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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/124682


    Title: 癌症病患存活與醫療利用之分析
    A Study of Survival and Medical Usage of Cancer Patients
    Authors: 陳焌彥
    Chen, Chun-Yen
    Contributors: 余清祥
    黃泓智
    陳焌彥
    Chen, Chun-Yen
    Keywords: 全民健康保險
    重大傷病
    癌症
    大數據
    醫療利用
    National Health Insurance
    Catastrophic illness
    Cancer
    Big Data
    Medical Utilization
    Date: 2019
    Issue Date: 2019-08-07 16:01:13 (UTC+8)
    Abstract: 我國全民健康保險（簡稱健保）於民國84年開始實施，至今超過 20 年且納保率高達99%，其中重大傷病卡是全民健康保險的主要特色之一，罹患重大傷病者需要較多的醫療費用，因此享有免部分負擔。截至 108年5月，領有重大傷病證明者89萬餘人（約4%人口），其中重大傷病相關醫療費用佔健保支出27%，由於重大傷病的發生率隨年齡上升，這些數值將隨人口老化逐年增加，衝擊我國健保的永續經營（資料來源：衛生福利部）。有鑑於此，本文以重大傷病為研究目標，探討患者的重大傷病、非重大傷病相關醫療利用，以及患者於罹病前後的醫療行為，希冀研究成果可提供政策規劃，以及患者於罹病後醫療需求的參考。
    本研究主旨在於探討重大傷病患者的醫療利用，以及罹病後的存活及死亡率趨勢，提供政府及各界的參考，以尋求因應重大傷病帶來挑戰的解決方法。癌症是我國死因之首，同時也是重大傷病領卡數最多者（約佔45%），分析醫療利用時將重大傷病分為癌症、非癌症兩大類。本研究根據我國健保資料庫，使用重大傷病證明明細檔、重大傷病門診處方及治療明細檔及重大傷病住院醫療費用清單明細檔。本文從盛行率、發生率、死亡率出發，分析病患罹患重大傷病之醫療服務利用，如醫療費用、門診次數、住院次數及天數等，並比較癌症與非癌症的重大傷病患者的醫療利用之差異。分析發現近年來癌症發生率逐年上升、非癌症重大傷病發生率逐年下降，而癌症死亡率逐漸下降、非癌症重大傷病死亡率無明顯變化，兩者趨勢非常不同。另外，罹癌後的醫療利用隨著時間下降，大約5~7年達到穩定，配合罹癌後五年存活率，可以設計成本較易掌握的癌症保險商品。
    Taiwan implemented the National Health Insurance (NHI) in 1995 and now more than 99% Taiwan’s citizens participate in the NHI. Catastrophic illness (CI) card is one of the main features of NHI and people with CI card can enjoy waiver of copayment. More than 890,000 people are with CI card (about 4% of Taiwan’s population) and their medical expenses related to CI account for 27% of the NHI expenses, as of May 2019. The number of CI patients and their medical expenses are expected to grow with Taiwan’s population ageing, since the incidence rates of CI increase with age. (Source: Ministry of Health and Welfare). The goal of this study is to explore the medical utilization of CI patients, separating the CI into the cancer and non-cancer groups, and to evaluate the impact of population ageing on the NHI.
    There are at least two reasons for separating the CI into cancer and non-cancer: cancer is the leading illness of CI (about 50%) and the cancer’s incidence rate and medical utilization grow faster than those of non-cancer CI patients. We estimated the incidence rates, mortality rates, and medical utilization related to the CI (cancer and non-cancer) patients. Also, the survival rates of cancer patients are studied as well. The empirical study is based on the NHI database, including registry for catastrophic illness patients, inpatient expenditures by admissions and HV’s Ambulatory care expenditures by visits. We found that the incident rates of cancer increase with time and the mortality rates of cancer patients decrease with time. On the other hand, the incidence rates of non-cancer CI’s decrease annually but their mortality rates do not change much. The medical usages of cancer patients decrease with the time since they had cancer, i.e., the longer cancer patients survive the less medical usage is needed.
    Reference: 一、 中文部分
    1、 行政院衛生福利部（2019），癌症登記年報。
    2、 行政院衛生福利部（2019），死因統計。
    3、 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，頁223 - 231。
    4、 周立筠（2018），「以全民健保資料庫探討重大傷病患者的醫療利用」，國立政治大學商學院統計學系碩士論文。
    5、 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。
    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、 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。
    8、 國家發展委員會（2108），中華民國人口推估（2018至2065年）。
    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、 楊佩雯（2019），「以全民健保資料庫探討癌症之醫療服務利用」，國立政治大學商學院統計學系碩士論文。
    11、 蔡偉德、陳芝嘉、余清祥（2014），「老人醫療利用的價格效果-以 921 震災的自然實驗為例」，《經濟論文》，42卷4期，頁599-645。
    12、 盧瑞芬、李佳琳、莊逸洲（1999），全民健康保險重大傷病患者住院醫療資源使用，中華公共衛生雜誌；18卷4期，頁283-292。


    二、 英文部分
    1. Jung, K., Won, Y., Oh, C., Kong, H., Lee, D., Lee, K. (2017), “Cancer Statistics in Korea: Incidence”, Mortality, Survival, and Prevalence in 2014, Cancer Res. Treat 49(2): 292-305.
    2. Jung, K., Won, Y., Kong, H., Lee, E. (2018), “Cancer Statistics in Korea: Incidence, Mortality, Survival, and Prevalence in 2015”, Cancer Res. Treat 50(2): 303-316.
    3. Jung, K., Won, Y., Kong, H., Lee, E. (2019), “Cancer Statistics in Korea: Incidence, Mortality, Survival, and Prevalence in 2016”, Cancer Res. Treat 51(2): 417-430.
    4. Lee, R.D. and Carter, L. (1992), “Modeling and Forecasting the Time Series of U.S. Mortality”, Journal of the American Statistical Association 87: 659-675.
    5. Lee, R.D. (2013), “The Lee-Carter Method for Forecasting Mortality, with Various Extensions and Applications”, North American Actuarial Journal 4(1): 80-93.
    6. Lindsey A., Torre, R.L., Siegel, E.M., and Ward, A. (2015), “Global Cancer Incidence and Mortality Rates and Trends -- An Update”, Cancer Epidemiology Biomarkers Prev. 25, Issue 1.
    7. Oh, C., Won, Y., Jung, K., Kong, H., Cho, H., Lee, J., Lee, D., and Lee, K. (2016), “Cancer Statistics in Korea: Incidence, Mortality, Survival, and Prevalence in 2013”, Cancer Res. Treat 48(2): 436-450.
    8. Siegel, R., Miller, K., and Jemal, A. (2015), “Cancer Statistics, 2015”, CA: A Cancer Journal for Clinicians 65: 5-29.
    9. Siegel, R., Miller, K., and Jemal, A. (2016), “Cancer Statistics, 2016”, CA: A Cancer Journal for Clinicians 66: 7-30.
    10. 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
    106354010
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0106354010
    Data Type: thesis
    DOI: 10.6814/NCCU201900403
    Appears in Collections:[Department of Statistics] Theses

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