臺灣博碩士論文加值系統

背景與動機：乳癌在世界各國都對女性健康造成重大威脅，為促進乳癌女性健康，國內外著重早期診斷與早期治療的重要性，故而提出治療延遲的概念，並對此進行許多相關研究，研究顯示延遲治療對於病患的預後（存活、診斷期別、總醫療費用）會有重大影響。2015年Neal等人的針對癌症相關研究進行系統性回顧，指出過去的研究結果缺乏一致性，且探討相關因子面向過於侷限，由於延遲治療對於乳癌病患的健康存在影響，該回顧提出應再針對醫療機構特性因子進行分析，且應遵循2012年Weller等人提出的指引。本研究期望能透過資料庫分析，去針對過去探討較少的醫療機構特性因子進行分析，另外，使用大型資料庫探討對預後的影響。
研究目的：本研究目的有二，其一為瞭解相關因子中醫療機構特性因子對延遲治療時間的影響，其二則是探討延遲治療的時間影響乳癌預後的情況。
研究方法：本研究將利用健保資料庫結合癌症登記檔進行資料分析，使用SAS 9.4，分析方法採用T-Test、ANOVA、卡方、多變量迴歸進行資料分析。
研究結果：分析結果顯示乳癌病患平均診斷延遲天數為9.45天（±11.75天），平均治療延遲天數為13.94天（±18.08天）。醫療機構特性因子當中，初次確診乳癌服務量對診斷延遲天數呈現顯著相關，每增加一個確診服務量，會增加0.000203天的診斷延遲天數，醫院權屬別則對診斷延遲天數和治療延遲天數都呈現顯著相關，在診斷延遲天數部分，公立醫院的平均天數為8.76天（±11.21天），非公立平均天數則是9.96天（±12.11天），而在治療延遲天數部份，公立醫院的平均延遲天數為14.12天（±18.88天），非公立醫院的平均天數為13.82天（±17.79天）。本研究依據延遲治療時間的平均值作為切點，將診斷延遲天數與治療延遲天數切為兩組，結果顯示診斷延遲天數較長的病患其在各個診斷期別都有較高的風險存在。診斷延遲天數對存活的影響上，兩組間存在顯著差異，高於平均值的組別其OR值為1.095，而治療延遲天數對存活的影響上，兩組亦存在顯著差異，高於平均值的組別其OR值為0.977。
結論與建議：本研究發現到醫療機構特性對延遲治療時間存在影響，而延遲治療時間也與病患預後有著相關性，根據研究結果，針對政策、實務與未來研究三個面向分別給予建議，政策方面建議衛生主管機關可以利用診斷延遲天數來做為癌症照護的過程指標，並且應對現行的癌症改善規畫重新思考。實務方面建議醫療提供者可使用資訊系統來協助監測診斷延遲天數，此外，建議區域醫院和地區醫院應針對治療流程改善，幫助病患儘早獲得治療，最後，未來研究建議可針對其他種癌症疾病進行分析，並將醫院評鑑等級和權屬列入分析考量。

Background：Breast cancer threats the whole world women’s health, so many countries emphasis the concept, ‘Early diagnosis and early treatment’, to improve the health outcomes of breast cancer patients. Under this circumstance, researcher put their attention on ‘Delay treatment’, which measured the time of diagnosis and treatment, and has impact on patient’s outcomes (such as survive, stage and expense). In 2015, Neal and his team systematic reviewed the researches of Cancer delay treatment, pointed out that the studies’ results without consistency and the studies of relevant factors still lacking. Delay treatment is one of the important factors influenced patient’ health, they suggested the future researcher should focus on the hospital factors’ relationship and follow the guideline of Weller, which posted in 2012. This research expects to use database analyze exploring the relationship between hospital factors and delay treatment, moreover, understanding the delay treatment effect on patient’ health outcomes.
