Implementation of information-driven healthcare through AI application

The project is a sub-project in a larger collaboration project financed by Vinnova with the aim of developing Swedish healthcare to become more information-driven, individually adapted and scalable through AI application.

Healthcare is facing major challenges that cannot be solved solely through more resources or by individual actors. How we use data and information in healthcare will play an important role in solving several of healthcare's challenges. It will require both new working methods and collaborations. Region Halland and Halmstad University are far ahead with the work in information-driven care, which has also attracted national as well as international interest.

Within the framework of the collaboration project, this sub-project is carried out, with the aim of investigating stakeholders' needs, requirements and preferences for a successful implementation of AI technology in healthcare. We will study whether the implementation of AI technology has special implementation requirements that require specific and/or additional considerations in relation to established implementation models. The sub-project will investigate how existing knowledge from implementation research can be mobilized to support practice and increase the success of AI implementation initiatives.

About the project

Project period:

2020–2024

Financier:

Vinnova

Collaboration partners:

AI Innovation of Sweden
Sweden's municipalities and county councils
Region Halland
Halmstad University
Innovationsplatsen, Karolinska University Hospital

Project leaders:

Project participants:

Julie Reed, Visiting Professor of Healthcare Implementation
James Barlow, Visiting Professor of Innovation Science/Health Innovation
Fabio Gama, Senior Lecturer of Innovation
Ingrid Larsson, Professor
Lena Petersson, Lecturer of Pedagogy
Daniel Tyskbo, Associate Senior Lecturer

Publications:

Svedberg, P., Reed, J.E., Nilsen, P., Barlow, J., Macrae, C., Nygren, J.M. (2022). Towards successful implementation of artificial intelligence in healthcare practice: A research program. JMIR Research protocols. 11(3):e34920 doi:2196/34920 External link.
Sharma, M., Savage, C., Nair, M., Larsson, I., Svedberg, P., and Nygren, J.M. Artificial Intelligence Applications in Health Care Practice: A Scoping Review. Journal of Medical Internet Research, 24 (10). Doi: 2196/40238 External link.
Nilsen, P., Reed, J.E., Nair, M., Savage, C., Macrae, C., Barlow, J., Svedberg, P., Larsson, I., Lundgren, L., and Nygren, J.M. Realizing the Potential of Artificial Intelligence in Healthcare: Learning from Intervention, Innovation, Implementation and Improvement Sciences. Frontiers in Health Services, section Implementation Science, 2:961475.
Nilsen, P., Svedberg, P. Nygren, J.M., Frideros, M., Johansson, J., Schueller, S. (2022). Accelerating the impact of artificial intelligence in mental healthcare through implementation science. Implementation Research and Practice. 3: 1–10.
Petersson, L., Larsson, I., Nygren, J.M., Reed, J.E., Nilsen, P., Neher, M., Tyskbo, D., and Svedberg, P. (2022). Healthcare leaders’ perspectives on implementation of Artificial Intelligence: A qualitative study with healthcare leaders in Sweden. BMC – Health services research, 22:850. https://doi.org/10.1186/s12913-022-08215-8 External link.
Gama, F., Tyskbo, D., Nygren, J.M., Barlow, J. Reed, J.E., and Svedberg, P. (2022). Implementation Frameworks for Artificial Intelligence Translation Into Health Care Practice: Scoping Review. Journal of Medical Internet Research. 24,1. doi:2196/32215 External link.