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題 名 | 我國全民健康保險醫療費用審查制度之研究=The Study on Auditing the Expenditure of National Health Insurance |
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作 者 | 陳建勝; 林佳慧; 陳美菁; 王安平; | 書刊名 | 朝陽商管評論 |
卷 期 | 5:1民95.01 |
頁 次 | 頁111-130 |
分類號 | 412.56 |
關鍵詞 | 行政核減; 類神經網路; 邏輯特迴歸; 專業審查; 誤判成本; Administrative examination; Neural network; Logistic regression; Professional examination; Misclassification cost; |
語 文 | 中文(Chinese) |
中文摘要 | 我國全民健康保險的財務結構一直受到各界的高度重視,其中又以醫療受費用最受矚目,本研究以健保局中醫分局基層院所申報案件為研究對象,應用資料探勘技術建置申報案件核減與否的分類預測模型,並比較邏輯特迴歸與類神經網路所建構的模型,其實証結果發現利用邏輯特迴歸方法所得的型I(誤差將隨臨界值的不同而有所變動,而若以誤判成本為評估依據,類神經網路模型擁有較佳之分類效果,該模式將可做為協助健保局於審查申報案件的初步過濾分類,提供可能遭核減的異常申報案件,進而改進抽審制度。 |
英文摘要 | The financial structure is the significant target for National Health Insurance in Taiwan, especially t he medical expenditure. This paper applies data mining technology to build the predication model. We compared logistic regression with neural network. The research results indicate that type I error produced by logistic regression will be changed with cut off value. but, when use misclassification cost to be the evaluate basis, type I error produced by neural network is relatively stable. According to the sensitivity analysis, we find the administrative examination is the most important factor that affects the probability of the professional examination. In other words, an overall checkup on administrative examination can greatly reduce the load of the professional examination. Hence, we can improve the level of auditing. |
本系統中英文摘要資訊取自各篇刊載內容。