Graph databases for openEHR clinical repositories

Samar El Helou, Shinji Kobayashi, Goshiro Yamamoto, Naoto Kume, Eiji Kondoh, Shusuke Hiragi, Kazuya Okamoto, Hiroshi Tamura, Tomohiro Kuroda

研究成果: ジャーナルへの寄稿学術論文査読

11 被引用数 (Scopus)

抄録

The archetype-based approach has now been adopted by major EHR interoperability standards. Soon, due to an increase in EHR adoption, more health data will be created and frequently accessed. Previous research shows that conventional persistence mechanisms such as relational and XML databases have scalability issues when storing and querying archetype-based datasets. Accordingly, we need to explore and evaluate new persistence strategies for archetype-based EHR repositories. To address the performance issues expected to occur with the increase of data, we proposed an approach using labelled property graph databases for implementing openEHR clinical repositories. We implemented the proposed approach using Neo4j and compared it to an object relational mapping (ORM) approach using Microsoft SQL server. We evaluated both approaches over a simulation of a pregnancy home-monitoring application in terms of required storage space and query response time. The results show that the proposed approach provides a better overall performance for clinical querying.

本文言語英語
ページ(範囲)281-298
ページ数18
ジャーナルInternational Journal of Computational Science and Engineering
20
3
DOI
出版ステータス出版済み - 2019
外部発表はい

All Science Journal Classification (ASJC) codes

  • ソフトウェア
  • モデリングとシミュレーション
  • ハードウェアとアーキテクチャ
  • 計算数学
  • 計算理論と計算数学

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