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Improving the identification of confused drug names in Spanish.

Authors :
Millán-Hernández, Christian Eduardo
García-Hernández, René Arnulfo
Ledeneva, Yulia
Pinto, David
Singh, Vivek
Perez, Fernando
Source :
Journal of Intelligent & Fuzzy Systems. 2020, Vol. 39 Issue 2, p2027-2036. 10p.
Publication Year :
2020

Abstract

Since a drug name goes through different communication means and circumstances when it is prescribed, written, advertised, listened to, searched and administered; it tends to be confused with similar drug names that Look-Alike and Sound-Alike (LASA). LASA drug names have caused costs and damage to health. For this problem, the institutions of the United Kingdom, Canada, and the United States have implemented programs for several decades to report lists of confusing drug names pairs. Thanks to these kinds of list, it has been possible to propose new models to identify confusing drug names in English and are used to reject new drug name proposals or to alert when a confusing drug name is being dispensed. However, countries such as Spain also have published a list with the Spanish LASA drug names, and it is not clear enough whether the models previously proposed for the drug names in English are useful for the list in Spanish or if it is necessary to adjust and update them for the Spanish language. This paper focuses on updating and improving the identification of LASA drug names in Spanish. First, we update the state-of-the-art by evaluating all the individual similarity measures proposed previously and all the models that combine these measures with the list in Spanish. Second, we updated the models with new individual measures and then adjusted them with the list in Spanish to improve the identification of LASA drug names in Spanish. After that, 25 individual similarity measures and 8 models to identify confused drug names in Spanish are compared to obtain the best result and conclusions. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10641246
Volume :
39
Issue :
2
Database :
Academic Search Index
Journal :
Journal of Intelligent & Fuzzy Systems
Publication Type :
Academic Journal
Accession number :
145429339
Full Text :
https://doi.org/10.3233/JIFS-179869