hh.sePublications
Change search
Link to record
Permanent link

Direct link
Publications (10 of 41) Show all publications
Karnehed, S., Pejner, M. N., Erlandsson, L.-K. & Petersson, L. (2024). Electronic medication administration record (eMAR) in Swedish home healthcare—Implications for Nurses' and nurse Assistants' Work environment: A qualitative study. Scandinavian Journal of Caring Sciences
Open this publication in new window or tab >>Electronic medication administration record (eMAR) in Swedish home healthcare—Implications for Nurses' and nurse Assistants' Work environment: A qualitative study
2024 (English)In: Scandinavian Journal of Caring Sciences, ISSN 0283-9318, E-ISSN 1471-6712Article in journal (Refereed) Epub ahead of print
Abstract [en]

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.

Place, publisher, year, edition, pages
Chichester: John Wiley & Sons, 2024
Keywords
digital technology, eHealth, eMAR, home healthcare, JDCS model, job-demand-control-support model, nurse assistant, nursing, qualitative, work environment
National Category
Nursing
Research subject
Health Innovation, IDC
Identifiers
urn:nbn:se:hh:diva-52590 (URN)10.1111/scs.13237 (DOI)001145942500001 ()2-s2.0-85182821967 (Scopus ID)
Note

Funding: Open access funding provided by Halmstad University. The funders for this study are Kungsbacka municipality and Halmstad University. 

Available from: 2024-02-08 Created: 2024-02-08 Last updated: 2024-02-12Bibliographically approved
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
Show others...
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
Karnehed, S., Erlandsson, L.-K., Petersson, L. & Norell Pejner, M. (2023). Developers' beliefs and values – a discursive analysis of e-health technology in home healthcare. In: : . Paper presented at The 10th Nordic Health Promotion Research Conference: ”Sustainability and the impact on health and well-being”, Halmstad, Sweden, June 14–16, 2023.
Open this publication in new window or tab >>Developers' beliefs and values – a discursive analysis of e-health technology in home healthcare
2023 (English)Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

Background

The 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.

Purpose

The 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.

Method

Information 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.

Findings

Preliminary 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.

Keywords
e-health, eMar, values, discourse
National Category
Health Care Service and Management, Health Policy and Services and Health Economy Information Systems, Social aspects
Research subject
Health Innovation, IDC
Identifiers
urn:nbn:se:hh:diva-52288 (URN)
Conference
The 10th Nordic Health Promotion Research Conference: ”Sustainability and the impact on health and well-being”, Halmstad, Sweden, June 14–16, 2023
Funder
Halmstad University
Available from: 2023-12-20 Created: 2023-12-20 Last updated: 2024-01-15Bibliographically 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
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
Show others...
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
Show others...
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
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
Petersson, L., Larsson, I., Nygren, J. M. & Svedberg, P. (2023). Implementering av AI i hälso- och sjukvården – ledares gränsarbete kan förändra professionella gränser. In: : . Paper presented at NORDPRO 2023 – Nordisk professionsforskningskonferens, Göteborg, Sweden, 22-23 november, 2023.
Open this publication in new window or tab >>Implementering av AI i hälso- och sjukvården – ledares gränsarbete kan förändra professionella gränser
2023 (Swedish)Conference paper, Oral presentation only (Refereed)
Abstract [sv]

Just nu pågår en digital transformation av svensk hälso- och sjukvård och artificiell intelligens (AI) är tänkt att vara lösningen på många av de utmaningar sjukvården står inför. I en kunskapssammanställning från Myndigheten för arbetsmiljökunskap (MYNAK) (2020) om digitalisering och arbetsmiljö påtalas att den snabba tekniska utvecklingen kommer att förändra arbetsmiljö och yrkesrollers karaktär. Professionellas arbete är traditionellt omgärdat av gränser och att upprätthålla gränserna kring det egna kunskapsområdet är en grundläggande del av professionens utveckling. Digitalisering och implementering av olika former av teknik kan förändra professionella gränser och därmed generera så kallat gränsarbete (Petersson, 2020) som kan indelas i tre former; konkurrenskraftigt gränsarbete, kollaborativt gränsarbete och konfigurativt gränsarbete (Langley et al. 2019). De tre formerna av gränsarbete är ofta sammanflätade i praktiken, men konfigurativt gränsarbete kan dock beskrivas som en kraft som driver de andra två kategorierna av gränsarbete, eftersom det riktar sig emot andras aktiviteter i syfte att utforma gränser för förändring mellan grupper (Langley et al., 2019). Denna studie fokuserar på hur gränserna kring vårdprofessionernas arbete kan förändras vid implementering av AI och på vilket konfigurativt gränsarbete som aktörer på ledningsnivån i ett sjukvårdssystem förutser kommer att ske när sjukvården blir mer datadriven genom användning av AI-analyser.Vi genomförde semistrukturerade intervjuer med 26 ledare som var i en position att potentiellt påverka implementeringen och användningen av AI i en svensk region. Intervjuerna analyserades med hjälp av kvalitativ innehållsanalys. Analysen i studien fokuserar på den konfigurativa formen av gränsarbete.Sammantaget visar resultatet att ledarna beskriver olika typer av konfigurativt gränsarbete. Ledarna har makten att bedriva gränsarbete som förändrar gränserna kring vårdpersonalens arbete och de beskriver att de, medvetet eller omedvetet, vill förändra gränserna kring i första hand läkarnas arbete vid implementeringen av AI i hälso- och sjukvården.

