learning analytics can be identified in existing literature on big data analytics, business analytics, and learning analytics?” Our research is grounded in resource-based view theory and we extend the scope beyond the field of learning analytics and include capability frameworks for the more mature research fields of big data analytics and business analytics. This paper’s contribution is twofold: 1) it provides a literature review on known capabilities for big data analytics, business analytics, and learning analytics and 2) it introduces a capability model to support the implementation and uptake of learning analytics. During our study, we identified and analyzed 15 key studies. By synthesizing the results, we found 34 organizational capabilities important to the adoption of analytical activities within an institution and provide 461 ways to operationalize these capabilities. Five categories of capabilities can be distinguished – Data, Management, People, Technology, and Privacy & Ethics. Capabilities presently absent from existing learning analytics frameworks concern sourcing and integration, market, knowledge, training, automation, and connectivity. Based on the results of the review, we present the Learning Analytics Capability Model: a model that provides senior management and policymakers with concrete operationalizations to build the necessary capabilities for successful learning analytics adoption.
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Background: The transformation in global demography and the shortage of health care workers require innovation and efficiency in the field of health care. Digital technology can help improve the efficiency of health care. The Mercury Advance SMARTcare solution is an example of digital technology. The system is connected to a hybrid mattress and is able to detect patient movement, based on which the air pump either starts automatically or sends a notification to the app. Barriers to the adoption of the system are unknown, and it is unclear if the solution will be able to support health care workers in their work. Objective: This study aims to gain insight into health care workers’ expectations of factors that could either hamper or support the adoption of the Mercury Advance SMARTcare unit connected to a Mercury Advance mattress to help prevent patients from developing pressure injuries in hospitals and long-term care facilities. Methods: We conducted a generic qualitative study from February to December 2022. Interviews were conducted, and a focus group was established using an interview guide of health care workers from both the United Kingdom and the Netherlands. Thematic analysis was performed by 2 independent researchers. Results: A total of 14 participants took part in the study: 6 (43%) participants joined the focus group, and 8 (57%) participants took part in the individual interviews. We identified 13 factors based on four themes: (1) factors specifically related to SMARTresponse, (2) vision on innovation, (3) match with health care activities, and (4) materials and resources involved. Signaling function, SMARTresponse as prevention, patient category, representatives, and implementation strategy were identified as facilitators. Perception of patient repositioning, accessibility to pressure injury aids, and connectivity were identified as barriers. Conclusions: Several conditions must be met to enhance the adoption of the Mercury Advance SMARTcare solution, including the engagement of representatives during training and a reliable wireless network. The identified factors can be used to facilitate the implementation process. JMIR Nursing 2024;7:e47992
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Clinical decision support systems (CDSSs) have gained prominence in health care, aiding professionals in decision-making and improving patient outcomes. While physicians often use CDSSs for diagnosis and treatment optimization, nurses rely on these systems for tasks such as patient monitoring, prioritization, and care planning. In nursing practice, CDSSs can assist with timely detection of clinical deterioration, support infection control, and streamline care documentation. Despite their potential, the adoption and use of CDSSs by nurses face diverse challenges. Barriers such as alarm fatigue, limited usability, lack of integration with workflows, and insufficient training continue to undermine effective implementation. In contrast to the relatively extensive body of research on CDSS use by physicians, studies focusing on nurses remain limited, leaving a gap in understanding the unique facilitators and barriers they encounter. This study aimed to explore the facilitators and barriers influencing the adoption and use of CDSSs by nurses in hospitals, using an extended Fit Between Individuals, Tasks, and Technology (FITT) framework.
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Technology in general, and assistive technology in particular, is considered to be a promising opportunity to address the challenges of an aging population. Nevertheless, in health care, technology is not as widely used as could be expected. In this chapter, an overview is given of theories and models that help to understand this phenomenon. First, the design of (assistive) technologies will be addressed and the importance of human-centered design in the development of new assistive devices will be discussed. Also theories and models are addressed about technology acceptance in general. Specific attention will be given to technology acceptance in healthcare professionals, and the implementation of technology within healthcare organizations. The chapter will be based on the state of the art of scientific literature and will be illustrated with examples from our research in daily practice considering the different perspectives of involved stakeholders.
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In order to accept and implement technology in a successful manner, not only determinants (acceptance barriers or facilitators) related to individual persons, for instance, health care providers as well as health care recipients, are important. Also interpersonal relationships on the work floor as well as the readiness and support of the organization itself are involved in the process of uptake of innovations. The Normalization Process Theory explains how this can be understood. The Technology Adoption Readiness Scale (TARS), developed based on this theory, offers a tool to diagnose the opportunities and challenges in health care organizations with respect to the implementation of certain technology- or eHealth applications. In order to guide the process of large scale implementation of technological innovations, also a pre implementation diagnosis is useful. This diagnosis, when provided by a “neutral party” has proved to be helpful for monitoring, guiding and thus supporting the implementation process of technological innovations in health care settings.
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