Objective: Similarity of drug names is one factor of dispensing incidents.  The aim of this study was to survey the relation between sensual similarities of drug names and the occurrence of taking errors for pharmacists who actually prepare medicine.
Methods: A pair of drugs (15 incident pairs and 104 control pairs) was displayed on a computer screen at random.  The subject’s task was to determine the sensual similarity of them.  Thirteen pharmacists who prepared these pairs and caused their incidents participated in the experiment.
Results: The result showed that the sensual similarity of drug names of incident pairs was found to be highly significant in comparison to one of the control pairs [p=0.026].  However, the similarity in incident pairs is not necessarily high.  It was suggested that the similarity of drug name was not the only factor of taking error.  Multiple linear regression analyses of the sensual similarity in control pairs were performed, in which 10 variables were reported as quantitative indicators of similarity of drug name and were able to be measured on the internet.  The correlation was good [R²=0.828].  However, this regression model was not useful when adjusting to incident pairs.  In incident pairs, the similarity value calculated by the regression model was lower than the measured sensual similarity.
Conclusion: The result suggested that measured sensual similarity includes other risk factors of taking error, such as appearance similarity and/or efficacy similarity and/or short distance arrangement.  It seemed that the pharmacist’s ability complicated the factor of taking error.

Objective: Taking the wrong medicine or medication error is a serious concern to patient safety.  The aim of this study was to statistically survey the relation between the placement of drugs on medicine shelf and the occurrence of error in taking a medicine.
Methods: The study comprised 2 groups.  The incident group contained 43 cases that were erroneously taken in the Obihiro Kosei General Hospital.  The control group contained 43 drug pairs matched by the similarity index of the drug names from among the drugs used in the hospital at random.  The similarity index of drug names was based on 10 quantitative indicators.  The distance of medicine shelf arrangement was represented by three variables: the horizontal distance, the vertical distance and the distance of shelf block.  Conditional logistic regression analyses of the occurrence of medication errors were performed by evaluating the three variables of the distance factor and their interaction for error in taking a similar-sounding named drugs.
Results: Conditional logistic regression analysis revealed that the vertical distance (OR: 0.64, 95%CI: 0.42-0.99) and the distance of the shelf block (OR: 0.74, 95%CI: 0.57-0.97) were significant risk-reduction factors of medication errors.  Four variables were extracted as the most suitable logistic regression model in terms of the interaction between them.  As the interaction between 3 variables (the horizontal distance, the vertical distance and the distance of shelf block) was significant (OR: 0.93, 95%CI: 0.86-0.99), they may be considered as synergistic risk-reduction factors.  Moreover, the horizontal distance was found to be a risk-enhancement factor (OR: 1.52, 95%CI: 0.93-2.48).
Discussion: In order to reduce the risk of medication errors due to similar-sounding drug names, placement of drug on the medicine shelf should take into consideration the three coordinates of the distance factor.

The establishment of enhanced surveillance systems for mass gatherings to detect infectious diseases that may be imported during an event is recommended. The World Health Organization Regional Office for the Western Pacific contributed to enhanced event-based surveillance for the Tokyo 2020 Olympic and Paralympic Games (the Games) by using Epidemic Intelligence from Open Sources (EIOS) to detect potential imported diseases and report them to the National Institute of Infectious Diseases (NIID), Japan. Daily screening of media articles on global infectious diseases was conducted using EIOS, which were systematically assessed to determine the likelihood of disease importation, spread and significant impact to Japan during the Games. Over 81 days of surveillance, 103 830 articles were screened by EIOS, of which 5441 (5.2%) met the selection criteria for initial assessment, with 587 (0.6%) assessed as signals and reported to NIID. None of the signals were considered to pose a significant risk to the Games based on three risk assessment criteria. While EIOS successfully captured media articles on infectious diseases with a likelihood of importation to and spread in Japan, a significant manual effort was required to assess the articles for duplicates and against the risk assessment criteria. Continued improvement of artificial intelligence is recommended to reduce this effort.