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題名：人口老化與全民健保支出：死亡距離取向的分析
作者：李大正 引用關係
作者(外文)：Ta-cheng Li
校院名稱：國立中正大學
系所名稱：社會福利所
指導教授：楊靜利
王德睦
學位類別：博士
出版日期：2010
主題關鍵詞：人口老化；壽命延長；死亡距離；醫療費用；全民健康保險；population aging；longevity extension；time to death；health care expenditure；National Health Insurance
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一般認為醫療費用隨著年齡增加而增加，因此人口老化將加重醫療費用上漲壓力。然而過去許多研究結果並未發現人口老化對醫療費用有顯著而正向的影響，反而是經濟發展、醫療供給增加、納保範圍擴張等因素的影響較大。部分學者指出問題在於從年齡別醫療費用的角度來理解人口老化的影響會忽略了真正引發高齡者醫療費用較高的原因---死亡。個人一生醫療費用大多數集中於臨終前，顯然老年人的平均醫療費用比年輕人高不是年齡較大，而是老年人較年輕人更接近死亡。因此Zweifel等人主張「死亡距離」（time to death）才是探討人口老化對醫療費用影響的關鍵因素。
換句話說，年齡別醫療費用變化反映的是死亡距離效果，如果將死亡視為身體狀況最差的情形，則距離死亡近者的健康狀況比距離死亡遠者差，有較多的醫療需求，進而引發較高的醫療費用。年齡雖然是健康狀況與醫療需求的重要指標，但相同年齡者的健康狀況不盡相同，亦即年齡別醫療費用中包含不同死亡距離階段人口的費用，易受死亡距離因素的影響。相對地，死亡距離別醫療費用直接衡量類似健康狀況或醫療需求者的支出情形，而無論其歲數為何。從年齡取向分析人口老化與總體醫療費用的關連，容易獲致死亡率下降、壽命延長下高齡人口增加將促使醫療費用上漲的結論，卻忽略了壽命延長同時也延後了臨終費用高峰期的發生時間，此遞延作用形成抑制時期別醫療費用上漲的力量，因此橫斷面年齡取向的分析方式會高估人口老化對醫療費用的影響。死亡距離取向以死亡為起點回溯觀察個人生前醫療費用的變化，估計結果是緊隨著人口死亡時點變動而調整，較不受死亡步調改變的影響而能更準確掌握醫療支出的變動情形。
人口老化與整體醫療費用的關連不僅與年齡結構、年齡別平均醫療費用的變化有關，應該進一步將死亡距離納入考量。本文的目的即在以死亡距離分析取向探討台灣人口老化下未來全民健保費用的可能趨勢，企圖回答以下問題：第一，台灣人口之死亡距離別醫療費用分佈與變化為何？年齡、死亡距離、醫療費用三者的關係為何？第二，在死亡距離分析取向下，未來健保整體支出成長趨勢為何，與年齡分析取向獲得的結果有何不同？
本文以全民健保資料庫之2000年承保抽樣歸人檔為分析素材，首先從樣本之承保記錄與就醫歷史中估計死亡樣本，計算死亡距離別平均醫療費用並與年齡作交叉分析。就年齡、死亡距離與醫療費用的關係而言，各年齡組均顯現距離死亡越近者醫療支出越高的情形。然而，50歲以前死亡距離別平均醫療費用呈現隨年齡增加而增加的趨勢，之後則呈現死亡年齡越高平均費用越低的情形，隱含壽命延長有延緩整體醫療費用上漲的作用，且不同年齡人口壽命延長的費用遞延效果不同。中年人口壽命延長帶來的費用遞延效果高於高齡人口，假設在死亡數相同的情形下，50歲死亡者延後至51歲死亡，平均每人造成的遞延費用會高於80歲死亡者延後至81歲死亡帶來的遞延效果。
此外，觀察2000-2007年死亡距離別醫療費用的分佈情形後，發現平均每人醫療費用開始增加的時點有向前推移的趨勢；2000年時平均費用大約於死亡前兩至三年起開始明顯增加，2007年則前推至死亡前四到五年起。此現象似乎反映疾病期間拉長、或延長的壽命乃為不健康壽命之疾病擴張態勢。換句話說，以年齡模型評估人口老化對醫療費用的影響容易忽略死亡率下降、壽命延長引發之費用遞延效果而高估人口老化的衝擊，但由於費用開始增加的起點提早了，也就是罹病的期間拉長，因此壽命延長引發之費用遞延效果將被抵銷。不過這兩個力量如何消長，仍有待進一步的探討。結合2009-2050年間人口推計結果，以及基礎年（2007年）之平均每人費用，並考慮醫療成本成長率，獲得之整體醫療支出推計結果顯示未來健保支出將持續上升，顯示壽命延長產生的費用遞延效果仍不足以抵銷人口老化下高齡人口與接近死人口持續增加造成之費用上漲壓力。
本研究雖然建立了死亡距離與醫療費用之關係的分析模型，但在實證工作上仍有頗多限制。雖然承保抽樣歸人檔有個人長時間的費用資料可供分析，但是在健保資料缺乏死亡時點訊息而又不能連結死因資料檔的狀況下，只能暫時以估計死亡樣本的資料推測死亡距離別醫療費用的分佈。未來若能開放不同資料庫個體資料的串連，將能有效提升分析結果的準確性。另外，本文的討論範疇僅止於全民健保費用，人口老化引發之長期照護需求將日益明顯，若要完整討論人口老化對整體健康照護費用的衝擊必須將長期照護費用納入考量，這也是在規劃長照保險時必須重視的議題。
Taiwan is experiencing a dramatic increase in the numbers and proportions of older people. In 2000 there were 1.92 million persons aged 65 and over. According official population projection, the number of old age people in 2050 will be 3.59 times of today’s figure and the proportion of older people will be more than 30 percent. The scenario makes people worry about that the financial balances of Taiwan’s healthcare insurance will be inevitably jeopardized. The link between aging and increases of health expenditure derives from that per capita consumption continuously increases with age. Therefore, a larger share of old people will imply an increase in health care expenditure.
