請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/6486完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 鍾國彪 | |
| dc.contributor.author | Hsiao-Chen Hsu | en |
| dc.contributor.author | 許曉溱 | zh_TW |
| dc.date.accessioned | 2021-05-17T09:14:08Z | - |
| dc.date.available | 2017-09-17 | |
| dc.date.available | 2021-05-17T09:14:08Z | - |
| dc.date.copyright | 2012-09-17 | |
| dc.date.issued | 2012 | |
| dc.date.submitted | 2012-08-16 | |
| dc.identifier.citation | 1. Donabedian, A., Explorations in Quality Assessment and Monitoring: The definition of quality and approaches to its assessment. Vol. 1. 1980: Health Administration Press.
2. Veillard, J., F. Champagne, N. Klazinga, V. Kazandjian, O.A. Arah, and A.L. Guisset, A performance assessment framework for hospitals: the WHO regional office for Europe PATH project. International Journal for Quality in Health Care, 2005. 17(6): p. 487-496. 3. 財團法人醫院評鑑暨醫療品質策進會, 醫療品質指標理論與應用. 指標系統簡介, ed. 郭乃文2003, 台北: 合計圖書出版社. 1-11. 4. McGlynn, E.A., S.M. Asch, J. Adams, J. Keesey, J. Hicks, A. DeCristofaro, and E.A. Kerr, The quality of health care delivered to adults in the United States. N Engl J Med, 2003. 348(26): p. 2635-45. 5. 行政院衛生署, 行政院衛生署衛生統計系列(三)死因統計, 1993-2010. 6. 邱春吉, 李炳鈺, and 廖繼洲, 急性心肌梗塞之病例報告與用藥討論. 台灣臨床藥學雜誌, 1999. 7(1): p. 93-111. 7. Ryan, T.J., J.L. Anderson, E.M. Antman, B.A. Braniff, N.H. Brooks, R.M. Califf, L.D. Hillis, L.F. Hiratzka, E. Rapaport, B.J. Riegel, R.O. Russell, E.E. Smith, W.D. Weaver, J.L. Ritchie, M.D. Cheitlin, K.A. Eagle, T.J. Gardner, A. Garson, R.J. Gibbons, R.P. Lewis, and R.A. Orourke, ACC/AHA guidelines for the management of patients with acute myocardial infarction - A report of the American College of Cardiology American Heart Association task force on practice guidelines (Committee on management of acute myocardial infarction). Journal of the American College of Cardiology, 1996. 28(5): p. 1328-1419. 8. Organisation for Economic Co-operation and Development(OECD). Health Care Quality Indicators. 2012 [cited 2012 Jan 01]; Available from: http://www.oecd.org/document/34/0,3746,en_2649_37407_37088930_1_1_1_37407,00.html. 9. Mattke, S., A.M. Epstein, and S. Leatherman, The OECD Health Care Quality Indicators Project: History and background. International Journal for Quality in Health Care, 2006. 18: p. 1-4. 10. U.S. Department of Health & Human Services. Hospital Compare. 2012 [cited 2012 Jan 05]; Available from: http://www.hospitalcompare.hhs.gov/hospital-search.aspx. 11. U.K. National Health Service(NHS). Indicator Portal. 2012 [cited 2012 Jan 05]; Available from: https://indicators.ic.nhs.uk/webview/. 12. Goss, M.E.W. and J.I. Reed, Evaluating quality of hospital care through severity-adjusted death rates - some pitfalls Medical Care, 1974. 12(3): p. 202-213. 13. Desharnais, S., L.F. McMahon, and R. Wroblewski, Measuring outcomes of hospital-care using multiple risk-adjusted indexes. Health Services Research, 1991. 26(4): p. 425-445. 14. Desharnais, S.I., L.F. McMahon, R.T. Wroblewski, and A.J. Hogan, Measuring hospital performance - the development and validation of risk-adjusted indexes of mortality, readmissions, and complications. Medical Care, 1990. 28(12): p. 1127-1141. 