Identification of confusable drug names: a new approach and evaluation methodology

  • Authors:
  • Grzegorz Kondrak;Bonnie Dorr

  • Affiliations:
  • University of Alberta Edmonton, Alberta, Canada;University of Maryland, College Park

  • Venue:
  • COLING '04 Proceedings of the 20th international conference on Computational Linguistics
  • Year:
  • 2004

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Abstract

This paper addresses the mitigation of medical errors due to the confusion of sound-alike and look-alike drug names. Our approach involves application of two new methods---one based on orthographic similarity ("look-alike") and the other based on phonetic similarity ("sound-alike"). We present a new recall-based evaluation methodology for determining the effectiveness of different similarity measures on drug names. We show that the new orthographic measure (BI-SIM) outperforms other commonly used measures of similarity on a set containing both look-alike and sound-alike pairs, and that the feature-based phonetic approach (ALINE) outperforms orthographic approaches on a test set containing solely sound-alike confusion pairs. However, an approach that combines several different measures achieves the best results on both test sets.