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  1. NTU Theses and Dissertations Repository
  2. 公共衛生學院
  3. 健康政策與管理研究所
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/25732
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor張睿詒
dc.contributor.authorMing-Fang Changen
dc.contributor.author張明芳zh_TW
dc.date.accessioned2021-06-08T06:27:09Z-
dc.date.copyright2006-08-04
dc.date.issued2006
dc.date.submitted2006-07-27
dc.identifier.citation中文部分
石淦生、羅紀瓊:牙科病患健保門診就醫選擇現況探討。中華牙誌,19:299-305,2000。
林思甄:牙醫醫療利用風險因子之探討。中國醫藥大學醫務管理學研究所碩士論文,2004。
張睿詒、賴秋伶:風險校正因子:論人計酬醫療費用預測之基礎。台灣衛誌,23(2),2004。
張舒婷:建構所有診斷資訊群組及其風險預測模式。台北:台灣大學公共衛生學院醫療機構管理研究所碩士論文,2005。
張雅嵐:中醫門診風險計價模式之建立。台北:台灣大學公共衛生學院醫療機構管理研究所碩士論文,2006。
蔡偉德、羅紀琼:「論人計酬」之支付標準探討。經濟論文 2000;28:231-261。
謝孟甫,張睿詒:處方資訊用於台灣風險校正模型之初探,台灣公共衛生雜誌2006:25(3),189-200。
鄭麗美:牙醫師人口比與民眾牙科就醫行為比較之探討:以台中縣為例。高雄醫學大學口腔衛生科學研究所碩士論文,2003。

英文部分
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Bahru Y, Abdu SS. A study of dental problems in diabetic patients. Ethiopian Medical Journal 1992: 30: 95–103.
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Brennan DS, Spencer AJ: Influence of patient, visit, and oral health factors on dental service provision. Journal of Public Health Dentistry 2002;62:148-157.
Breiman, L.; Friedman, J. H.; Olshen, R. A.; Stone, C. G. Classification and Regression Trees; Wadsworth International Group: Belmont, CA, 1984.
Chang RE, Lin WD, Hsieh CJ, Chiang TL. (2002), “Healthcare utilization patterns and risk adjustment under Taiwan's National Health Insurance system” J FORMOS MED ASSOC 101 (1), 52-59.
Chang RE, Lai CL: Using Diagnosis-Based Risk Adjustment Models to Predict Individual Healthcare Expenditure under the National Health Insurance in Taiwan. J Formos Med Assoc 2006. (Forthcoming).
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Ettner S. L., Johnson, S. Do Adjusted Clinical Groups Eliminate Incentives for HMOs to Avoid Substance Abusers? Evidence from the Maryland Medicaid HealthChoice Program. The Journal of Behavioral Health Services & Research; 30(1):63-77, 2003.
Grimaldi P. L.: Medicae’s risk-adjusted Capitation Method. Journal of Health Care Finance; 28:105-119, 2002.
Laine MA. Effect of pregnancy on periodontal and dental health. Acta Odontol Scand 2002;60:257 –264.
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Lapp CA, Thomas ME, Lewis JB. Modulation by progesterone of interleukin-6 production by gingival fibroblasts. J Periodontol 1995;66:279–84.
Lin WD, Chang RE, Hsieh CJ, Yaung CL, Chiang TL: The development of a risk-adjusted capitation model based on principal inpatient diagnoses in Taiwan. Journal of Formosan Medical Association 2003;102:637-43.
Locker D, Clarke M, Geographic variations in dental services provided to older adults in Ontario, Canada. Community Dent Oral Epidemiol 1999;27:275-82.
Lubitz J. and Prihoda R.: Use and Cost of Medicare Services in the Last Years of Life. Health Care Financing Review 5(3):117-131, Spring 1984.
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Manski, RJ and Moeller, JF, “Dental Services: An Analysis of Visits, Procedures and Providers, 1996,” Journal of the American Dental Association, 133(2):167-175, February 2002
Manski, RJ, Moeller, JF and Maas, W. “Dental Services: Use, Expenditures and Sources of Payment, 1987,” Journal of the American Dental Association, 130(4):500-508, April 1999.
