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- Title
Archetype relational mapping - a practical openEHR persistence solution.
- Authors
Li Wang; Lingtong Min; Rui Wang; Xudong Lu; Huilong Duan; Wang, Li; Min, Lingtong; Wang, Rui; Lu, Xudong; Duan, Huilong
- Abstract
<bold>Background: </bold>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. This paper presents an archetype relational mapping (ARM) persistence solution for the archetype-based EHR systems to support healthcare delivery in the clinical environment.<bold>Methods: </bold>First, the data requirements of the EHR systems are analysed and organized into archetype-friendly concepts. 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. Next, a template is designed for each archetype to apply constraints related to the local EHR context. Finally, a set of rules is designed to map the archetypes to data tables and provide data persistence based on the relational database.<bold>Results: </bold>A 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. Five data-retrieving tests were designed based on clinical workflow to retrieve exams and laboratory tests. Additionally, two patient-searching tests were designed to identify patients who satisfy certain criteria. 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. The time difference of query executions conducted by the ARM database and the conventional database is less than 130 %. 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.<bold>Conclusions: </bold>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. ARM performance is similar to that of conventionally-designed EHR systems, and can be applied in a practical clinical environment. System components such as ARM can greatly facilitate the adoption of openEHR architecture within EHR systems.
- Subjects
ELECTRONIC health records; KNOWLEDGE management; MEDICAL informatics; INFORMATION retrieval; MEDICAL practice; MEDICAL decision making; DATABASES; MEDICAL care
- Publication
BMC Medical Informatics & Decision Making, 2015, Vol 15, p1
- ISSN
1472-6947
- Publication type
journal article
- DOI
10.1186/s12911-015-0212-0