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Nilsen, P., Svedberg, P., Neher, M., Nair, M., Larsson, I., Petersson, L. & Nygren, J. M. (2023). A Framework to Guide Implementation of AI in Health Care: Protocol for a Cocreation Research Project. JMIR Research Protocols, 12, Article ID e50216.
Open this publication in new window or tab >>A Framework to Guide Implementation of AI in Health Care: Protocol for a Cocreation Research Project
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2023 (English)In: JMIR Research Protocols, E-ISSN 1929-0748, Vol. 12, article id e50216Article in journal (Refereed) Published
Abstract [en]

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).

Place, publisher, year, edition, pages
Toronto: JMIR Publications, 2023
Keywords
artificial intelligence, AI, health care, implementation, process models, frameworks, framework, process model
National Category
Health Care Service and Management, Health Policy and Services and Health Economy
Research subject
Health Innovation, IDC
Identifiers
urn:nbn:se:hh:diva-52291 (URN)10.2196/50216 (DOI)001115572400003 ()37938896 (PubMedID)2-s2.0-85178219393 (Scopus ID)
Funder
Knowledge FoundationVinnova
Available from: 2023-12-22 Created: 2023-12-22 Last updated: 2024-01-17Bibliographically approved
Engdahl, P., Svedberg, P., Lexén, A., Tjörnstrand, C., Strid, C. & Bejerholm, U. (2023). Co-design Process of a Digital Return-to-Work Solution for People with Common Mental Disorders: Stakeholder Perception Study. JMIR Formative Research, 7, 1-15, Article ID e39422.
Open this publication in new window or tab >>Co-design Process of a Digital Return-to-Work Solution for People with Common Mental Disorders: Stakeholder Perception Study
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2023 (English)In: JMIR Formative Research, E-ISSN 2561-326X, Vol. 7, p. 1-15, article id e39422Article in journal (Refereed) Published
Abstract [en]

Background: Service users and other stakeholders have had few opportunities to influence the design of their mental health and return-to-work services. Likewise, digital solutions often fail to align with stakeholders’ needs and preferences, negatively impacting their utility. mWorks is a co-design initiative to create a digital return-to-work solution for persons with common mental disorders that is acceptable and engaging for those receiving and delivering the intervention. Objective: This study aimed to describe stakeholder perceptions and the involvement of a design process during the prototype development of mWorks. Methods: A co-design approach was used during the iterative development of mWorks. Overall, 86 stakeholders were recruited using a combination of purposeful and convenience sampling. Five stakeholder groups represented service users with experience of sick leave and common mental disorders (n=25), return-to-work professionals (n=19), employers (n=1), digital design and system developers (n=4), and members of the public (n=37). Multiple data sources were gathered using 7 iterations, from March 2018 to November 2020. The rich material was organized and analyzed using content analysis to generate themes and categories that represented this study’s findings. Results: The themes revealed the importance of mWorks in empowering service users with a personal digital support solution that engages them back in work. The categories highlighted that mWorks needs to be a self-management tool that enables service users to self-manage as a supplement to traditional return-to-work services. It was also important that content features helped to reshape a positive self-narrative, with a focus on service users’ strengths and resources to break the downward spiral of ill health during sick leave. Additional crucial features included helping service users mobilize their own strategies to cope with thoughts and feelings and formulate goals and a plan for their work return. Once testing of the alpha and beta prototypes began, user engagement became the main focus for greater usability. It is critical to facilitate the comprehension and purpose of mWorks, offer clear guidance, and enhance motivational and goal-setting strategies. Conclusions: Stakeholders’ experience-based knowledge asserted that mWorks needs to empower service users by providing them with a personal support tool. To enhance return-to-work prospects, users must be engaged in a meaningful manner while focusing on their strengths and resources. ©Patrik Engdahl, Petra Svedberg, Annika Lexén, Carina Tjörnstrand, Catharina Strid, Ulrika Bejerholm

