Title
Entity Attribute Value Style Modeling Approach For Archetype Based Data
Abstract
Entity Attribute Value (EAV) storage model is extensively used to manage healthcare data in existing systems, however it lacks search efficiency. This study examines an entity attribute value style modeling approach for standardized Electronic Health Records (EHRs) database. It sustains qualities of EAV (i.e., handling sparseness and frequent schema evolution) and provides better performance for queries in comparison to EAV. It is termed as the Two Dimensional Entity Attribute Value (2D EAV) model. Support for ad-hoc queries is provided through a user interface for better user-interaction. 2D EAV focuses on how to handle template-centric queries as well as other health query scenarios. 2D EAV is analyzed (in terms of minimum non-null density) to make a judgment about the adoption of 2D EAV over n-ary storage model of RDBMS. The primary aim of current research is to handle sparseness, frequent schema evolution, and efficient query support altogether for standardized EHRs. 2D EAV will benefit data administrators to handle standardized heterogeneous data that demands high search efficiency. It will also benefit both skilled and semi-skilled database users (such as, doctors, nurses, and patients) by providing a global semantic interoperable mechanism of data retrieval.
Year
DOI
Venue
2018
10.3390/info9010002
INFORMATION
Keywords
Field
DocType
entity attribute value model, Electronic Health Records (EHRs), standardization, archetype based EHRs
Data mining,Information retrieval,Interoperability,Computer science,Data retrieval,Storage model,Relational database management system,User interface,Schema evolution,Standardization,Entity–attribute–value model
Journal
Volume
Issue
ISSN
9
1
2078-2489
Citations 
PageRank 
References 
0
0.34
13
Authors
3
Name
Order
Citations
PageRank
Shivani Batra174.30
Shelly Sachdeva211217.13
Subhash Bhalla330084.64