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A method for encoding clinical datasets with SNOMED CT.

Dennis H Lee1, Francis Y Lau, Hue Quan

  • 1School of Health Information Science, University of Victoria, Human & Social Development Building A202, Victoria, BC V8P 5C2, Canada.

BMC Medical Informatics and Decision Making
|September 21, 2010
PubMed
Summary
This summary is machine-generated.

This study presents a heuristic method for encoding clinical terms into Systematised Nomenclature of Medicine Clinical Terms (SNOMED CT). The approach successfully encoded approximately 84% of terms in a palliative care dataset, demonstrating its potential for broader clinical applications.

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Area of Science:

  • Medical Informatics
  • Clinical Terminology Management
  • Health Data Standards

Background:

  • Growing literature on Systematised Nomenclature of Medicine Clinical Terms (SNOMED CT) implementation in clinical settings.
  • Lack of detailed encoding instructions and examples for integrating SNOMED CT into clinical applications.
  • Need for practical methods to encode existing clinical datasets into SNOMED CT.

Purpose of the Study:

  • To describe a heuristic method for encoding clinical terms into SNOMED CT.
  • To illustrate the application of this method using a palliative care dataset.
  • To assess the feasibility and effectiveness of the proposed encoding approach.

Main Methods:

  • A four-step encoding process: identifying, cleaning, encoding, and exporting data items.
  • Development of a heuristic method for systematic SNOMED CT encoding.
  • Application of the method to a palliative care dataset, generating multiple output term sets.

Main Results:

  • Successfully encoded approximately 84% of terms from the palliative care database.
  • Identified ~8% of terms requiring further encoding and verification.
  • Determined that terms with a frequency of fewer than five were not encoded (~7%).

Conclusions:

  • The developed SNOMED CT encoding method shows potential as a general-purpose approach.
  • The method can be adapted for use across different clinical information systems.
  • The pilot study validates the heuristic method's applicability in real-world clinical data.