Place, publisher, year, edition, pages
Toronto: JMIR Publications Inc., 2023
Keywords
co-design, mental health, mobile health, return-to-work, supported employment
National Category
Public Health, Global Health, Social Medicine and Epidemiology
Identifiers
urn:nbn:se:hh:diva-50116 (URN)10.2196/39422 (DOI)000998490100005 ()2-s2.0-85148997580 (Scopus ID)
Available from: 2023-03-24 Created: 2023-03-24 Last updated: 2023-08-21Bibliographically approved
Petersson, L., Svedberg, P., Nygren, J. M. & Larsson, I. (2023). Developing an ethical model for guidance the implementation of AI in healthcare. In: Nordic Health Promotion Research Conference 2023 Abstracts: . Paper presented at Nordic Health Promotion Research Conference 2023. Halmstad
Open this publication in new window or tab >>Developing an ethical model for guidance the implementation of AI in healthcare
2023 (English)In: Nordic Health Promotion Research Conference 2023 Abstracts, Halmstad, 2023Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

Background: Artificial intelligence (AI) is predicted to improve healthcare, increase efficiency, save time andresources. However, research shows an urgent need to develop guidance to ensure that the use of AI in healthcare isethically acceptable.

Purpose: To develop an ethical model to support AI implementation in practice.

Methods: The study used an explorative and empirically driven qualitative design. Individual interviews wereconducted with 18 healthcare professionals from two emergency departments in Sweden where the county council hasdeveloped an AI application to predict the risk for unexpected mortality within 30 days after visiting an emergencydepartment. A deductive analysis based on ethical theory i.e virtue, deontology and consequentialism, was used.

Findings: The developed model shows how the healthcare professionals use ethical reasoning in relation to theimplementation of AI. In relation to virtue ethics, moral considerations in relation to the use of AI were mentioned. Inrelation to deontology, considerations were mentioned on actions performed based on information acquired from thetechnology and adherence to specific duties, roles and responsibilities. In relation to consequentialism, considerationsabout how to provide better resources more rapidly in an equal way and how the technology can be adjusted to eachpatients’ individual needs and preferences in order to support decisions, self-determination, and actions that are in thepatients best interest.

Conclusions: Our findings provide an ethical model demonstrating the relevance of virtue, deontology andconsequentialism when AI are to be implemented in practice.

Place, publisher, year, edition, pages
Halmstad: , 2023
Keywords
Artificial intelligence, ethic, healthcare professionals, implementation, qualitative method
National Category
Social Sciences
Research subject
Health Innovation; Health Innovation, IDC
Identifiers
urn:nbn:se:hh:diva-52342 (URN)
Conference
Nordic Health Promotion Research Conference 2023
Funder
Halmstad University
Available from: 2023-12-28 Created: 2023-12-28 Last updated: 2023-12-28
Markström, U., Näslund, H., Schön, U. K., Rosenberg, D., Bejerholm, U., Gustavsson, A., . . . Svedberg, P. (2023). Developing sustainable service user involvement practices in mental health services in Sweden: the “Userinvolve” research program protocol. Frontiers in Psychiatry, 14, 1-12, Article ID 1282700.
Open this publication in new window or tab >>Developing sustainable service user involvement practices in mental health services in Sweden: the “Userinvolve” research program protocol
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2023 (English)In: Frontiers in Psychiatry, E-ISSN 1664-0640, Vol. 14, p. 1-12, article id 1282700Article in journal (Refereed) Published
Abstract [en]

