| Project/Area Number |
17300048
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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 |
Intelligent informatics
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| Research Institution | Shimane University |
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Principal Investigator |
TSUMOTO Shusaku Shimane University, Faculty of Medicine, Professor, 医学部, 教授 (10251555)
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| Co-Investigator(Kenkyū-buntansha) |
HANADA Eisuke Shimane University, Faculty of Medicine, Associate Professor, 医学部, 助教授 (90244095)
HIRANO Shoji Shimane University, Faculty of Medicine, Associate Professor, 医学部, 助教授 (60333506)
NAKAKUNI Hideaki Shimane University, Faculty of Medicine, Research Associate, 医学部, 助手 (90379678)
ABE Hidenao Shimane University, Faculty of Medicine, Research Associate, 医学部, 助手 (00397853)
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| Project Period (FY) |
2005 – 2006
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| Project Status |
Completed (Fiscal Year 2006)
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| Budget Amount *help |
¥9,300,000 (Direct Cost: ¥9,300,000)
Fiscal Year 2006: ¥5,300,000 (Direct Cost: ¥5,300,000)
Fiscal Year 2005: ¥4,000,000 (Direct Cost: ¥4,000,000)
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| Keywords | Active Mining / Data Mining / Hospital Information System / Risk Discovery / Medical Incidents / 医療事故防止 / インシデント |
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| Research Abstract |
Reports on medical incidents and accidents have been stored for their analysis and prevention. This study aims at developing a system to analyze stored data by using active mining technology and to clarify the hidden factors behind these incidents. In 2005, we developed a data-warehouse system which stores incident reports electronically. In this fiscal year, based on the stored data, we apply several data mining methods to stored data and the data related with incidents, extracted from hospital information system (HIS) as follows. In the upper half of 2006, we developed a data-warehouse server which combines incident data with data related with incidents, which are extracted from HIS. In the latter half of 2006, data mining methods were applied to data in the data-warehouse server. The results obtained from this analysis are the following: (1) While about 7000 actions are performed and registered in the university hospital, 120 cases were registered as medical incidents, 10 cases a month. Thus, the probability of medical accidents is at most 1 to 20000. (2) Age of a patient is one of the principal factor for accidents. (3) diagnosis departments are not so related with incidents. Although data is imbalanced, several interesting results were observed from extracted patterns.
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