15. Wu, A.W., The measure and mismeasure of hospital quality - appropriate risk-adjustment methods in comparing hospitals. Annals of Internal Medicine, 1995. 122(2): p. 149-150. 16. Iezzoni, L.I., Using risk-adjusted outcomes to assess clinical-practice - an overview of issues pertaining to risk adjustment. Annals of Thoracic Surgery, 1994. 58(6): p. 1822-1826. 17. Mainz, J., Defining and classifying clinical indicators for quality improvement. International Journal for Quality in Health Care, 2003. 15(6): p. 523-530. 18. Iezzoni, L.I., Risk Adjustment for Measuring Healthcare Outcomes, Third Edition 3 edition ed2003, Chicago: Health Administration Press. 508. 19. Iezzoni, L.I., The risks of risk adjustment. Jama-Journal of the American Medical Association, 1997. 278(19): p. 1600-1607. 20. Poses, R.M., D.K. McClish, W.R. Smith, E.C. Huber, F.L. Clemo, B.P. Schmitt, D. Alexander, E.M. Racht, and C.C. Colenda, 3rd, Results of report cards for patients with congestive heart failure depend on the method used to adjust for severity. Ann Intern Med, 2000. 133(1): p. 10-20. 21. 曲直部壽夫, 心肌梗塞•狹心症2000, 台北: 武陵出版有限公司. 147. 22. 陳明豐, 冠狀動脈與心臟病. 2nd ed. 冠狀動脈心臟病─心肌梗塞1994, 台北: 健康世界雜誌社. 23. 朱樹勳, 心臟病與開心手術. 2nd ed. 冠狀動脈性心臟病1995, 台北: 健康世界雜誌社. 24. 李碩粲 and 許勝雄, 急性心肌梗塞. 高醫醫訊月刊, 2002. 21(9). 25. 李瑞華等修訂 and 鄭茉莉、張樹棠主編, ICD-9-CM分類規則彙編2007, 台北市: 台灣病歷管理協會. 26. 許百豐 and 常敏之, 急性冠心症:不穩定型心紋痛與非ST段上升心肌梗塞的最新處置原則. 中華民國重症醫學雜誌, 2004. 6(1): p. 91-100. 27. Killip Iii, T. and J.T. Kimball, Treatment of myocardial infarction in a coronary care unit: A Two year experience with 250 patients. The American Journal of Cardiology, 1967. 20(4): p. 457-464. 28. Forrester, J.S., G. Diamond, K. Chatterjee, and H.J. Swan, Medical therapy of acute myocardial infarction by application of hemodynamic subsets (second of two parts). N Engl J Med, 1976. 295(25): p. 1404-13. 29. Lee, K.L., L.H. Woodlief, E.J. Topol, W.D. Weaver, A. Betriu, J. Col, M. Simoons, P. Aylward, F. Vandewerf, and R.M. Califf, Predictors of 30-day mortality in the era of reperfusion for acute myocardial-infarction - results from an international trial of 41 021 patients. Circulation, 1995. 91(6): p. 1659-1668. 30. Spertus, J.A., M.J. Radford, N.R. Every, E.F. Ellerbeck, E.D. Peterson, and H.M. Krumholz, Challenges and opportunities in quantifying the quality of care for acute myocardial infarction: summary from the Acute Myocardial Infarction Working Group of the American Heart Association/American College of Cardiology First Scientific Forum on Quality of Care and Outcomes Research in Cardiovascular Disease and Stroke. Circulation, 2003. 107(12): p. 1681-91. 31. Amer Coll Cardiol Amer Heart Assoc Task Force Performance, M. and S.T.E.N.-S.T.E.M. Writing Comm Dev Performance Measures, ACC/AHA clinical performance measures for adults with ST-elevation and non-ST-elevation myocardial infarction - A report of the American College of Cardiology/American Heart Association Task Force on performance measures (Writing Committee to develop performance measures on ST-elevation and non-ST-elevation myocardial infarction). Circulation, 2006. 113(5): p. 732-761. 