Purpose: There were two purposes of this study, first, understanding the hospital factors’ relation to delay treatment, second, exploring the delay treatment effect to patient’ health outcome.
Method: This research used the National Health Insurance Database and Cancer Registry Database to analysis. Version of SAS is 9.4. Statistic methods contain T-test, ANOVA, Chi-square and regression.
Results: The results showed breast cancer patient’ average diagnosis delay is 9.45 days (±11.75 days), average treatment delay is 13.94 days (±18.08 days). In Hospital factors’ relation with delay treatment, the amount of first time diagnosis has significant correlation with diagnosis delay, the amount raise 1 unit, the diagnosis delay will increase 0.000203 days. The hospital ownership has significant correlation with diagnosis delay and treatment delay. The average diagnosis delay of public hospital is 8.76 days(±11.21 days), besides the average of non-public hospital is 9.96 days (±12.11 days). The average treatment delay of public hospital is 14.12 days(±18.88 days), besides the average of non-public hospital is 13.82days (±12.11 days). We seperated the delay time according the average point to two group, and found that longer diagnosis delay group significantly has higher risk to get serious stage than shorter delay group. Besides, the longer diagnosis delay group also has higher risk to die, and the OR is 1.095. However, the longer treatment delay group has lower risk to die, and the OR is 0.977.
Conclusion：Our findings suggest that the effect of diagnosis delay should be considered in formulation or revisiong national health policy. Besides, the hospital should use information system to monitor their patients’ condition of delay treatment, and improve their treatment process to help patient get therapy. Last, the effect of delay treatment in other cancers is unknow, we suggested the future research can focus on other cancer, and consider the effect of hospital character in the study.

目錄
口試委員會審定書 I
誌謝 II
中文摘要 III
英文摘要 V
目錄 VII
表目錄 IX
圖目錄 X
第一章 緒論 1
第一節 研究背景 1
第二節 研究動機與重要性 1
第三節 研究目的 3
第二章 文獻回顧 4
第一節 乳癌現況、診斷與治療 4
第二節 延遲治療的定義 6
第三節 延遲治療對乳癌病患預後的影響 11
第四節 影響乳癌病患延遲治療的因子 13
第五節 延遲治療相關實證研究－醫療機構特性因子與預後結果 20
第六節 綜合回顧整理 44
第三章 研究方法 45
第一節 研究架構 45
第二節 研究假說 46
第三節 研究對象 47
第四節 資料來源與研究區間 49
第五節 資料處理與統計方法 54
第四章 結果 61
第一節 描述性統計 61
第二節 雙變量分析 64
第三節 多變量分析 65
第五章 討論 85
第一節 研究方法 85
第二節 醫療機構特性因子對延遲治療天數的影響 87
第三節 延遲治療天數對預後因子的影響 90
第四節 研究限制 92
第六章 結論與建議 93
第一節 結論 93
第二節 建議 94
參考文獻 96
附錄 101
附錄一　The Arhus Checklist[6] 101
附錄一　The Arhus Checklist[6]（續） 102
附錄二　共病症代碼與權重[70, 71] 103

表目錄
表 1　2003年到2013年台灣乳癌發生率與死亡率 5
表 2　各國研究乳癌延遲治療時間整理 10
表 3　各國研究延遲治療時間整理 12
表 4　延遲治療相關因子研究整理－病患特性 16
表 5　延遲治療相關因子研究整理－疾病特性 18
表 6　延遲治療相關因子研究整理－醫療機構特性因子 19
表 7　延遲治療相關因子研究整理－其他 19
表 8　研遲治療對預後影響之文獻整理 22
表 9　研遲治療相關因子之文獻整理 29
表 10　操作型定義 50
表 11　描述性統計變項分析方法對照表 57
表 12　各假說變項雙變項統計方法對照表 59
表 13　各假說變項多變項統計方法對照表 60
表 14　描述性統計結果 67
表 15　延遲治療時間雙變量分析結果 70
表 16　預後因子雙變量相關分析結果 73
表 17　延遲治療時間多變量分析結果 77
表 18　預後因子多變量分析結果（未分組） 78
表 19　預後因子多變量分析結果（依平均值分組）－診斷期別 79
表 20　預後因子多變量分析結果（依平均值分組）－總醫療費用、存活情形 81
表 21　假說驗證 83
 
圖目錄
圖 1　病患延遲治療時間定義整理 9
圖 2　研究架構一（假說一） 45
圖 3　研究架構二（假說二） 46
圖 4　研究架構三（假說三） 46
圖 5　篩選流程 56
圖 6　診斷延遲天數趨勢 63
圖 7　治療延遲天數趨勢 64

1.Cancer control: knowledge into action: WHO guide for effective programmes. 2007, World Health Organization.
