Open data models for smart health interconnected applications: the example of openEHR

Area of Science:

• Health Informatics
• Software Engineering
• Data Science

Background:

• Smart Health leverages networking and intelligent data processing to integrate patient data.
• Open data models are crucial for creating interoperable data services supporting Smart Health innovation.
• Data fusion and sharing are key to developing advanced Smart Health applications.

Purpose of the Study:

• To present a model-driven engineering approach for developing interoperable electronic health record (EHR) systems.
• To explore the application of standardized clinical information models in EHR development.
• To demonstrate the practical use of this approach within the openEHR framework.

Main Methods:

• Utilized a model-driven engineering approach based on standardized clinical information models.
• Investigated procedures for data scheme provision, automated artifact generation, and model execution.
• Applied the openEHR framework to examine the practical applicability of the approach.

Main Results:

• Presented a comprehensive infrastructure for model-driven EHR engineering using openEHR.
• Demonstrated derivation of data schema definitions from domain models for software development.
• Showcased automatic creation of implementation artifacts like data entry forms.
• Introduced programming libraries and compatible health data platforms supporting open data models and interoperability.

Conclusions:

• Open data models establish a framework for interoperable data services, crucial for innovative Smart Health applications.
• Model-driven development tools enhance semantic interoperability and foster interconnected applications.
• The presented approach facilitates the development of advanced, interoperable health data systems.