title: [Analysis by structural equation modeling of the questionnaire about the risk and its preventive measures in a pharmacy].
abstract: Pharmacists are now facing a problem of developing measures for dispensing mistakes, because there recently is increasing social awareness on medical accidents and a tendency to increase medical accidents in pharmacies due to popularizing separation of dispensing and prescribing functions. In this study, questionnaire survey was conducted to investigate pharmacist's views on human error measures and the relationship between mistakes and the preventive measures. To clarify relationship between human error measures and preventive measures for avoiding mistakes, questionnaire result was analyzed based on structural equation modeling (SEM). Questionnaire survey was sent to community pharmacies in Hokkaido. The result was analyzed by SEM. The recovery rate of the questionnaire was 71.0%. Human error measures were classified into "The measures against deficient knowledge and insufficient experiences". "Attention problem measures" and "The measures against a cognitive error". While attention problem was strongly related to the cognitive error, there was no relationship between "Attention problem measures" and "The measures against a cognitive error". Moreover, it were clarified that to develop human error measures for deficient knowledge and insufficient experiences was effective for the preventive against the mismatch of the cognitive mechanism and the intentional mistake and for bridging the gap between knowledge and experiences. This study showed that SEM was effective for adopting efficient preventive measures for medical accident and analyzing risk management in pharmacies. Applying these results to the medical accident preventive measures contribute to improvement of the risk management.
authors.affiliation: Hokkaido College of Pharmacy, Otaru, Japan. shimamor@hokuyakudai.ac.jp
authors.forename: Yoshimitsu
authors.initials: Y
authors.lastname: Shimamori
authors.forename: Hirotaka
authors.initials: H
authors.lastname: Sato
authors.forename: Yukitoshi
authors.initials: Y
authors.lastname: Hayase
mesh_terms: D006801:Humans; D007564:Japan; D008318:Malpractice; D008508:Medication Errors / Q000517:prevention & control*; D015233:Models, Statistical; D010595:Pharmacists; D010604:Pharmacy; D012308:Risk Management; D011795:Surveys and Questionnaires