Independently of implementation technologies and standards, it is possible to find common patterns in methods for developing CIMs, suggesting the viability of defining a unified good practice methodology to be used by any clinical information modeler.

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Purpose. To develop a powerful archetype editing framework capable of handling multiple reference models and oriented towards the semantic description and standardization of legacy data.Methods. The main prerequisite for implementing tools providing enhanced support for archetypes is the clear specification of archetype semantics. We propose a formalization of the definition section of archetypes based on types over tree-structured data. It covers the specialization of archetypes, the relationship between reference models and archetypes and conformance of data instances to archetypes.Results. LinkEHR-Ed a visual archetype editor based on the former formalization with advanced processing capabilities that supports multiple reference models, the editing and semantic validation of archetypes, the specification of mappings to data sources, and the automatic generation of data transformation scripts.Conclusions. LinkEHR-Ed is a useful tool for building, processing and validating archetypes based on any reference model.

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Clinical Information Models (CIMs) expressed as archetypes play an essential role in the design and development of current Electronic Health Record (EHR) information structures. Although there exist many experiences about using archetypes in the literature, a comprehensive and formal methodology for archetype modeling does not exist. Having a modeling methodology is essential to develop quality archetypes, in order to guide the development of EHR systems and to allow the semantic interoperability of health data. In this work, an archetype modeling methodology is proposed. This paper describes its phases, the inputs and outputs of each phase, and the involved participants and tools. It also includes the description of the possible strategies to organize the modeling process. The proposed methodology is inspired by existing best practices of CIMs, software and ontology development. The methodology has been applied and evaluated in regional and national EHR projects. The application of the methodology provided useful feedback and improvements, and confirmed its advantages. The conclusion of this work is that having a formal methodology for archetype development facilitates the definition and adoption of interoperable archetypes, improves their quality, and facilitates their reuse among different information systems and EHR projects. Moreover, the proposed methodology can be also a reference for CIMs development using any other formalism.

Possibly the most important requirement to support co-operative work among health professionals and institutions is the ability of sharing EHRs in a meaningful way, and it is widely acknowledged that standardization of data and concepts is a prerequisite to achieve semantic interoperability in any domain. Different international organizations are working on the definition of EHR architectures but the lack of tools that implement them hinders their broad adoption. In this paper we present ResearchEHR, a software platform whose objective is to facilitate the practical application of EHR standards as a way of reaching the desired semantic interoperability. This platform is not only suitable for developing new systems but also for increasing the standardization of existing ones. The work reported here describes how the platform allows for the edition, validation, and search of archetypes, converts legacy data into normalized, archetypes extracts, is able to generate applications from archetypes and finally, transforms archetypes and data extracts into other EHR standards. We also include in this paper how ResearchEHR has made possible the application of the CEN/ISO 13606 standard in a real environment and the lessons learnt with this experience.

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Abstract. Clinical guidelines contain recommendations based on the best empirical evidence available at the moment. There is a wide consensus about the benefits of guidelines and about the fact that they should be deployed through clinical information systems, making them available during consultation time. However, one of the main obstacles to this integration is still the interaction with the electronic health record. In this paper we present an archetype-based approach to solve the interoperability problems of guideline systems, as well as to enable guideline sharing. We also describe the knowledge requirements for the development of archetype-enabled guideline systems, and then focus on the development of appropriate guideline archetypes and on the connection of these archetypes to the target electronic health record.