The use of Electronic Health Records (EHR) is wide spread in healthcare today. EHRs are not only used to support daily care but also used to support important secondary uses, e.g. clinical research, quality assurance and education. Although considered advantageous compared to paper-based records, EHRs still have a long way to go in realizing its full potential as an integral part of a safe, effective and efficient health care system.

Making EHRs interoperable is a prerequisite to support increasingly distributed and diverse healthcare. Bringing up-to-date knowledge into EHRs for decision support is a critical step to foster evidence based care. EHR data from different sources need to be analyzed in research in order to find new evidence for improvement of the current practice. Knowledge in the form of guidelines needs to be disseminated and applied in practice through continuous education. This cyclic flow of information and knowledge between care, research and education must be facilitated in order to achieve a safer and more efficient healthcare. An interoperable EHR framework can facilitate the sharing of information and knowledge between not only human users but also participating software systems. This is the aim of this thesis, which is built upon the research in the field of semantic interoperability, in particular the pioneering work by the openEHR Foundation.

The journey of this thesis started with a template-based supplementary EHR system - Julius, which allows clinicians to define and share record structures for care and research. The formalism behind Julius is comparable to the openEHR archetype formalism but less expressive and without the backing of international standards. This finding led to an open source implementation of the openEHR design, which in turn initiated the validation and further improvements of the archetype formalism. The software components made the archetype formalism more accessible to academic and commercial projects around the world.

The investigation of the convertibility between a legacy EHR content model and the archetype model showed that the archetype format is more expressive and thus can be used to preserve legacy EHR content definitions. A general strategy for migration from legacy EHRs to archetype-based EHRs was formulated. A novel way of representing clinical practice guidelines using archetype formalism was proposed and tested on a lymphoma chemotherapy guideline. The implication of this study is improved interoperability between guidelines and EHRs that could facilitate both clinical decision support and guideline-compliance checking. Maintainability of guidelines could be increased through reuse of EHR content models as building blocks of guidelines. In the last part of the research, a way of expressing fully structured care plans using openEHR and CONTsys has been explored based on the requirements for elderly home care. A sharable and semantically well-defined care plan could contribute to the coordination of shared care.

The key contribution of the thesis can be summarized as the validation and further improvement of the openEHR archetype formalism through software implementation and the explorations on clinical guidelines, shared care plans and legacy EHR content models in relation to archetypebased EHR framework.