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Updated: Jul 8, 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

Making the connection between standard terminologies, use cases and mapping.

Kathy Giannangelo¹

¹American Health Information Management Association, Chicago, IL 62707, USA. kathy.giannangelo@ahima.org

Health Information Management : Journal of the Health Information Management Association of Australia

|January 16, 2008

Summary

This summary is machine-generated.

Standard terminologies in electronic health records (EHR) enable efficient data use for administration and policy. Mapping tables link new clinical data codes to legacy systems, promoting data reuse and consistency.

Related Experiment Videos

Last Updated: Jul 8, 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

Area of Science:

Health Informatics
Clinical Data Management
Standardized Terminologies

Background:

Clinical data capture at the point of care is crucial for healthcare operations.
Standard terminologies facilitate efficient data utilization for administrative and secondary purposes.
Legacy terminologies pose challenges for integrating and analyzing current clinical data.

Purpose of the Study:

To demonstrate the value of standard terminologies in electronic health records (EHR).
To highlight the utility of mapping tables for data interoperability.
To support the 'code once, use many times' philosophy in clinical data management.

Main Methods:

Utilizing clinical data captured via standard terminologies in EHR systems.
Developing and applying mapping tables to link standard codes to legacy terminologies.
Focusing on specific use cases to refine mapping table utility.

Main Results:

Standard terminologies enable efficient and effective use of clinical data for diverse purposes.
Mapping tables facilitate the identification of related codes in legacy terminologies.
The approach supports administrative functions, statistics trending, and health policy decision-making.

Conclusions:

Standardized clinical data capture in EHRs is essential for secondary data use.
Mapping tables are vital tools for bridging legacy and standard terminologies.
This methodology enhances data reproducibility, understandability, and utility across healthcare systems.