2.衛生福利部國民健康署, 102年癌症登記報告. 2016.
3.Shieh, S.-H., et al., Delayed time from first medical visit to diagnosis for breast cancer patients in Taiwan. Journal of the Formosan Medical Association, 2014. 113(10): p. 696-703.
4.Richards, M., et al., Influence of delay on survival in patients with breast cancer: a systematic review. The Lancet, 1999. 353(9159): p. 1119-1126.
5.Webber, C., et al., Identifying predictors of delayed diagnoses in symptomatic breast cancer: a scoping review. European journal of cancer care, 2016.
6.Weller, D., et al., The Aarhus statement: improving design and reporting of studies on early cancer diagnosis. British Journal of Cancer, 2012. 106(7): p. 1262-1267.
7.Neal, R.D., et al., Is increased time to diagnosis and treatment in symptomatic cancer associated with poorer outcomes? Systematic review. British Journal of Cancer, 2015. 112: p. S92-S107.
8.Chang, H.-J., et al., Delay in seeking medical evaluations and predictors of self-efficacy among women with newly diagnosed breast cancer: A longitudinal study. International journal of nursing studies, 2014. 51(7): p. 1036-1047.
9.王秀紅 and 侯明鋒, 乳癌患者延遲診斷的相關因素探討. The Kaohsiung Journal of Medical Sciences, 1993. 9(2): p. 103-112.
10.林玉淨 and 胡淑貞, 乳癌婦女延遲就醫, 診斷與治療之相關因子研究: 以南部某醫學中心為例. 公共衛生, 2001. 27: p. 287-300.
11.王冠中, 台灣五大癌症與延遲治療之相關因素與探討. 中山醫學大學醫療產業科技管理學系碩士班學位論文, 2014: p. 1-99.
12.DeSantis, C.E., et al., International variation in female breast cancer incidence and mortality rates. Cancer Epidemiology Biomarkers & Prevention, 2015. 24(10): p. 1495-1506.
13.Youlden, D.R., et al., Incidence and mortality of female breast cancer in the Asia-Pacific region. Cancer biology & medicine, 2014. 11(2): p. 101-115.
14.張金堅, 郭文宏, and 王明暘, 台灣乳癌之流行病學. 中華民國癌症醫學會雜誌, 2008. 24(2): p. 85-93.
15.林惠文, 顏啟華, and 應宗和, 乳癌的篩檢與診斷. 基層醫學, 2006. 21(12): p. 352-358.
16.衛生福利部國民健康署, 民國103年健康危害行為監測調查¡B. 2014.
17.DeSantis, C., et al., Breast cancer statistics, 2013. CA: a cancer journal for clinicians, 2014. 64(1): p. 52-62.
18.衛生福利部國民健康署, 101年癌症登記報告. 2015.
19.衛生福利部國民健康署, 100年癌症登記報告. 2014.
20.衛生福利部國民健康署, 99年癌症登記報告. 2013.
21.衛生福利部國民健康署, 98年癌症登記報告. 2012.
22.衛生福利部國民健康署, 97年癌症登記報告. 2011.
