自全民健保開辦後，洗腎病人平均每年成長16％到20％，截至民國95年3月國內請領洗腎重大傷病者已達52,000名，發生率高居世界第一，盛行率為世界第二，可想而知洗腎費用相當驚人，目前透析治療一年花費高達250億元，占全民健保整體支出的6％以上，若再加上尿毒症相關併發症醫療支出則超過400億元，是健保單一治療最大耗費項目。 洗腎人口的增加 使得洗腎費用急遽躍升，基於財務規劃的考量，健保局屢次希望調降洗腎的支付點值，然而這個想法卻引起醫界強烈的反彈，強調相較於美國和日本的洗腎費用，台灣的透析給付已無調降空間，認為若強行調降血液透析給付恐會影響洗腎品質；相反的，健保局依據新加坡的資料及調查門診洗腎耗用資源相對值的結果，卻呈現臺灣洗腎費用過高的現象，醫界與健保局各有依據，雙方始終無法達成共識。 整個問題的核心在於了解影響透析治療的相關因素，究竟臺灣的洗腎品質如何？是否會因洗腎支付調整而有變動？不同醫療院所之間的洗腎品質是否存在差異性呢？由於臺灣過去的透析資料均掌握在醫界團體手中，社會大眾對於洗腎議題縱有諸多討論，因受資料的限制總是不得其門而入，然則自健保開辦後，所有的洗腎病患皆列入重大傷病紀錄，透過國衛院的健保資料庫理當能了解洗腎病患的就醫費用和存活變項，可惜的是透析治療資料繁雜，外界不容易進行分析，因此本文將健保資料庫加以彙整出完備的透析病患資訊。 由於洗腎病人多為慢性腎臟患者，需要長期治療，故本研究以洗腎三個月以上的血液透析病患為主要研究對象，同時為了排除不同洗腎院所的影響，本文進一步以未轉院的新進病人為分析基礎，利用危險率模型（Cox Proportional Hazard Model）探討病人特性（年齡別、性別、疾病別），以及醫院特性（醫院權屬別、層級別、地區別與洗腎治療床規模）對長期血液透析病患的存活率與死亡相對危險性之影響。 研究結果發現病人的特性指標扮演較重要的角色，年齡愈大、男性、僅罹患糖尿病，或同時合併糖尿病以及高血壓的多重診斷病人，其死亡的相對危險性較高；僅罹患高血壓的透析病人短期死亡風險不顯著，長期則有顯著差異。醫院特性方面，洗腎治療床規模愈大，病患存活率愈高，公立醫療院所的病患存活率最低，基層診所的病人存活率最高。不區分長短期效果時，私立的死亡風險高於公立，基層診所的相對危險性低於醫學中心；但長期而言，公立的相對危險性就高於私立，基層診所的死亡風險仍顯著低於醫學中心，和存活率分析結果一致。 探究公立醫療院所存活率較低的原因，本研究認為可能是源於公立醫療機構缺乏追求高績效的動機，致使經營績效疲弱，進而影響到血液透析病人的洗腎品質；本文從三方面探討醫學中心存活率較基層診所為低之因，一可能源於醫學中心的病人滿意度較低，二為醫學中心的糖尿病透析病患比例較基層診所為高，三則可能由於醫學中心的院內感染機率較大之故。 本文的研究貢獻主要有四點，一是國內對於洗腎品質的研究少有以存活率作為品質之指標者，同時相關研究多受限於樣本數不足的困境，而本文利用全民健保資料庫可進行大規模且全面性的研究；另者，本文改進過去對於洗腎病患存活情形的分析方法謬誤，以新進病人為分析基礎；三為連結醫院特性與存活率的關係，針對所有透析醫療院所探討供給者特性對於洗腎病人存活率之影響；最後，本文發現醫學中心和其他醫院權屬別相較並未有較高的存活率，是以可藉此教育民眾正確就醫觀念，以落實轉診制度，使醫學中心的功能得以真正發揮，醫療資源得以善加分配。

Who can survive longer and what factors could prolong the trading life of individual investors in the market? This is the questions we ask in the dissertation. Based on our knowledge, there is not any research about the issue of survival analysis on analyzing individual investors in stock market. The paper classifies three possibilities could affect the trading life of investors: personal characteristics, trading behavior, and market condition. In the dissertation, we use tick-by-tick transaction data from the Taiwan Stock Exchange to profile survivors versus non-survivors, to investigate how the traders’ characteristics (such as, gender), trading behaviors (such as the degree of diversification, trading amount and trading frequency) and market condition affect the trading life of investors. We borrow the proportional hazard models proposed by Cox (1972) who used in bio-statistics to analyze the survival rate. Using the Kaplan-Meier curves for male and female, we find that survival functions and hazard rates of female investors have better survival prognosis than the male investors. Different timing of entering results in distinct patterns of survival curves and hazard rates. Investors entering that market in the bull and bear market have a larger survival rate than those who enter the market in normal time during the trading life from 1 to 7 years. Moreover, as the trading life increases larger 7 year, the three curves of bull, bear and normal market conditions, respectively, appear to get closer, suggesting that if trading life is shorter than 7 years, the investors entering in the bull and bear markets seemly have lower hazard ratio than that in the normal market to leave the market. Finally, the results of Cox’s proportional hazard model show that female investors stay in the market 74 days longer than the male. Trading cycle increasing by one day will prolong the traders in the market by 4.8 days. Average volume per trade measured in ten thousands does not have economic effect on the trading duration, although its estimate is statistically significant. A one percentage increase of portfolio return will reduce about 151 days of the trading life. One more stock in the portfolio will prolong about 133 days in the trading life. The effect on the trading duration of trading performance of those who enter in the bull market is positive. / Who can survive longer and what factors could prolong the trading life of individual investors in the market? This is the questions we ask in the dissertation. Based on our knowledge, there is not any research about the issue of survival analysis on analyzing individual investors in stock market. The paper classifies three possibilities could affect the trading life of investors: personal characteristics, trading behavior, and market condition. In the dissertation, we use tick-by-tick transaction data from the Taiwan Stock Exchange to profile survivors versus non-survivors, to investigate how the traders’ characteristics (such as, gender), trading behaviors (such as the degree of diversification, trading amount and trading frequency) and market condition affect the trading life of investors. We borrow the proportional hazard models proposed by Cox (1972) who used in bio-statistics to analyze the survival rate. Using the Kaplan-Meier curves for male and female, we find that survival functions and hazard rates of female investors have better survival prognosis than the male investors. Different timing of entering results in distinct patterns of survival curves and hazard rates. Investors entering that market in the bull and bear market have a larger survival rate than those who enter the market in normal time during the trading life from 1 to 7 years. Moreover, as the trading life increases larger 7 year, the three curves of bull, bear and normal market conditions, respectively, appear to get closer, suggesting that if trading life is shorter than 7 years, the investors entering in the bull and bear markets seemly have lower hazard ratio than that in the normal market to leave the market. Finally, the results of Cox’s proportional hazard model show that female investors stay in the market 74 days longer than the male. Trading cycle increasing by one day will prolong the traders in the market by 4.8 days. Average volume per trade measured in ten thousands does not have economic effect on the trading duration, although its estimate is statistically significant. A one percentage increase of portfolio return will reduce about 151 days of the trading life. One more stock in the portfolio will prolong about 133 days in the trading life. The effect on the trading duration of trading performance of those who enter in the bull market is positive.