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    政大機構典藏 > 商學院 > 統計學系 > 學位論文 >  Item 140.119/131475
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/131475


    Title: 癌症存活與醫療利用之關係
    A Study of Cancer Survival and Medical Utilization
    Authors: 張庭禎
    Chang, Ting-Chen
    Contributors: 楊曉文
    余清祥

    Yang, Sheau-Wen
    Yue, Ching-Syang

    張庭禎
    Chang, Ting-Chen
    Keywords: 全民健康保險
    癌症
    存活分析
    醫療利用
    人口老化
    National Health Insurance
    Cancer
    Survival Analysis
    Medical Utilization
    Population Aging
    Date: 2020
    Issue Date: 2020-09-02 11:42:36 (UTC+8)
    Abstract: 重大傷病卡為全民健康保險的主要特色之一,因其患者使用較多醫療資源,為降低患者及其家庭的經濟負擔,免除重大傷病相關就醫的部分負擔。重大傷病患者中約有一半為癌症患者,2018年每位癌症病患健保花費超過14萬元,約為全國平均值的七倍以上,由於癌症發生率隨年齡增加,加上罹癌後存活率持續改善及人口老化,預期我國罹癌人數將逐年上升,未來健保財務負擔將更加沈重。有鑑於此,本研究以癌症病患為研究對象,藉由健保資料庫探討癌症存活時間與其醫療利用的關係,評估人口老化對我國健保造成的影響,希冀研究結果可供政府及各界參考。
    有別於過去癌症研究,本文以罹癌後的存活時間為基準,分析罹癌後各年度的醫療利用,作為評估罹癌歷程醫療費用的基礎。本研究依據健保資料庫的重大傷病證明明細檔、重大傷病門診處方及治療明細檔、重大傷病住院醫療費用清單明細檔,藉由癌症發生率、盛行率、存活率、門診住院醫療利用,分析癌症人數與醫療利用的時間趨勢。研究發現:健保資料庫經資料年度重整後,無論在癌症新發生或是存活人數上,皆與癌登及衛福部公佈人數相近,顯示由健保資料庫可推得與官方紀錄類似的結果。另外,趨勢分析顯示癌症發生率逐年增加、死亡率逐年下降,其中死亡率下降較為快速;存活率逐年改善,且改善幅度隨罹癌年度遞增。此外,癌症門診醫療利用高峰落在罹癌前三個月與罹癌後第一年,此後無論平均就醫次數與點數皆逐年遞減,但罹癌後五年仍高於罹癌前;罹癌後各年度之門診平均就醫次數與點數皆隨時間增加,且成長幅度隨罹癌年度遞減。在住院方面,癌症之住院需求集中在罹癌第一年,且平均每人住院天數逐年遞減。
    Catastrophic illness (CI) is one of the main features of Taiwan’s National Health Insurance (NHI). People with CI card enjoy the waiver of co-payment to reduce the financial burden. About 2% of Taiwan people are with cancer and the medical expenditure of every cancer patient is about seven times of national average. As the cancer incidence increases with age, coupled with the prolonging survival probability of cancer patients and aging population, it is expected that there will be more cancer patients, increasing the financial burden of NHI. This study aims to evaluate the impact of cancer on Taiwan’s NHI, focusing on the cancer survival time and its medical utilization.
    Different from the past work, the impact of cancer is measured via the survival time of cancer patients since the medical utilization varies a lot after patients suffering from cancer. We use the NHI Research Database to estimate the cancer incidence, the survival time of cancer patients, and the medical expenditure of cancer patients. The analysis shows that the cancer incidence and the survival rate of cancer patients improve with time. The outpatient medical utilization of cancer patients decrease with the survival time, after hitting the peak within the first three months before cancer and the first year after cancer. On average, the outpatient visits of cancer patients increase with time, while the inpatient visits decrease with time.
    Reference: 一、 中文文獻
    1. 行政院衛生福利部(2020)。癌症登記年報。
    2. 行政院衛生福利部(2020)。死因統計。
    3. 行政院衛生福利部(2019)。衛生福利年報。
    4. 行政院衛生福利部(2018)。全民健康保險年報。
    5. 李妙純、沈茂庭(2008)。全民健保下不同所得群體醫療利用不均因素分析,台灣公共衛生雜誌;27卷3期。
    6. 陳建仁、林莉華(1997)。「健康保險資料庫之學術應用:重大傷病證明資料 檔分析之經驗」,《中華公共衛生雜誌》,16卷6期,頁 513-521。
    7. 陳芝嘉、余清祥、蔡偉德(2015)。921震災對中老年人死亡風險的影響, 人口學刊,50卷,頁61-99。
    8. 陳昱霈(2016)。「全民健保資料庫分析:以全民健康保險資料庫探討癌症的發生與死亡」,國立政治大學商學院統計學系碩士論文。
    9. 張鴻仁、黃信忠、蔣翠蘋(2002)。全民健保醫療利用集中狀況及高、低使 用者特性之探討,台灣公共衛生雜誌,21卷3期,頁207-213。
    10. 黃泓智、劉明昌、余清祥(2004)。「台灣地區重大傷病醫療費用推估」 , 《人口學刊》,29卷,頁35-70。
    11. 喬治華、莊聲和、梁正德、鍾孟鈴(2010)。1996-2007重大傷病經驗統計研究-以全民健康保險研究資料庫為基礎。財團法人保險事業發展中心。
    12. 蔡秉諺(2010)。「台灣慢性腎臟疾病患者盛行率與醫療利用分析-以健保資料庫為例」,臺北醫學大學醫務管理學研究所學位論文。
    13. 鄭志新(2015)。「全民健保資料庫分析:以全民健保資料庫探討長期照護需求」,國立政治大學商學院統計學系碩士論文。
    14. 蘇維屏(2014)。「全民健保資料庫分析:重大傷病及癌症之研究」,國立政治大學商學院統計學系碩士論文。

