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Related Experiment Video

Updated: Jun 21, 2026

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

Achieving clinical statement interoperability using R-MIM and archetype-based semantic transformations.

Ozgur Kilic¹, Asuman Dogac

¹Department of Computer Engineering, Middle East Technical University, 06531 Ankara, Turkey.

IEEE Transactions on Information Technology in Biomedicine : a Publication of the IEEE Engineering in Medicine and Biology Society

|July 10, 2009

Summary

This study demonstrates a method for mapping electronic healthcare records (EHRs) between different standards. It uses archetypes and semantic tools to ensure interoperability and accurate data sharing in healthcare information technology.

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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

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Executing Complexity-Increasing Queries in Relational (MySQL) and NoSQL (MongoDB and EXist) Size-Growing ISO/EN 13606 Standardized EHR Databases

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Published on: March 19, 2018

Area of Science:

Health Informatics
Computer Science

Background:

Electronic healthcare records (EHRs) are crucial for improving healthcare quality and cost-efficiency.
Sharing patient EHRs globally is a priority in healthcare information technology.

Purpose of the Study:

To address the interoperability of EHR structure and content.
To demonstrate a method for mapping between different EHR standards derived from the same reference information model (RIM).

Main Methods:

Utilizing archetypes, refined message information model (R-MIM) derivations, and semantic tools.
Employing well-defined R-MIM derivation rules to trace class properties and identify equivalences.
Inferring derivation statements from Web Ontology Language definitions of the RIM, R-MIMs, and archetypes.

Main Results:

Successfully mapped clinical statements between two different EHR standards (Health Level Seven and EHRcom).
Demonstrated that R-MIM derivation rules facilitate tracing properties and finding equivalences.
Showcased the use of archetype semantics for finer granularity in mapping clinical statements.

Conclusions:

A robust method for achieving EHR interoperability using archetypes and semantic tools has been presented.
The proposed approach enables accurate transformation of clinical statement instances between different EHR standards.
This facilitates seamless data sharing and enhances the effectiveness of EHR systems.