23.衛生福利部國民健康署, 96年癌症登記報告. 2010.
24.衛生福利部國民健康署, 95年癌症登記報告. 2009.
25.衛生福利部國民健康署, 94年癌症登記報告. 2008.
26.衛生福利部國民健康署, 93年癌症登記報告. 2007.
27.謝德熾 and 陳立奇, 乳癌治療之演進. 北市醫學雜誌, 2010. 7(3): p. 313-322.
28.Ruddy, K.J., et al., Breast cancer presentation and diagnostic delays in young women. Cancer, 2014. 120(1): p. 20-25.
29.Elmore, J.G., et al., Racial inequities in the timing of breast cancer detection, diagnosis, and initiation of treatment. Medical care, 2005. 43(2): p. 141-148.
30.Haas, J.S., et al., Differences in the quality of care for women with an abnormal mammogram or breast complaint. Journal of general internal medicine, 2000. 15(5): p. 321-328.
31.Maly, R.C., et al., What influences diagnostic delay in low-income women with breast cancer? Journal of Women''s Health, 2011. 20(7): p. 1017-1023.
32.Sue, G.R., et al., Does time to definitive treatment matter in patients with ductal carcinoma in situ? The American Surgeon, 2013. 79(6): p. 561-565.
33.Smith, E.C., A. Ziogas, and H. Anton-Culver, Delay in surgical treatment and survival after breast cancer diagnosis in young women by race/ethnicity. JAMA surgery, 2013. 148(6): p. 516-523.
34.Bilimoria, K.Y., et al., Wait times for cancer surgery in the United States: trends and predictors of delays. Annals of surgery, 2011. 253(4): p. 779-785.
35.Brazda, A., et al., Delays in time to treatment and survival impact in breast cancer. Annals of surgical oncology, 2010. 17(3): p. 291-296.
36.Wagner, J.L., et al., Delays in primary surgical treatment are not associated with significant tumor size progression in breast cancer patients. Annals of surgery, 2011. 254(1): p. 119.
37.Fedewa, S.A., et al., Race and ethnicity are associated with delays in breast cancer treatment (2003–2006). Journal of health care for the poor and underserved, 2011. 22(1): p. 128-141.
38.Smith, E.R., et al., Breast cancer survival among economically disadvantaged women: the influences of delayed diagnosis and treatment on mortality. Cancer Epidemiology Biomarkers & Prevention, 2008. 17(10): p. 2882-2890.
39.McGee, S.A., et al., Determinants of breast cancer treatment delay differ for African American and White women. Cancer Epidemiology Biomarkers & Prevention, 2013. 22(7): p. 1227-1238.
40.Redaniel, M.T., et al., Diagnostic intervals and its association with breast, prostate, lung and colorectal cancer survival in England: historical cohort study using the clinical practice research datalink. PloS one, 2015. 10(5): p. e0126608.
41.Xu, Y., et al., Quantifying treatment delays in adolescents and young adults with cancer at McGill University. Current Oncology, 2015. 22(6): p. e470.
42.Jassem, J., et al., Delays in diagnosis and treatment of breast cancer: a multinational analysis. The European Journal of Public Health, 2014. 24(5): p. 761-767.
43.Tørring, M.L., et al., Time to diagnosis and mortality in colorectal cancer: a cohort study in primary care. British journal of cancer, 2011. 104(6): p. 934-940.
44.Ermiah, E., et al., Diagnosis delay in Libyan female breast cancer. BMC research notes, 2012. 5(1): p. 1.
45.Allgar, V. and R. Neal, Delays in the diagnosis of six cancers: analysis of data from the National Survey of NHS Patients: Cancer. British journal of cancer, 2005. 92(11): p. 1959-1970.
46.McLaughlin, J.M., et al., Effect on survival of longer intervals between confirmed diagnosis and treatment initiation among low-income women with breast cancer. Journal of Clinical Oncology, 2012. 30(36): p. 4493-4500.
