Revista de Saúde e Informática Médica

A Model-Driven Based Methodology for the Generation of Context-Aware Medical Interfaces from Open EHR Archetypes

Abstract

Afef Samet Ellouzea*,Sandra Hammami Tlilia,Rafik Bouazizb

Purpose: Different medical computer science standards, such as ISO\EN 13606, openEHR and HL7 CDA, use the dual model approach to support interoperability between medical information systems. However, use of these standards encounters some obstacles: (i) lack methodological tools to facilitate design of Electronic Health Record (EHR) systems in accordance to two conceptual levels, (ii) Lack of methodologies to perform semantic activities on EHR content in the semantic web environment, and (iii) Absence of models to adapt medical knowledge, modelled by means of archetypes, in different contexts of use. This paper presents a model-driven based methodology for the generation of context-aware medical interfaces. This methodology, entitled OpenEHR modelling Methodology: OpenEHR-MM includes concepts, models, rules, processes and tools aimed to assist EHR designer in the generation process of context-aware medical interfaces.

Methods: OpenEHR-MM is based on the use of the model driven architecture technological space, and it includes the following four steps:

1. Analysis and specification of requirements: This first step aims to guide EHR interface designer in the definition of users’ needs.

2. Conceptualization: This step aims to define tools, concepts and approaches that assist EHR designer in the two conceptual levels modelling process. At this step, we define an approach to provide the context information modelling.

3. Ontologization: This step aims to assist the designer to integrate the semantic dimension in the EHR systems modeled in accordance to the dual model approach.

4. Implementation: Finally, OpenEHR-MM provides an adaptive approach to enable medical interface configuration with respect to contexts settings.

Results: A model driven-based methodology for context-aware medical interfaces generation process. The experimentation of this methodology is performed on the EHR related to patients affected by cerebral palsy.