32. Krumholz, H.M., ACC/AHA clinical performance measures for adults with ST-elevation and non-ST-elevation myocardial infarction: A report of the American College of Cardiology/American Heart Association Task Force on Performance Measures (Writing Committee to Develop Performance Measures on ST-Elevation and Non-ST-Elevation Myocardial Infarction) (vol 47, pg 236, 2006). Journal of the American College of Cardiology, 2006. 47(10): p. 2140-2140. 33. Krumholz, H.M., J.L. Anderson, B.L. Bachelder, F.M. Fesmire, S.D. Fihn, J.M. Foody, P.M. Ho, M.N. Kosiborod, F.A. Masoudi, and B.K. Nallamothu, ACC/AHA 2008 Performance Measures for Adults With ST-Elevation and Non-ST-Elevation Myocardial Infarction A Report of the American College of Cardiology/American Heart Association Task Force on Performance Measures (Writing Committee to Develop Performance Measures for ST-Elevation and Non-ST-Elevation Myocardial Infarction) Developed in Collaboration With the American Academy of Family Physicians and American College of Emergency Physicians Endorsed by the American Association of Cardiovascular and Pulmonary Rehabilitation, Society for Cardiovascular Angiography and Interventions, and Society of Hospital Medicine. Journal of the American College of Cardiology, 2008. 52(24): p. 2046-2099. 34. U.S. Center for Medicare & Medicaid Services(CMS). Premier Hospital Quality Incentive Demonstration (HQID). 2012 [cited 2012 Jan 05]; Available from: http://www.premierinc.com/p4p/hqi/. 35. U.S. The Joint Commission. Core Measure Sets. 2012 [cited 2012 Feb 05]; Available from: http://www.jointcommission.org/core_measure_sets.aspx. 36. U.S. Agency for Healthcare Research and Quality(AHRQ). Quality Indicators. 2012 [cited 2012 Feb 05]; Available from: http://www.qualityindicators.ahrq.gov/modules/iqi_overview.aspx. 37. Tran, C.T.T., D.S. Lee, V.F. Flintoft, L. Higginson, F.C. Grant, J.V. Tu, J. Cox, D. Holder, C. Jackevicius, L. Pilote, P. Tanser, C. Thompson, E. Tsoi, W. Warnica, A. Wielgosz, and R. Canadian Cardiovascular Outcomes, CCORT/CCS quality indicators for acute myocardial infarction care. Canadian Journal of Cardiology, 2003. 19(1): p. 38-45. 38. A.U. Westchester Community Opportunity Program(WESTCOP). 2012 [cited 2012 Feb 05]; Available from: http://www.westcop.org/. 39. Borzecki, A.M., C.L. Christiansen, P. Chew, S. Loveland, and A.K. Rosen, Comparison of In-Hospital Versus 30-Day Mortality Assessments for Selected Medical Conditions. Medical Care, 2010. 48(12): p. 1117-1121. 40. Baker, D.W., D. Einstadter, C.L. Thomas, S.S. Husak, N.H. Gordon, and R.D. Cebul, Mortality trends during a program that publicly reported hospital performance. Medical Care, 2002. 40(10): p. 879-890. 41. Werner, R.M. and E.T. Bradlow, Relationship between medicare's hospital compare performance measures and mortality rates. Jama-Journal of the American Medical Association, 2006. 296(22): p. 2694-2702. 42. Ellerbeck, E.F., S.F. Jencks, M.J. Radford, T.F. Kresowik, A.S. Craig, J.A. Gold, H.M. Krumholz, and R.A. Vogel, Quality of care for medicare patients with acute myocardial-infarction - a 4-state pilot-study from the cooperative cardiovascular project. Jama-Journal of the American Medical Association, 1995. 273(19): p. 1509-1514. 43. Hayashida, K., Y. Imanaka, M. Sekimoto, H. Kobuse, and H. Fukuda, Evaluation of acute myocardial infarction in-hospital mortality using a risk-adjustment model based on Japanese administrative data. J Int Med Res, 2007. 