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研究生: 陳柏勲
Chen, Bo-Xun
論文名稱: 探勘不同檢傷級數之診斷碼樣式進行急診滯留時間預測
Mining ICD-9 Code Patterns based on Triage Levels for Predicting ED Visits Length of Stay
指導教授: 吳怡瑾
Wu, I-Chin
學位類別: 碩士
Master
系所名稱: 圖書資訊學研究所
Graduate Institute of Library and Information Studies
論文出版年: 2019
畢業學年度: 107
語文別: 中文
論文頁數: 101
中文關鍵詞: 急診室ICD-9 醫療診斷碼決策樹FP-tree 演算法檢傷級數滯留時間
英文關鍵詞: Emergency room, ICD-9 Code, Decision tree, FP-Tree algorithm, Triage, Length of stay
DOI URL: http://doi.org/10.6345/THE.NTNU.GLIS.011.2019.A01
論文種類: 學術論文
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  • 本研究以台灣代表性醫院之一的急診室資料分析近幾年的急診醫療資源情 況及問題。在健保制度的實施下,民眾對醫療資源的仰賴也逐漸提高,造成近 幾年全台急診室醫療費用的增加及滯留與壅塞的情況。因此透過急診室資料, 將病患的病情以 TTAS 急診五級檢傷分類標準,並分析病患醫療診斷碼之關聯 性,進而去探討病患在急診室中的滯留情況與行為。研究主要以關聯規則探勘 診斷碼樣式,對病患的 ICD-9 診斷碼以演算法 FP-Growth 找出具有相關性的醫 療診斷碼樣式。接著建立 J48 決策樹模型,預測病患滯留時間,再加入醫療診 斷屬性和病患屬性。分組探討在不同檢傷級數下病患的滯留行為,分析決策樹 規則和醫療與病患屬性的重要程度及正確率。研究結果發現,加入醫療診斷碼 樣式在決策樹預測分析中,能更容易了解急診室病患的情況。從決策樹規則可 以發現有些病情相當分散,且大部分會滯留的原因可能屬於個人行為。與醫師 的討論分析後,可能只有在病情中度嚴重的病患是較急需要急診醫療資源的群 眾。因此現今急診室的壅塞情況,目前大部分的急診室壅塞問題可能是病患。 所以多跟民眾溝通和宣導,建立正確的醫療觀念與制度,並協助醫院了解不同 病患的情況,才能將醫療資源用在真正有需要的人身上。

    The research is aim to analyze the utilization situation and problems of emergency medical resources in Taiwan during the past years by exploring the information of representative hospital emergency rooms in northern Taiwan. Under the implementation of the health insurance system, the demand for medical resources increased gradually, which has resulted in an increase of medical expenses and the extension of length of stay in the emergency rooms recent years.In this research, the information of patient's condition in emergency rooms is classified according to the TTAS emergency five-level classification standard. By analyzing the relevance of the patient's medical diagnosis code to explore the situation of the length of stay in the emergency rooms.
    The research examines mainly the diagnostic code style with association rules, and finds the relevant medical diagnosis code patterns with the algorithm FP-Growth for the patient's ICD-9 diagnostic code. Therefore, establishing the J48 decision tree model to predict the length of stay, then add medical diagnostic attributes and patient attributes to discuss the retention behavior of patients under different levels of injury ,analyzing decision tree rules and the importance and accuracy of medical and patient attributes. The study indicated that adding ICD codes can make it easier to understand the patients’ situation of emergency room by means of decision tree prediction analysis.Through the decision tree rules, it’s found that some conditions are quite scattered and extension of the length of stay mostly resulting from personal behavior. After discussing with the attedning physician, it’s also found that only those patients who are moderately ill conditions have urgent need of emergency medical resources. In summary, the congestion in the emergency rooms mostly depends on patients.
    In order to make sure people who really need can utilize medical resources in time, it is essential to the enhance the communication between personnel and people, strengthen the publicity for correct medical concepts. Furthermore, it is important to establish comprehensive systems and make hospitals to understand the situation of different patients well.

    摘要 i Abstract ii 目次 iv 表次 v 圖次 vii 第一章 緒論 1 第一節 研究背景與動機 1 第二節 研究目的與問題歸納 3 第三節 名詞解釋 5 第二章 文獻探討 7 第一節 ICD-9診斷碼與國內現況 7 第二節 整合ICD-9診斷碼於資料探勘之相關研究 10 第三章 研究方法 16 第一節 研究問題 16 第二節 研究流程與架構 18 第四章 關聯規則探勘診斷碼樣式方法與結果 20 第一節 關聯規則探勘ICD-9診斷碼關聯 20 第二節 診斷樣式分析與討論 26 第五章 滯留時間預測與分析 37 第一節 決策樹預測模型建立 37 第二節 決策樹參數評估 41 第三節 實驗評估 52 第四節 決策樹觀察與討論 53 第五節 醫療決策樹綜合討論 82 第六章 結論與未來展望 97 參考文獻 99

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