@article{oai:kansai-u.repo.nii.ac.jp:00010997,
 author = {阿辻, 茂夫 and 藤本, 良介 and 山本, 悠文 and 濵口, 隆彰 and 吉野, 雄紀 and 野崎, 篤志},
 journal = {情報研究 : 関西大学総合情報学部紀要},
 month = {Mar},
 note = {医療先進国のアメリカ，イギリス，日本において生じている医療事故・過誤が報じられている．これらは，単にヒューマンエラーだけでなく，病院組織における医療管理上のシステムエラーによるものも多い．本稿では，実際にあった2000-16の17年間の医療事故をもとに，新聞紙上にランダムに報じられた430件を超える医療事故（過誤を含む）を分析した．そこから，第Ⅰ 部では，新聞紙上で公表された医療事故と過誤を整序（定式化）した．第Ⅱ部は，医療事故439件の凡例に従い，非定型なビッグデータとして 9つの事故原因に分類し，失敗マンダラに視覚化した．第Ⅲ部は，日本医療機能評価機構の取組みと基本文献について紹介した．本研究は，医療機関の医療スタッフや，政府の医療政策を批判するものではなく，近未来に向けてメディカルサービスの‘改善’を狙った研究である．医療事故の社会化は医療先進国の特徴であり，医療の民主化が進んでいる一方，医療の後進国では，医療事故が公表されない傾向があるといえよう．, The medical accidents and negligence reported frequently in the medically advanced nations of the United States, United Kingdom, and Japan are widely claimed to have been due not only to ‘human error’ but also to ‘system error’ within the medical management process in hospital organizations. Using  ill-structured big-data on actual examples of medical accidents and negligence in the 17 years from 2000 to 2016, the present study analyzed more than 430 medical accidents reported in the pages of newspapers in Japan. The study adopts the following structure: first part, diversibility of medical accidents reported by newspapers with big-data; second part, the causative factors are classified from nine different perspectives using ill-structured big-data on the 439 medical accidents to visualize a ‘failure Mandara’; and third part, Japan Council for Quality Healthcare tackeled with the bibliography of medical accident and healthcare treatment. Rather than criticizing medical staff, hospital organizations and government policy, the aim of the study is to achieve an improvement (Kaizen) in medical care services in the near future for next age. The socialization of medical accidents is a feature of medically advanced nations, accompanying the democratization of medical treatment. On the other hand, in countries with less developed medical treatment systems, there is a tendency for medical accidents not to be publicized., Big-data collaboration: Atsushi NOZAKI},
 pages = {47--90},
 title = {[資料] 医療事故ビッグデータ2000-2016},
 volume = {45},
 year = {2017}
}