| Project/Area Number |
23241047
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| Research Category |
Grant-in-Aid for Scientific Research (A)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Social systems engineering/Safety system
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| Research Institution | University of Tsukuba |
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Principal Investigator |
TAKAGI Hideaki 筑波大学, システム情報系, 教授 (30260467)
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| Co-Investigator(Kenkyū-buntansha) |
IKUINE Fumihiko 筑波大学, システム情報系, 准教授 (10377046)
UEICHI Hideo 筑波大学, システム情報系, 准教授 (20334534)
KURATA Hisashi 筑波大学, システム情報系, 准教授 (20508428)
SHIGENO Maiko 筑波大学, システム情報系, 教授 (40272687)
YOSHISE Akiko 筑波大学, システム情報系, 教授 (50234472)
MISUE Kazuo 筑波大学, システム情報系, 准教授 (50375424)
ILIC Mika (SATO Mika) 筑波大学, システム情報系, 教授 (60269214)
TAKEHARA Kota 筑波大学, システム情報系, 助教 (70611747)
ZHANG Yongbing 筑波大学, システム情報系, 教授 (80242353)
OKADA Yukihiko 筑波大学, システム情報系, 准教授 (80432053)
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| Co-Investigator(Renkei-kenkyūsha) |
YAMASHITA Keizo 筑波大学, 学内共同利用施設等, 病院講師 (00239964)
KAWANO Satoru 筑波大学, 人間総合科学研究科, 講師 (90323295)
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| Research Collaborator |
SHIRAKAWA Yoko 筑波大学, 附属病院, 看護部長(副病院長)
KURAMOCHI Ryoko 筑波大学, 附属病院, 副看護部長
NOTAKE Noriko 筑波大学, 附属病院, 副看護部長
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| Project Period (FY) |
2011-04-01 – 2015-03-31
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| Project Status |
Completed (Fiscal Year 2014)
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| Budget Amount *help |
¥49,140,000 (Direct Cost: ¥37,800,000、Indirect Cost: ¥11,340,000)
Fiscal Year 2013: ¥14,690,000 (Direct Cost: ¥11,300,000、Indirect Cost: ¥3,390,000)
Fiscal Year 2012: ¥16,510,000 (Direct Cost: ¥12,700,000、Indirect Cost: ¥3,810,000)
Fiscal Year 2011: ¥17,940,000 (Direct Cost: ¥13,800,000、Indirect Cost: ¥4,140,000)
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| Keywords | 医療・福祉 / サービス科学 / 患者満足 / 最適化アルゴリズム / ライフ・イノベーション |
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| Outline of Final Research Achievements |
We studied the algorithm for determining the admission and bed allocation for patients by hearing from doctors and nurses in charge of bed control in the University of Tsukuba Hospital. We then implemented the algorithm and user interface on the tablet terminal. However, our system has not been used in real operation, because all the wards moved to a new building at the final stage of this research period. We also received a complete log of orders for the movement of patients from room to room during hospitalization over two years. We have succeeded in modeling the flow of obstetric patients by a queueing network, which can predict the number of patients in the obstetric wards from the statistics of admission rates and length-of-stay.
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