However, the effects of ageing on health care spending are uncertain. Some argue that health care expenditures increase substantially with age primarily because mortality rates increase with age and expenditures increase with closeness to death. The main reason why healthcare costs increase with age is that older people are closer to death than younger people (Zweifel et al. 1999；Yang et al. 2003). The pattern of health expenditure by age is considerably influenced by the concentration of expenditure in the final years of life. The greater expenditure on the elderly is a consequence of the heavy weight of so-called death costs (Fuchs 1984；Scitovsky 2005). In addition, increases in longevity may be expected to lead to postponement of these costs of the final years of life and declines in age specific mortality may be expected to lead to declines in age specific costs because declining mortality reduces the proportion of those near death. If we overlook this aspect, we envisage a misleading scenario of health expenditure increase. In fact, there is some evidence that health costs prior to death even decrease with age (Lubitz 1995；Polder 2006) and in the short run, the more rapid the increase in longevity, the lower the health care costs (Miller 2001).
Incorporating the concept of time to death, this paper is to reexamine the relationship of population aging and healthcare expenditure in Taiwan. We will estimate health care expenditure not only by age but also by time to death. We analyzed data from the Longitudinal Health Insurance Database (LHID2000) which is based on the registration files and original claim data in National Health Insurance Research Database (NHIRD). LHID2000 contains medical use and costs information of both decedents and survivors, and all enrollees are traced retrospectively to 1996 and followed up to 2007, therefore we can depict how health care expenditures change as people age and as people approach the end of their life, and the observation of health care expenditures over a long period are available. The final sample has 954,496 persons and consists of 45,447 persons who died between 2000 and 2007.
Two parts of analyses are employed in this study. Firstly we examine the correlation between age/time to death and health care expenditures from 1996 to 2007. Secondly we explore the relationship between longevity and future health care expenditures by comparing two approaches of healthcare costs projection to year 2050: one is based on a fixed age schedule of costs and the other on a fixed time to death schedule.
The results include: (1) Decedents have a much higher average expenditures than survivors when the pattern plotted against age. It means that the expenditure patterns by age will be changed when time to death included. (2) For decedents, different dead age groups have similar average expenditures pattern against time to death, but expenditures are higher for younger people than for older people. These implicate that increases in longevity delay both death and the high costs associated with the final stage of life. (3) Projections failing to take time to death into account might result in upward biased simulations while total expenditures still will be raised by the absolute number of elderly people.
