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BMC Medical Informatics and Decision Making
Published in: BMC Medical Informatics and Decision Making 1/2015

Open Access 01-12-2015 | Research article

Archetype relational mapping - a practical openEHR persistence solution

Authors: Li Wang, Lingtong Min, Rui Wang, Xudong Lu, Huilong Duan

Published in: BMC Medical Informatics and Decision Making | Issue 1/2015

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Abstract

Background

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.

Methods

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.

Results

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.

Conclusions

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.
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Metadata
Title
Archetype relational mapping - a practical openEHR persistence solution
Authors
Li Wang
Lingtong Min
Rui Wang
Xudong Lu
Huilong Duan
Publication date
01-12-2015
Publisher
BioMed Central
Published in
BMC Medical Informatics and Decision Making / Issue 1/2015
Electronic ISSN: 1472-6947
DOI
https://doi.org/10.1186/s12911-015-0212-0

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