Constructing an Operation Time Prediction System Based on EBN(Evidence-Based Nursing)

• Main Authors: CHEN, YUN-SHU, 陳蘊書
• Other Authors: CHU, KUO-CHUNG
• Format: Others
• Language: zh-TW
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/79894381862150167453

碩士 === 國立臺北護理健康大學 === 資訊管理研究所 === 104 === In the enterprise management, the main method of limited cost control by using the precise time management, human resources and material resources to enhance productively, and reduce the unnecessary waste. However, in the clinical care, operation is one of the most important part of the hospital revenue. But the main different between them is that the operation is not able to control the time, material and human recourse probably, and it would cause the difference operating time, and make the first line of the medical resources control become more complex. In the recent clinic management, we do not have a effective system to assist the surgery schedule. So This essay will combined cluster analysis and classification tree analysis, then building an operation time prediction model system to provide the predicting value of operation time which is able to help clinical staff make decision about the human resources and the operation schedule. CONCLUSIONS: The system model(Model B)which integrate cluster analysis with classification tree analysis by using the factors that the surgical physician’s department and the type of anesthesia. In this predicted model system, the correct rate in operation time cluster groups is 58.2% and could not provide a time value of prediction. Also more than 50% of the predicted results, there will have overtime for 30 minutes ; Compared with the clinical staff’s experience model(Model A) , there has 74.33% of the predicted results, which that the prediction time be within 30 minutes, Model A also can provide a clear prediction time value. The results of this essay demonstrate that predicting operation time is feasible.