王德睦、李大正（2009）。「台灣的存活曲線矩型化與壽命延長」。人口學刊 38: 1-31。new window
王德睦、劉一龍（2008）。「台灣總生育率再分析---ACF法的運用」。人口學刊 36: 37-65。new window
行政院經建會（2008）。中華民國台灣97年至145年人口推計。台北：行政院經濟建設委員會人力規劃處。
行政院衛生署（2008）。中華民國97年國民醫療保健支出。台北：行政院衛生署。
李大正、楊靜利、王德睦（2009）。「死亡距離與醫療費用之關連」。論文發表於台灣公共衛生學會2009年年會。台北：2009年12月6日。
李隆安（1998）。「人口老化對全民健康保險醫療利用與費用影響之評估研究」。行政院衛生署委託研究計畫（DOH87-NH-003）。
健保局（2009）。民國98年全民健康保險費率精算報告。台北：中央健保局。
陳世能、邱雅苓（2003）。「醫療保健支出成長因素之探討」。經濟研究39(2): 197-240。
陳孝平（1998）。「影響全民健保醫療費用因素之探討（供給面）」。行政院衛生署委託研究計畫（DOH87-NH-028）。
陳紹馨（1979）。台灣的人口變遷與社會變遷。台北：聯經出版事業公司。new window
陳寬政、林子瑜、邱毅潔、紀筱涵（2009）。「人口老化、疾病擴張與健保醫療費用」。人口學刊39: 59-83。
陳寬政、劉正、涂肇慶（1999）。「出生時平均餘命的長期趨勢」。台灣社會學研究3: 87-114。
游慧光、洪乙禛、王漢民、謝啟瑞（2007）。「醫療保健支出的跨國與跨時比較」。社會科學論叢 1(2): 23-70。new window
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: 35-70。new window
楊銘欽（2001）。「全民健保制度下民眾臨終前一年之醫療資源耗用分析」。行政院衛生署委託研究計畫（DOH89-NH-042）。
楊靜利、李大正（2008）。「台灣人口資料之編製與調整：1905-1943與1951-1997」。調查研究23: 119-154。new window
劉嘉年、楊銘欽、楊志良（2001）。「台灣成年民眾於死亡前三個月健保醫療費用支出之影響因素分析」。台灣衛誌 20(6): 451-462。new window
謝啟瑞、林建甫、游慧光（1998）。「台灣醫療保健支出成長原因的探討」。人文及社會科學集刊 10(1): 1-32。new window
藍祚運（2003）。「台灣人口老化對未來健康面的影響」。台灣衛誌 22(3): 237-244。
Bongaarts, J. (2005). “Long-Range Trends in Adult Mortality: Models and Projection Methods” Demography 42(1): 23-49.
Bongaarts, J. (2006). “How Long Will We Live” Population and Development Review 32 (4): 605-628.
Bongaarts, J. (2009). “Trends in Senescent Life Expectancy” Population Studies 63(3): 203-213.
Buettner, T. (2002). “Approaches and Experiences in Projecting Mortality Patterns for the Oldest-old” North American Actuarial Journal 6(3): 14-29.
Caltabiano, M., M. Castiglioni and A. Rosina. (2009). “Lowest-low Fertility: Sign of a Recovery in Italy?” Demographic Research 21: 681-718.
Carnes, B. and S. Olshansky. (1993). “Evolutionary Perspectives on Human Senescence” Population and Development Review 19(4): 793-806.
Carnes, B., L. Holden, S. Olshansky, T. Witten and J. Siegel. (2006). “Mortality Partitions and Their Relevance of Research on Senescence” Biogerontology 7(4): 183-198.
Carnes, B., S. Olshansky and D. Grahn. (1996). “Continuing the Search for a Law of Mortality” Population and Development Review 22(2): 231-264.
Carnes, B., S. Olshansky. (1997). “A Biologically Motived Partitioning of Mortality” Experiment Gerontology 32 (6): 615-631.
Carnes, B., S. Olshansky. (2007). “A Realist View of Aging, Mortality and Future Longevity” Population and Development Review 33(2): 367-381.
Cheung, Karen S-L., J. Robine, J-C Tu and G. Caselli. (2005). “Three Dimensions of the Survival Curve: Horizontalization, Verticalization and Longevity Extension” Demography 42(2): 243-258.
Cheung, Karen S-L., J. Robine.(2007).“Increase in Common Longevity and the Compression of Mortality: The Case of Japan. Population Studies 61(1): 85-97.
Coale, A. and G. Guo. (1989). “Revised Regional Model Life Tables at Very Low Levels of Mortality” Population Index 55(4): 613-643.