Background: The purpose of this paper is to outline the protocol for the research program “UserInvolve,” with the aim of developing sustainable, service user involvement practices in mental health services in Sweden. Methods: This protocol outlines the knowledge gap and aim of the UserInvolve-program. It further provides an overview of the research infrastructure, with specific focus on the organization and management of the program as well as the design of the six underlying research projects. These six research projects form the core of the UserInvolve-program and will be carried out during a six-year period (2022–2027). The projects are focused on examining articulations of experiential knowledge in user collectives, on four specific user involvement interventions (shared decision-making, peer support, user-focused monitoring, and systemic involvement methods) and on developing theory and method on co-production in mental health research and practice. Results or conclusion: The knowledge gained through the co-production approach will be disseminated throughout the program years, targeting service users, welfare actors and the research community. Based on these research activities, our impact goals relate to strengthening the legitimacy of and methods for co-production in the mental health research and practice field. Copyright © 2023 Markström, Näslund, Schön, Rosenberg, Bejerholm, Gustavsson, Jansson, Argentzell, Grim, Engdahl, Nouf, Lilliehorn and Svedberg.

Place, publisher, year, edition, pages
Lausanne: Frontiers Media S.A., 2023
Keywords
co-production, involvement, mental health, protocol, research program, service users
National Category
Health Sciences
Research subject
Health Innovation; Health Innovation, IDC
Identifiers
urn:nbn:se:hh:diva-51938 (URN)10.3389/fpsyt.2023.1282700 (DOI)001088962400001 ()37900294 (PubMedID)2-s2.0-85174892656 (Scopus ID)
Funder
Forte, Swedish Research Council for Health, Working Life and Welfare, 2021–01427
Available from: 2023-11-17 Created: 2023-11-17 Last updated: 2024-01-17Bibliographically approved
Petersson, L., Vincent, K., Svedberg, P., Nygren, J. M. & Larsson, I. (2023). Ethical considerations in implementing AI for mortality prediction in the emergency department: Linking theory and practice. Digital Health, 9
Open this publication in new window or tab >>Ethical considerations in implementing AI for mortality prediction in the emergency department: Linking theory and practice
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2023 (English)In: Digital Health, E-ISSN 2055-2076, Vol. 9Article in journal (Refereed) Published
Abstract [en]

Background: Artificial intelligence (AI) is predicted to be a solution for improving healthcare, increasing efficiency, and saving time and recourses. A lack of ethical principles for the use of AI in practice has been highlighted by several stakeholders due to the recent attention given to it. Research has shown an urgent need for more knowledge regarding the ethical implications of AI applications in healthcare. However, fundamental ethical principles may not be sufficient to describe ethical concerns associated with implementing AI applications.

Objective: The aim of this study is twofold, (1) to use the implementation of AI applications to predict patient mortality in emergency departments as a setting to explore healthcare professionals’ perspectives on ethical issues in relation to ethical principles and (2) to develop a model to guide ethical considerations in AI implementation in healthcare based on ethical theory.

Methods: Semi-structured interviews were conducted with 18 participants. The abductive approach used to analyze the empirical data consisted of four steps alternating between inductive and deductive analyses. Results: Our findings provide an ethical model demonstrating the need to address six ethical principles (autonomy, beneficence, non-maleficence, justice, explicability, and professional governance) in relation to ethical theories defined as virtue, deontology, and consequentialism when AI applications are to be implemented in clinical practice.

Conclusions: Ethical aspects of AI applications are broader than the prima facie principles of medical ethics and the principle of explicability. Ethical aspects thus need to be viewed from a broader perspective to cover different situations that healthcare professionals, in general, and physicians, in particular, may face when using AI applications in clinical practice. © The Author(s) 2023.

