病人安全被視為全球性醫療照護重要議題，監測「病人安全事件」是為了促進病人安全。本研究是透過有效監測工具，運用病人安全事件所造成傷害的嚴重度之多層級管制圖，再結合模糊理論，透過警示線概念進行監測，並運用品管手法分析原因，找出改善最適切對策，以提升病人安全。進一步，針對病人安全通報系統評估事件嚴重度評估級數，傷害的嚴重度與再發生頻率，應用模糊理論方法，建置模糊風險矩陣，評估病人安全事件所造成的風險，讓管理者在時間的位移因素上，透過管制圖方式，發現異常狀態，給予適當的對策措施。經由實證研究的結果，發現應用管制圖是病人安全事件監測系統中有效工具，傳統管制圖雖能予以即時的監測，但缺乏考量因病人安全事件所造成傷害的嚴重度。因此，使用多層級管制圖補足傳統管制圖不足之處，同時透過模糊規則建立，降低傳統管制圖當中造成誤差與低敏感度的缺點，確保病人安全，追求更安全完善之醫療環境。

Patient safety is regarded as an important global health care issue and monitoring patient safety events further promotes patient safety. This study, identified improvement measures to enhance patient safety by analyzing, injury severity and problems caused by patient safety adverse events through effective monitoring tools, multi-level control chart, combined with fuzzy theory, warning lines and application of an appropriate program of quality control to identify and analyze the cause of the adverse events, as well as an appropriate improvements are provided to enhance patient safety. In particular, this study has built a fuzzy risk matrix by using fuzzy theory for evaluating the severity and likelihood of event recurrence in Taiwan Patient-Safety Reporting System in the Severity Assessment Code and assessing the risks of patient safety events. As a results, health care manager could provide timely countermeasures when any graphically abnormal status on the control charts surfaces. This study showed the application of control chart is an important and effective tool to monitor in patient safety adverse events. Although the traditional control charts can be used as a timely monitor tool, however it has lack of inclusive in the severity of injuries. Thus, multi-level control chart complements the deficiencies of the traditional control charts, by establishing multi-level control chart and implementing fuzzy rules could reduce the problems of low sensitivity in traditional control chart, which could improve healthcare environment and ensure patient safety.

目 錄
頁次
第 壹 章 緒論 1
第 一 節 研究背景與動機 1
第 二 節 研究問題與目的 4
第 三 節 研究流程 5
第 四 節 論文結構 7

第 貳 章 文獻探討 9
第 一 節 病人安全事件 9
第 二 節 病人跌倒定義 10
第 三 節 病人跌倒相關危險因子 11
第 四 節 跌倒傷害分類 12
第 五 節 管制圖 14
第 六 節 風險管理 19
第 七 節 模糊理論應用 24

第 參 章 研究方法 29
第 一 節 病人安全事件監測系統架構 31
第 二 節 建置病人安全事件監測系統步驟 31
第 三 節 多層級管制圖 36
第 四 節 模糊理論結合多層級管制圖 38
第 五 節 警示線計算 39
第 六 節 模糊風險矩陣 40

頁次
第 肆 章 實證研究 43
第 一 節 u管制圖進行跌倒異常不良事件監測 43
第 二 節 多層級u管制圖結果 51
第 三 節 模糊理論結合多層級u管制圖結果 55
第 四 節 模糊多層級警示線概念u管制圖結果 57
第 五 節 模糊風險矩陣結果 58

第 伍 章 結論與建議 69
第 一 節 結論 69
第 二 節 建議 71

參考文獻 73


表　目 錄
頁次
表 2-4-1 TPR之嚴重度分級摘錄表 14
表 2-6-1澳洲嚴重度評估矩陣之發生頻率分級表 20
表 2-6-2澳洲嚴重度評估矩陣之嚴重度分級表 21
表 2-6-3澳洲嚴重度評估矩陣SAC 22
表 2-6-4台灣TPR事件發生後對病人健康的影響程度 22
表 2-6-5台灣TPR SAC 矩陣表 23
表 3-4-1嚴重度的模糊分級 39
表 4-1-1病人跌倒異常不良事件基本資料 45
表 4-1-2 2011〜2014年跌倒異常不良事件監測值 46
表 4-2-1 2011〜2014年跌倒異常不良事件多層級監測值 52
表 4-3-1模糊理論多層級監測值 55
表 4-5-1嚴重度模糊數 59
表 4-5-2嚴重度的三角模糊數 59
表 4-5-3事件可能再發頻率的模糊數 61
表 4-5-4事件可能再發頻率的三角模糊數 61
表 4-5-5 SAC模糊值 62
表 4-5-6 還原SAC三角模糊值 64
表 4-5-7 各類管制圖優缺點比較表 66



圖　目 錄
頁次
圖 1-3-1 研究流程圖 06
圖 2-1-1 醫療異常事件分類 10
圖 2-4-1 2005～2014病人安全通報系統跌倒有傷害極重度傷害以
上事件趨勢 13
圖 2-7-1 三角歸屬函數 25
圖 2-7-2 模糊運算補集 26
圖 2-7-3 模糊運算交集 26
圖 2-7-4 模糊運算聯集 27
圖 3-1-1 監測系統流程圖 30
圖 3-1-2 病人安全事件監測系統架構圖 31
圖 3-2-1 跌倒異常不良事件特性要因圖 32
圖 4-1-1 2011年～2014年5月跌倒異常不良事件 48
圖 4-1-2 2014年3～5月跌倒異常不良事件發生原因柏拉圖 49
圖 4-1-3 2014年3～5月與2011～2014年跌倒異常不良事件時段
49
圖 4-1-4 2014年3～5月與2011～2014年跌倒異常不良事件發生類
別 50
圖 4-1-5 2011年～2014年病人跌倒異常不良事件u管制圖 51
圖 4-2-1多層級u管制圖 54
圖 4-3-1模糊多層級u管制圖 57
圖 4-4-1模糊多層級警示線概念u管制圖 58
圖 4-5-1模糊SAC u管制圖 65
圖 4-5-2模糊SAC警示線概念u管制圖 65

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