Coale, A. and G. Guo. (1991). “The Use of New Model Life Tables at Very Low Mortality in Population Projections” Population Bulletin of the UN. No 30: 1-22.
Coale, A., P. Demeny and B. Vaughan. (1983). Regional Model Life Tables and Stable Populations. Orlando: Academic Press.
Felder, S., M. Meier and H. Schmitt. (2000). “Health Care Expenditure in the Last Months of Life” Journal of Health Economics 19(5): 679–695.
Fries, J. (1980). “Aging, Nature Death, and the Compression of Morbidity” The New England Journal of Medicine 303(3): 130-135.
Fuchs, V. (1984). “Though Much Is Taken: Reflections on Aging, Health, and Medical Care” Milbank Memorial Fund Quarterly 62(2): 143-166.
Garber, A., T. MaCurdy and M. McClellan. (1998). “Medical Care at the End of Life: Diseases, Treatment Patterns and Costs” NBER Working Paper No.6748.
Getzen, T. (1992). “Population Ageing and the Growth of Health Expenditures” Journal of Gerontology: Social Sciences 47(3): S98–S104.
Hoover, D., S. Crystal, R. Kumar, U. Sambamoorthi. and J. Cantor. (2002). “Medical Expenditures During the Last Year of Life: Finding from the 1992-1996 Medicare Current Beneficiary Survey” Health Service Research 37(6): 1625-1642.
Horiuchi, S. and J. Wilmoth. (1998). “Deceleration in the Age Pattern of Mortality at Older Ages” Demography 35 (4): 391-412.
Kannisto, V. (2001). “Mode and Dispersion of the Length of Life” Population: An English Selection 13(1): 159-172.
Kannisto, V., J. Lauritsen, A. Thatcher and J. Vaupel. (1994). “Ruductions in Mortality at Advanced Ages: Several Decades of Evidence from 27 Countries” Population and Development Review 20(4): 793-810.
Kytir, J. and A. Prskawetz. (1995). “Life Expectancy at Age 60---Epidemiologic Scenarios Assuming Delayed Mortality for Selected Causes of Death” European Journal of Population 11(3): 261-273.
Liu Chia-Nien and Yang Ming-Chin. (2002). “National Health Insurance Expenditure for Adult Beneficiaries in Taiwan in Their Last Year of Life” Journal of Formosan Medical Association 101(8): 552-559.
Lubitz, J. and G. Riley. (1993). “Trends in Medicare Payments in the Last Year of Life” New England Journal of Medicine 328(15): 1092–1096.
Lubitz, J., J. Beebe, and C. Baker. (1995). “Longevity and Medicare Expenditures” New England Journal of Medicine 332(15): 999-1003.
Manton, K., E. Stallard and D. Tolley. (1991). “Limits to Human Life Expectancy” Population and Development Review 17(4): 603-637.
Manton, K., L. Corder and E. Stallard. (1997). “Chronic Disability Trends in Elderly United States Populations: 1982-1994” Academy of Sciences of the United States of America 94 (6): 2593-2598.
Mendelson D. and W.Schwartz. (1993). “The Effects of Aging and Population Growth on Health Care Costs” Health Affairs 12(1): 119–125.
Miller, T. (2001). “Increasing Longevity and Medicare Expenditures” Demography 38(2): 215-226.
Oeppen, J. and J. Vaupel. (2002). “Broken the Limits to Life Expectancy” Science 296: 1029-1031.
Olshansky, J. (1985). “Pursuing Longevity: Delay vs Elimination of Degenerative Diseases” American Journal of Public Health 75(7): 754-757.
Olshansky, J. (1987). “Simultaneous/Multiple Cause-Delay(SIMCAD): An Epidemiological Approach to Projecting Mortality” Journal of Gerontology 42(4): 358-365.
Olshansky, S and B. Ault. (1986). “The Fourth Stage of the Epidemiologic Transition: The Age of Delayed Degenerative Diseases” Milbank Quarterly 64(3):355-391.
Olshansky, S. and B. Carnes. (1997). “Ever Since Gompertz” Demography 34(1): 1-15.
Olshansky, S., B. Carnes and C. Cassel. (1990). “In Search of Methuselah: Estimating the Upper Limits to Human Longevity” Science 250: 634-640.
