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  1. NTU Theses and Dissertations Repository
  2. 管理學院
  3. 資訊管理學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/60167
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor陳靜枝(Ching-Chin Chern)
dc.contributor.authorYu Jen Chenen
dc.contributor.author陳佑任zh_TW
dc.date.accessioned2021-06-16T10:00:32Z-
dc.date.available2017-02-08
dc.date.copyright2017-02-08
dc.date.issued2016
dc.date.submitted2016-11-16
dc.identifier.citation[1] Apparicio, P., M. Abdelmajid, M. Riva, and R. Shearmur, “Comparing alternative
approaches to measuring the geographical accessibility of urban health services:
Distance types and aggregation-error issues”, International journal of health
geographics, Vol. 7, no. 1, 2008, pp 7.
[2] Barlow, J., D. Singh, S. Bayer, and R. Curry, “A systematic review of the benefits of
home telecare for frail elderly people and those with long-term conditions”, Journal
of Telemedicine and Telecare, Vol. 13, no. 4, 2007, pp 172-179.
[3] Celler, B.G., N.H. Lovell, and J. Basilakis, “Using information technology to improve
the management of chronic disease”, Medical Journal of Australia, Vol. 179, no. 5,
2003, pp 242-246.
[4] Chen, Y. H., Y. H. Lin, C. S. Hung, C. C. Huang, D. F. Yeih, P. Y. Chuang, Y. L. Ho,
and M. F. Chen, “Clinical outcome and cost-effectiveness of a synchronous telehealth
service for seniors and nonseniors with cardiovascular diseases: quasi-experimental
study”, J Med Internet Res, Vol. 15, no. 4, 2013.
[5] Chiang L. C., W. C. Chen, Y. T. Dai, and Y. L. Ho, “The effectiveness of telehealth
care on caregiver burden, mastery of stress, and family function among family
caregivers of heart failure patients: A quasi-experimental study”, International Journal
of Nursing Studies, Vol. 49, no. 10, 2012, pp 1230-1242.
[6] Chiang T. L., “Taiwan's 1995 health care reform”, Health policy, Vol. 39, no.3, 1997,
pp 225-239.
[7] Durrani H. and S. Khoja, “A systematic review of the use of telehealth in Asian
countries”, Journal of telemedicine and telecare, Vol. 15, no. 4, 2009, pp 175-181.
[8] Fujii M. and M. R. Reich, “Rising medical costs and the reform of Japan's health
insurance system”, Health Policy, Vol. 9, no. 1, 1988, pp 9-24.
[9] Fujimoto M., K. Miyazaki, and N. Von Tunzelmann, “Complex systems in technology
and policy: telemedicine and telecare in Japan”, Journal of telemedicine and telecare,
Vol. 6, no. 4, 2000, pp 187-192.
[10] GACD, Global Alliance for Chronic Diseases Annual Report 2014/15.
[11] Ho Y. L., J. Y. Yu, Y. H. Lin, Y. H. Chen, C. C. Huang, T. P. Hsu, P. Y. Chuang, C. S.
Hung, and M. F. Chen, “Assessment of the Cost-Effectiveness and Clinical Outcomes
of a Fourth-Generation Synchronous Telehealth Program for the Management of
Chronic Cardiovascular Disease”, Journal of Medical Internet Research, Vol. 16, no.
6, 2014, pp 145.
[12] Hung C.S., Y. H. Chen, C. C. Huang, D. F. Yeih, Y. H. Lin, Y. L. Ho, and M. F. Chen,
“A Fourth Generation Telehealth Care Program is Associated With Lower
Hospitalization Rate, Duration and Lower Medical Cost”, Circulation, Vol. 128, no.
22 Supplement, 2013, pp A11964.
[13] Kenneth B., B. Daniel, and L. Mark, “Clinical investigation-nursing assistants detect
behavior changes in nursing home residents that precede acute illness: development
and validation of an illness warning instrument”, Journal of the American Geriatrics
Society, Vol. 48, no. 9, 2000, pp 1086-1091.
[14] Kuttner R., “Health insurance coverage”, New England Journal of Medicine, Vol. 340,
no. 2, 1999, pp 163-168.
