Research on improvement and sophistication support of long-term care behavior by long-term care life log analysis
| Project/Area Number |
18K11530
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 62010:Life, health and medical informatics-related
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| Research Institution | University of Miyazaki |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
串間 宗夫 宮崎大学, 医学部, 研究員 (00727414)
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| Project Period (FY) |
2018-04-01 – 2022-03-31
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| Project Status |
Completed (Fiscal Year 2021)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2020: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2019: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2018: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
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| Keywords | 電子介護記録 / テキストマイニング / 介護記録データ / 標準的介護記録辞書 / リアルデータワールド / 介護記録 |
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| Outline of Final Research Achievements |
The purpose of this study is to develop a dictionary for long-term care records that enables the creation of electronic long-term care records according to the degree of long-term care required. In the initial plan for the year, a huge amount of long-term care records generated at the site of the Long-Term Care Health Facility
It was to collect data (hereinafter referred to as "long-term care life log") and analyze its contents (text mining). Although data could be extracted in 2018, it was difficult to create guidelines for dictionary revision methods face-to-face with care workers due to the effects of the covid-19 infection. Talks with care workers through net meeting also did not progress. Therefore, we conducted a vocabulary analysis of long-term care using the extracted data and announced the results. As papers, 7 English papers and 10 Japanese papers were published.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究の目的は、要介護度に対応した電子介護記録作成を可能にする介護記録用辞書の開発である。研究初年度はテキストの介護記録の抽出と介護記録用辞書を初稿を作成できた。
しかし、それ以降は新型コロナ感染症により、研究手法を変更した。その結果、抽出したデータをデータマイニング（シーケンシャルパターンマイニング）の手法で解析した。
その結果、時系列的に介護の必須パターンを得ることが可能となった。必須パターンを得ることで、今まで困難とされていた介護の標準化が可能となることが示唆できたことは、学術的に意義がある。介護が標準化されることで、人・モノ・金の適正化を推進できる社会的意義もある。
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Report
(5 results)
Research Products
(33 results)
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[Journal Article] Extraction and Graph Structuring of Variants by Detecting Common Parts of Frequent Clinical Pathways2020
Author(s)
M, Kushima, Y, Honda, Hanh, Le, T, Yamazaki, K, Araki, and H, Yokota
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Journal Title
Transactions on Engineering Technologies, Springer
Volume: 無
Pages: 207-218
Related Report
Peer Reviewed
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