Impact of Cognitive Decline on Medical Outcomes and Nursing Workload
Project/Area Number |
18K10009
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Research Category |
Grant-in-Aid for Scientific Research (C)
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Allocation Type | Multi-year Fund |
Section | 一般 |
Review Section |
Basic Section 58010:Medical management and medical sociology-related
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Research Institution | Kagoshima University |
Principal Investigator |
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Co-Investigator(Kenkyū-buntansha) |
村永 文学 鹿児島大学, 医歯学総合研究科, 客員研究員 (00325812)
宇都 由美子 鹿児島大学, 医歯学域医学系, 准教授 (50223582)
|
Project Period (FY) |
2018-04-01 – 2023-03-31
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Project Status |
Completed (Fiscal Year 2022)
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Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2021: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2020: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2019: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2018: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
|
Keywords | 看護情報 / 病院情報システム / 認知機能 / 看護ケア量 / 認知症 / 医療資源投入量 / 診療アウトカム / 地域包括ケア / ケア量 |
Outline of Final Research Achievements |
We aimed to investigate whether cognitive decline can be identified from a nurse assessment and the effect on medical outcomes and nurse workload. This retrospective cohort study used electronic medical record data to investigate whether patients judged by nurses to have cognitive decline were as affected as patients with a dementia diagnosis. Further, a model formula was created and validated to predict the probability of needing physical restraint, the nursing care workload, and the record volume. The implementation of physical control and a discharge support conference was significantly higher in patients deemed by nurses to have cognitive decline. Nurse-deemed patients with cognitive decline were affected by the outcome and workload as much as patients with dementia. Combining nurse assessment and patient attribute information in a model was useful for predicting nurse workload.
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Academic Significance and Societal Importance of the Research Achievements |
近年、Real World Dataを用いた分析に注目が集まっている。特定の病態を有する患者を抽出する際は診断名が用いられるが、認知症の抽出力は高くない。精神科の受診や認知機能の検査を避ける傾向にあり、診断に至らないこと、また、検査や処方を伴わないため「認知症」が診断名として登録されないことが要因である。本研究で用いた変数は、多くの医療機関において入院時点で取得可能なデータであり、研究成果として得られたモデル式は、入院初期からの介入方法やケア提供体制を検討するためのClinical Decision Support Systemのエンジンとしての活用が期待できる。
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Report
(6 results)
Research Products
(27 results)