介護サービス向上に向けた介護事故事例テキストの分析(Text Analysis of Incident Reports for Preventing Accidents in Caregiving)

Reviewed, Featured
Tomohiro Minezaki, Moe Matsuki, Sozo Inoue,
情報処理学会論文誌
58
10
1701-1711
2017-07-09
In this paper, we analyze incident report data from several nursing homes for understanding the situations related to the incidents and for reducing future incidents, by utilizing text mining and supervised machine learning.
First, we propose a method for extracting important factors for incidents for the mixed data of text and multivariate data, combining word-document matrix, clustering, and the random forest.
Next, we applied the method to 5,189 incident reports from the nursing homes, and found several patterns such as how the unknown bruises were discovered, behaviors leading to bruises from falls and falls, situations leading to aspiration, and behaviors leading to unattended going out.

Data Files

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