35(5): p. 590-6. 44. Chin, C.T., A.Y. Chen, T.Y. Wang, K.P. Alexander, R. Mathews, J.S. Rumsfeld, C.P. Cannon, G.C. Fonarow, E.D. Peterson, and M.T. Roe, Risk adjustment for in-hospital mortality of contemporary patients with acute myocardial infarction: the acute coronary treatment and intervention outcomes network (ACTION) registry-get with the guidelines (GWTG) acute myocardial infarction mortality model and risk score. Am Heart J, 2011. 161(1): p. 113-122 e2. 45. Marciniak, T.A., E.F. Ellerbeck, M.J. Radford, T.F. Kresowik, J.A. Gold, H.M. Krumholz, C.I. Kiefe, R.M. Allman, R.A. Vogel, and S.F. Jencks, Improving the quality of care for Medicare patients with acute myocardial infarction - Results from the Cooperative Cardiovascular Project. Jama-Journal of the American Medical Association, 1998. 279(17): p. 1351-1357. 46. Krumholz, H.M., Y. Wang, J.A. Mattera, Y.F. Wang, L.F. Han, M.J. Ingber, S. Roman, and S.L.T. Normand, An administrative claims model suitable for profiling hospital performance based on 30-day mortality rates among patients with an acute myocardial infarction. Circulation, 2006. 113(13): p. 1683-1692. 47. Bradley, E.H., J. Herrin, L. Curry, E.J. Cherlin, Y.F. Wang, T.R. Webster, E.E. Drye, S.L.T. Normand, and H.M. Krumholz, Variation in Hospital Mortality Rates for Patients With Acute Myocardial Infarction. American Journal of Cardiology, 2010. 106(8): p. 1108-1112. 48. Bradley, E.H., J. Herrin, B. Elbel, R.L. McNamara, D.J. Magid, B.K. Nallamothu, Y.F. Wang, S.L.T. Normand, J.A. Spertus, and H.M. Krumholz, Hospital quality for acute myocardial infarction - Correlation among process measures and relationship with short-term mortality. Jama-Journal of the American Medical Association, 2006. 296(1): p. 72-78. 49. Normand, S.L.T., M.E. Glickman, R. Sharma, and B.J. McNeil, Using admission characteristics to predict short-term mortality from myocardial infarction in elderly patients - Results from the Cooperative Cardiovascular Project. Jama-Journal of the American Medical Association, 1996. 275(17): p. 1322-1328. 50. Krumholz, H.M., J. Chen, Y.F. Wang, M.J. Radford, Y.T. Chen, and T.A. Marciniak, Comparing AMI mortality among hospitals in patients 65 years of age and older - Evaluating methods of risk adjustment. Circulation, 1999. 99(23): p. 2986-2992. 51. Ross, J.S., C. Maynard, H.M. Krumholz, H. Sun, J.S. Rumsfeld, S.L. Normand, Y. Wang, and S.D. Fihn, Use of administrative claims models to assess 30-day mortality among Veterans Health Administration hospitals. Med Care, 2010. 48(7): p. 652-8. 52. Normand, S.L.T., C.N. Morris, K.S. Fung, B.J. McNeil, and A.M. Epstein, Development and validation of a claims based index for adjusting for risk of mortality - the case of acute myocardial-infarction. Journal of Clinical Epidemiology, 1995. 48(2): p. 229-243. 53. Harbaugh, R., Hospital quality for acute myocardial infarction: Correlation among process measures and relationship with short-term mortality. Neurosurgery, 2006. 59(4): p. N7-N7. 54. Krumholz, H.M., Z. Lin, E.E. Drye, M.M. Desai, L.F. Han, M.T. Rapp, J.A. Mattera, and S.