Standardized electronic health record data modeling and persistence: A comparative review

[Display omitted] •Each storage model offers different performance according to application scenario.•EHRs usage scenarios are divided into two main tasks: primary use and secondary use.•NoSQL data models provide superior solutions for managing standardized EHRs data.•Polyglot stores are a hybrid da...

Full description

Saved in:
Bibliographic Details
Published inJournal of biomedical informatics Vol. 114; p. 103670
Main Authors Gamal, Aya, Barakat, Sherif, Rezk, Amira
Format Journal Article
LanguageEnglish
Published United States Elsevier Inc 01.02.2021
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:[Display omitted] •Each storage model offers different performance according to application scenario.•EHRs usage scenarios are divided into two main tasks: primary use and secondary use.•NoSQL data models provide superior solutions for managing standardized EHRs data.•Polyglot stores are a hybrid database architecture solution. With the extensive adoption of electronic health records (EHRs) by several healthcare organizations, more efforts are needed to manage and utilize such massive, various, and complex healthcare data. Databases' performance and suitability to health care tasks are dramatically affected by how their data storage model and query capabilities are well-adapted to the use case scenario. On the other hand, standardized healthcare data modeling is one of the most favorable paths for achieving semantic interoperability, facilitating patient data integration from different healthcare systems. This paper compares the state-of-the-art of the most crucial database management systems used for storing standardized EHRs data. It discusses different database models' appropriateness for meeting different EHRs functions with different database specifications and workload scenarios. Insights into relevant literature show how flexible NoSQL databases (document, column, and graph) effectively deal with standardized EHRs data's distinctive features, especially in the distributed healthcare system, leading to better EHR.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-3
content type line 23
ObjectType-Review-1
ISSN:1532-0464
1532-0480
DOI:10.1016/j.jbi.2020.103670