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Published on: January 22, 2011

Developing a national emergency department data reference set based on SNOMED CT.

David P Hansen¹, Madonna L Kemp, Sandra R Mills

¹Australian e-Health Research Centre, CSIRO ICT Centre, Brisbane, QLD, Australia. David.Hansen@csiro.au

The Medical Journal of Australia

|March 16, 2011

Summary

This summary is machine-generated.

Australian emergency departments are adopting Systematized Nomenclature of Medicine--Clinical Terms (SNOMED CT) for standardized patient data. Mapping existing terms using the Snapper software improves data consistency and clinical decision-making.

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Area of Science:

Health Informatics
Clinical Terminology
Emergency Medicine

Background:

Australian emergency departments utilize diverse software for patient data, often based on ICD-10-AM codes.
Existing terminologies vary across departments, leading to data inconsistencies.
The National E-Health Transition Authority is promoting SNOMED CT for a unified e-health infrastructure.

Purpose of the Study:

To develop and implement a national SNOMED CT reference set for Australian emergency departments.
To facilitate the mapping of existing clinical terms to SNOMED CT.
To enhance the standardization and utility of emergency department data.

Main Methods:

Development of the Snapper software platform for mapping clinical terms.
Creation of reference sets based on SNOMED CT-AU for emergency departments.
Integration of SNOMED CT reference sets into existing emergency department software systems.

Main Results:

The Snapper software enables efficient mapping of existing terms to SNOMED CT.
Reference sets for emergency departments are being established using SNOMED CT-AU.
Standardized data recording at the point of care is becoming feasible.

Conclusions:

Mapping to a national SNOMED CT reference set promotes consistency in emergency department data.
Standardized data improves patient admission/discharge summaries and clinical decision support.
This initiative enhances the clinical and analytical value of emergency department data.