請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/44219完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 張睿詒 | |
| dc.contributor.author | Hung-Wei Chang | en |
| dc.contributor.author | 張宏瑋 | zh_TW |
| dc.date.accessioned | 2021-06-15T02:45:34Z | - |
| dc.date.available | 2014-08-23 | |
| dc.date.copyright | 2011-08-23 | |
| dc.date.issued | 2011 | |
| dc.date.submitted | 2011-08-22 | |
| dc.identifier.citation | 黃智英、楊郁:慢性腎臟病衛教簡介。台灣腎臟護理學會雜誌,3(2):81-87,2004。
于宗先:經濟預測。大中國圖書有限公司,1972。 行政院衛生署中央健康保險局:97年全民健康統計:重大傷病門診與住院醫療費用申報。2011。 行政院經濟建設委員會:2010年至2060年臺灣人口推計。2010。 行政院內政部統計處:內政統計年報。2010。 行政院衛生署中央健康保險局:全民健康保險醫療統計年報。2010。 林明彥、黃尚志:台灣慢性腎臟病/末期腎臟病流行病學過、現在與未來。腎臟與透析,19(1):1-5,2007。 吳肖琪、黃麟珠、雷秀麗、吳義勇:從健保透析申報資料定義並分析國內慢性腎衰竭病患透析情形。台灣衛誌:Vol.23, No.5,2004。 吳柏林:時間序列分析導論。華泰書局,1995。 楊奕農:時間序列分析:經濟與財務上之應用。雙葉書廊有限公司,2006。 Chamber, J. C., Mullick, S. K. & Smith, D. D.: How to Choose the Right Forecasting Technique. Harvard Business Review, 45-74, 1971. Davies R, Roderick P: Predicting the future demand for renal replacement therapy in England using simulation modeling. Nephrol Dial Transplant 12: 2512-2516, 1997. Lysaght, M. (2002). Maintenance dialysis population dynamics: current trends and long-term implications. Journal of the American Society of Nephrology, 13(Supplement 1), S37-40 Motohashi Y, Nishi S: Prediction of end-stage renal disease patient population in Japan by system dynamics model. Int J Epidemiol 20: 1032-1036, 1991. Remer, D. S. & Jorgens, C.: Ethylene Economics and Production Forecasting in a Changing Enviroment. Engineering and Process Economics, 3, 4, 267-278, 1978. Roderick P, Davies R, Jones C, Feest T, Smith S, Farrington K: Simulation model of renal replacement therapy: Predicting future demand in England. Nephrol Dial Transplant 19: 692-701, 2004. Schaubel DE, Morrison HI, Desmeules M, Parsons DA, Fenton SS: End-stage renal disease in Canada: Prevalence projections to 2005. CMAJ 160:1557-1563, 1999. Schaubel DE, Morrison HI, Desmeules M, Parsons DA, Fenton SS: End-stage renal disease projections for Canada to 2005 using Poisson and Markov models. Int Epidemiol 27: 274-281, 1998. United States Renal Data System: USRDS 2009 Annual Data Report, Atlas of End-Stage Renal Disease. World Wide Web: http://www.usrds.org/atlas.htm United States Renal Data System: USRDS 2010 Annual Data Report, Atlas of End-Stage Renal Disease. World Wide Web: http://www.usrds.org/atlas.htm Xue JL, Ma JZ, Louis TA, Collins AJ: Forecast of the number of patients with end-stage renal disease in the United States to the year 2010. J Am Soc Nephrol 12: 2753-2758,2001. Yang, W. C., Hwang, S.J.; Taiwan Society of Nephrology. ”Incidence, prevalence and mortality trends of dialysis end-stage renal disease in Taiwan from 1990 to 2001: the impact of national health insurance.” Nephrol Dial Transplant. 23(12): 3977-3982, 2008. Foundation, N. K. : Clinical Practice Guidelines and Clinical Practice Recommendations for Diabetes and Chronic Kidney Disease. Am J Kidney Dis. 49(Suppl 2): 1-183, 2007. Ohkubo Y, Kishikawa H, Araki E, et al: Intensive insulin therapy prevents the progression of diabetic microvascular complications in Japanese patients with non-insulindependent diabetes mellitus: A randomized prospective 6-year study. Diabetes Res Clin Pract 28:103-117, 1995. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/44219 | - |
| dc.description.abstract | 世界各國末期腎臟病患數均不斷上升,估計至2010年全世界末期腎臟病人口將超過200萬人。美國腎臟資料系統2010年度報告顯示,台灣末期腎臟病發生率與盛行率皆為世界第一,而不斷增加的罹病人口將對醫療支出造成壓力。中央健康保險局2010年統計資料指出,透析醫療費用佔總醫療支出的7.88%,接受透析治療的患者人數卻只佔總人口的0.27%,平均一位接受透析治療患者的醫療費用為全國每人平均的26.4倍,醫療資源的耗用不可謂不大。因此,本研究嘗試以歷史資料分析發生率、盛行率的變化趨勢,進而預測未來至2020年之新發生人數與盛行人數,期予衛生醫療政策擬定者於預算、資源擬定分配之參考依據,減少資源錯置,達到最大利用,促使末期腎臟病的蔓延得以妥善預防與控制。
使用全民健康保險學術研究資料庫1997年至2009年之資料,篩選共114966位末期腎臟病連續四個月以上透析患者。以自我迴歸整合移動平均模型預測發生率,並記錄各年死亡人數以逐年推估盛行人數至2020年。 ARIMA(0,3,3)模式與ARIMA(p,d,q)較適組合模式之2020年預測發生人數分別為17032人與16289人,較2008年實際發生人數增加83%與75%。自2009年至2020年兩組預測模式之平均年增率分別為4.79%、4.67%。ARIMA(0,3,3)+死亡率1模式與ARIMA(較適組合)+死亡率1模式之2020年預測盛行人數分別為102145人、99688人,為2008年的1.7倍之多,平均年增率為4.85%與4.68%。 末期腎臟病患人數的增加主要來自於糖尿病腎病變患者,估計至2020年新發生病例中將有超過八成來自糖尿病患,而盛行人數中糖尿病性腎病變患者人數也將逼近六成。因此,若能針對糖尿病患,積極控制慢性腎臟病的發展,避免進入接受透析治療的最終階段,應可有效降低末期腎臟病接受透析治療的人口數。 | zh_TW |
