Authors:
Keita Nabeta
1
;
Hirotsugu Ishida
1
;
Masaomi Kimura
1
;
Michiko Ohkura
1
and
Fumito Tsuchiya
2
Affiliations:
1
Shibaura Institute of Technology, Japan
;
2
International University of Health and Welfare, Japan
Keyword(s):
Medical safety, Medical education, Drug information, Prescription drug name.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence and Decision Support Systems
;
Computer-Supported Education
;
e-Learning
;
Enterprise Information Systems
;
Information Technologies Supporting Learning
;
Intelligent Tutoring Systems
;
Ontologies and Meta-Data Standards
;
Web-Based Learning, Wikis and Blogs
Abstract:
An educational program aimed at orienting medical staff on proper prescription drug use needs to be implemented to avoid medical errors. Presently, pharmacists are guided by information provided in package inserts. However, these inserts are not suitable educational materials because their descriptions are usually very complex. A huge effort is needed to create educational materials for each of the 20,000 prescription drugs currently used in Japan. Therefore, it is necessary to develop a learning support system with functions that can generate educational materials automatically from a drug information database. Here, we propose a method for generating multiple-choice tests that allows students to associate brand and generic drug names based on similarity.