Project/Area Number |
17K09196
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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 |
Research Field |
Hygiene and public health
|
Research Institution | The University of Tokyo |
Principal Investigator |
Toyokawa Satoshi 東京大学, 大学院医学系研究科(医学部), 准教授 (40345046)
|
Project Period (FY) |
2017-04-01 – 2020-03-31
|
Project Status |
Completed (Fiscal Year 2019)
|
Budget Amount *help |
¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2019: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2018: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2017: ¥2,990,000 (Direct Cost: ¥2,300,000、Indirect Cost: ¥690,000)
|
Keywords | 複雑系 / ネットワーク理論 / 医師供給 / 複雑系シミュレーション / ABM / システムダイナミクス / ネットワーク分析 / 健康医療政策学 / Agent based modeling / 医師分布 / Agent Based Modeling / 健康医療政策 / GIS / 社会医学 |
Outline of Final Research Achievements |
A distribution that follows a power law to characterize a complex system is an efficient distribution of information. It is expected that the distribution of doctors and medical resources will be efficiently distributed. It is expected that the distribution will follow a complex system. In this study, we examined whether we could observe the distribution of doctors according to the power law expected in the network theory of complex systems, using the individual data from the surveys of doctors, dentists, pharmacists and medical facilities, and found that MFICU, NICU, The number of beds and the number of patients using CT in GCU and PICU follow the power distribution, and the result is expected to have the small world characteristic in network theory.
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Academic Significance and Societal Importance of the Research Achievements |
ネットワーク分布に基づいた医療資源の分析について、最も精度の高い医師歯科医師薬剤師調査及び医療施設調査の個票データを用いて分析したことは、本邦で独創的かつ初めての報告である。MFICU、NICU、GCU、PICUは病床数及びCT利用患者数はべき乗分布に従い、ネットワーク理論におけるスモールワールド特性を有することが期待される結果は、コロナウイルスなどの緊急な対応に柔軟に対応できるネットワークを有している可能性が示唆された。
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