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研究生:張志明
研究生(外文):CHANG,CHIH-MING
論文名稱:病人安全事件監測系統研究
論文名稱(外文):The Monitoring System Study of Patient Safety Events
指導教授:陳瑞照陳瑞照引用關係吳文祥吳文祥引用關係
指導教授(外文):CHEN,JUEI-CHAOWU,WEN-HSIANG
口試委員:吳進家陳銘芷吳柏林鄭舜仁
口試委員(外文):Wu,CHIN-CHIACHEN,MING-CHIHWU,BERLINCHENG,SHUENN-REN
口試日期:2016-06-04
學位類別:博士
校院名稱:輔仁大學
系所名稱:商學研究所博士班
學門:商業及管理學門
學類:一般商業學類
論文種類:學術論文
論文出版年:2016
畢業學年度:104
語文別:中文
論文頁數:79
中文關鍵詞:跌倒異常不良事件健康照護品質指標多層級修瓦特管制圖風險評估模糊理論
外文關鍵詞:accidental fallsfuzzy set theoryhealth caremultilevel shewhart control chartquality indicatorsrisk assessment
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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



中文部分
1.林原宏(2006),模糊統計(初版),台北市:五南。(Buckley, J. J. (2004). Fuzzy Statistics. Berlin Heidelberg:Springer-Verlag.)
2.林原宏(2007),「模糊理論在社會科學研究的方法論之回顧」,量化研究學刊,1(1),53-84。
3.吳柏林(2015),模糊統計導論方法與應用(第二版),台北市:五南。
4.財團法人醫院評鑑暨醫療品質策進會 (2014),台灣病人安全通報系統2014年年報,1-172.
5.衛生福利部台灣病人安全資訊網站(2016/4/21),「2013病人安全名詞定
義公告」http://www.patientsafety.mohw.gov.tw/病人安全名詞定義公告
( pdf )20131206.pdf

英文部分
1.Abreu N., Hutchins J., Polizzi N. & Seymour C.J. (1998). Effect of group
Versus home visit safety education and prevention strategies for falling in
Community-dwelling elderly persons. Home Health Care Management &
Practice, 10(4), 57-63.
2.American Geriatrics Society, British Geriatrics Society, and American Academy of Orthopaedic Surgeons Panel on Fall Prevention. (2001). Guideline for the prevention of falls in older persons. Journal of American Geriatrics Society, 49, 664-672.
3.Akihito, N. (2006). Incidence and risk factors for inpatient falls in an academic acute-care hospital. Journal of Nippon Medical School, 73(5), 265-270.
4.AHRQ, 2013 Preventing Falls in Hospitals
http://www.ahrq.gov/professionals/systems/hospital/fallpxtoolkit/index.html
5.Aleksandra, A.Z., Alan, W.S., Mark, S. & Anthony, A.V. (2006). Defining a Fall and Reasons for Falling Comparisons Among the Views of Seniors, Health Care Providers and the Research Literature. The Gerontological Society of America, 46(3), 367-376.
6.Amirzadeh, V., Mashinchi, M. & Yaghoobi, M. A. (2008). Construction of control charts using fuzzy multinomial quality. Journal of Mathematics and Statistics, 4(1), 26-31.
7.Aliakbar, G.A. & Farzaneh, A. (2013). Risk Prioritization Based on Health, Safety and Environmental Factors by Using Fuzzy FMEA. International Journal of Mining, Metallurgy & Mechanical Engineering, 1(4),233-237
8.Albert, S. M., King, J., Boudreau, R., Prasad, T., Lin, C. J. & Newman, A. B. (2014). Primary prevention of falls: effectiveness of a statewide program. A mJ Public Health, 104(5), e77-84.
9.Arnold, F.S. (2015). Risk Assessment Applications of Fuzzy Logic. Casualty Actuarial Society, Canadian Institute of Actuaries, Society of Actuaries, 1-112
10.Berg, W. P., Alessio, H. M., Mills, E. M. & Tong, C. (1997). Circumstances and consequences of falls in independent community-dwelling older adults. Age and Ageing, 26, 261-268.
