Scientific approach to reduce the number of medical incidents
| Project/Area Number |
15590454
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Medical sociology
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| Research Institution | Shinshu University |
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Principal Investigator |
MURASE Sumio Shinshu University, Shinshu University Hospital, Professor, 医学部附属病院, 教授 (70200285)
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| Co-Investigator(Kenkyū-buntansha) |
SAKATA Nobuhiro Shinshu University, Shinshu University Hospital, Assistant Professor, 医学部附属病院, 講師 (50362132)
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| Project Period (FY) |
2003 – 2005
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| Project Status |
Completed (Fiscal Year 2005)
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| Budget Amount *help |
¥2,300,000 (Direct Cost: ¥2,300,000)
Fiscal Year 2005: ¥100,000 (Direct Cost: ¥100,000)
Fiscal Year 2004: ¥900,000 (Direct Cost: ¥900,000)
Fiscal Year 2003: ¥1,300,000 (Direct Cost: ¥1,300,000)
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| Keywords | Riskmanagement / Medical incident / Hospital / 医療事故予防の取り組み / 医療事故 / ディスクマネージメント |
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| Research Abstract |
In Japan, it is hard to say that measures to reduce medical accidents are made by scientific approach. Therefore, in this study, we used technique of operation research and examined interaction between medical workers. We extracted problems in a background of medical accidents from data of medical incidents. The present study could help prevention of medical accidents.
With technique of text-mining, we analyzed medical incidents freely mentioned in incident reports. About a mechanism how produces incidents, we made a model which predicted medical accidents. By the model, we could estimate the degree of fatigue among medical workers according to schedules at wards and could quantify the frequency of medical accidents. This model predicted a real phenomenon well, when we measured degree of fatigue observed at wards.
Furthermore, we could clarify a situation of the falling incident concretely, applying the present technique of model analysis. In addition, by application of some analytical techniques, we could improve precision of the prediction of the falling incident. Based on the result, I we made a new evaluation seat for the estimation of the falling risk.
We found that, by making a model, the situation that a medical accident was easy to occur would be extracted. Therefore, if we utilized this method, a preventive action for medical accidents seemed to be enabled : to increase the numbers of nurses on the day of high risk.
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Report
(4 results)
Research Products
(10 results)
