A Model-Driven Approach to Customize the Vocabulary of Communication Boards: Towards More Humanization of Health Care

Objective: This work presents a Modeling Language and its technological infrastructure to customize the vocabulary of Communication Boards (CB), which are important tools to provide more humanization of health care. Method: Using a technological infrastructure based on Model-Driven Development (MDD) approach, our Modeling Language (ML) creates an abstraction layer between users (e.g., health professionals such as an audiologist or speech therapist) and application code. Moreover, the use of a metamodel enables a syntactic corrector for preventing creation of wrong models. Results: Our ML and metamodel enable more autonomy for health professionals in creating customized CB because it abstracts complexities and permits them to deal only with the domain concepts (e.g., vocabulary and patient needs). Additionally, our infrastructure provides a configuration file that can be used to share and reuse models. This way, the vocabulary modeling effort will decrease over time since people share vocabulary models. Conclusion: Our study provides an infrastructure that aims to abstract the complexity of CB vocabulary customization, giving more autonomy to health professionals when they need customizing, sharing and reusing vocabularies for CB.