1. |
- Karnehed, Sara, 1979-, et al.
(author)
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Kan samproduktion av framtidens teknik bidra till en hållbar arbetsmiljö för sjuksköterskor?
- 2023
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Conference paper (peer-reviewed)abstract
- Svensk primärvård står inför stora utmaningar med en åldrande befolkning och ett ökat antal personer som vårdas i hemmet (Landers et al., 2016). Digital teknik implementeras med förhoppning om att förbättra kommunikationen mellan vårdpersonal och underlätta möjligheterna till egenvård och tillgänglighet för patienter (Socialstyrelsen, 2021). Tidigare studier visar att användningen av digital teknik kan förändra det professionella landskapet (Petersson, 2020) och påverka arbetsmiljö och arbetets innehåll (Ertner, 2019). Trots att teknik som implementeras inom vården bör vara anpassad till hälso- och sjukvårdspersonalens arbete och värderingar (Palmer et al., 2019; Reed et al., 2019) är sjuksköterskor sällan involverade i beslut kring utformning eller implementering av ny teknik (von Gerich et al., 2022). Det behövs mer kunskap om hur digitaliseringen kan ske i samproduktion med sjuksköterskor och utformas så att en god arbetsmiljö bibehålls.Presentationen syftar till att beskriva sjuksköterskors arbete och arbetsmiljö inom hemsjukvården och hur dessa kunskaper kan användas vid utvecklingen och implementeringen av framtida digital teknik.Individuella semi-strukturerade intervjuer har genomförts med 20 sjuksköterskor som arbetar på vårdcentral och inom hemsjukvård i två halländska kommuner. Intervjuerna har analyserats genom kvalitativ innehållsanalys (Hsieh & Shannon, 2005). Implementeringsteoretiska ramverk används för att undersöka hur kunskapen kan inkorporeras vid innovation och implementering av digitala tekniker inom vårdverksamheter (Nilsen, 2015).Preliminära resultat kommer att presenteras vid konferensen.ReferenserErtner, S. M. (2019). Enchanting, evoking, and affecting: the invisible work of technology implementation in homecare. Nordic Journal of Working Life Studies, 9(S5), 33-47.Hsieh, H.-F., & Shannon, S. E. (2005). Three Approaches to Qualitative Content Analysis. Qualitative health research, 15(9), 1277-1288.Landers, S., Madigan, E., Leff, B., Rosati, R. J., McCann, B. A., Hornbake, R., MacMillan, R., Jones, K., Bowles, K., Dowding, D., Lee, T., Moorhead, T., Rodriguez, S., & Breese, E. (2016). The Future of Home Health Care: A Strategic Framework for Optimizing Value. Home Health Care Management & Practice, 28(4), 262-278.Nilsen, P. (2015). Making sense of implementation theories, models and frameworks. Implementation science : IS, 10(1), 53-53.Palmer, V. J., Weavell, W., Callander, R., Piper, D., Richard, L., Maher, L., Boyd, H., Herrman, H., Furler, J., & Gunn, J. (2019). The Participatory Zeitgeist: an explanatory theoretical model of change in an era of coproduction and codesign in healthcare improvement. Medical humanities, 45(3), 247-257.Petersson, L. (2020). Paving the way for transparency: How eHealth technology can change boundaries in healthcare Lund University].Reed, J. E., Howe, C., Doyle, C., & Bell, D. (2019). Successful healthcare improvements from translating evidence in complex systems (SHIFT-Evidence): simple rules to guide practice and research. International journal for quality in health care, 31(3), 238-244.Socialstyrelsen. (2021). E-hälsa och välfärdsteknik i kommunerna 2021. Uppföljning av den digitala utvecklingen i socialtjänsten och den kommunala hälso-och sjukvården.von Gerich, H., Moen, H., Block, L. J., Chu, C. H., DeForest, H., Hobensack, M., Michalowski, M., Mitchell, J., Nibber, R., & Olalia, M. A. (2022). Artificial Intelligence-based technologies in nursing: A scoping literature review of the evidence. International Journal of Nursing Studies, 127, 104153.
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2. |
- Hagberg, Johan, 1973, et al.
(author)
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Konsumtionsrapporten 2024
- 2024
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Reports (other academic/artistic)abstract
- I Konsumtionsrapporten 2024 sammanfattas och analyseras konsumtionen i Sverige under 2023. I den första delen, ”Hushållens konsumtion” ges en översikt över den privata konsumtionen i Sverige och hur den förändrats. Här beskrivs även hållbarhetsaspekter på konsumtionen samt hushållens framtidsförväntningar på den egna ekonomin. I andra delen, ”Detaljhandeln” beskrivs försäljning och utveckling inom detaljhandeln under 2023 med fokus på olika delbranscher, kanaler och platser, inom e-handeln respektive den butiksbaserade detaljhandeln. Den andra delen avslutas med handelns framtidsförväntningar. Årets Konsumtionsrapport innehåller två fördjupningsdelar som var en och analyserar aktuella teman inom konsumtion. I den första av fördjupningsdelarna diskuterar Magdalena Petersson McIntyre och Emma Björner lyxkonsumtionens utveckling, status, hållbarhet och moral. I den andra fördjupningsdelen belyser Karin M. Ekström kulturkonsumtion med fokus på konstutställningar.