Place, publisher, year, edition, pages
London: Sage Publications, 2023
Keywords
Artificial intelligence, codes of ethics, emergency department, ethical theory, healthcare, healthcare professionals, implementation, qualitative research
National Category
Health Care Service and Management, Health Policy and Services and Health Economy
Research subject
Health Innovation; Health Innovation, IDC
Identifiers
urn:nbn:se:hh:diva-51854 (URN)10.1177/20552076231206588 (DOI)001078896200001 ()37829612 (PubMedID)2-s2.0-85173652948 (Scopus ID)
Funder
Vinnova, 2019-04526Knowledge Foundation, 20200208 01H
Available from: 2023-11-08 Created: 2023-11-08 Last updated: 2023-11-09Bibliographically approved
Petersson, L., Vincent, K., Svedberg, P., Nygren, J. M. & Larsson, I. (2023). Ethical Perspectives on Implementing AI to Predict Mortality Risk in Emergency Department Patients: A Qualitative Study. In: Maria Hägglund; Madeleine Blusi; Stefano Bonacina; Lina Nilsson; Inge Cort Madsen; Sylvia Pelayo; Anne Moen; Arriel Benis; Lars Lindsköld; Parisis Gallos (Ed.), Caring is sharing - exploiting the value in data for health and innovation: Proceedings of MIE 2023. Paper presented at 33rd Medical Informatics Europe Conference: Caring is Sharing - Exploiting the Value in Data for Health and Innovation, MIE 2023, Gothenburg, 22-25 May, 2023 (pp. 676-677). Amsterdam: IOS Press, 302
Open this publication in new window or tab >>Ethical Perspectives on Implementing AI to Predict Mortality Risk in Emergency Department Patients: A Qualitative Study
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2023 (English)In: Caring is sharing - exploiting the value in data for health and innovation: Proceedings of MIE 2023 / [ed] Maria Hägglund; Madeleine Blusi; Stefano Bonacina; Lina Nilsson; Inge Cort Madsen; Sylvia Pelayo; Anne Moen; Arriel Benis; Lars Lindsköld; Parisis Gallos, Amsterdam: IOS Press, 2023, Vol. 302, p. 676-677Conference paper, Published paper (Refereed)
Abstract [en]

Artificial intelligence (AI) is predicted to improve health care, increase efficiency and save time and recourses, especially in the context of emergency care where many critical decisions are made. Research shows the urgent need to develop principles and guidance to ensure ethical AI use in healthcare. This study aimed to explore healthcare professionals' perceptions of the ethical aspects of implementing an AI application to predict the mortality risk of patients in emergency departments. The analysis used an abductive qualitative content analysis based on the principles of medical ethics (autonomy, beneficence, non-maleficence, and justice), the principle of explicability, and the new principle of professional governance, that emerged from the analysis. In the analysis, two conflicts and/or considerations emerged tied to each ethical principle elucidating healthcare professionals' perceptions of the ethical aspects of implementing the AI application in emergency departments. The results were related to aspects of sharing information from the AI application, resources versus demands, providing equal care, using AI as a support system, trustworthiness to AI, AI-based knowledge, professional knowledge versus AI-based information, and conflict of interests in the healthcare system. © 2023 European Federation for Medical Informatics (EFMI) and IOS Press.

Place, publisher, year, edition, pages
Amsterdam: IOS Press, 2023
Series
Studies in Health Technology and Informatics, ISSN 0926-9630, E-ISSN 1879-8365 ; 302
Keywords
AI applications, ethical aspects, healthcare professionals, qualitative study
National Category
Nursing
Research subject
Health Innovation; Health Innovation, IDC
Identifiers
urn:nbn:se:hh:diva-51747 (URN)10.3233/SHTI230234 (DOI)001071432900176 ()37203776 (PubMedID)2-s2.0-85159761458 (Scopus ID)978-1-64368-388-1 (ISBN)978-1-64368-389-8 (ISBN)
Conference
33rd Medical Informatics Europe Conference: Caring is Sharing - Exploiting the Value in Data for Health and Innovation, MIE 2023, Gothenburg, 22-25 May, 2023
Available from: 2023-11-17 Created: 2023-11-17 Last updated: 2023-11-20Bibliographically approved
Petersson, L., Svedberg, P., Nygren, J. M. & Larsson, I. (2023). Expected values of implementing AI in healthcare – A Qualitative study. In: Nordic Health Promotion Research Conference 2023: Abstracts. Paper presented at The 10th Nordic Health Promotion Research Conference "Sustainability and the impact on health and well-being", Halmstad, Sweden, 14-16 June, 2023. Halmstad
Open this publication in new window or tab >>Expected values of implementing AI in healthcare – A Qualitative study
2023 (English)In: Nordic Health Promotion Research Conference 2023: Abstracts, Halmstad, 2023Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

