重大傷病是我國全民健康保險的重要特色之一，透過社會保險的風險分擔機制，病患享有免部分負擔等優惠，降低因為罹病帶來的財務負擔，但重大傷病同時也成為全民健保的主要支出項目。民國102年領取重大傷病證明者不過98餘萬人（約總人口的4%），但其一年的醫療費用多達一千五百多億元（接近總支出的27%），平均每位重大傷病患者的醫療費用約為平均值的7.34倍，其中癌症又是重大傷病中人數最多者，大約佔了49%（資料來源：衛生福利部中央健康保險署）。因為許多重大傷病的發生率、盛行率與年齡成正比（黃泓智等人，2004），未來隨著人口老化，全民健保支出也將跟著上升。 　　本文使用全民健保資料庫，探討近十年重大傷病（尤其是癌症）趨勢，估計重大傷病的年齡別發生率、死亡率，評估人口老化對全民健保造成的影響，其中承保資料檔（ID）、重大傷病檔（HV）為本研究主要的依據資料。而由於健保資料庫的資料種類及數量龐雜，在初期資料的偵錯及處理上非常重要但也相當費時，至於發生率、死亡與否的判斷亦十分棘手，因此過程中我們將一一說明資料分析步驟及注意事項。本文發現癌症及重大傷病的盛行率逐年上升，但發生率並沒有明顯變化，加上近年癌症死亡率幾乎不變（但台灣全體國民的死亡率逐年遞降），因為台灣的人口老化，預期未來罹患癌症人數會逐年增加，癌症將繼續蟬聯十大死因之首，但罹癌死亡率的下降也可發現近年醫療進步所造成的影響。此外，我們也考量隨機死亡模型（Lee-Carter Model），發現無論是癌症死亡率、或是罹癌死亡率都有不錯的估計結果。而在文末也提出癌症病患的就醫行為以供後續研究者參考。 / Catastrophic illness (CI) is one of the key features of Taiwan’s National Health Insurance (NHI). Through risk-sharing mechanisms of social insurance, it can reduce the financial burden of the CI patients since treating the CI is usually expensive. However, the CI also becomes a major expenditure item of NHI. The people receiving the CI card are just 0.98 million in 2013 (about 4% of the total population), but their smedical costs are over 150 billion NT dollars (nearly 27% of total expenditures). The average medical cost per CI patient is about 7.34 times of the national average. (Source: Department of Health and National Health Insurance Agency). Because the incidence and prevalence rates increase with age (Huang et al, 2004), the total NHI expenditure is expected to increase in the future due to population aging. This study intends to use the NHI database, including the records of personal identification and out-patient visit from all CI patients, to explore the incidence and mortality rates, for example, of CI patients. Because the NHI database is big and messy, we shall first debug and clean them. Also, since the death of CI patients are not fully reported in the NHI database, we propose a method to identify the deaths and use the official statistics to evaluate. The results show that the prevalence rates of all CI increased every year, but their incidence rates did not change significantly. The mortality rates of cancer patients also did not change much. Based on these findings, we expect the proportion of CI patients and their size will continue to grow. In addition, we applied the Lee-Carter model to the cancer mortality rates, and the fit is pretty good.

