| 研究生: |
朱品潔 Zhu, Pin-Jie |
|---|---|
| 論文名稱: |
以知識流觀點探討遠距照護之模糊失效模式 Analysis to Fuzzy FMEA for Telecare based on the Perspective of Knowledge Flow |
| 指導教授: |
林清河
Lin, Chin-Ho |
| 學位類別: |
碩士 Master |
| 系所名稱: |
管理學院 - 工業與資訊管理學系 Department of Industrial and Information Management |
| 論文出版年: | 2017 |
| 畢業學年度: | 105 |
| 語文別: | 中文 |
| 論文頁數: | 79 |
| 中文關鍵詞: | 遠距照護 、知識流 、失效模式與效應分析 、模糊理論 |
| 外文關鍵詞: | telecare, knowledge flow, failure mode and effects analysis (FMEA), fuzzy theory. |
| 相關次數: | 點閱:227 下載:1 |
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現今社會正面臨人口老化的問題,隨之伴隨許多慢性疾病的發生,而這些慢性疾病都是需要受到長時間的照顧,但在有限的時間和交通便利性的限制下,遠距照護已經成為照顧老年人或是慢性疾病患者的重要工具之一。
遠距照護將使年長者的照護型態改變,由傳統的集中式醫療轉化為在地老化(aging in place),讓年長者能在自己熟悉的環境,擁有隱私的生活、獨立自主的生活、有尊嚴,一樣享有醫療服務的資源,並且達到健康老化以及成功老化的目標。
本研究將運用FMEA(Failure Modes And Effect)失效模式與效應分析的方法來探討遠距照護的問題,此方法是常見的風險管理工具,至今已經廣泛應用在許多行業,但傳統的FMEA所計算出來的風險優先指數(Risk Priority Number,RPN)有缺陷,可能會造成修正判斷的錯誤,而造成資源和時間的浪費,故本研究將加入模糊理論,來計算RPN,進一步的降低傳統FMEA所造成的缺陷。
研究過程大致上分成三個階段:第一階段,利用文獻和專家深度訪談,並且從知識流的障礙面來探討遠距照護失效的影響因子,並且建構初步的模式。第二階段,將第一階段所整理的問題,以問卷的方式發給其他有接觸遠距照護的專家填寫。第三階段,利用所得到到的數據來進行分析,比且比較傳統RPN和模糊RPN的値,以利於後續的結果追蹤。
經由本研究計算分析結果,認為「使用遠距照護的醫生在報酬上的激勵,論量計酬對醫生的效益較低」應當為優先處理的原因,雖與傳統的失效模式與效益分析在其他原因排序是有些許差異,為了使這些差異結果更加符合實際狀況,在後續的研究將會再與專家進行討論。
Today's society has been faced the problem of aging, along with many chronic diseases. The telecare is necessary for the chronic diseases. Furthermore, telecare has become a tool of care elderly and chronic disease patients due to the limited time and traffic inconvenience. It is a useful approach and local place for each individual patient.
By using Failure Modes and Effects Analysis (FMEA), the study explores the problem of telecare. The FMEA is a common risk management tool, which has been widely used in many industries, but this study will apply fuzzy theory to calculate Risk Priority Number (RPN) for reducing the impact of the defect of traditional FMEA, which may result from its algorithm of priority calculation.
Three stages involved in the study which are: the first stage, the use of literature review and experts in-depth interviews which are based on the knowledge flow barriers for exploring the impact of telecare’s failure factors to construct the initial model. The second stage use results of the first stage to be the questionnaire, and then sent to other telecare experts to fill out it; the third stage, use the data from questionnaire to calculated and compare the traditional RPN and fuzzy RPN values.
The results of the study showed that “the reason 6 is the first priority issue (i.e., most important) in two calculation algorithms. It implies that “the use of telecare’s doctor most important issue to enhance the effective of the telecare.” However, the priority values calculated by traditional RPN and fuzzy RPN for other reasons are different, which will be a valuable study for future.
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網站資料
衛生署.(2013),遠距健康照護服務發展計畫,Retrieved 05-01,2013, fromhttp://doh.telecare.com.tw/index.aspx