Background: Artificial intelligence (AI) is often presented as a technology that will change healthcare and be useful inclinical work in disease prediction, diagnosis, and precision health. More knowledge is needed regarding the value of AI applications based on the perspectives of healthcare leaders to understand their roles as gatekeepers and facilitatorsfor successful implementation.

The purpose of the study: To explore healthcare leaders’ perceptions of the value of AI applications in clinical work.

Methods: The study had an explorative qualitative approach. Individual interviews were conducted from October2020 to May 2021 with 26 healthcare leaders with different experiences in implementing AI in clinical practice in acounty council in Sweden. Inductive qualitative content analysis was used, and eight sub-categories and threecategories emerged.

Findings: The value of AI applications in clinical care was described in terms of expected benefits for patients as toolssupporting person-centered information and individualized self-management. The expected benefits for healthcareprofessionals included decision-support in diagnostics, risk assessments, and treatment recommendations but alsoproviding warning systems and second opinions in clinical work. On an organizational level, the benefits comprisedpatient safety and decision-support in prioritizing healthcare resources in and across healthcare organizations.

Conclusions: The healthcare leaders perceived that AI applications would provide value on different levels inhealthcare for patients, healthcare professionals, and organizations. Across these levels, the implementation of AI cansupport person-centeredness, patient self-management, quality of care, patient safety, and resource optimization.

Place, publisher, year, edition, pages
Halmstad: , 2023
Keywords
AI applications, healthcare leaders, qualitative study, value
National Category
Health Sciences
Research subject
Health Innovation; Health Innovation, IDC
Identifiers
urn:nbn:se:hh:diva-52343 (URN)
Conference
The 10th Nordic Health Promotion Research Conference "Sustainability and the impact on health and well-being", Halmstad, Sweden, 14-16 June, 2023
Funder
Halmstad University
Available from: 2023-12-28 Created: 2023-12-28 Last updated: 2024-01-02Bibliographically approved
Lönn, M., Aili, K., Svedberg, P., Nygren, J. M., Jarbin, H. & Larsson, I. (2023). Experiences of Using Weighted Blankets among Children with ADHD and Sleeping Difficulties. Occupational Therapy International, 2023, 1-12, Article ID 1945290.
Open this publication in new window or tab >>Experiences of Using Weighted Blankets among Children with ADHD and Sleeping Difficulties
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2023 (English)In: Occupational Therapy International, ISSN 0966-7903, E-ISSN 1557-0703, Vol. 2023, p. 1-12, article id 1945290Article in journal (Refereed) Published
Abstract [en]

Introduction. Sleeping difficulties are common in children with attention deficit hyperactivity disorder (ADHD). A sleep intervention with weighted blankets was designed to increase current understanding of using weighted blankets to target children’s individual needs in connection with sleep and daytime functioning. Aim. To explore how children with ADHD and sleeping difficulties experience the use of weighted blankets. Methods. An explorative qualitative design in which 26 children with ADHD and sleeping difficulties, 6-15 years old, were interviewed about a sleep intervention with weighted blankets. Four categories emerged from qualitative content analysis. Results. Children’s experiences revealed that the use of weighted blankets 1) requires a commitment, by adjusting according to needs and preferences and adapting to the environment; 2) improves emotional regulation by feeling calm and feeling safe; 3) changes sleeping patterns by creating new routines for sleep and improving sleep quality; and 4) promotes everyday participation by promoting daily function and balancing activity and sleep. Conclusions. Using weighted blankets promoted children’s management of daily life with ADHD and sleeping difficulties. Occupational therapists can improve the assessment and delivery of weighted blankets tailored to individual needs based on increased knowledge from the children themselves. Copyright © 2023 Maria Lönn et al.

