研究生: |
羅玉君 Lo, Yu Chun |
---|---|
論文名稱: |
應用根本原因分析方法(RCA)於TPR系統之後端資料分析 : 針對藥物異常事件 Application of RCA to the Data Analysis in Adverse Drug Events of the TPR system |
指導教授: |
王明揚
Wang, Min Yang |
口試委員: |
張堅琦
Chang, Chien Chi 潘錫光 Poon, Sek Kwong |
學位類別: |
碩士 Master |
系所名稱: |
工學院 - 工業工程與工程管理學系 Department of Industrial Engineering and Engineering Management |
論文出版年: | 2016 |
畢業學年度: | 104 |
語文別: | 中文 |
論文頁數: | 91 |
中文關鍵詞: | 藥物異常事件 、根本原因分析(RCA) 、台灣病人安全通報系統(TPR) 、HFACS模型 |
外文關鍵詞: | Adverse drug events, Human Factors Analysis and Classification System (HFACS), Root Cause Analysis (RCA), Taiwan Patient Safety Reporting System (TPR) |
相關次數: | 點閱:2 下載:0 |
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隨著病人安全重要性的提升,促進病人安全能夠有效改善醫療品質、醫病關係、以及降低醫療成本。台灣病人安全通報系統(Taiwan Patient Safety Reporting System, TPR)成立目的即在透過異常事件經驗之分享,提升病安環境、成就更完備的醫療品質。本研究之目的在於提升TPR系統後端資料分析效用,找出藥物異常事件根本原因,以期更有效地運用TPR系統所收集之資料,提升病人安全。
本研究主要分成兩階段,第一階段針對原有系統做評估。此階段利用18筆藥物異常事件進行根本原因分析(Root Cause Analysis, RCA),並招募30位護理師進行此18筆藥物異常事件之通報,再利用Human Factors Analysis and Classification System (HFACS)模型分析比較兩者結果,評估原有TPR系統後端資料分析之效用。研究結果顯示,原版TPR系統所獲得之因果要素總數少於RCA所獲得之總數;而將因果要素利用HFACS模型分類之後,由原版TPR系統所萃取之各層級因果要素數量包含總數皆顯著少於由RCA方法所獲得之因果要素數量,結果顯示,原版TPR系統的後端資料分析效用與RCA結果差異極大。第二階段針對前階段結果提出改良後的新版TPR系統,並招募另外30名護理師再次通報此18筆異常事件,利用相同方式評估新版系統效用,新版系統將導入RCA概念,引導通報者系統化地思考事件內容。研究結果發現,新版系統能夠獲得較多的因果要素,以HFACS模型分類因果要素後,新版系統於第二層級、第三層級所獲的因果要素數量皆顯著多於原版系統,結果顯示改良後的新版系統確實能協助使用者更全面地思考藥物異常事件,並獲得更貼近於RCA結果之資料,提升後端資料分析效用。
With the importance of patient safety increasing, improving patient safety can enhance the medical quality. The goal of the Taiwan Patient Safety Reporting System (TPR System) is to promote the patient safety and the quality of medical service by knowledge sharing between hospital institutions. The purpose of this study is to make good use of the data gathered from the TPR system by identifying the root causes of the
adverse events precisely and correctly.
The study consists of two stages. The first stage is to evaluate the original TPR system by comparing the results of the Root Cause Analysis (RCA) and the TPR system itself. We used 18 adverse drug events as our materials and recruited 4 experts to analyze those events by using RCA. Thirty nurses were recruited to report those events to the TPR system. With systematical approach, we applied the HFACS model to analyze these two results. The study indicated that the sum of the causal factors and the number of causal factors from all layers in HFACS model are less than the results from the RCA. It implied that the original TPR system cannot offer useful and effective information for causal analysis. The second stage was based on the conclusions in the previous stage. We established an improved TPR system which was added the core thinking of the RCA and guided the user to consider the adverse events in systematic approach. We recruited another 30 nurses to report those 18 events by the new system and used the same way to evaluate the new system. Comparing the original and improved TPR system, the results showed that the new system can obtain more causal factors; moreover, the number of causal factors in the second, third layer in HFACS model are significantly much more than the original system. After the improvement, the new system may help user to reconsider the adverse event completely and the results from the new system is more closed to the RCA. It suggested that the new TPR system can enhance the utility of the
data which the system obtained and discover the root causes more easily.
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