Universal database vs eav modeling12/6/2023 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.
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