    二、 英文部分
    1. Clive Hoggart, Paul Brennan, Anne Tjonneland, Ulla Vogel, Kim Overvad, Jane Nautrup Østergaard, Rudolf Kaaks, Federico Canzian, Heiner Boeing, Annika Steffen, Antonia Trichopoulou, Christina Bamia, Dimitrios Trichopoulos, Mattias Johansson, Domenico Palli, Vittorio Krogh, Rosario Tumino, Carlotta Sacerdote, Salvatore Panico, Hendriek Boshuizen, H. Bas Bueno-de-Mesquita, Petra H.M. Peeters, Eiliv Lund, Inger Torhild Gram, Tonje Braaten, Laudina Rodríguez, Antonio Agudo, Emilio Sanchez-Cantalejo, Larraitz Arriola, Maria-Dolores Chirlaque, Aurelio Barricarte, Torgny Rasmuson, Kay-Tee Khaw, Nicholas Wareham, Naomi E. Allen, Elio Riboli, and Paolo Vineis (2012), “A Risk Model for Lung Cancer Incidence.” Cancer Prevention Research 5, 834–846.
    2. Jung, K., Won, Y., Kong, H., and Lee, E. (2020), “Cancer Statistics in Korea: Incidence, Mortality, Survival, and Prevalence in 2011”, Cancer Res. Treat 52(2): 431-437.
    3. Pompei, F. and Wilson, R. (2001), “The Age Distribution of Cancer: The Turnover
    at Old Age.” Health Environment Risk Assess 7, 1619-1650.
    4. Siegel, R., Miller, K., and Jemal, A. (2020), “Cancer Statistics, 2020”, CA: A Cancer Journal for Clinicians 70: 7-30.
    5. Yue, C.J., Wang, H., Leong, Y. and Su, S. (2018), “Using Taiwan National Health Insurance Database to Model Cancer Incidence and Mortality Rates”, Insurance: Mathematics and Economics 78: 318-324.
    Description: 碩士
    國立政治大學
    統計學系
    107354013
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0107354013
    Data Type: thesis
    DOI: 10.6814/NCCU202001441
    Appears in Collections:[統計學系] 學位論文

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