McDerra EJ, Pollard MA, Currzon ME: The dental status of asthmatic British school children. Pedia Den 1998;20:281-85.
Newhouse, J.P.: Rate Adjustors for Medicare Under Capitation. Health Care Financing Review Annual Supplement, 45-56, 1986
Oliver RC, Tervonen T. Periodontitis and tooth loss. Comparing diabetics with the general population. J Am Dent Assoc 1993: 124: 71–76.
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Pope, G. C., Kautter, J., Ellis, R. P., Ash, A. S., et al. Risk Adjustment of Medicare Capitation Payments Using the CMS-HCC Model. Health Care Financing Review; 25(4):119-141, 2004.
Rees TD. Periodontal management of the patient with diabetes mellitus. Periodontol 2000; 23(1):63-72
Richard J. Manski, Laurence S. Magder: Demographic and Socioeconomic Predictors of Dental Care Utilization. Journal of the American Dental Association 1998;129:195-200.
Shlossman M, Knowler WC, Pettitt DJ, Genco RJ. Type 2 diabetes mellitus and periodontal disease. J Am Dent Assoc 1990: 121: 532–536.
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Sta°hlnacke K, So¨derfeldt B, Unell L, Halling A, Axtelius B: Changes over 5 years in utilization of dental care by a Swedish age cohort. Community Dent Oral Epidemiol 2005;33:64–73.
Thorstensson H, Falk H, Hugoson A, Olsson J. Some salivary factors in insulin-dependent diabetics. Acta Odontologica Scandinavica 1989: 47: 175–183.
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/25732-
dc.description.abstract國際間許多國家之健康保險制度皆面臨醫療費用高漲的問題,採前瞻性支付制度以為因應。前瞻式預算近年來多採用校正論人方式計算預算額度。台灣全民健保支付制度亦引入總額預算之方式,擬有效抑制費用成長,然其總額預算額度之設定並非藉由論人計酬方式,本研究首先發展牙醫風險校正論人計酬之計價模式,期提供未來前瞻性預算額度設定之參考。
本研究利用全民健康保險研究資料庫中2001年與2002年保險對象相關資料進行研究,隨機抽取樣本共計2,131,067人,以迴歸(Weighted Least Square)方式及分類與迴歸樹(Classification and Regression Trees, CART)方式分別建構三種不同之風險計價模式。人口因子模式選用年齡與性別為自變項,先前利用模式採用年齡、性別與前一年牙醫門診費用,診斷資料模式則利用年齡、性別以及9種與牙醫醫療利用相關之疾病,而6個模式的依變項皆為保險對象2002年年化後牙醫門診費用。
在PR2方面,利用CART方法之風險計價模式其預測力較迴歸方法略高,其中診斷資料模式預測力皆優於人口因子模式且不低於先前利用模式。在特定群體預測比方面,不論迴歸或CART方法,診斷資料模式與先前利用模式相當,此兩模式皆優於人口因子模式。
人口因子模式資料容易取得但預測力偏低,先前利用模式相較人口因子模式其PR2的提升有限,推論應與牙醫醫療特性及國內民眾就醫習慣有關,而診斷資料模式中3項牙科疾病可掌握樣本大部分的牙醫醫療利用,但其前後年個人醫療費用相關係數僅0.125,因此預測力有所侷限。未來可思考不同牙科疾病其第二年牙醫門診照護需要的差異,且是否有更細緻的資訊可提供區分同一疾病者對於次年需要之差異,藉此建構較為細緻的診斷群組,應可對未來牙醫門診醫療需要提供更為精確的預測。
zh_TW
dc.description.abstractMany countries have experienced the escalation of health care expenditure and have adopted prospective payment system. Under prospective payment system, risk-adjusted capitation has been considered and implemented to set budgets in recent years. In order to contain the growth of expenditure, Taiwan’s National Health Insurance program has adopted a global budget payment system, and budgets were not set through capitation. This study intends to develop risk assessment capitation models for dental care. The results may provide alternative approaches of allocating prospective budgets in Taiwan’s NHI program.