[15] Lee Y. C., Y. T. Huang, Y. W. Tsai, S. M. Huang, K. N. Kuo, M. McKee, and E. Nolte,
“The impact of universal National Health Insurance on population health: the
experience of Taiwan”, BMC Health Services Research, Vol. 10, no. 1, 2010 pp 225.
[16] Li X.B., J. Sweigart, J. Teng, J. Donohue, and L. Thombs, “A dynamic programming
based pruning method for decision trees”, INFORMS Journal on Computing, Vol. 13,
51
no. 4, 2001, pp 332-344.
[17] Lillie-Blanton M. and C. Hoffman, “The role of health insurance coverage in reducing
racial/ethnic disparities in health care”, Health Affairs, Vol. 24, no. 2, 2005, pp 398-
408.
[18] McDermott S., R. Breen, T. Platt, D. Dhar, J. Shelton, and S. Krishnaswami, “Do
behavior changes herald physical illness in adults with mental retardation?”,
Community mental health journal, Vol. 33, no. 2, 1997, pp 85-97.
[19] Quinlan J. R., “Induction of decision trees”, Machine learning, Vol. 1, no. 1, 1986, pp
81-106.
[20] Scott R. E., M. F. U. Chowdhury, and S. Varghese, “Telehealth policy: looking for
global complementarity”, Journal of telemedicine and telecare, Vol. 8, no. 2
supplement, 2002, pp 55-57.
[21] Wen C. P., S. P. Tsai, and W. S. Chung, “A 10-year experience with universal health
insurance in Taiwan: measuring changes in health and health disparity”, Annals of
Internal Medicine, Vol. 148, no. 4, 2008, pp 258-267.
[22] WHO, World Health Statistics 2015. 2015: World Health Organization, Geneva,
Switzerland, 2015.
[23] 內政部統計處, 103 年簡易生命表. 2014.
[24] 行政院主計處, 內政部統計處, 衛生福利部, 中華民國102 年老人狀況調查報
告. 2013, 行政院主計處: 臺北市.
[25] 李卓倫, 陳文意, 陳慈純, 洪弘昌, 台灣發展遠距健康照護的現況與挑戰. 醫
學與健康期刊, 2013. 2(2): pp 1-10.
[26] 國立臺灣大學, 知識經濟新興產業與技術展望: 公務人員知識經濟與服務理念
訓練學員參考讀本. 2001: 公務人力發展中心出版.
[27] 國家發展委員會, 中華民國人口推計(103 至150 年). 2014.
[28] 許哲瀚, 唐憶淨, 遠距居家照護的現況與未來. 台灣老年醫學暨老年學雜誌,
2008. 3(4): pp 272-285.
[29] 蔡宗宏, 莊碧焜, 遠距照護系統成效評估之研究. 電腦稽核, 2011(23): pp
113-135.
[30] 衛生福利部, 102-105 年中程施政計畫, 衛生福利部, 2013: 綜合規劃司.
[31] 衛生福利部統計處, 死因統計. 2015.
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/60167-
dc.description.abstract在臺灣,政府必須發展一套系統性的老人福利政策以因應高齡化社會的來臨。透過
資通訊技術與健康保險的幫助,遠距照護成為協助高齡化社會的一種可能方案。然而遠
距照護除了使用成本仍居高不下外,其適用的人數也相對稀少,因此我們必須要能找出
那些少數適合遠距照護服務的民眾。
本篇研究中,我們提出一個使用決策樹做為主要資料探勘的啟發式模型(HDTTCA),
用來找出符合適用遠距照護民眾的條件。我們假設遠距照護服務能被納入在台灣特有的
健康保險制度(全民健康保險)裡,因此必須設計出一套找出全臺兩千三百萬人中適用的
民眾的演算法以降低人工分類的負擔。
由於決策樹的易讀性讓民眾能明確地了解適用遠距照護的條件,也提供政府在擬定
相關遠距照護政策時參考的規則。在這個模型中共有三個步驟:資料前處理、建構決策
樹、預測並解釋分類結果。本篇研究也找出三個在遠距照護產業影響甚大的關鍵因素:
醫療紀錄、就醫方便性與申請人的社經地位。
zh_TW
dc.description.abstractIn Taiwan, it is top priority to develop a systematic policy for the elderly in the coming era
of ageing society. Telecare is one possible solution that combine the help of information
technology and health policy. However, the telecare service is expensive and is only adoptable
for chronic citizens nowadays.
