Diego Boscá

LinkEHR-Ed: A multi-reference model archetype editor based on formal semantics

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, is developed. CONCLUSIONS LinkEHR-Ed is a useful tool for building, processing and validating archetypes based on any reference model.

Interoperability of clinical decision-support systems and electronic health records using archetypes

Clinical decision-support systems (CDSSs) comprise systems as diverse as sophisticated platforms to store and manage clinical data, tools to alert clinicians of problematic situations, or decision-making tools to assist clinicians. Irrespective of the kind of decision-support task CDSSs should be smoothly integrated within the clinical information system, interacting with other components, in particular with the electronic health record (EHR). However, despite decades of developments, most CDSSs lack interoperability features. We deal with the interoperability problem of CDSSs and EHRs by exploiting the dual-model methodology. This methodology distinguishes a reference model and archetypes. A reference model is represented by a stable and small object-oriented model that describes the generic properties of health record information. For their part, archetypes are reusable and domain-specific definitions of clinical concepts in the form of structured and constrained combinations of the entities of the reference model. We rely on archetypes to make the CDSS compatible with EHRs from different institutions. Concretely, we use archetypes for modelling the clinical concepts that the CDSS requires, in conjunction with a series of knowledge-intensive mappings relating the archetypes to the data sources (EHR and/or other archetypes) they depend on. We introduce a comprehensive approach, including a set of tools as well as methodological guidelines, to deal with the interoperability of CDSSs and EHRs based on archetypes. Archetypes are used to build a conceptual layer of the kind of a virtual health record (VHR) over the EHR whose contents need to be integrated and used in the CDSS, associating them with structural and terminology-based semantics. Subsequently, the archetypes are mapped to the EHR by means of an expressive mapping language and specific-purpose tools. We also describe a case study where the tools and methodology have been employed in a CDSS to support patient recruitment in the framework of a clinical trial for colorectal cancer screening. The utilisation of archetypes not only has proved satisfactory to achieve interoperability between CDSSs and EHRs but also offers various advantages, in particular from a data model perspective. First, the VHR/data models we work with are of a high level of abstraction and can incorporate semantic descriptions. Second, archetypes can potentially deal with different EHR architectures, due to their deliberate independence of the reference model. Third, the archetype instances we obtain are valid instances of the underlying reference model, which would enable e.g. feeding back the EHR with data derived by abstraction mechanisms. Lastly, the medical and technical validity of archetype models would be assured, since in principle clinicians should be the main actors in their development.

Using the ResearchEHR platform to facilitate the practical application of the EHR standards

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.

Archetype-based semantic integration and standardization of clinical data.

One of the basic needs for any healthcare professional is to be able to access to clinical information of patients in an understandable and normalized way. The lifelong clinical information of any person supported by electronic means configures his/her Electronic Health Record (EHR). This information is usually distributed among several independent and heterogeneous systems that may be syntactically or semantically incompatible. The Dual Model architecture has appeared as a new proposal for maintaining a homogeneous representation of the EHR with a clear separation between information and knowledge. Information is represented by a Reference Model which describes common data structures with minimal semantics. Knowledge is specified by archetypes, which are formal representations of clinical concepts built upon a particular Reference Model. This kind of architecture is originally thought for implantation of new clinical information systems, but archetypes can be also used for integrating data of existing and not normalized systems, adding at the same time a semantic meaning to the integrated data. In this paper we explain the possible use of a Dual Model approach for semantic integration and standardization of heterogeneous clinical data sources and present LinkEHR-Ed, a tool for developing archetypes as elements for integration purposes. LinkEHR-Ed has been designed to be easily used by the two main participants of the creation process of archetypes for clinical data integration: the Health domain expert and the Information Technologies domain expert

An archetype-based solution for the interoperability of computerised guidelines and electronic health records

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.

Semantic upgrade and normalization of existing EHR extracts

We present the mapping and data transformation capabilities of LinkEHR-Ed, a visual tool to construct formal definitions of medical concepts in the form of archetypes which can be defined on the basis on multiple electronic health record architecture such as ISO 13606. With LinkEHR-Ed, users can enrich archetypes with mapping information which captures the relationship between relational or XML data sources and archetype structures. This mapping information is then analyzed and compiled into an XQuery expression that transforms source instances into an XML document. The target document satisfies the constraints imposed by the archetype and at the same time is compliant with the underlying electronic health record architecture.

Isosemantic rendering of clinical information using formal ontologies and RDF

The generation of a semantic clinical infostructure requires linking ontologies, clinical models and terminologies [1]. Here we describe an approach that would permit data coming from different sources and represented in different standards to be queried in a homogeneous and integrated way. Our assumption is that data providers should be able to agree and share the meaning of the data they want to exchange and to exploit. We will describe how Clinical Element Model (CEM) and OpenEHR datasets can be jointly exploited in Semantic Web environments.

Concept-Based Exchange of Healthcare Information: The LinkEHR Approach

the most important requirement to support cooperative work among health professionals is the ability of sharing Electronic Healthcare Records. This is particularly difficult due to the intrinsic complexity and heterogeneity of the health domain. One approach to overcoming heterogeneity relies on the agreement on a set of domain-specific concepts that hide the particularities of the source EHRs. In this paper we present a software platform called Link EHR that empowers concept-based exchange of EHRs by bridging the gap between domain concepts expressed as archetypes and EHRs. Bridging the gap involves: i) editing domain concepts ii) mapping EHR data to reference information models and archetypes, iii) automatically creating data transformation programs to transform source data into archetype instances. We also present the utilization of the Link EHR platform in different settings and for different data exchange purposes.

Automatic generation of computable implementation guides from clinical information models

Clinical information models are increasingly used to describe the contents of Electronic Health Records. Implementation guides are a common specification mechanism used to define such models. They contain, among other reference materials, all the constraints and rules that clinical information must obey. However, these implementation guides typically are oriented to human-readability, and thus cannot be processed by computers. As a consequence, they must be reinterpreted and transformed manually into an executable language such as Schematron or Object Constraint Language (OCL). This task can be difficult and error prone due to the big gap between both representations. The challenge is to develop a methodology for the specification of implementation guides in such a way that humans can read and understand easily and at the same time can be processed by computers. In this paper, we propose and describe a novel methodology that uses archetypes as basis for generation of implementation guides. We use archetypes to generate formal rules expressed in Natural Rule Language (NRL) and other reference materials usually included in implementation guides such as sample XML instances. We also generate Schematron rules from NRL rules to be used for the validation of data instances. We have implemented these methods in LinkEHR, an archetype editing platform, and exemplify our approach by generating NRL rules and implementation guides from EN ISO 13606, openEHR, and HL7 CDA archetypes.

Detailed Clinical Models Governance System in a Regional EHR Project

In this work we present the Concept Oriented Repository (ROC), a system developed for the management of clinical information models, also known as detailed clinical models (DCM). It has been developed to be used in the Electronic Health Record project of the Valencia regional health agency (AVS). The system uses DCMs as a way to define clinical models independently of the healthcare standard chosen by the organization. These definitions create a framework where different actors can come to agreements on which information has to be represented and managed in the project. These concepts can be used later for the definition of technical artifacts (archetypes, templates, forms or message definitions) to be used by AVS information systems.