-L.T. Normand, An Administrative Claims Measure Suitable for Profiling Hospital Performance Based on 30-Day All-Cause Readmission Rates Among Patients With Acute Myocardial Infarction. Circulation-Cardiovascular Quality and Outcomes, 2011. 4(2): p. 243-252. 55. Mannion, R. and H.T.O. Davies, Reporting health care performance: learning from the past, prospects for the future. Journal of Evaluation in Clinical Practice, 2002. 8(2): p. 215-228. 56. McGlynn, E.A. and S.M. Asch, Developing a clinical performance measure. American Journal of Preventive Medicine, 1998. 14(3): p. 14-21. 57. Dubois, R.W., W.H. Rogers, J.H. Moxley, D. Draper, and R.H. Brook, Hospital inpatient mortality - is it a predictor of quality. New England Journal of Medicine, 1987. 317(26): p. 1674-1680. 58. Kahn, K.L., M.L. Pearson, E.R. Harrison, K.A. Desmond, W.H. Rogers, L.V. Rubenstein, R.H. Brook, and E.B. Keeler, Health-care for black and poor hospitalized medicare patients. Jama-Journal of the American Medical Association, 1994. 271(15): p. 1169-1174. 59. Thomas, J.W., J.J. Holloway, and K.E. Guire, Validating risk-adjusted mortality as an indicator for quality of care. Inquiry-the Journal of Health Care Organization Provision and Financing, 1993. 30(1): p. 6-22. 60. Hartz, A.J., M.S. Gottlieb, E.M. Kuhn, and A.A. Rimm, The relationship between adjusted hospital mortality and the results of peer-review. Health Services Research, 1993. 27(6): p. 765-777. 61. Park, R.E., R.H. Brook, J. Kosecoff, J. Keesey, L. Rubenstein, E. Keeler, K.L. Kahn, W.H. Rogers, and M.R. Chassin, Explaining variations in hospital death rates - randomness, severity of illness, quality of care. Jama-Journal of the American Medical Association, 1990. 264(4): p. 484-490. 62. Best, W.R. and D.C. Cowper, The ratio of observed-to-expected mortality as a quality of care indicator in nonsurgical va patients. Medical Care, 1994. 32(4): p. 390-400. 63. Tu, J.V., P.C. Austin, W.A. Filate, H.L. Johansen, S.E. Brien, L. Pilote, and D.A. Alter, Outcomes of acute myocardial infarction in Canada. Can J Cardiol, 2003. 19(8): p. 893-901. 64. Lave, J.R. and L.B. Lave, The extent of role differentiation among hospitals. Health Serv Res, 1971. 6(1): p. 15-38. 65. Goss, M.E. and J.I. Reed, Evaluating the quality of hospital care through severity-adjusted death rates: some pitfalls. Med Care, 1974. 12(3): p. 202-13. 66. Thomas, J.W. and T.P. Hofer, Research evidence on the validity of risk-adjusted mortality rate as a measure of hospital quality of care. Medical Care Research and Review, 1998. 55(4): p. 371-404. 67. Brook, R.H., A. Davies-Avery, S. Greenfield, L.J. Harris, T. Lelah, N.E. Solomon, and J.E. Ware, Jr., Assessing the quality of medical care using outcome measures: an overview of the method. Med Care, 1977. 15(9 Suppl): p. suppl 1-165. 68. Daley, J., W.G. Henderson, and S.F. Khuri, Risk-adjusted surgical outcomes. Annu Rev Med, 2001. 52: p. 275-87. 69. Kansagara, D., H. Englander, A. Salanitro, D. Kagen, C. Theobald, M. Freeman, and S. Kripalani, Risk Prediction Models for Hospital Readmission A Systematic Review. Jama-Journal of the American Medical Association, 2011. 306(15): p. 1688-1698. 70. Charlson, M.E., P. Pompei, K.L. Ales, and C.R. MacKenzie, A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis, 1987. 