Place, publisher, year, edition, pages
Oxford: John Wiley & Sons, 2023
National Category
Psychiatry
Identifiers
urn:nbn:se:hh:diva-50117 (URN)10.1155/2023/1945290 (DOI)000938743200001 ()36824380 (PubMedID)2-s2.0-85148774514 (Scopus ID)
Available from: 2023-03-27 Created: 2023-03-27 Last updated: 2023-03-27Bibliographically approved
Andersson, P., Schön, U.-K., Svedberg, P. & Grim, K. (2023). Exploring stakeholder perspectives to facilitate the implementation of shared decision-making in coordinated individual care planning. European Journal of Social Work
Open this publication in new window or tab >>Exploring stakeholder perspectives to facilitate the implementation of shared decision-making in coordinated individual care planning
2023 (English)In: European Journal of Social Work, ISSN 1369-1457, E-ISSN 1468-2664Article in journal (Refereed) Epub ahead of print
Abstract [en]

This article explores conditions for implementing shared decision-making (SDM) in coordinated individual care planning (CIP) with individuals with complex mental health needs. SDM in CIP are described as central, although such user centred collaboration still remains to be realised. Research underlines the need for a changed way of working, where user expertise is valued and a balance of power is promoted. The aim of the present study is to investigate the conditions for implementing SDM in connection with CIP for and with people with mental illness. To better understand the context and conditions that can promote such an implementation, altogether 15 participants were interviewed in three regions in Sweden within the scope of a stakeholder analysis. Both hindering and supporting factors were identified with respect to an implementation process, such as staff turnover, differences in work culture and committed leadership. Further focus should be directed specifically towards professionals working more closely with CIP and towards in-depth analysis of the construct of culture in terms of implementation processes. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Place, publisher, year, edition, pages
Abingdon, Oxon: Routledge, 2023
Keywords
Shared decision-making (SDM), coordinated individual care planning (CIP), workplace culture, stakeholder analysis, Delat beslutsfattande (DBF), Samordnad individuell plan (SIP), Arbetsplatskultur, Stakeholderanalys
National Category
Nursing
Research subject
Health Innovation, IDC
Identifiers
urn:nbn:se:hh:diva-52191 (URN)10.1080/13691457.2023.2281868 (DOI)001102691400001 ()2-s2.0-85176908504& (Scopus ID)
Funder
The Kamprad Family Foundation
Note

Funding: Familjen Kamprads Stiftelse; Forskningsrådet om Hälsa, Arbetsliv och Välfärd.

Available from: 2023-12-06 Created: 2023-12-06 Last updated: 2023-12-07Bibliographically approved
Petersson, L., Svedberg, P., Nygren, J. M. & Larsson, I. (2023). Healthcare Leaders' Perceptions of the Usefulness of AI Applications in Clinical Work: A Qualitative Study. In: Caring is sharing - exploiting the value in data for health and innovation: 33rd Medical Informatics Europe Conference, MIE2023, Gothenburg, Sweden, 22-25 May. Paper presented at 33rd Medical Informatics Europe Conference: Caring is Sharing - Exploiting the Value in Data for Health and Innovation, MIE2023. Gothenburg, Sweden, 22-25 May, 2023 (pp. 678-679). Amsterdam: IOS Press, 302
Open this publication in new window or tab >>Healthcare Leaders' Perceptions of the Usefulness of AI Applications in Clinical Work: A Qualitative Study
2023 (English)In: Caring is sharing - exploiting the value in data for health and innovation: 33rd Medical Informatics Europe Conference, MIE2023, Gothenburg, Sweden, 22-25 May, Amsterdam: IOS Press, 2023, Vol. 302, p. 678-679Conference paper, Published paper (Refereed)
Abstract [en]

