Similarity As a Risk Factor in Drug-Name Confusion Errors

The Look-Alike (Orthographic) and Sound-Alike (Phonetic) Model

Bibliographic Data

ID9099035
AuthorsBruce L Lambert (University of Illinois Chicago, corresponding author), Shu-Jung Lin (0000-0003-0953-9988, corresponding author), Swu-Jane Lin, Ken-Yu Chang (corresponding author), Sanjay K Gandhi, Sanjay Gandhi (0000-0003-4782-3883, corresponding author)
Year1999
Volume37
Issue12
Pages1214-1225
Publication date1999-12-01
Open AccessNo
TypeARTICLE
VenueMedical Care (JOURNAL)
Journal identifiersISSN: 0025-7079 • E-ISSN: 1537-1948
PublisherOvid Technologies (Wolters Kluwer Health) (PUBLISHER)
DOI10.1097/00005650-199912000-00005
PMID10599603
OpenAlexW2008060909
LanguageEN
Citations received6
References cited17

BACKGROUND: One of every four medication errors reported in the United States is a name-confusion error. The rate of name-confusion errors might be reduced if new and confusing names were not allowed on the market and if safeguards could be put in place to avoid confusion between existing names. OBJECTIVES: To evaluate several prognostic tests of drug-name confusion, alone and in combination, with respect to their sensitivity, specificity, and overall accuracy. RESEARCH DESIGN: Case-control study. Twenty-two different computerized measures of orthographic similarity, orthographic distance, and phonetic similarity were used to compute similarity/distance scores for n = 1,127 cases (ie, pairs of names that appeared in published error reports or national error databases) and n = 1,127 controls. MAIN OUTCOME MEASURES: Mean similarity/distance scores were compared across cases and controls. The performance of each measure at distinguishing between cases and controls was evaluated by tenfold crossvalidation. Dose-response relationships were examined. Univariate and multivariate logistic regression models were formed and evaluated by 10 fold crossvalidation. RESULTS: Cases had significantly higher similarity scores than controls. Every measure of similarity proved to be a significant risk factor for error. There was a significant increasing trend in the odds-ratio as a function of similarity. A three-predictor logistic regression model had crossvalidated sensitivity of 93.7%, specificity of 95.9% and accuracy of 94.8%. CONCLUSIONS: A sensitive and specific test of drug-name confusion potential can be formed using objective measures of orthographic similarity, orthographic distance, and phonetic distance

Confusion · Logistic regression · Multivariate statistics · Odds ratio · Similarity (geometry) · Statistics · Univariate · Artificial Intelligence · Computer Science · Electronic Health Records Systems · Mathematics · Medicine · Pharmaceutical Practices and Patient Outcomes · Pharmacovigilance and Adverse Drug Reactions · Psychology

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