40(5): p. 373-83. 71. Deyo, R.A., D.C. Cherkin, and M.A. Ciol, Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol, 1992. 45(6): p. 613-9. 72. Romano, P.S., L.L. Roos, and J.G. Jollis, Adapting a clinical comorbidity index for use with icd-9-cm administrative data - differing perspectives. Journal of Clinical Epidemiology, 1993. 46(10): p. 1075-1079. 73. Needham, D.M., D.C. Scales, A. Laupacis, and P.J. Pronovost, A systematic review of the Charlson comorbidity index using Canadian administrative databases: a perspective on risk adjustment in critical care research. J Crit Care, 2005. 20(1): p. 12-9. 74. D'Hoore, W., A. Bouckaert, and C. Tilquin, Practical considerations on the use of the Charlson comorbidity index with administrative data bases. J Clin Epidemiol, 1996. 49(12): p. 1429-33. 75. 朱育增 and 吳肖琪, 回顧與探討次級資料適用之共病測量方法. 臺灣公共衛生雜誌, 2010. 29(1): p. 8-21. 76. Elixhauser, A., C. Steiner, D.R. Harris, and R.M. Coffey, Comorbidity measures for use with administrative data. Med Care, 1998. 36(1): p. 8-27. 77. Krumholz, H.M. and S.-L.T. Normand, Public reporting of 30-day mortality for patients hospitalized with acute myocardial infarction and heart failure. Circulation, 2008. 118(13): p. 1394-1397. 78. Khuri, S.F., J. Daley, W. Henderson, K. Hur, J. Demakis, J.B. Aust, V. Chong, P.J. Fabri, J.O. Gibbs, F. Grover, K. Hammermeister, G. Irvin, 3rd, G. McDonald, E. Passaro, Jr., L. Phillips, F. Scamman, J. Spencer, and J.F. Stremple, The Department of Veterans Affairs' NSQIP: the first national, validated, outcome-based, risk-adjusted, and peer-controlled program for the measurement and enhancement of the quality of surgical care. National VA Surgical Quality Improvement Program. Ann Surg, 1998. 228(4): p. 491-507. 79. Von Korff, M., E.H. Wagner, and K. Saunders, A chronic disease score from automated pharmacy data. J Clin Epidemiol, 1992. 45(2): p. 197-203. 80. Clark, D.O., M. Von Korff, K. Saunders, W.M. Baluch, and G.E. Simon, A chronic disease score with empirically derived weights. Med Care, 1995. 33(8): p. 783-95. 81. Petersen, L.A., K. Pietz, L.D. Woodard, and M. Byrne, Comparison of the predictive validity of diagnosis-based risk adjusters for clinical outcomes. Med Care, 2005. 43(1): p. 61-7. 82. Cohen, M.E., J.B. Dimick, K.Y. Bilimoria, C.Y. Ko, K. Richards, and B.L. Hall, Risk adjustment in the American College of Surgeons National Surgical Quality Improvement Program: a comparison of logistic versus hierarchical modeling. Journal of the American College of Surgeons, 2009. 209(6): p. 687-93. 83. Iezzoni, L.I., Assessing quality using administrative data. Ann Intern Med, 1997. 127(8 Pt 2): p. 666-74. 84. Cohen, M.E., J.B. Dimick, K.Y. Bilimoria, C.Y. Ko, K. Richards, and B.L. Hall, Risk Adjustment in the American College of Surgeons National Surgical Quality Improvement Program: A Comparison of Logistic Versus Hierarchical Modeling. Journal of the American College of Surgeons, 2009. 209(6): p. 687-693. 85. Greiner, G., E. Lowy, C. Maynard, A. Sales, and S. Fihn, Comparison of six mortality risk adjustment models for acute myocardial infarction. Circulation, 2006. 113(21): p. E807-E807. 86. Chu, Y.-T., Y.-Y. Ng, and S.