有害事象の分類に基づいたヒューマンエラーの防止対策

Abstract

It is impossible to entirely eliminate human error; however, systematic attempts have been made to comprehensively minimize accidents originating in human error. It appears that the "work classification" we proposed previously is not able to reduce adverse events, fifty percent of which were duty confirmation failures. We have therefore reviewed and classified the causes of human error from the perspective of working conditions to create a simpler and more preventative strategy. Text-mining analysis was applied to speech part classification to reveal areas with room for improvement. In an objective approach, a conduct code was created and put into practice, based on the common features revealed from a classification of human error in the examples investigated. The average number of accidents per year was reduced from 36 to 24, and those due to human error per year were reduced from 17.6 to 11. This objective approach appears to achieve a reduction of adverse events, including those caused by human error. However, these results were obtained over only one year, in a single-center analysis, and thus, widespread and continuous enforcement would be needed to demonstrate the validity of this objective approach to the prevention of human error.