一個國家對全國人口有充分瞭解，方能依據國情制定適合的政策，地方發展更是如此，更須洞悉各地的人口結構，以善用有限的資源。台灣近年人口老化日益明顯，各縣市的老化速度及人口問題也不盡相同，若可獲得各地區未來的人口相關數值 (亦即人口推估)，當能減輕未來人口老化對台灣造成的衝擊。本文以縣市層級的人口推估，也就是小區域人口推估為研究目標，探討需注意的事項，尋找適合台灣地區的小區域推估方法。 本文整理小區域人口推估方法，並使用人口要素變動合成法 (Cohort Component Method)，以雲嘉兩縣、臺北市、澎湖縣為範例，測試縣市層級的人口推估。人口推估與生育、死亡、遷移三者的假設有密切關係，我們以死亡率為目標，比較不同模型的優劣，考慮的模型包括 Lee-Carter 模型、區塊拔靴法 (Block Bootstrap)、篩網拔靴法 (Sieve Bootstrap) 以及泛函資料分析 (Functional Data Analysis) 中的主成份分析 (Principle Component Analysis)，以估計誤差為衡量方法優劣的標準。分析發現篩網拔靴法、區塊拔靴法、Lee-Carter 模型三者的結果較佳，因此在小區域推估中使用較簡便的區塊拔靴法。研究發現對小區域的人口推估而言，遷移假設扮演非常重要的角色，此與全國規模的人口推估結果截然不同。研究過程亦發現人口三要素對人口推估有明顯的影響，若假設三要素間互相獨立 (也就是傳統推估時的假設)，推估結果的預測區間遠小於三要素不獨立。 / The government can make policy according to the population change in this country, while the local government can develop their district by using their limited resources well after realizing the populaton structure. The population ageing is becoming more serious and being more different among every counties in Taiwan day by day. If we can get the relative numbers of population in the future (population projection), we can decrease the attack of population ageing for Taiwan. The aim of this paper is to find an appropriate method and some notations of small area population projection in Taiwan. The paper includes the summary of methods of small area population projection and the results by using cohort component method on three areas in Taiwan, YunLin & ChiaYi, Taipein City and PengHu. Population projection is highly related with birth, death and migration, hence we test the mortality rate by using several methods, Lee-Carter, block bootstrap, sieve bootstrap and principal component analysis of functional data analysis are included. We found that the result of sieve bootstrap, block bootstrap and Lee-Carter are much better than the others, therefore, we take block bootstrap which is much simpler than the other two to analysis the effect of birth, death and migration in population projection. The sutdy found that, in small area population projecton, migration plays an important role, which is totally different from the whole country population projection.

生育率的降低是影響台灣地區近年來人口老化的顯著因素，因其變化幅度通常高於死亡率，對人口結構的影響較大。過去台灣地區生育率研究多為整體生育(如：總生育率、年齡別生育率)趨勢的模型，較少探討台灣各地區的特色。為能更深入瞭解台灣生育行為變化的特性，本文將生育率的研究層面由整體的資料，延伸至全台灣地區的各鄉鎮市區（不含離島地區有350個鄉鎮市區），希冀能更精確地找出與台灣地區生育率持續下降的相關因素。本文分為兩個部份，以鄉鎮市區的年齡別婦女生育率與年齡別有偶婦女生育率為研究對象，資料時間為1991、1992、2001、2002年：第一部份探討各鄉鎮市區的生育率數值間是否存在空間相關性，並進一步瞭解生育率較高（或較低）的地區是否有聚集的現象。第二部份則套用空間迴歸模型探討與生育率數值有關的因素（例如：人口密度、教育程度等），更精確且客觀地提供生育率未來趨勢的建議。 關鍵字：生育率、人口老化、空間統計、空間群聚、空間迴歸 / Both the fertility rates and mortality rates, especially the fertility rates, have been experiencing dramatic decreases in recent years, and the population aging thus has become one of the major concerns in Taiwan area. In order to identify the factors that are related to the decrease of fertility rates, unlike the previous works that deal with the aggregate national data, we will study the fertility pattern in township level. We will use the data of age-specific fertility rates and total fertility rates in 1991, 1992, 2001, and 2002 in 350 townships of Taiwan area. This study will be separated into two parts. First, we shall explore if there is spatial correlation among 350 townships of Taiwan area and detect if there are spatial clusters for higher fertility townships. The second part of this project will be focused on the spatial regression model. We will use this model to determine the factors that are highly correlated to the dropping of fertility rates. Key Words: Fertility Rates, Aging Population, Spatial Statistics, Spatial Clustering, Spatial Regression

