#Universal database vs eav modeling series

In the single-level modelling approach, domain concepts that are processed by the EHR system are hard-coded directly into the application and database models. Among these three paradigms, the separation of information models, domain content models and terminologies promotes a significant shift from the single-level modelling approach of information system development to a two-level modelling approach.

The concept of openEHR focuses on systems and tools necessary to the computation of complex and constantly evolving health information at a semantic level, according to the following three paradigms: separation of information models, domain content models, and terminologies separation of responsibilities and separation of viewpoints. Solutions span from information modelling to system architecture, to meet the continually evolving needs of EHR systems.

#Universal database vs eav modeling series

In order to protect EHR systems from changes in the healthcare domain, openEHR has published a series of specifications to guide the development of future-proof EHR systems. Highly-specialized and complex EHR systems cannot acclimate to the evolution of healthcare data requirements, which require EHR systems to embrace a dynamic, state-of-the-art, rapidly evolving information infrastructure.

However, healthcare data is generally too complicated, flexible, and changeable to capture a universal, comprehensive and stable schema of information, which is the foundation of the entire EHR architecture. EHR is a repository of information regarding the health status of a subject of care in computer processable form. System components such as ARM can greatly facilitate the adoption of openEHR architecture within EHR systems.Ĭurrently, an electronic health record (EHR) system is essential to support clinical practice with information technology in healthcare environments. ARM performance is similar to that of conventionally-designed EHR systems, and can be applied in a practical clinical environment. The ARM approach is capable of generating relational databases using archetypes and templates for archetype-based EHR systems, thus successfully adapting to changes in data requirements. The ARM database was approximately 6–50 times more efficient than the conventional database in the patient-searching tests, while the Node + Path database requires far more time than the other two databases to execute both the data-retrieving and the patient-searching tests. The time difference of query executions conducted by the ARM database and the conventional database is less than 130 %. The ARM database achieved better performance than the conventional database in three of the five data-retrieving tests, but was less efficient in the remaining two tests. Additionally, two patient-searching tests were designed to identify patients who satisfy certain criteria. Five data-retrieving tests were designed based on clinical workflow to retrieve exams and laboratory tests. ResultsĪ comparison study was conducted to investigate the differences among the conventional database of an EHR system from a tertiary Class A hospital in China, the generated ARM database, and the Node + Path database.

Finally, a set of rules is designed to map the archetypes to data tables and provide data persistence based on the relational database. Next, a template is designed for each archetype to apply constraints related to the local EHR context. The Clinical Knowledge Manager (CKM) is queried for matching archetypes when necessary, new archetypes are developed to reflect concepts that are not encompassed by existing archetypes. Methodsįirst, the data requirements of the EHR systems are analysed and organized into archetype-friendly concepts. This paper presents an archetype relational mapping (ARM) persistence solution for the archetype-based EHR systems to support healthcare delivery in the clinical environment. One of the primary obstacles to the widespread adoption of openEHR methodology is the lack of practical persistence solutions for future-proof electronic health record (EHR) systems as described by the openEHR specifications.