Evaluating Terminologies to Enable Imaging-Related Decision Rule Sharing

AMIA Annu Symp Proc. 2017 Feb 10:2016:2082-2089. eCollection 2016.

Abstract

Purpose: Clinical decision support tools provide recommendations based on decision rules. A fundamental challenge regarding decision rule-sharing involves inadequate expression using standard terminology. We aimed to evaluate the coverage of three standard terminologies for mapping imaging-related decision rules. Methods: 50 decision rules, randomly selected from an existing library, were mapped to Systemized Nomenclature of Medicine (SNOMED CT), Radiology Lexicon (RadLex) and International Classification of Disease (ICD-10-CM). Decision rule attributes and values were mapped to unique concepts, obtaining the best possible coverage with the fewest concepts. Manual and automated mapping using Clinical Text Analysis and Knowledge Extraction System (cTAKES) were performed. Results: Using manual mapping, SNOMED CT provided the greatest concept coverage (83%), compared to RadLex (36%) and ICD-10-CM (8%) (p<0.0001). Combined mapping had 86% concept coverage. Automated mapping achieved 85% mapping coverage vs. 94% with manual mapping (p<0.001). Conclusion: Although some gaps remain, standard terminologies provide ample coverage for mapping imaging- related evidence.

MeSH terms

  • Decision Support Systems, Clinical*
  • Decision Support Techniques
  • Humans
  • Information Storage and Retrieval*
  • International Classification of Diseases
  • Natural Language Processing
  • Radiography / classification
  • Radiology Information Systems*
  • Radiology*
  • Systematized Nomenclature of Medicine
  • Vocabulary, Controlled*