| dc.description.abstract | The worldwide patients with end-stage renal disease are increasing and are estimated that there will be over two million patients in 2020. According to the United States Renal Data System 2010 Annual Report, Taiwan ranks first in the world in the incidence and the prevalence of end-stage renal disease. Moreover, the medical expenses will be under pressure by the increasing patients in Taiwan. Statistics from Bureau of National Health Insurance, Department of Health, Executive Yuan in 2010 indicated that the expenses of dialysis therapy contributed 7.88% of the total medical expenditure, but the patients on dialysis only accounted for 0.27% of the total population in Taiwan. Indeed, spending of the medical expenditure was at great expense of that the average expenses for one patient on dialysis is 26.4-fold than for any other person. Thus, the purpose of the present research is to use the historical data of the incidence and the prevalence to project the number of dialysis patients with end-stage renal disease in the year 2020, and then to help the Department of Health to optimize the budget and resource allocation and the prevention and control of the spread of end-stage renal disease.
In the present study, 114,996 patients with end-stage renal disease who were on dialysis for over continuous four months were chosen from National Health Insurance Research Database of 1997 to 2009. The prediction of incidence was estimated using autoregressive integrated moving average model (ARIMA), and the mortality was recorded by year to speculate the prevalence until 2020. The projecting number of patients with end-stage renal disease in 2020 using ARIMA (0, 3, 3) and ARIMA (p, d, q)better in 2008, respectively. The average year increase rate from 2009 to 2020 estimated by ARIMA (0, 3, 3) and ARIMA (p, d, q)better were 4.79% and 4.67%, respectively. The predicted prevalence in 2020 were 102,145 and 99,688 people speculated by ARIMA (0, 3, 3) + mortality and ARIMA (p, d, q)better + mortality, respectively, which were 1.7-fold than in 2008, and the year increase rate of prevalence were 4.85% and 4.68%. Patients with diabetic nephropathy are the major contributors to the increase of the number of patients with end-stage renal disease. Based on the present prediction in 2020, there will be over 80% of patients on dialysis come from the patients with diabetes, and the patients with diabetic nephropathy will take almost 60% in the prevalence. Thus, efficiently lowering the number of patients with end-stage renal disease could depend on preventing course of disease into the end-stage by controlling actively the development of chronic kidney disease (CKD) which runs in the patients with diabetes. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-15T02:45:34Z (GMT). No. of bitstreams: 1 ntu-100-R93843019-1.pdf: 1850358 bytes, checksum: 3b1f8393acea3219a83e2ab4591933bf (MD5) Previous issue date: 2011 | en |
| dc.description.tableofcontents | 中文摘要 i
Abstract ii 目錄 iv 表目錄 v 圖目錄 vii 第壹章 緒論 1 第貳章 文獻探討 3 第叁章 研究方法 17 第肆章 研究結果 25 第伍章 討論 33 參考文獻 36 | |
| dc.language.iso | zh-TW | |
| dc.subject | 末期腎臟病 | zh_TW |
| dc.subject | 透析 | zh_TW |
| dc.subject | 預測 | zh_TW |
| dc.subject | 時間序列 | zh_TW |
| dc.subject | 自我迴歸整合移動平均 | zh_TW |
| dc.subject | 盛行人數 | zh_TW |
| dc.subject | ARIMA | en |
| dc.subject | dialysis | en |
| dc.subject | prevalence | en |
| dc.subject | ESRD | en |
| dc.subject | time series | en |
| dc.subject | predict | en |
| dc.title | 台灣2020年末期腎臟病透析人數預測 | zh_TW |
| dc.title | Projecting the Number of Dialysis Patients with End-Stage Renal Disease in Taiwan to the Year 2020 | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 99-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 高森永,張怡秋 | |
| dc.subject.keyword | 末期腎臟病,透析,預測,時間序列,自我迴歸整合移動平均,盛行人數, | zh_TW |
| dc.subject.keyword | ESRD,dialysis,predict,time series,ARIMA,prevalence, | en |
| dc.relation.page | 76 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2011-08-22 | |
| dc.contributor.author-college | 公共衛生學院 | zh_TW |
| dc.contributor.author-dept | 健康政策與管理研究所 | zh_TW |
| 顯示於系所單位: | 健康政策與管理研究所 | |
文件中的檔案:
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-100-1.pdf 未授權公開取用 | 1.81 MB | Adobe PDF |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。
