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Challenge of Tacit Knowledge Extraction embedded Nursing Scene for Medical Safety

Research Project

Project/Area Number 17K19845
Research Category

Grant-in-Aid for Challenging Research (Exploratory)

Allocation TypeMulti-year Fund
Research Field Society medicine, Nursing, and related fields
Research InstitutionKanagawa University

Principal Investigator

Akiyoshi Masanori  神奈川大学, 工学部, 教授 (20403040)

Co-Investigator(Kenkyū-buntansha) 真嶋 由貴恵  大阪府立大学, 人間社会システム科学研究科, 教授 (70285360)
泉 正夫  大阪府立大学, 人間社会システム科学研究科, 教授 (60223046)
Project Period (FY) 2017-06-30 – 2020-03-31
Project Status Completed (Fiscal Year 2019)
Budget Amount *help
¥3,120,000 (Direct Cost: ¥2,400,000、Indirect Cost: ¥720,000)
Fiscal Year 2019: ¥520,000 (Direct Cost: ¥400,000、Indirect Cost: ¥120,000)
Fiscal Year 2018: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2017: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Keywords頻出パターンマイニング / サポートベクターマシン / 視線計測 / 脳波計測 / 脳血流計測 / 薬剤注入圧力計測 / 作業画像 / 脳波 / 脳血流 / 機械学習 / 情報システム / マルチモーダルインターフェース
Outline of Final Research Achievements

For medical safety, there is a use of tacit knowledge that is inherent in various data such as nursing teams and work rules. Therefore, we constructed a framework for extracting as data, including exception handling not specified in the work rules, and obtained the following results.
The data attributes that should be noted were extracted as the characteristics of “similarity” and “frequency” that are inherent in “nurse roaster scheduling data”. In addition, in order to collect sensing data of nursing work" at the site, multiple line-of-sight measurements can be performed, such as line-of-sight measurement, measurement of pulling pressure on the arm skin to search for the injection target point, EEG measurement, cerebral blood flow measurement. It was possible to judge the success or failure of the work by synchronizing the time of various data.

Academic Significance and Societal Importance of the Research Achievements

暗黙知の重要性が認識されていても、組織の規範に基づく業務や個人のスキルに依存する作業に関わるものの明示的な抽出を計算機等を援用して行うことは十分なされていなかった。特に、医療分野での暗黙知を抽出して利活用することは、医療安全の面でインシデントを減らすことが期待される。そこで、看護に関わる「属人的特性」と「属組織的特性」を各々分析する環境を準備し、実組織のデータや模擬作業環境を用いた実験により、抽出の可能性が示されたことは学術的意義がある。これらをもとに、現場に応じた暗黙知の抽出や明文化につながる可能性もあり、医療安全を考えるリスクマネージャにとっても重要な示唆を与えるという社会的意義もある。

Report

(4 results)
  • 2019 Annual Research Report   Final Research Report ( PDF )
  • 2018 Research-status Report
  • 2017 Research-status Report
  • Research Products

    (3 results)

All 2020 2018

All Presentation (3 results) (of which Int'l Joint Research: 2 results)

  • [Presentation] Analysis of Gaze Trajectory and Skin Extension Pressure Data in Blood Collection Technology2020

    • Author(s)
      Mihara Kazuma、Matsuda Takeshi、Majima Yukie、Masuda Seiko、Akiyoshi Masanori、Adachi Kenji、Taira Naoki
    • Organizer
      13th International Conference on Health Informatics
    • Related Report
      2019 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Differences in Brain Activity of Skilled and Novice Nurses during Blood Collection2020

    • Author(s)
      Taira Naoki、Majima Yukie、Masuda Seiko、Kawano Tsuneo、Akiyoshi Masanori、Adachi Kenji、Mihara Kazuma、Namba Ryoma
    • Organizer
      13th International Conference on Health Informatics
    • Related Report
      2019 Annual Research Report
    • Int'l Joint Research
  • [Presentation] インシデント発生につながる看護師シフトデータに関する考察2018

    • Author(s)
      秋吉政徳、真嶋由貴恵、田中小百合、堀美和子
    • Organizer
      電子情報通信学会 ヘルスケア・医療情報通信技術研究会
    • Related Report
      2017 Research-status Report

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Published: 2017-07-21   Modified: 2021-02-19  

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