Lasso回帰を用いた看護師の臨床判断モデリングとアセスメント項目の削減

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2023/06/01

タイトル(英語): Modeling of Clinical Judgment Using Lasso Regression and Reduction of Assessment Items

著者名: 服部　夏実（鳥取大学大学院持続性社会創生科学研究科），磯本　佳助（鳥取大学大学院工学研究科），櫛田　大輔（鳥取大学工学部電気情報系学科（クロス情報科学研究センター）），深田　美香（鳥取大学医学部保健学科）

著者名(英語): Natsumi Hattori (Graduate School of Sustainability Science, Tottori University), Keisuke Isomoto (Graduate School of Engineering, Tottori University), Daisuke Kushida (Electrical Engineering and Computer Science, Faculty of Engineering (Cross-Informatics Research Center), Tottori University), Mika Fukada (School of Health Science, Faculty of Medicine, Tottori Univercity)

キーワード: Lasso回帰，転倒アセスメント，臨床判断，モデル化，項目削減　　Lasso regression，fall assessment，clinical judgment，modeling，item reduction

要約(英語): In the medical field, accidents involving the fall of inpatients around beds have become an increasing problem. To prevent such accidents, nurses record the condition of inpatients using a check sheet referred to as the Fall Assessment Score Sheet (Fall AS). These sheets are utilized for each inpatient and provide useful information for daily clinical judgment. However, compiling these sheets adds to the excessive workload of nurses, as the Fall AS contains numerous items to be checked and assessments frequently necessitate revision. We sought to model the clinical judgment of nurses using Lasso regression, with the aim of reducing the number items of the Fall AS. Three nurses were assigned a questionnaire that included 200 patterns of Fall AS and seven patterns of patient posture, and were requested to fill in the fall risk (0% to 100%) for all 1400 pattern combinations. The clinical judgment model was constructed based Lasso regression, adopting each fall risk and Fall AS as objective and explanatory variables, respectively. The proposed model succeeded in reducing the number of Fall AS items from 50 to 25. Moreover, the mean error of estimated values for the clinical judgment increased by only 3.44% compared with the general least-squares method.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.143 No.6 （2023）

本誌掲載ページ: 590-596 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/143/6/143_590/_article/-char/ja/