47.Mujar, M., et al., Delays in time to primary treatment after a diagnosis of breast cancer: does it impact survival? Preventive medicine, 2013. 56(3): p. 222-224.
48.Redondo, M., et al., Prognostic implications of emergency admission and delays in patients with breast cancer. Supportive care in cancer, 2009. 17(5): p. 595-599.
49.Eastman, A., et al., Outcomes of delays in time to treatment in triple negative breast cancer. Annals of surgical oncology, 2013. 20(6): p. 1880-1885.
50.Yun, Y., et al., The influence of hospital volume and surgical treatment delay on long-term survival after cancer surgery. Annals of oncology, 2012: p. mds101.
51.Warner, E.T., et al., Time to diagnosis and breast cancer stage by race/ethnicity. Breast cancer research and treatment, 2012. 136(3): p. 813-821.
52.Wright, G.P., et al., Time from diagnosis to surgical treatment of breast cancer: factors influencing delays in initiating treatment. The American Surgeon, 2010. 76(10): p. 1119-1122.
53.Caplan, L., Delay in breast cancer: implications for stage at diagnosis and survival. Frontiers in public health, 2014. 2.
54.Alok Kumar, D., et al., An epidemiological study on delay in treatment initiation of cancer patients. Health, 2012. 2012.
55.Bouche, G., et al., Determinants of variability in waiting times for radiotherapy in the treatment of breast cancer. Radiotherapy and Oncology, 2010. 97(3): p. 541-547.
56.Redaniel, M., et al., The association of waiting times from diagnosis to surgery with survival in women with localised breast cancer in England. British journal of cancer, 2013. 109(1): p. 42-49.
57.Tørring, M.L., et al., Evidence of increasing mortality with longer diagnostic intervals for five common cancers: a cohort study in primary care. European journal of cancer, 2013. 49(9): p. 2187-2198.
58.Burgess, C., et al., Who and what influences delayed presentation in breast cancer? British journal of cancer, 1998. 77(8): p. 1343.
59.林玉淨 and 胡淑貞, 乳癌婦女延遲就醫, 診斷與治療之相關因子研究: 以南部某醫學中心為例. 公共衛生, 2000. 27: p. 287-300.
60.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.
61.蔡文正, et al., 偏遠地區民眾就醫可近性及滿意度調查. 台灣公共衛生雜誌, 2006. 25(5): p. 394-404.
62.洪乙禎, 健保支付制度與分級轉診的落實. 2005: 行政院國家科學委員會專題研究計畫.
63.衛生福利部, 第三期國家癌症防治計畫（103-107 年）. 2015.
64.張樂心, 不同權屬別醫院之經濟行為研究. 公共衛生學院衛生政策與管理研究所, 國立台灣大學. 博士, 2004. 132.
65.邱鈺珊, 總額支付制度對不同特性醫療院所用藥行為之影響: 以高血壓藥品為例. 淡江大學會計學系碩士班學位論文, 2012: p. 1-83.
66.林瑟嬿, 醫療機構擁擠效率與品質效率之探討. 國立台北護理健康大學健康事業管理研究所, 2015.
67.劉滄浯, 癌症診療品質認證作業計畫組成果報告, 財團法人國家衛生研究院, Editor. 2016.
68.張樂心, et al., 醫院權屬別與醫療收費. 台灣公共衛生雜誌, 2004. 23(2): p. 130-140.
69.蔡宜樺, 楊銘欽, and 季瑋珠, 乳癌確診後之初期罹病成本與相關因子之探討-以台大醫院病患為例. 中華公共衛生雜誌, 1998. 17(3): p. 242-252.
70.朱育增, et al., 探討共病測量方法於健保次級資料之應用. 台灣公共衛生雜誌, 2010. 29(3): p. 191-200.
71.Charlson, M.E., et al., A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. Journal of chronic diseases, 1987. 40(5): p. 373-383.