By using NHI’s research data bank of 2001 and 2002, 2,131,067 enrollees was randomly selected as the study sample. Three risk assessment models were developed through weight least square estimation and Classification and Regression Trees (CART) respectively. The independent variables of demographic model are age and sex. In addition to age and sex, while the prior utilization model includes individual’s 2001 outpatient expenditure of dental care as an independent variable, and the diagnostic model includes nine diseases as the independent variables. The dependent variable of the six models is enrollee’s 2002 annualized dental care expenditure.
The PR2 of risk assessment model through CART are slightly higher than those through regression. The PR2 of diagnostic model is better than demographic model and at least as good as the prior utilization model. The PR values of diagnostic model are similar to prior utilization model, and both of them are better than demographic model.
Demographic data are easy to gain but the PR2 is low. Although the PR2 of prior utilization model is higher than that of the demographic model, the improvement is somewhat limited. The reason may be related to the characteristics of dental care and the utilization behavior. The three oral diseases included in the diagnostic model account for most utilization of outpatient dental care; however, the correlation of individual expenditures between 2001 and 2002 is relatively low, only 0.125. The predictability of the diagnostic model is therefore restricted. It is encouraged to investigate the difference of the need for outpatient dental care in subsequent year for individual oral diseases. This subtle diagnostic information can provide a basis of developing refined diagnostic groups which may predict the need of outpatient dental care more accurately.
en
dc.description.provenanceMade available in DSpace on 2021-06-08T06:27:09Z (GMT). No. of bitstreams: 1
ntu-95-R93843016-1.pdf: 340369 bytes, checksum: a5dcf84408a6b5deee3bf1aa2ae52364 (MD5)
Previous issue date: 2006
en
dc.description.tableofcontents目 錄
致謝i
中 文 摘 要 ii
英 文 摘 要 iii
第一章 緒論 1
第二章 文獻探討 4
第三章 研究設計與方法 13
第四章 研究結果 17
第五章 討論 22
參考文獻 26
附表 30
表 目 錄
附表1 牙醫醫療利用之相關因素整理 30
附表2 牙醫風險計價模式之疾病診斷碼對照表 31
附表3 樣本各性別年齡層人數分佈 31
附表4 樣本各性別年齡層平均每人牙醫門診費用、標準差與變異係數(CV)值 32
附表5 人口因子模式之分組內容與樣本人數、平均費用分佈 33
附表6 先前利用模式之分組內容與樣本人數、平均費用分佈 34
附表7 診斷資料模式之分組內容與樣本人數、平均費用分佈 35
附表8 牙醫風險計價模式之迴歸係數及adjusted R2 38
附表9 牙醫風險計價模式之PR2 39
附表10 牙醫風險計價模式特定群體預測比 39
附表11 總研究樣本2001年與2002年牙醫門診利用情形 40
附表12 總研究樣本與各疾病樣本之牙醫醫療利用分析 40
dc.language.isozh-TW
dc.subject風險校正zh_TW
dc.subject分類與迴歸樹zh_TW
dc.subject牙醫zh_TW
dc.subjectClassification and Regression Treesen
dc.subjectRisk Adjustmenten
dc.subjectDental Careen
dc.title牙醫門診風險計價模式之建立zh_TW
dc.titleDevelopment of Risk Assessment Models for Dental Careen
dc.typeThesis
dc.date.schoolyear94-2
dc.description.degree碩士
dc.contributor.oralexamcommittee江東亮,林文德
dc.subject.keyword牙醫,風險校正,分類與迴歸樹,zh_TW
dc.subject.keywordDental Care,Risk Adjustment,Classification and Regression Trees,en
dc.relation.page40
dc.rights.note未授權
dc.date.accepted2006-07-27
dc.contributor.author-college公共衛生學院zh_TW
dc.contributor.author-dept醫療機構管理研究所zh_TW
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