Catalina Martínez-Costa

A model-driven approach for representing clinical archetypes for Semantic Web environments

The life-long clinical information of any person supported by electronic means configures his Electronic Health Record (EHR). This information is usually distributed among several independent and heterogeneous systems that may be syntactically or semantically incompatible. There are currently different standards for representing and exchanging EHR information among different systems. In advanced EHR approaches, clinical information is represented by means of archetypes. Most of these approaches use the Archetype Definition Language (ADL) to specify archetypes. However, ADL has some drawbacks when attempting to perform semantic activities in Semantic Web environments. In this work, Semantic Web technologies are used to specify clinical archetypes for advanced EHR architectures. The advantages of using the Ontology Web Language (OWL) instead of ADL are described and discussed in this work. Moreover, a solution combining Semantic Web and Model-driven Engineering technologies is proposed to transform ADL into OWL for the CEN EN13606 EHR architecture.

An approach for the semantic interoperability of ISO EN 13606 and OpenEHR archetypes

The communication between health information systems of hospitals and primary care organizations is currently an important challenge to improve the quality of clinical practice and patient safety. However, clinical information is usually distributed among several independent systems that may be syntactically or semantically incompatible. This fact prevents healthcare professionals from accessing clinical information of patients in an understandable and normalized way. In this work, we address the semantic interoperability of two EHR standards: OpenEHR and ISO EN 13606. Both standards follow the dual model approach which distinguishes information and knowledge, this being represented through archetypes. The solution presented here is capable of transforming OpenEHR archetypes into ISO EN 13606 and vice versa by combining Semantic Web and Model-driven Engineering technologies. The resulting software implementation has been tested using publicly available collections of archetypes for both standards.

A semantic web-based system for managing clinical archetypes

Archetypes facilitate the sharing of clinical knowledge and therefore are a basic tool for achieving interoperability between healthcare information systems. In this paper, a Semantic Web System for Managing Archetypes is presented. This system allows for the semantic annotation of archetypes, as well for performing semantic searches. The current system is capable of working with both ISO13606 and OpenEHR archetypes.

An Ontological Analysis of Reference in Health Record Statements

The relation between an information entity and its referent can be described as a second-order statement, as long as the referent is a type. This is typical for medical discourse such as diagnostic ...

Semantic enrichment of clinical models towards semantic interoperability. The heart failure summary use case

OBJECTIVE To improve semantic interoperability of electronic health records (EHRs) by ontology-based mediation across syntactically heterogeneous representations of the same or similar clinical information. MATERIALS AND METHODS Our approach is based on a semantic layer that consists of: (1) a set of ontologies supported by (2) a set of semantic patterns. The first aspect of the semantic layer helps standardize the clinical information modeling task and the second shields modelers from the complexity of ontology modeling. We applied this approach to heterogeneous representations of an excerpt of a heart failure summary. RESULTS Using a set of finite top-level patterns to derive semantic patterns, we demonstrate that those patterns, or compositions thereof, can be used to represent information from clinical models. Homogeneous querying of the same or similar information, when represented according to heterogeneous clinical models, is feasible. DISCUSSION Our approach focuses on the meaning embedded in EHRs, regardless of their structure. This complex task requires a clear ontological commitment (ie, agreement to consistently use the shared vocabulary within some context), together with formalization rules. These requirements are supported by semantic patterns. Other potential uses of this approach, such as clinical models validation, require further investigation. CONCLUSION We show how an ontology-based representation of a clinical summary, guided by semantic patterns, allows homogeneous querying of heterogeneous information structures. Whether there are a finite number of top-level patterns is an open question.

Ontology Content Patterns as Bridge for the Semantic Representation of Clinical Information

OBJECTIVE Semantic interoperability of the Electronic Health Record (EHR) requires a rigorous and precise modelling of clinical information. Our objective is to facilitate the representation of clinical facts based on formal principles. METHODS We here explore the potential of ontology content patterns, which are grounded on a formal and semantically rich ontology model and can be specialised and composed. RESULTS We describe and apply two content patterns for the representation of data on tobacco use, rendered according to two heterogeneous models, represented in openEHR and in HL7 CDA. Finally, we provide some query exemplars that demonstrate a data interoperability use case. CONCLUSION The use of ontology content patterns facilitate the semantic representation of clinical information and therefore improve their semantic interoperability. There are open issues such as the scalability and performance of the approach if a logic-based language is used. Implementation decisions might determine the final degree of semantic interoperability, influenced by the state of the art of the semantic technologies.

A Generative Tool for Building Health Applications Driven by ISO 13606 Archetypes

The use of Electronic Healthcare Records (EHR) standards in the development of healthcare applications is crucial for achieving the semantic interoperability of clinical information. Advanced EHR standards make use of the dual model architecture, which provides a solution for clinical interoperability based on the separation of the information and knowledge. However, the impact of such standards is biased by the limited availability of tools that facilitate their usage and practical implementation. In this paper, we present an approach for the automatic generation of clinical applications for the ISO 13606 EHR standard, which is based on the dual model architecture. This generator has been generically designed, so it can be easily adapted to other dual model standards and can generate applications for multiple technological platforms. Such good properties are based on the combination of standards for the representation of generic user interfaces and model-driven engineering techniques.

A semantic web based framework for the interoperability and exploitation of clinical models and EHR data

The advent of electronic healthcare records (EHR) systems has triggered the need for their semantic interoperability, which is reinforced by the opportunities for the secondary use of EHR data. The joint use of EHR standards and semantic resources has been identified as key for semantic interoperability. To date, existing tools focused on EHR standards permit to create, search, explore clinical models and to map data sources to clinical models, but do not provide an appropriate support and integration of semantic resources or permit the secondary use of EHR data. In this paper we describe an OWL-based framework that leverages EHR and Semantic Web technologies for the interoperability and exploitation of archetypes, EHR data and ontologies. It also enables the secondary use of clinical data. This framework has been implemented in the Archetype Management System (ArchMS). We also describe how ArchMS has been used in a real study in the colorectal cancer domain.

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.

Ontology-Based Reengineering of the SNOMED CT Context Model

SNOMED CT is a terminology system partially built on formalontological principles. Although its on-going redesign efforts increasingly consider principles of formal ontology, SNOMED CT’s top-level categories and relations still reflect the legacy of its predecessors rather than formal ontological principles. This is apparent in its Context Model, which blends characteristics of information models with characteristics of ontologies. We propose a reengineering of the SNOMED CT Context Model formulated with ontology design patterns based on the BioTopLite upper ontology. Our analysis yields a clear division between clinical situations in a strict sense and information artefacts that denote clinical situations.