| Project/Area Number |
17H04144
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Medical and hospital managemen
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| Research Institution | Kyushu University |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
下野 信行 九州大学, 大学病院, 准教授 (70346782)
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| Project Period (FY) |
2017-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥16,640,000 (Direct Cost: ¥12,800,000、Indirect Cost: ¥3,840,000)
Fiscal Year 2019: ¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2018: ¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2017: ¥8,450,000 (Direct Cost: ¥6,500,000、Indirect Cost: ¥1,950,000)
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| Keywords | 抗菌薬 / 耐性菌 / 薬剤感受性 / DPC / JANIS / NDB / 感染症 / 費用効果分析 / レセプトデータ / 感受性 |
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| Outline of Final Research Achievements |
The following four research topics were addressed: (1) Elucidation of the association between antibiotic resistance onset and antibiotic use, (2) Visualization of antibiotic treatment strategies and evaluation of appropriate use, (3) Effectiveness evaluation of appropriate antibiotic use support programs, and (4) Healthcare economic evaluation of antibiotic resistance onset and antibiotic use. For each topic, medical big data (including DPC data, JANIS data, payment data, and NDB data) were utilized as appropriate to quantitatively analyze the associations between the real-world conditions of antibiotic resistance and antibiotic use.
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| Academic Significance and Societal Importance of the Research Achievements |
薬剤耐性菌は世界的に蔓延し，決定的に重大な国際課題である．本研究では我が国に整備されている医療ビッグデータを活用し，耐性菌および抗菌薬の実態を可視化する方法を開発した．また，継続的に可視化がなされることにより，薬剤耐性菌発現の抑止に貢献しうることが明らかにされた．さらに，感染症発症による追加敵医療費を推定することにより，経済性の観点から感染対策の開発推進に資する成果をあげた．
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