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研究生:郭明璇
研究生(外文):GUO,MING-XUAN
論文名稱:探討各種類癌症之統計生命價值
論文名稱(外文):Investigating Value of Statistical Life among the Major Category of Cancer
指導教授:王中儀王中儀引用關係
指導教授(外文):WANG,JONG-YI
口試委員:劉秋松龍紀萱
口試委員(外文):Liu,Chiu-ShongLung,Chi-Hsuan
口試日期:2022-06-28
學位類別:碩士
校院名稱:中國醫藥大學
系所名稱:醫務管理學系碩士班
學門:商業及管理學門
學類:醫管學類
論文種類:學術論文
論文出版年:2022
畢業學年度:110
語文別:中文
論文頁數:153
中文關鍵詞:癌症統計生命價值存活增益生命價值餘命增益生命價值醫療照護
外文關鍵詞:cancervalue of statistical lifesurvival gain VSLlife expectancy gain VSLmedical care
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  • 下載下載:30
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摘 要

目的:癌症長年為國人十大死因之首,帶來國家健保財政沉重負擔。台灣針對各種癌症欲達到降低死亡率或延長生命之代價—統計生命價值(Value of Statistical Life)之醫療經濟研究仍為闕如。故本研究完整地探討各種類癌症之兩種統計生命價值—存活增益生命價值及餘命增益生命價值。
方法:屬回溯性世代配對研究,擷取2008-2018年衛生福利部資科中心二千三百萬全人口檔20歲以上罹癌者(140.x-208.x/Cxx.x, C7A.x)。進一步以台灣癌症死亡人數排名前八位癌症種類為研究對象,以傾向分數將性別、年齡、共病嚴重度進行1:1配對各確診年份期間,以達各組別屬性相似,總樣本數分別為43,404人與70,233人。以人均總醫療費用,估算為降低1%死亡率所付出的實際價值,得出存活增益生命價值。以人均總醫療費用與癌症病患存活時間之關係,計算餘命價值後,再計算欲增加一年存活時間需付出之價值,為餘命增益生命價值。於SAS 9.4進行Cox比例風險模型及廣義線性模型。
結果:校正後Cox比例風險模型顯示,胰臟癌患者(三年死亡率=48.61%)之死亡風險顯著較高(aHR=3.315,p<.05);肺癌其次。存活增益生命價值以「其他癌症」最高,為319,348元。校正後廣義線性模型顯示,各種類癌症之人均醫療費用呈現顯著差異(p<.05)。餘命增益生命價值以胰臟癌最高,為34,732,592元,肝癌及肺癌位居第二位及第三位,其他癌症最低。
結論:各種類癌症之統計生命價值呈現差異。「其他癌症」欲降低1%死亡率之價值最高。胰臟癌欲延長一年壽命所付出之價值最大。建議衛生及醫療單位提高挹注醫療資源於死亡風險最高之胰臟癌與肺癌,並整體衡量生命與價值,以適量配置各癌症種類之醫療資源,精進癌症照護效益。



Abstract
Purposes: Cancer has been the top cause of death in Taiwan for over three decades, bringing a heavy burden to the national health insurance medical expenditure. Medical economic research on the value of statistical life (VSL), the cost of reducing mortality or extending life expectancy for major categories of cancer, is still unclear in Taiwan. Therefore, this study aimed to fully investigate the two types of VSL for major categories of cancer—survival gain VSL and life expectancy gain VSL.
Methods: This study performed retrospective cohort analyses using the 2008 to 2018 National Health Insurance Research Database of the entire population of Taiwan. The top eight cancer (140.x-208.x/Cxx.x, C7A.x) types ranked by the number of cancer deaths in Taiwan were identified and propensity score-matched with each diagnosis period at a 1:1 ratio using gender, age, and comorbidity index score, ensuring similarity in each study group. Consequently, a total of 43,404 and 70,233 adult cancer patients for Framework One and Framework Two, respectively, were identified. The survival gain VSL was obtained by calculating the actual value in reducing the mortality rate by 1% using the total medical expenditures per capita. The estimation of the life expectancy gain VSL was based on the relationship between the total medical expenditures per capita and the survival time in cancer patients, which calculates the value to increase the one-year survival time to produce the life expectancy gain VSL. The major statistical methods included chi-square test, Cox proportional hazards model, and generalized linear model (GzLM). All analyses were conducted in SAS 9.4.
Results: The adjusted Cox proportional hazards model indicated that the mortality of patients with pancreatic cancer (three-year mortality=48.61%) was significantly highest (aHR=3.315, p<.0001); followed by that of patients with lung cancer. "Other cancer" generated the highest survival gain VSL at TWD$319,348. The adjusted GzLM revealed significant differences in the medical expenditures per capita among major categories of cancer (p<.05). Pancreatic cancer was found to have the highest life expectancy gain VSL at TWD$34,732,592; followed by liver cancer and lung cancer in the second and third place, with other cancer ranked the lowest.
Conclusion: The differences in the value of statistical life among major categories of cancer are identified. "Other cancer" requires the highest value in reducing 1% mortality. Pancreatic cancer demands the greatest value in extending life expectancy by one year. Health authorities and medical organizations should increase medical resources to pancreatic cancer and lung cancer both of which have high mortality. Integral evaluation toward life and value may be discreetly conducted to enhance allocation appropriateness of medical resources and thus advance the effectiveness of cancer care.


目錄
致謝 i
摘要 ii
目錄 v
表目錄 vii
圖目錄 ix
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 5
第三節 研究目的 6
第二章 文獻探討 7
第一節 醫療支出與生命價值 7
第二節 存活增益生命價值與餘命增益生命價值 10
第三節 各種類癌症之生命價值 12
第四節 存活增益生命價值與餘命增益生命價值之其他相關因素 13
第五節 文獻小結 17
第三章 研究方法 18
第一節 研究架構 18
第二節 研究假設 22
第三節 研究對象與資料來源 23
第四節 研究變項操作型定義 29
第五節 分析工具及方法 35
第四章 結果 38
第一節 存活滿三年之癌症患者存活增益生命價值 38
第二節 加入癌症期別變項存活滿三年之癌症患者存活增益生命價值 65
第三節 僅死亡之癌症患者餘命增益生命價值 94
第四節 加入癌症期別變項死亡之癌症患者餘命增益生命價值 110
第五章 討論 127
第一節 醫療支出與死亡率 127
第二節 各種類癌症之存活增益生命價值 130
第三節 各種類癌症之餘命增益生命價值 134
第四節 存活增益生命價值與餘命增益生命價值之其他相關因素 138
第六章 結論與建議 140
第一節 結論 140
第二節 建議 143
第三節 研究限制 146
參考文獻 147


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