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3. |
- Hansson, Lena, 1968, et al.
(author)
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Design, gender and competitiveness
- 2009
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In: I: John Bryson and Grete Rusten (eds.) Industrial Design and Competitiveness: Spatial and Organizational Dimensions. - : Palgrave Macmillan. - 9780230203495 ; , s. 169-194
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Book chapter (other academic/artistic)
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4. |
- Karnehed, Sara, 1979-, et al.
(author)
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Developers' beliefs and values – a discursive analysis of e-health technology in home healthcare
- 2023
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Conference paper (peer-reviewed)abstract
- BackgroundThe implementation of e-health is transforming healthcare. The acknowledged benefits of digitalization are quality improvement, patient empowerment, and increased efficiency. The mobility of e-health makes it especially suitable for home healthcare. eMar is a common e-health technology used in Swedish home healthcare. Decisions about technology design are governed by developers’ perceptions of intended users. These perceptions can be identified in the description and promotion of a specific product.PurposeThe purpose of the presentation is to contribute to increased knowledge about the values entailed in a specific eMar used in Swedish home healthcare, and furthermore to discuss how these values conform with existing national missions such as people-centered care.MethodInformation consisting of sales materials about a specific eMar used in several Swedish municipalities has been analyzed through critical discourse analysis to visualize values embedded in the eMar.FindingsPreliminary results show that the provider of the specific eMar describes care in terms borrowed from the industrial sector, such as shift changes and production of care. Good and safe care is defined as the right person receiving the right medicine at the right time. Furthermore, the app is advertised as a tool for monitoring assuming that the performance of tasks can be influenced through the remote control of the employee. The eMar is described as representing new and modern technologies that are expected to raise the status of healthcare professions and facilitate the recruitment of employees.
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5. |
- Karnehed, Sara, 1979-, et al.
(author)
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Digital technologies in home healthcare – implications for job demands, job control, and support among healthcare professionals
- 2022
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In: Abstract Book of the 7th International Triennial Conference on Healthcare Systems Ergonomics and Patient Safety (HEPS) 2022. - Delft : Delft University of Technology. - 9789463666237 ; , s. 165-167
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Conference paper (peer-reviewed)abstract
- Increased use of digital technologies in healthcare offers healthcare professionals multiple ways to perform tasks and interact with patients and colleagues. We used the JDCS model to identify employee´s well-being in relation to the use of an eMar. The analysis indicated that the specific technology influenced the work environment for registered nurses and nursing assistants in different ways.
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6. |
- Karnehed, Sara, 1979-, et al.
(author)
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Electronic medication administration record (eMAR) in Swedish home healthcare—Implications for Nurses' and nurse Assistants' Work environment : A qualitative study
- 2024
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In: Scandinavian Journal of Caring Sciences. - Chichester : John Wiley & Sons. - 0283-9318 .- 1471-6712. ; 38:2, s. 347-357
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Journal article (peer-reviewed)abstract
- Background: The electronic medication administration record (eMAR) is an eHealth system that has replaced the traditional paper-based medication administration used in many healthcare settings. Research has highlighted that eHealth technologies can change working methods and professional roles in both expected and unexpected ways. To date, there is sparse research that has explored how nurses and nurse assistants (NA) in home healthcare experience eMAR in relation to their work environment. Aim: The aim was to explore how nurses and nurse assistants experienced their work environment, in terms of job-demand, control, and support in a Swedish home healthcare setting where an electronic medication administration record had been implemented to facilitate delegation of medical administration. Method: We took a qualitative approach, where focus groups were used as data collection method. The focus groups included 16 nurses and nine NAs employed in a Swedish municipality where an eMAR had been implemented 6 months before the first focus groups were performed. The analysis adapted the job-demand-control-support model, by condensing the professionals' experiences into the three categories of demand, control, and support, in alignment with the model. Results: NAs experienced high levels of job demand and low levels of job control. The use of the eMAR limited NAs' ability to control their work, in terms of priorities, content, and timing. In contrast, the nurses described demands as high but manageable, and described having a high level of control. Both professions found the eMar supportive. Conclusion: Nurses and NAs in home healthcare experienced changes in their work environment regarding demand, control, and support when an eMAR was implemented to facilitate delegation of medical administration. In general, nurses were satisfied with the eMAR. However, NAs felt that the eMAR did not cover all aspects of their daily work. Healthcare organisations should be aware of the changes that digitalisation processes entail in the work environment of nurses and NAs in home healthcare. © 2024 The Authors. Scandinavian Journal of Caring Sciences published by John Wiley & Sons Ltd on behalf of Nordic College of Caring Science.
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8. |
- Neher, Margit, 1959-, et al.