Olshansky, S., L. Hayflick and B. Carnes. (2002). “Position Statement on Human Aging” The Journal of Gerontology 57(8): B292-B297.
Omran, A. (1971). “The Epidemiologic Transition: A Theory of the Epidemiology of Population Change” Milbank Memorial Fund Quarterly 49(4): 509–538.
Payne, G., A. Laporte, D. Foot and P. Coyte. (2009). “Temporal Trends in the Relative Costs of Dying: Evidence from Canada” Health Policy 90(2): 270-276.
Polder, J., J. Barendregt and H. Oers. (2006). “Health Care Costs in the Last Year of Life-The Dutch Experience” Social Science and Medicine 63(7): 1720-1731.
Robine, J. and J. Vaupel. (2002). “Emergence of Super Centenarians in Low Mortality Countries” North American Acturial Journal 6(3): 54-63.
Sánchez-Barricarte, J. and R. Fernández-Carro. (2007). Patterns in the Delay and Recovery of Fertility in Europe. European Journal of Population 23(2):145-170.
Schatzkin, A. (1980). “How Long Can We Live? A More Optimistic View of Potential Gains in Life Expectancy” American Journal of Public Health 70(11): 1199-1200.
Schneider, E. and J. Guralnik. (1990). “The aging of American: Impact on Health Care Costs” Journal of the American Medical Association 263(17): 2335-2340.
Scitovsky, A.(2005). “ The High Cost of Dying: What Do the Data Show?” The Milbank Quarterly 83(4): 825-841.
Serup-Hansen, N., J. Wickstrom and I. Kirstiansen. (2002). “Future Health Care Costs---Do Health Care Costs during the Last Year of Life Matter” Health Policy 62(2): 161-172.
Seshamani, M. and A. Gray. (2004). “Ageing and Health Care Expenditure: The Red Herring Argument Revisited ” Health Economics 13(4): 303-314.
Shang, B. and D. Goldman. (2007). “Does Age or Life Expectancy Better Predict Health Care Expenditures?” Health Economics 17(4): 487-501.
Shryock, H. and J. Siegel.(1976). The Methods and Materials of Demography. New York: Academic Press.
Spillman, B. and J. Lubitz. (2000). “The Effect of Longevity on Spending for Acute and Long-term Care” The New England Journal of Medicine 342(19): 1409-1415.
Stearns, S. and E. Norton.(2004). “Time to Include Time to Death? The Future of Health Care Expenditure Predictions” Health Economics 13(4): 315-327.
Thatcher, A.(1999). “The Long-Term Pattern of Adult Mortality and the Highest Attained Age” Journal of the Royal Statistical Society 162(1): 5-43.
Thatcher, A., V. Kannisto and J. Vaupel. (1998). The Force of Mortality at Ages 80 to 120. Odense: Odense University Press.
Tsai, S., E. Lee and R. Hardy. (1978). “The Effect of a Reduction in Leading Causes of Death: Potential Gains in Life Expectancy” American Journal of Public Health 68(10): 966-971.
Van de Kaa, D. (2004). “The True Communality: In Reflexive Modern Societies Fertility is a Derivative. Population Studies 58(1): 77-81.
Van Weel, C. and J. Michels. (1997). “Dying, Not Old Age, to Blame for Costs of Health Care” The Lancet 350(9085): 1159–1160.
Werblow, A., S. Felder and P. Zweifel. (2007). “Population Ageing and Health Care Expenditure: A School of Red Herrings?” Health Economics 146(10): 1109-1127.
Wilmoth, J. and J. Robine. (2003). “The World Trend in Maximum Life Span” Population and Development Review 32 (4): 605-628. 29(Supplement): 239-257.
Wilmoth, J. and S. Horiuchi. (1999). “Rectangularization Revisited: Variability of Age at Death within Human Populations” Demography 36(4): 475-495.
Yang, Z., E. Norton and S. Stearns. (2003). “Longevity and Health Care Expenditures: The Real Reasons Older People Spend More” Journal of Gerontology 58(1): S2-S10.
Zweifel, P., S. Felder and A. Werblow. (2004). “Population Ageing and Health Care Expenditure: New Evidence on the Red Herring” Geneva Papers on Risk and Insurance:Issues and Practice 29 (4): 653-667.
Zweifel, P., S. Felder and M. Meiers. (1999). “Ageing of Population and Health Care Expenditure: A Red Herring?” Health Economics 8(6): 485-496.
 
 
 
 
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