11.Bagian, J. P., Lee, C. Z., Gosbee, J., Derosier, J., Stalhandske, E., Eldridge, N., Williams, R. and Burkhardt, M. (2001). Developing and Deploying a Patient Safety Program in a Large Health Care Delivery System. The Journal on Quality Improvement, 27(10), 522-532.
12.Benneyan, J. C., Lloyd, R. C. & Plsek, P. E. (2003). Statistical process control as a tool for research and healthcare improvement. Quality and Safety in Health Care, 12(6), 458–464.
13.Baker, A., Morton, A., Gatton, M., Tong, E. & Clements, A.(2009). Sequential monitoring of hospital adverse events when control charts fail: The example of fall injuries in hospitals. Quality and Safety in Health Care, 18(6), 473-477.
14.Cesari, M., Landi, F., Torre, S., Onder, G., Lattanzio, F. & Bernabei, R. (2002). Prevalence and risk factors for falls in an older community- dwelling population. Journal of Gerontology, 57, 722-726.
15.COSO (Committee of Sponsoring Organizations of the Tread way Commission), (2004), Enterprise risk management – integrated framework, COSO.
16.Cassady, C.R. & Nachlas, J. A. (2006). Evaluating and Implementing 3-LevelControl Charts. Quality Engineering, 18(3), 285-292.
17.Cox, J., Charlotte, T.H., Edmund, P., Susan, D., Edna, C. & Miguel, M. (2015). Factors associated with falls in hospitalized adult patients. Applied Nursing Research, 28, 78-82
18.Ball, D.J. & Watt, J. (2013). Further Thoughts on the Utility of Risk Matrices. Risk Analysis, 33(11), 2068-2078.
19.Faraz, A., & Moghadam, M. B. (2007). Fuzzy control chart a better alternative for shewhart average chart. Quality and Quantity, 41(3), 375–385.
20.Feldman, F., & Chaudhury, H. (2008). Falls and the physical environment: A review and a new multifactorial falls - risk conceptual framework. The Canadian Journal of Occupational Therapy, 75 (2), 82-90.
21.Haines, T. P., Hill, K., Walsh, W., & Osborne, R. (2007). Design-related biasin hospital fall risk screening tool predictive accuracy evaluations: Systematic review and meta-analysis. Journal of Gerontoly, Series A. Biological Sciences and Medical Sciences, 62(6), 664-672.
22.Hauer, K., Lamb, S. E., Jorstad, E. C., Todd, C., & Becker, C. (2006). Systematic review of definitions and methods of measuring falls in randomized controlled fall prevention trials. Age Ageing, 35(1), 5-10.
23.Heinze, C.L., Dassen, T., (2002). Sturzhäufigkeit in deutschen Kliniken. Gesundheitswesen, 64(11), 598-601.
24.Huang, T.T. & Acton, G. J. (2004). Effectiveness of home visit falls prevention strategy for Taiwanese community-dwelling elders: randomized trial. Public Health Nursing, 21(3), 247-256.
25.Henderson, G. R., Mead, G. E., Dijke, M.L., Ramsay, S., McDowall, M. A. & Dennis, M. (2008). Use of Statistical Process Control Charts in Stroke Medicine to Determine if Clinical Evidence and Changes in Service Delivery Were Associated with Improvement in The Quality of Care. Quality and Safety in Health Care, 17, 301-306.
26.Irene D. F., .Melissa J. K., William C. D., Stanley B., Eileen H., Shirley J., Eileen C., Victoria J. F. (2005). Patterns and predictors of inpatient falls and fall-related injuries in a large academic hospital. Infection Control and Hospital Epidemiology, 26(10), 822-827.
27.Morton, A. P., Whitby, M., McLaws, M. L., Dobson, A., McElwain, S., Looke, D., Jenny, R. N. & Anna, S. (2001). The Application of Statistical Process Control Charts to The Detection and Monitoring of Hospital -acquired Infections. Journal of Quality in Clinical Practice, 21, 112-117.
28.Middleton, S., Chapman, B., Griffiths, R. & Chester, R. (2007). Reviewing Recommendations of Root Cause Analyses. Australian Health Review, 31(2), 288-295.
