A comparison of the effects of different typographical methods on the recognizability of printed drug names.
BACKGROUND
Tall Man lettering is a text enhancement method currently recommended by various organizations for distinguishing look-alike drug names to prevent medication errors. However, the literature has suggested that other typographic styles may be more effective.


OBJECTIVE
Our objective was to examine the effects of text enhancements and orthographic similarity on the accuracy of look-alike drug name differentiation.


METHODS
We conducted two experiments that were based on a two-way, repeated-measures design with text enhancement (Tall Man, boldface, boldface plus Tall Man, colored text [red] and contrast with lowercase as a 'no text enhancement' control) and orthographic similarity (low, medium, and high) as factors. Engineering students without a pharmacy background in experiment 1 (n = 40) and student pharmacists in experiment 2 (n = 40) participated in a computer-based drug name differentiation task in which they determined whether the two drug names in each of the 336 name pairs were the same or different. Only the data generated from the pairs in which the two names were different were used in the analysis. The differentiation accuracy was measured as the proportion of correct responses.


RESULTS
In both experiments, all five text enhancements significantly improved accuracy compared with the lowercase condition; and boldface plus Tall Man and color significantly outperformed Tall Man lettering. A high degree of orthographic similarity yielded the least accuracy, followed by medium and low degrees.


CONCLUSIONS
Highlighting the differing portions of confusing drug name pairs using enhanced text clearly renders differentiation easier, although Tall Man lettering may not be the most effective choice for this method.
Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam, Hong Kong, klor@hku.hk.
Calvin K L
CK
Or
Hailiang
H
Wang
D000328:Adult; D003201:Computers; D004348:Drug Labeling / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D008508:Medication Errors / Q000517:prevention & control*; D055815:Young Adult