A Similarity-Based Approach and Evaluation Methodology for Reduction of Drug Name Confusion

Abstract

This paper facilitates the task of mitigating medical errors due to the confusion of look-alike and sound-alike drug names. Detection of potential confusion is based on both feature-based phonetic comparison (for sound-alike drug names) and orthographic similarity (for look-alike drug names). We present a new recall-based evaluation methodology for determining the effectiveness of different similarity measures on drug names. Using this methodology, we show that a new orthographic measure called BI-SIM outperforms other commonly used measures of similarity on a set containing both look-alike and sound-alike pairs, In addition, we demonstrate that the feature-based phonetic approach outperforms other standard approaches on a test set containing solely look-alike confusion pairs. However, an approach that combines several different approaches achieves the best results on both test sets.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2003
Accession Number
ADA452242

Entities

People

  • Bonnie J. Dorr
  • Grzegorz Kondrak

Organizations

  • University of Alberta

Tags

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Computational Linguistics
  • Computer Programming
  • Computer Science
  • Computers
  • Detection
  • Drug Therapy
  • Dynamic Programming
  • Errors
  • Language
  • Linguistics
  • Neurobehavioral Manifestations
  • Pattern Recognition
  • Test And Evaluation
  • Test Sets
  • United States

Readers

  • Computational Linguistics
  • Computational Modeling and Simulation
  • Speech Processing/Speech Recognition.