Artificial intelligence (AI) is often presented as a technology that changes healthcare and is useful in clinical work in disease prediction, diagnosis, treatment effectiveness, and precision health. This study aimed to explore healthcare leaders' perceptions of the usefulness of AI applications in clinical work. The study was based on qualitative content analysis. Individual interviews were conducted with 26 healthcare leaders. The usefulness of AI applications in clinical care was described in terms of expected benefits for 1) patients as supporting individualized self-management and person-centered information support tools 2) healthcare professionals in terms of providing decision-support in diagnostics, risk assessments, treatment recommendations, warning systems, and as a new colleague supporting the clinical work, and 3) organizations as providing patient safety and decision-support in prioritizing healthcare resources in organizing healthcare.

Place, publisher, year, edition, pages
Amsterdam: IOS Press, 2023
Series
Studies in Health Technology and Informatics, ISSN 0926-9630, E-ISSN 1879-8365 ; 302
Keywords
AI-based applications, healthcare leaders, qualitative study, usefulness
National Category
Health Care Service and Management, Health Policy and Services and Health Economy
Research subject
Health Innovation, IDC
Identifiers
urn:nbn:se:hh:diva-51972 (URN)10.3233/SHTI230235 (DOI)001071432900177 ()37203777 (PubMedID)2-s2.0-85159767799 (Scopus ID)
Conference
33rd Medical Informatics Europe Conference: Caring is Sharing - Exploiting the Value in Data for Health and Innovation, MIE2023. Gothenburg, Sweden, 22-25 May, 2023
Available from: 2023-11-13 Created: 2023-11-13 Last updated: 2023-11-14Bibliographically approved
Projects
Peer support intervention for improved mental health in children [2012-00027_Formas]; Halmstad University; Publications
Einberg, E.-L., Nygren, J., Svedberg, P. & Enskär, K. (2016). ‘Through my eyes’: health-promoting factors described by photographs taken by children with experience of cancer treatment. Child Care Health and Development, 42(1), 76-86
Evaluation of health effects and cost effectiveness from a sleep intervention with weight blankets in children with ADHD and sleep problems [2021-00664_Forte]; Halmstad University; Publications
Lönn, M., Svedberg, P., Nygren, J. M., Jarbin, H., Aili, K. & Larsson, I. (2023). The efficacy of weighted blankets for sleep in children with attention-deficit/hyperactivity disorder—A randomized controlled crossover trial. Journal of Sleep Research, Article ID e13990. Harris, U., Svedberg, P., Aili, K., Nygren, J. M. & Larsson, I. (2022). Parents’ Experiences of Direct and Indirect Implications of Sleep Quality on the Health of Children with ADHD: A Qualitative Study. International Journal of Environmental Research and Public Health, 19(22), Article ID 15099.
Health Data Sweden [1083629]; Implementing Artificial Intelligence (AI): Exploring how AI changes information and knowledge practices in healthcare [2022-05406_VR]; Halmstad University; Publications
Petersson, L., Steerling, E., Neher, M., Larsson, I., Nygren, J. M., Svedberg, P. & Nilsen, P. (2023). Implementering av artificiell intelligens (AI): Ett projekt om hur AI förändrar information och kunskapspraktiker i hälso- och sjukvården. In: : . Paper presented at FALF 2023 - Forum för arbetslivsforskning. Apeloig, A. (2023). Stakeholders’ perceptions on potential barriers and facilitators of implementing technology based on Artificial Intelligence for predicting and preventing mental illness among young adults: – a qualitative study applying the NASSS framework. (Student paper). Högskolan i Halmstad
UserInvolve: Developing sustainable user involvement practices in community mental health [2021-01427_Forte]; Umeå UniversitySocial capital for identification and support of young people's mental Health;
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-4438-6673

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