29.Montgomery, D. C. (2009). Introduction to Statistical Quality Control 6 th ed. New York, NY: John Wiley and Sons.
30.Morse, J.M. (2009). Preventing patient falls. Establishing a fall intervention program 2nd ed. New York, NY. Springer Publishing Company.
31.Morton, A., Clements, A. & Whitby, M. (2009). Hospital Adverse Events and Control Charts: The Need for a New Paradigm. Journal of Hospital Infection, 73, 225-231.
32.New South Wales Health Department. (2011, Sep.30). Severity Assessment Code (SAC) Matrix. Sydney: NSW Health, 2005. Retrieved from http://www.health. nsw.gov.au/pubs/2005/sac_matrix.html.
33.New Zealand Incident Management System. (2011, September 30). Severity Assessment Code (SAC) Matrix. New Zealand Quality Improvement Committee. Retrievedfromhttp://www.hqsc.govt.nz/assets/ Reportable-
Events/ Resources/ severity-assessment-code-poster-v1-1.pdf.
34.Oliver, D., Britton, M., Seed, P., Martin, F. C. & Hopper, A. H. (1997). Development and evaluation of evidence based risk assessment tool (STRATIFY) to Predict which elderly inpatients will fall: Case - control and cohort studies. British Medical Journal, 315 (7115), 1049 -1053.
35.Oliver, D., Fergus, D. & Martin F.C. (2004). Risk factors and risk assessment tools for falls in hospital in-patients. A systematic review. Age Ageing, 33, 122-30.
36.Ossama, Y. A-H. & Walied, B. (2013). Application of Fuzzy Logic for Risk Assessment using Risk Matrix. International Journal of Emerging Technology and Advanced Engineering, 3(1), 50-54.
37.Patel, S. & Wu, A. W. (2014). Safety culture in Indian hospitals: A cultural adaptation of the safety attitudes questionnaire. Journal of Patient Safety. doi: 10.1097/PTS.0000000000000085
38.Ronald, I. S., Lorraine, C. M., Chandler, A. M., Linda, C. R., Debra, L. & Lori, A. K. (2008). Improving the capture of fall events in hospitals: Combining a service for evaluating inpatient falls with an incident report system. Journal of the American Geriatrics Society, 56(4), 701-704.
39.Sohrab, K., Saeed, G., & Saeed, K. (2013). Fuzzy Risk Assessment and Categorization, based on Event Tree Analysis (ETA) and Layer of Protection Analysis (LOPA): Case Study in Gas Transport System. World Applied Programming, 3(9), 417-426
40.Spoelstra, S. L., Given, B. A. & Given, C. W. (2012). Fall prevention in hospitals: An integrative review. Clinical Nursing Research, 21, 92-112.
41.Sylvain T. & Julie H. (2014). A Hospital System Approach at Decreasing Falls with Injuries and Cost. Nursing Economic , 32(3) ,135-141
42.Sabegh, M. H. Z., Mirzazadeh, A., Saber, S. & Weberb, G. W. (2014). A Literature Review on the Fuzzy Control Chart; Classifications & Analysis. International Journal of Supply and Operations Management, 1(2), 167-189.
43.Tinetti, M. E. (2003). Clinical Practice: Preventing falls in elderly persons. New England Journal of Medicine, 348(1), 42-49.
44.Tilling, L. M., Darawil, K., & Britton, M. (2006). Falls as a complication of diabetes mellitus in older people. Journal of Diabetes and its Complications, 20(3), 158-162.
45.Tzeng, H. M. & Yin, C. Y. (2008). The extrinsic risk factors for inpatient falls in hospital patient rooms. Journal Nursing Care Quality, 23(3), 233-241.
46.William, H. W. (2003). Health-care and public-health surveillance. Journal of Quality Technology, 38(2), 89–104.
47.Zarandi, M. H. F., Turksen, I. B. & Kashan, A. H. (2006). Fuzzy control charts for variable and attribute quality characteristics. Iranian Journal of Fuzzy Systems, 3(1), 31-44.

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