This study proposes a Heuristic Decision Tree based Telecare Classification Approach
(HDTTCA), a systematic structure to figure out those who are applicable for telecare service.
We assume that National Health Insurance scheme subsidy the cost. Therefore, it is necessary
to classify all the people in the country, we apply classification algorithm to reduce the research
time. The main process of HDTTCA has three steps: (1) datasets preprocessing; (2) decision
tree model building; and (3) prediction and explanation. In this study, we find out three of most
important dimensions in telecare industry: clinical records, convenience, and social-economic
status.
We apply HDTTCA in a real world dataset and find that decision tree is a potential
classification algorithm in solving this problem because of its interpretability. The see-through
rules also give government a clear guideline to improve the decision-making process.
en
dc.description.provenanceMade available in DSpace on 2021-06-16T10:00:32Z (GMT). No. of bitstreams: 1
ntu-105-R03725053-1.pdf: 1333825 bytes, checksum: f405eae7b135df2bae628792a2ac2508 (MD5)
Previous issue date: 2016
en
dc.description.tableofcontentsList of Figures ......................................................................................................................................... v
Acknowledgment .................................................................................................................................... v
List of Tables .......................................................................................................................................... vi
Chapter 1 Introduction ................................................................................................................... 1
1.1 Background and Motivation .............................................................................................. 1
1.2 Research Objectives .......................................................................................................... 5
1.3 Research Scope and Limitation ......................................................................................... 6
Chapter 2 Literature Review .......................................................................................................... 8
2.1 Health Insurance ................................................................................................................ 8
2.2 Decision Tree ..................................................................................................................... 9
Chapter 3 Problem Description.................................................................................................... 11
3.1 Problem Description ........................................................................................................ 11
3.2 Data Preparation .............................................................................................................. 12
3.3 Classification ................................................................................................................... 15
Chapter 4 The Heuristic Decision-Tree based Telecare Classification Approach (HDTTCA) ... 18
4.1 Step 1: Datasets Preprocessing ........................................................................................ 19
4.2 Step 2: Decision Tree Model Building ............................................................................ 31
4.3 Step 3: Prediction and Explanation ................................................................................. 33
4.4 Complexity ...................................................................................................................... 34
Chapter 5 Computational Analysis .............................................................................................. 35
5.1 Introduction of the Real-World Dataset ........................................................................... 35
5.2 An Example of Year 2012 ............................................................................................... 36
5.3 Experiments ..................................................................................................................... 45
5.4 Results ............................................................................................................................. 47
Chapter 6 Conclusion and Future Work ....................................................................................... 48
6.1 Conclusion ....................................................................................................................... 48
6.2 Future Work ..................................................................................................................... 49
Reference .............................................................................................................................................. 50
Appendix .............................................................................................................................................. 52
dc.language.isoen
dc.subject決策樹zh_TW
dc.subject資料分類zh_TW
dc.subject資料處理zh_TW
dc.subject資料探勘zh_TW
dc.subject遠距照護zh_TW
dc.subjectTelecareen
dc.subjectData Miningen
dc.subjectData Preprocessingen
dc.subjectData Classificationen
dc.subjectDecision Treeen
dc.title採用遠距照護之決策樹分類-以臺灣遠距照護系統為例zh_TW
dc.titleThe Application of Decision-Tree Based Classification on Telecare System: A Case Study of Taiwan’s Telecare Systemen
dc.typeThesis
dc.date.schoolyear105-1
dc.description.degree碩士
dc.contributor.oralexamcommittee魏志平(Chih-Ping Wei),盧信銘(Hsin-Min Lu),孔令傑
dc.subject.keyword遠距照護,資料探勘,資料處理,資料分類,決策樹,zh_TW
dc.subject.keywordTelecare,Data Mining,Data Preprocessing,Data Classification,Decision Tree,en
dc.relation.page53
dc.identifier.doi10.6342/NTU201603747
dc.rights.note有償授權
dc.date.accepted2016-11-16
dc.contributor.author-college管理學院zh_TW
dc.contributor.author-dept資訊管理學研究所zh_TW
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