(author)
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Innovation in healthcare : leadership perceptions about the innovation characteristics of artificial intelligence—a qualitative interview study with healthcare leaders in Sweden
- 2023
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In: Implementation Science Communications. - London : BioMed Central (BMC). - 2662-2211. ; 4
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Journal article (peer-reviewed)abstract
- Background: Despite the extensive hopes and expectations for value creation resulting from the implementation of artificial intelligence (AI) applications in healthcare, research has predominantly been technology-centric rather than focused on the many changes that are required in clinical practice for the technology to be successfully implemented. The importance of leaders in the successful implementation of innovations in healthcare is well recognised, yet their perspectives on the specific innovation characteristics of AI are still unknown. The aim of this study was therefore to explore the perceptions of leaders in healthcare concerning the innovation characteristics of AI intended to be implemented into their organisation.Methods: The study had a deductive qualitative design, using constructs from the innovation domain in the Consolidated Framework for Implementation Research (CFIR). Interviews were conducted with 26 leaders in healthcare.Results: Participants perceived that AI could provide relative advantages when it came to care management, supporting clinical decisions, and the early detection of disease and risk of disease. The development of AI in the organisation itself was perceived as the main current innovation source. The evidence base behind AI technology was questioned, in relation to its transparency, potential quality improvement, and safety risks. Although the participants acknowledged AI to be superior to human action in terms of effectiveness and precision in some situations, they also expressed uncertainty about the adaptability and trialability of AI. Complexities such as the characteristics of the technology, the lack of conceptual consensus about AI, and the need for a variety of implementation strategies to accomplish transformative change in practice were identified, as were uncertainties about the costs involved in AI implementation.Conclusion: Healthcare leaders not only saw potential in the technology and its use in practice, but also felt that AI’s opacity limits its evidence strength and that complexities in relation to AI itself and its implementation influence its current use in healthcare practice. More research is needed based on actual experiences using AI applications in real-world situations and their impact on clinical practice. New theories, models, and frameworks may need to be developed to meet challenges related to the implementation of AI in healthcare. © 2023, The Author(s).
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9. |
- Nilsen, Per, 1960-, et al.
(author)
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A Framework to Guide Implementation of AI in Health Care : Protocol for a Cocreation Research Project
- 2023
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In: JMIR Research Protocols. - Toronto : JMIR Publications. - 1929-0748. ; 12
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Journal article (peer-reviewed)abstract
- Background: Artificial intelligence (AI) has the potential in health care to transform patient care and administrative processes, yet health care has been slow to adopt AI due to many types of barriers. Implementation science has shown the importance of structured implementation processes to overcome implementation barriers. However, there is a lack of knowledge and tools to guide such processes when implementing AI-based applications in health care.Objective: The aim of this protocol is to describe the development, testing, and evaluation of a framework, “Artificial Intelligence-Quality Implementation Framework” (AI-QIF), intended to guide decisions and activities related to the implementation of various AI-based applications in health care.Methods: The paper outlines the development of an AI implementation framework for broad use in health care based on the Quality Implementation Framework (QIF). QIF is a process model developed in implementation science. The model guides the user to consider implementation-related issues in a step-by-step design and plan and perform activities that support implementation. This framework was chosen for its adaptability, usability, broad scope, and detailed guidance concerning important activities and considerations for successful implementation. The development will proceed in 5 phases with primarily qualitative methods being used. The process starts with phase I, in which an AI-adapted version of QIF is created (AI-QIF). Phase II will produce a digital mockup of the AI-QIF. Phase III will involve the development of a prototype of the AI-QIF with an intuitive user interface. Phase IV is dedicated to usability testing of the prototype in health care environments. Phase V will focus on evaluating the usability and effectiveness of the AI-QIF. Cocreation is a guiding principle for the project and is an important aspect in 4 of the 5 development phases. The cocreation process will enable the use of both on research-based and practice-based knowledge.Results: The project is being conducted within the frame of a larger research program, with the overall objective of developing theoretically and empirically informed frameworks to support AI implementation in routine health care. The program was launched in 2021 and has carried out numerous research activities. The development of AI-QIF as a tool to guide the implementation of AI-based applications in health care will draw on knowledge and experience acquired from these activities. The framework is being developed over 2 years, from January 2023 to December 2024. It is under continuous development and refinement.Conclusions: The development of the AI implementation framework, AI-QIF, described in this study protocol aims to facilitate the implementation of AI-based applications in health care based on the premise that implementation processes benefit from being well-prepared and structured. The framework will be coproduced to enhance its relevance, validity, usefulness, and potential value for application in practice. © 2023 The Author(s).
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10. |
- Petersson, Lena, 1968-, et al.
(author)
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Challenges to implementing artificial intelligence in healthcare : a qualitative interview study with healthcare leaders in Sweden
- 2022
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In: BMC Health Services Research. - London : BioMed Central (BMC). - 1472-6963. ; 22
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Journal article (peer-reviewed)abstract
- 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. © The Author(s) 2022.
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