-C. Wu, Comparison of different comorbidity measures for use with administrative data in predicting short- and long-term mortality. Bmc Health Services Research, 2010. 10. 87. Southern, D.A., H. Quan, and W.A. Ghali, Comparison of the Elixhauser and Charlson/Deyo methods of comorbidity measurement in administrative data. Medical Care, 2004. 42(4): p. 355-360. 88. Stukenborg, G.J., D.P. Wagner, and A.F. Connors, Comparison of the performance of two comorbidity measures, with and without information from prior hospitalizations. Medical Care, 2001. 39(7): p. 727-739. 89. Daley, J., S. Jencks, D. Draper, G. Lenhart, N. Thomas, and J. Walker, Predicting hospital-associated mortality for medicare patients - a method for patients with stroke, pneumonia, acute myocardial-infarction, and congestive heart-failure. Jama-Journal of the American Medical Association, 1988. 260(24): p. 3617-3624. 90. Quan, H.D., V. Sundararajan, P. Halfon, A. Fong, B. Burnand, J.C. Luthi, L.D. Saunders, C.A. Beck, T.E. Feasby, and W.A. Ghali, Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Medical Care, 2005. 43(11): p. 1130-1139. 91. 朱育增, 吳肖琪, 李玉春, 賴美淑, and 譚醒朝, 探討共病測量方法於健保次級資料之應用. 臺灣公共衛生雜誌, 2010. 29(3): p. 191-200. 92. Schneeweiss, S. and M. Maclure, Use of comorbidity scores for control of confounding in studies using administrative data bases. International Journal of Epidemiology, 2000. 29(5): p. 891-898. 93. Hanley, J.A. and B.J. McNeil, The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology, 1982. 143(1): p. 29-36. 94. Bernheim, S.M., J.N. Grady, Z. Lin, Y. Wang, S.V. Savage, K.R. Bhat, J.S. Ross, M.M. Desai, A.R. Merrill, L.F. Han, M.T. Rapp, E.E. Drye, S.L. Normand, and H.M. Krumholz, National patterns of risk-standardized mortality and readmission for acute myocardial infarction and heart failure. Update on publicly reported outcomes measures based on the 2010 release. Circ Cardiovasc Qual Outcomes, 2010. 3(5): p. 459-67. 95. Statistical Methods Used to Calculate Rate. 2011; Available from: http://www.hospitalcompare.hhs.gov/(X(1)S(ijb5nkjapzi5jebnakvl3o55))/staticpages/for-professionals/ooc/statistcal-methods.aspx. 96. 柯玲晶, 譚醒朝, and 譚家惠, Charlson合併症指數對全民健康保險資料庫適用性之探討. 臺灣公共衛生雜誌, 2007. 26(6): p. 491-498. 97. Schneeweiss, S., P.S. Wang, J. Avorn, and R.J. Glynn, Improved comorbidity adjustment for predicting mortality in Medicare populations. Health Services Research, 2003. 38(4): p. 1103-1120. 98. Thiemann, D.R., J. Coresh, W.J. Oetgen, and N.R. Powe, The association between hospital volume and survival after acute myocardial infarction in elderly patients. New England Journal of Medicine, 1999. 340(21): p. 1640-1648. 99. Silber, J.H., P.R. Rosenbaum, T.J. Brachet, R.N. Ross, L.J. Bressler, O. Even-Shoshan, S.A. Lorch, and K.G. Volpp, The Hospital Compare Mortality Model and the Volume-Outcome Relationship. Health Services Research, 2010. 45(5): p. 1148-1167. 100. Jensen, P.H., E. Webster, and J. Witt, Hospital type and patient outcomes: an empirical examination using ami readmission and mortality records. Health Economics, 2009. 18(12): p. 1440-1460. 101. Rasmussen, S., A.D.O. Zwisler, S.Z. Abildstrom, J.K. Madsen, and M. Madsen, Hospital variation in mortality after first acute myocardial infarction in Denmark from 1995 to 2002 - Lower short-term and 1-year mortality in high-volume and specialized hospitals. Medical Care, 2005. 43(10): p. 970-978. 102. Mason, A. and A. Street, Publishing outcome data: is it an effective approach? Journal of Evaluation in Clinical Practice, 2006. 12(1): p. 37-48. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/6486 | - |
