IDC – Information Driven Care
Healthcare is facing extensive challenges – an aging population, various chronic diseases, pandemics, changing patient expectations and limited resources. Information driven care addresses some of these challenges through a shift towards more proactive, predictive, accurate, participatory, innovative and democratised healthcare.
The programme takes a broad approach to examine and develop information driven care solutions in healthcare, including for example decision support systems in clinical practice.
The programme takes a broad approach to develop and research information driven care solutions, for example decision support systems in clinical practice. This will require building up knowledge about the whole healthcare innovation chain, from formulating and prioritizing questions, to data collection, to algorithms, to engagement, to explainability, to innovation, diffusion, and implementation in practice. TThe programme has a multidisciplinary approach and addresses challenges related to the complexity of developing information driven healthcare solutions, particularly in terms of AI systems, data, implementation and innovation challenges.
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Research ambitions
The overall ambitions of the program are:
- To further develop a multidisciplinary information driven care research environment, strengthening and integrating the disciplines of AI and machine learning, data infrastructure, implementation research and innovation science. A research environment which promotes career development in the field and provides equal opportunities to people of all genders and ethnicities.
- To further strengthen long-term collaborations and co-production with leading national and international universities, companies and public sector in the field of information driven care. A research environment which has an established model for how industry and public partners can collaborate to create and implement AI systems for sustainable adoption and diffusion as part of long-term efforts to improve healthcare and health outcomes.
- To continue developing a strong academic position (including research, education and collaboration) and add value to society. A research environment that addresses complex research questions from multi-disciplinary perspectives and provides excellent research and education that is practically useful and contributes to new understandings, knowledge and innovations. The research environment should be characterized by high specialization in information driven care and high impact.
Connection to focus area
Personalized proactive care is one of two directions for the health innovation focus area. In this, implementation of information driven care constitutes a substantial part. This research program aims to continue developing this direction and contribute to the strategic goals of the focus area. This involves for example to position the research area nationally and internationally and to perform collaborative research that makes an impact in society. The research program will contribute to the goals set out in the focus area strategy.

Three integrating research fields
AI and machine learning research
The AI and machine learning research is tightly connected to challenges of working with applications and data from healthcare. It involves pure algorithmic developments as well as specific solutions developed for a single application.
Implementation research
The research within healthcare implementation focuses on questions on how health innovations, such as interventions supported by digital services and health data, can be developed, implemented and evaluated to provide healthcare organizations with knowledge and support to achieve high quality of care and improved health outcomes for particular groups.
Innovation research
The research within innovation science is tightly connected to challenges working with healthcare innovation from the perspective of firms and healthcare organizations.
What’s new?
Participating researchers
School of Business, Innovation and Sustainability
Siri Jagstedt, Senior Lecturer
Hélène Laurell, Senior Lecturer
Ludvig Lindlöf, Senior Lecturer
Lina Lundgren, Senior Lecturer
Rögnvaldur Saemundsson, Senior Lecturer
Patrik Hidefjäll, Adjunct Senior Lecturer
Luís Irgang Dos Santos, PhD Student
Manoella Ramos da Silva, PhD Student
School of Health and Welfare
James Barlow, Visiting Professor
Carl Macrae, Visiting Professor
Per Nilsen, Visiting Professor
Julie Reed, Visiting Professor
Margit Neher, Assistant Professor
Katarina Aili, Senior Lecturer
Ing-Marie Carlsson, Senior Lecturer
Carina Göransson, Senior Lecturer
Ingrid Larsson, Senior Lecturer
Annelie Lindholm, Senior Lecturer
Lena Petersson, Senior Lecturer
Carl Savage, Visiting Senior Lecturer
Pia Johansson, Associate Senior Lecturer
Julia Malmborg Söderström, Associate Senior Lecturer
Daniel Tyskbo, Associate Senior Lecturer
Monica Nair, Postdoctoral Position
School of Information Technology
Markus Lingman, Adjunct Professor
Torkel Strömsten, Visiting Professor
Stefan Byttner, Senior Lecturer
Kobra Etminani, Senior Lecturer
Susanne Lindberg, Senior Lecturer
Jens Lundström, Senior Lecturer
Pontus Wärnestål, Senior Lecturer
Dimitrios Gkouskos, Associate Senior Lecturer
Amira Soliman, Associate Senior Lecturer
Awais Ashfaq, Postdoctoral Position
Ece Calikus, Postdoctoral Position
Anna Zukowicka-Surma, Postdoctoral Position
Ongoing projects
AI centered projects
- AIR Lund
- EDIH - Health Data Sweden
- HaRP – Heart failure Readmission Prediction
- IDC through AI Application
External link.
- Improved preparedness for future pandemics
- Information Driven Care – federated learning and synthetic data generation
- PadAI – AI for better mental health in young people
- Prevention 360
- Test Bed Sweden for Precision Health in Cancer
Implementation projects
- Covid-19 – symptoms and immunity
- Digital anamnes and triage in primary care
- Framework development for AI implementation in healthcare
- ID Wound Care
- Implementation of information-driven healthcare through AI application
- Implementation Artificial Intelligence (AI): A project on how AI is changing information and knowledge practices in healthcare
- Mental health in young adult cancer survivors
- SLEEP – Sleep intervention for children and adolescents with neuropsychiatric disabilities
- Social capital for identification and support of young people's mental health
- Understanding health innovation in practice
- UserInvolve: Developing sustainable user involvement practices in community mental health
- V3C – Value creating continence care (only in Swedish)
- Youth participation in healthcare
- Young people’s mental health, social capital and help-seeking behaviour
Innovation projects
- Approaches to evaluating implementation of health innovations
- Automatic Idea Detection: Implementing artificial intelligence in medical technology innovation (AID)
- BINECO – Business Models for Information-driven Healthcare Ecosystems
- ICHSI – Institutionellt entreprenörskap och utveckling i samverkan av företag i hälsosektorn på internationella marknader (only in Swedish)
- MeTARoad – Accelerating the roadmap for commercializing and adopting medical technology innovations – the role of different actors’ logics in a health innovation ecosystem