政府為促進國人健康,並以社會保險的形式分攤弱勢團體的就醫需求,於民國84年開始實施全民健康保險,實施至今超過20年,而且納保率已高達99%。重大傷病證明是全民健保的主要特色之一,持有重大傷病證明卡的病患就醫時可免除部分負擔,減輕罹患重病患者的醫療負擔。截至106年2月約有4%國人領有重大傷病證明卡,但其醫療費用佔健保支出超過 27%,預期這兩個數值會因人口老化而逐年上升,使得重大傷病的相關議題越來越受到重視。 本文以全民健保資料庫中的重大傷病證明明細檔(HV)為基礎,以2005年百萬人抽樣檔之承保紀錄檔(ID)、門診處方及治療明細檔(CD)及住院醫療費用清單明細檔(DD)輔助,探究罹患重大傷病發生及死亡議題,提出判定發生、死亡的準則,並且依此分析各種疾病發生率與死亡率的關係。另外,本文也使用資料庫內容驗證重大傷病患者與非重大傷病患者之間醫療費用的差異,研究也發現新發生的病患就醫率偏低,並以國際疾病分類代碼驗證重大傷病門診處方及治療明細檔(HV_CD)資料抓取的準確性。 / Taiwan started National Health Insurance (NHI) in 1995, for more than 20 years, and more than 99% people are covered in this social insurance plan. It is believed that the NHI has further enhanced the health of Taiwan’s people.Catastrophic illness(CI)card is one of the key features in the NHI and people with this card can enjoy waiver of copayment and other medical benefits which reduce the financial burden of CI patients. For example, about 4% Taiwan’s population were with the CI card and they spend more than 27% of total medical expenditure of NHI. Since the probability with CI increases with age, the population aging and prolonging life are expected to worsen the financial burden of the NHI. Our goal is to explore the medical need and its trend of CI patients, via the data from the NHI Database, including Registry for catastrophic illness patients(HV), Registry for beneficiaries(ID), Inpatient expenditures by admissions(DD)and HV’s Ambulatory care expenditures by visits(HV_CD). Since the medical records do not cover all the required information, we propose several criteria for data analysis, such as the rules of judging whether the patients incur CI and the CI patients passed away. We found that the incidence rates and mortality rates of CI patients decrease with time. Also, there are questions about the data quality regarding the HV_CD database and more than 50% new CI patients do not have medical records of CI diseases.

臺灣在2015年高齡人口（65歲以上）比例超過12.5%，依照國家發展委員會的2016年人口推估，預計將於2018年正式邁入高齡社會（高齡人口比例14%），2026年更突破20%的門檻，人口老化速度持續加快。因為身體機能隨年齡增長等因素逐漸老化，高齡人口的就醫需求通常也較多，包括就醫金額、就醫次數，根據中央健康保險署2014年統計，高齡人口比例約為12.0%，但其醫療費用卻佔總費用37.6%。因此本文以探討高齡人口就醫特性為目標，透過高齡人口就醫行為去了解醫療現況，並評估因老化而引發的醫療資源。 本文以高齡人口特性及就醫需求為研究方向，探討近十年高齡人口就醫需求的基本特性，如：醫療使用率、平均就醫次數及平均醫療費用。接著以高齡人口就醫選擇集中度做為出發點，計算各疾病下的就醫集中程度，探討是否高齡人口會隨著不同疾病而有不同的就醫行為。研究結果顯示年紀越大的高齡人口，醫療使用率反而下降，但平均總醫療花費隨著年齡增加亦跟著上升；另外在不同的疾病下會有不同的就醫行為，當就醫地選擇越一致其死亡率也越低。計算依據為全民健康保險資料庫2005年百萬高齡人口抽樣檔，包括承保資料檔(ID)、門診處方及治療明細檔(CD)、住院醫療費用清單明細檔(DD)，以六十五歲以上高齡人口為研究對象，探討其醫療利用行為及就醫習性。 / The population aging is speeding up in Taiwan. The elderly population (65 years and older) is more than 12.5% in 2015 and, according to the population projection of National Development Council, it is expected to reach 14% and 20% in 2017 and 2026, respectively. The elderly usually require more medical attention, partly due to the fact that the human organs degenerate with time. For example, in 2014, the proportion of elderly is about 12.0% and they account for 37.6% of total medical expenditure (Source: National Health Insurance Administration). Taiwan’s total medical expenditure will continue to grow and we need to understand the medical needs of Taiwan’s elderly, in order to cope with the need of aging society. Therefore, we use the data from the National Health Insurance Research Database (NHIRD) to explore the medical needs and behaviors of receiving medical care of Taiwan’s elderly. The dataset used in this study is a sample (one million people aged 65 and beyond, about 46% of total population) of Taiwan’s elderly and the dataset contains the Registry for beneficiaries (ID), outpatient visits (CD), and inpatient admissions (DD). Our analyses show that almost all elderly have at least one medical visit annually and their diseases are more diverse than those of younger generations. Also, the elderly have larger inertia in medical visits and, for example, the proportion of choosing the same medical institution is higher. The results of this study can serve as a reference to future policy planning and resource allocation for the elderly.