Health informatics


Health informatics is about capturing, processing, and presenting information generated in healthcare to make it as useful as possible. We go from patient-specific data to general medical knowledge and support individual decisions as well as the development of new knowledge.

In healthcare, the work on preventing, investigating, and treating disease and trauma generates more and more information and becomes increasingly dependent on the ability to manage that information. At the same time, the ongoing digitalisation brings new possibilities to measure, follow up, and develop activities and improve results, allocate and manage resources, and foster informed and involved consumers and learning organisations.

Real value is created when all parts of the healthcare system can communicate with each other, regardless of their being health apps, medical record systems, or persons who for various reasons are unable or unwilling to use computers or smartphones. Consequently, we work in different ways to make the healthcare information ecosystem interlock, thereby enabling new work procedures, reformed roles, and improved quality.

The research revolves around eHealth and electronic health records and concerns areas such as semantic interoperability, data analysis, clinical decision support, and interaction design. The research is applied and for example conducted within laboratory medicine, primary healthcare, emergency care, homecare, and palliative care. More specifically, clinical applications concern for instance infectious disease, neoplasms, heart failure, COPD, and multi-disease.

Health Information Systems

The research on health information systems involves formal representation of electronic health records, were we are interested in different aspects of information models and systems such as interoperability and technical performance. We also work on ontology and terminology, for example structures for formal representation of ontology content, but also usability and reliability facets. Internationally, we participate in collaborations and standardisation initiatives such as openEHR, SNOMED International, and HL7 CIMI.

Decision Support

We study methods for processing and visualising clinical and administrative information to support various kinds of decisions. For example, we use knowledge represented in ontologies to aggregate and expand patient information in statistical compilations. We also develop methods for creating and illustrating patient summaries, also with usability as a recurring aspect. A third example of decision support is structured chart review based on formal representation of health records content.


In the homecare projects we develop technology for improved quality of life among severely ill patients treated in their home environment. Symptoms and physiological parameters are reported and sent to the professional care providers for telemonitoring using technology accessible to patients who are unable or unwilling to use computers, tablets, or smartphones. This results in improved symptom control, earlier detection of deterioration and intervention needs, and fewer hospital readmissions, which in turn makes patients and their relatives feel safer. Through information fed back to the home environment, patients learn more about their disease and become more involved.