Objective: We aim to deliver a framework with 2 main objectives: 1) facilitating the design of theory-driven, adaptive, digital interventions addressing chronic illnesses or health problems and 2) producing personalized intervention delivery strategies to support self-management by optimizing various intervention components tailored to people's individual needs, momentary contexts, and psychosocial variables. Materials and Methods: We propose a template-based digital intervention design mechanism enabling the configuration of evidence-based, just-in-time, adaptive intervention components. The design mechanism incorporates a rule definition language enabling experts to specify triggering conditions for interventions based on momentary and historical contextual/personal data. The framework continuously monitors and processes personal data space and evaluates intervention-triggering conditions. We benefit from reinforcement learning methods to develop personalized intervention delivery strategies with respect to timing, frequency, and type (content) of interventions. To validate the personalization algorithm, we lay out a simulation testbed with 2 personas, differing in their various simulated real-life conditions. Results: We evaluate the design mechanism by presenting example intervention definitions based on behavior change taxonomies and clinical guidelines. Furthermore, we provide intervention definitions for a real-world care program targeting diabetes patients. Finally, we validate the personalized delivery mechanism through a set of hypotheses, asserting certain ways of adaptation in the delivery strategy, according to the differences in simulation related to personal preferences, traits, and lifestyle patterns. Conclusion: While the design mechanism is sufficiently expandable to meet the theoretical and clinical intervention design requirements, the personalization algorithm is capable of adapting intervention delivery strategies for simulated real-life conditions.

Adverse drug events (ADEs) are common, costly and a public health issue. Today, their detection relies on medical chart review and spontaneous reports, but this is known to be rather ineffective. Along with the increasing availability of clinical patient data in electronic health records (EHRs), a computer-based ADE detection has a tremendous potential to contribute to patient safety. Current ADE detection systems are very specific, usually built directly on top of clinical information systems through proprietary interfaces. Thus, it is not possible to run different ADE detection tools on top of already existing systems in an ad-hoc manner. The European project "SALUS" aims at providing the necessary infrastructure and toolset for accessing and analyzing clinical patient data of heterogeneous clinical information systems. This paper highlights the SALUS ADE notification system as the key tool to enable a semi-automatic ADE detection and notification. In contrast to previous work, the ADE notification system is not restricted to a specific clinical environment. It can be run on different clinical data models with different levels of data quality. The system is equipped with innovative features, building up an intelligent, comprehensive ADE detection and notification system that promises a profound impact in the domain of computer-based ADE detection.

Improving the efficiency with which clinical research studies are conducted can lead to faster medication innovation and decreased time to market for new drugs. To increase this efficiency, the parties involved in a regulated clinical research study, namely, the sponsor, the clinical investigator and the regulatory body, each with their own software applications, need to exchange data seamlessly. However, currently, the clinical research and the clinical care domains are quite disconnected because each use different standards and terminology systems. In this article, we describe an initial implementation of the Semantic Framework developed within the scope of SALUS project to achieve interoperability between the clinical research and the clinical care domains. In our Semantic Framework, the core ontology developed for semantic mediation is based on the shared conceptual model of both of these domains provided by the BRIDG initiative. The core ontology is then aligned with the extracted semantic models of the existing clinical care and research standards as well as with the ontological representations of the terminology systems to create a model of meaning for enabling semantic mediation. Although SALUS is a research and development effort rather than a product, the current SALUS knowledge base contains around 4.7 million triples representing BRIDG DAM, HL7 CDA model, CDISC standards and several terminology ontologies. In order to keep the reasoning process within acceptable limits without sacrificing the quality of mediation, we took an engineering approach by developing a number of heuristic mechanisms. The results indicate that it is possible to build a robust and scalable semantic framework with a solid theoretical foundation for achieving interoperability between the clinical research and clinical care domains.