Referenser

Langley, A., Lindberg, K., Mork, B. E., Nicolini, D., Raviola, E., Walter, L. (2019). Boundary work among groups, occupations, and organization: From Cartography to process. Academy of Management Annals, 13(2): 704–736.

Mynak (2020). Framtidens arbetsmiljö – trender, digitalisering och anställningsformer. 2020:3. www.mynak.se.

Petersson, L. (2020). Paving the way for transparency: How eHealth technology can change boundaries in healthcare. Lund: Department of Design Sciences, Faculty of Engineering, Lund University.

Keywords
Hälso- och sjukvårdspersonal, gränser, gränsarbete, implementering, AI Konferenstema: Formell och informell styrning av välfärdsprofessioner
National Category
Nursing
Research subject
Health Innovation, IDC
Identifiers
urn:nbn:se:hh:diva-52345 (URN)
Conference
NORDPRO 2023 – Nordisk professionsforskningskonferens, Göteborg, Sweden, 22-23 november, 2023
Funder
Halmstad University
Available from: 2023-12-28 Created: 2023-12-28 Last updated: 2024-01-26
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.
Open this publication in new window or tab >>Implementering av artificiell intelligens (AI): Ett projekt om hur AI förändrar information och kunskapspraktiker i hälso- och sjukvården
Show others...
2023 (Swedish)Conference paper, Oral presentation only (Refereed)
Abstract [sv]

Vi kommer att presentera ett nytt forskningsprojekt vid Högskolan i Halmstad med finansiering från Vetenskapsrådet, som förväntas bidra med kunskap om hur arbetets gränser i hälso- och sjukvården förändras vid implementering av artificiell intelligens (AI). Hälso- och sjukvården i Sverige brottas idag med utmaningar kring att klara av att fördela resurser där de gör mest nytta, säkerställa kvalitet i den vård som ges och att ställa om till en mer digitaliserad vård som sker i mer samproduktion mellan vårdpersonal och patienter. Ett teknikområde som förväntas kunna bidra till att lösa dessa utmaningar är AI, men forskning har visat att det finns många hinder för att lyckas med att införa och använda AI-applikationer inom hälso- och sjukvården. Hälso- och sjukvårdspersonal har en viktig roll att spela i förändringsarbete inom vården och AI-applikationer kan komma att konkurrera med det monopol på kunskap i förhållande till hälsa och behandling av sjukdomar som vårdpersonalen erhållit genom lång akademisk utbildning, träning och praktisk erfarenhet. Det övergripande syftet med forskningsprojektet ImpAI är att generera ny kunskap om implementering och användning av AI-applikationer i rutinsjukvård och hur professionella roller kan fungera som barriärer under implementeringsprocessen. Det teoretiska ramverket består av professionsteori med fokus på tillit och arbetets gränser samt implementeringsteori. Projektet bygger på olika case i form av AI-applikationer som implementeras under 2023–2024 i Region Halland, Sverige och mixad metod används vid processutvärderingen av dessa case. Resultatet kommer både att främja förståelsen för hur processer kan etableras vid införande av AI applikationer i hälso- och sjukvården och bidra med information om hur sådana processer kan bygga på hälso- och sjukvårdspersonalens kompetens och roller.

National Category
Social Sciences
Research subject
Health Innovation; Health Innovation, IDC
Identifiers
urn:nbn:se:hh:diva-52344 (URN)
Conference
FALF 2023 - Forum för arbetslivsforskning
Funder
Swedish Research Council, 2985
Available from: 2023-12-28 Created: 2023-12-28 Last updated: 2024-01-23
Projects
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
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-7874-7970

Search in DiVA

Show all publications