| dc.description.abstract | 急性心肌梗塞是一種需要緊急處理的缺血性心臟疾病,心肌梗塞發生時如能快速確認診斷並立即給予治療,則可減少與心肌梗塞有關的死亡率;故世界各國多有將急性心肌梗塞死亡率作為公告的照護指標。作為公開比較的照護結果指標,需要先進行校正程序,以求得比較上的公平。對於醫療照護品質的風險校正議題,自 1980 年代起即有相關文獻提出討論。早期對醫院品質指標的研究即指出,比較醫院的品質時不能依賴單一面向的測量指標,同時需要以適當的方式進行風險校正。藉由校正調整個人健康風險的差異後,可將醫療品質資訊公開(report card),避免未校正前對醫療照護結果比較上可能產生的偏差。然而,即使是針對同一疾病所發展出來的風險校正模型,在不同地區、對於不同族群,也可能會產生不一樣的結果,是故有必要建立台灣特有急性心肌梗塞風險校正之模型。
本研究旨在建立台灣急性心肌梗塞院內、30 天、1 年之風險校正模型,藉以校正因病患風險因子(risk factors)分布的不同,所導致個別醫院病例組合差異。藉由模型的確立,校正病人相關風險,將病人個別健康風險的差異加以調整,避免對醫療照護結果比較產生偏差。本研究所建立之 30 天死亡率、1 年死亡率和院內死亡率模型,C 統計值介於 0.732-0.737 間,驗證模型之 C 統計值介於 0.714-0.728 間,模型配適度佳。最終模型納入的因素包括:性別、年齡、AMI 梗塞部位及相關合併症,包括心律不整、高血壓、其他神經系統疾病、腎衰竭、肝臟疾病、凝血性病變、藥物濫用等。各風險因子對於死亡率的影響如下:女性的死亡風險高於男性;年齡愈大其死亡風險愈高;相較於其他部位 AMI,側壁型 AMI 的死亡風險顯著較低;患有心律不整、其他神經系統疾病、腎衰竭、肝臟疾病、凝血性病變、藥物濫用等合併症的病人其死亡風險較高,而患有高血壓的病人,其死亡風險較低。 並在模型建構完成後,以風險標準化死亡率(Risk Standardized Mortality Rate, RSMR)比較不同醫院在急性心肌梗塞照護成果上的差異,由此反應不同醫院照護急性心肌梗塞的品質。應用所建立之模型計算校正後 30 天、1 年或院內死亡率,發現每年急性心肌梗塞服務量小於 50 個個案的醫院死亡率較高;相較於公立醫院,私立醫院的死亡率較低;醫學中心的校正後死亡率低於區域醫院及地區醫院;就所屬健保的醫院進行區分,以東區分局的死亡率最低,然其醫院家數過少,以所屬高屏分局的醫院死亡率最高。 風險校正模型的確立,對於比較醫療指標時具有其重要性。期未來國家衛生政策決策者可藉由發展特定疾病之風險校正模型,進行相關醫療品質資訊公開。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2021-05-17T09:14:08Z (GMT). No. of bitstreams: 1 ntu-101-R99848013-1.pdf: 835984 bytes, checksum: deccf316a9f909f4e74a628167d6e75b (MD5) Previous issue date: 2012 | en |
| dc.description.tableofcontents | 口試委員會審定書 I
致謝 II 中文摘要 III 英文摘要 IV 第一章 緒論 1 第一節 研究背景與動機 1 第二節 研究重要性 4 第三節 研究目的 5 第二章 文獻探討 6 第一節 急性心肌梗塞 6 第二節 風險校正 15 第三節 急性心肌梗塞之風險校正 21 第三章 研究方法 32 第一節 資料來源與研究對象 32 第二節 研究方法與進行步驟 35 第三節 研究變項操作型定義 38 第四節 統計分析 46 第四章 研究結果 47 第一節 研究樣本特性分析 47 第二節 樣本特性對急性心肌梗塞死亡率之影響 53 第三節 急性心肌梗塞死亡率風險校正模型之預測成效 59 第四節 急性心肌梗塞風險校正指標及校正後死亡率比較 70 第五章 討論 85 第一節 研究方法之討論 85 第二節 急性心肌梗塞死亡率之風險因子 90 第三節 急性心肌梗塞風險校正指標及校正後死亡率討論 94 第四節 研究限制 97 第六章 結論與建議 98 第一節 結論 98 第二節 建議 99 參考文獻 101 附錄 109 | |
| dc.language.iso | zh-TW | |
| dc.subject | 風險因子 | zh_TW |
| dc.subject | 急性心肌梗塞 | zh_TW |
| dc.subject | 風險校正 | zh_TW |
| dc.subject | 死亡率 | zh_TW |
| dc.subject | risk adjustment | en |
| dc.subject | risk factors | en |
| dc.subject | mortality | en |
| dc.subject | Acute Myocardial Infarction(AMI) | en |
| dc.title | 死亡率風險校正模型之建立與驗證-以急性心肌梗塞為例 | zh_TW |
| dc.title | Derivation and validation for adjusting for risk of mortality-the case of acute myocardial infarction in Taiwan | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 100-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 楊哲銘,賴美淑,簡國龍 | |
| dc.subject.keyword | 急性心肌梗塞,風險校正,死亡率,風險因子, | zh_TW |
| dc.subject.keyword | Acute Myocardial Infarction(AMI),risk adjustment,mortality,risk factors, | en |
| dc.relation.page | 126 | |
| dc.rights.note | 同意授權(全球公開) | |
| dc.date.accepted | 2012-08-17 | |
| 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-101-1.pdf | 816.39 kB | Adobe PDF | 檢視/開啟 |
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。