Clinical guidelines are developed to assist healthcare practitioners to make decisions on patient's medical problems, and as such they communicate with external applications to retrieve patient data to initiate medical actions through clinical workflows, and transmit information to alert/reminder systems. The interoperability problems in the healthcare information technology domain prevent wider deployment of clinical guidelines because each deployment requires a tedious custom adaptation phase. In this paper, we provide machine-processable mechanisms that express the semantics of clinical guideline interfaces so that automated processes can be used to access the clinical resources for guideline deployment and execution. To be able to deploy the semantically extended guidelines to healthcare settings semiautomatically, the underlying application's semantics must also be available. We describe how this can be achieved based on two prominent implementation technologies in use in the eHealth domain: integrating healthcare enterprise cross-enterprise document sharing integration profile for discovering and exchanging electronic healthcare records and Web service technology for interacting with the clinical workflows and wireless medical sensor devices. The system described in this paper is realized within the scope of the SAPHIRE Project.

As a response to the challenge of providing high-quality healthcare services with reasonable costs while the elderly population and the associated chronic diseases increase, SAPHIRE architecture provides an intelligent healthcare monitoring architecture. The monitoring of patients is achieved through a clinical decision support system based on clinical guidelines. SAPHIRE provides the necessary interoperability layers to access the patient's vital signs from wireless medical sensors and the electronic healthcare records of the patient in order to exploit them in the decision process seamlessly. This architecture is presented through two pilot applications: one for the bedside monitoring of cardiac patients at hospitals, and the other for homecare monitoring of the cardiac patients rehabilitated after a revascularisation therapy.

One of the key problems in healthcare informatics is the inability to share patient records across enterprises. To address this problem, an important industry initiative called "integrating the healthcare enterprise (IHE)" specified the "cross enterprise document sharing (XDS)" profile. In the IHE XDS, healthcare enterprises that agree to work together form a "clinical affinity domain" and store healthcare documents in an ebXML registry/repository architecture to facilitate their sharing. The affinity domains also agree on a common set of policies such as coding lists to be used to annotate clinical documents in the registry/repository and the common schemes for patient identification. However, since patients expect their records to follow them as they move from one clinical affinity domain to another, there is a need for affinity domains to be federated to enable information exchange. In this paper, we describe how IHE XDS can be enhanced to support federated clinical affinity domains. We demonstrate that federation of affinity domains are facilitated when ontologies, rather than coding term lists, are used to annotate clinical documents. Furthermore, we describe a patient identification protocol that eliminates the need to keep a master patient index file for the federation.

Today's Internet based businesses need a level of interoperability which will allow trading partners to seamlessly and dynamically come together and do business without ad hoc and proprietary integrations. Such a level of interoperability involves being able to find potential business partners, discovering their services and business processes, and conducting business "on the fly". This process of dynamic interoperation is only possible through standard B2B frameworks. Indeed a number of B2B electronic commerce standard frameworks have emerged recently. Although most of these standards are overlapping and competing, each with its own strenghts and weeknesses, a closer investigation reveals that they can be used in a manner to complement one another.In this paper we describe such an implementation where an ebXML infrastructure is developed by exploiting the Universal Description, Discovery and Integration (UDDI) registries and RosettaNet Partner Interface Processes (PIPs). ebXML is an ambitious effort and produced detailed specifications of an infrastructure both for B2B and B2C e-commerce. However a public ebXML compliant registry/repository mechanism is not available yet. On the other hand, UDDI's approach to developing a registry has been a lot simpler and public registries are available. In ebXML, trading parties collaborate by agreeing on the same business process with complementary roles. Therefore there is a need for standardized business processes. In this respect, exploiting the already developed expertise through RosettaNet PIPs becomes indispensable. We show how to create and use ebXML "Binary Collaborations" based on RosettaNet PIPs and provide a GUI tool to allow users to graphically build their ebXML business processes by combining RosettaNet PIPs. In ebXML, trading parties reveal essential information about themselves through Collaboration Protocol Profiles (CPPs). To conduct business, an agreement between parties is necessary and this is expressed