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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 陳美州 | zh_TW |
| dc.contributor.advisor | Mei-Jou Chen | en |
| dc.contributor.author | 林冠廷 | zh_TW |
| dc.contributor.author | Kuan-Ting Lin | en |
| dc.date.accessioned | 2025-09-16T16:09:36Z | - |
| dc.date.available | 2025-09-17 | - |
| dc.date.copyright | 2025-09-16 | - |
| dc.date.issued | 2025 | - |
| dc.date.submitted | 2025-08-08 | - |
| dc.identifier.citation | 【參考文獻】
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Birth of a normal girl after in-vitro fertilization and preimplantation diagnostic testing for cystic fibrosis. N Engl J Med 1990;322:905-909. 16. Zheng Z, Tan J, Chen L, et al. PGT-A improved singleton live birth rate among all age groups of women who underwent elective single blastocyst transfer: a single-centre retrospective study. J Assist Reprod Genet. 2023;40(6):1417-1427. 17. Munné S, Kaplan B, Frattarelli JL, et al. Preimplantation genetic testing for aneuploidy versus morphology as selection criteria for single frozen-thawed embryo transfer in good-prognosis patients: a multicenter randomized clinical trial. Fertil Steril. 2019;112(6):1071-1079. 18. Maria Facadio Antero, et al. Cost-effectiveness of preimplantation genetic testing for aneuploidy in fresh donor oocyte IVF cycles. Fertil Steril. 2020 Dec 9;2(1):36-42 19. Lee E, Zhang J, McEwan P, et al. Which ART strategy is most cost-effective for women of advanced maternal age? A Markov model. BMC Health Serv Res. 2022;22:1197. 20. CNN Health Report. Global fertility rates to plunge in decades ahead, new report says. March 2024. 21. OECD. Declining fertility rates put prosperity of future generations at risk. June 2024 22. US Census Bureau. Population Trends Across the Globe. November 2024. 23. IMF Staff Country Reports. Japan's Fertility: More Children Please. May 2024. 24. World Population Review. Total Fertility Rate 2025 25. Bart C J M Fauser, et al. Declining global fertility rates and the implications for family planning and family building: an IFFS consensus document based on a narrative review of the literature. Human Reproduction Update. 2024 Mar 1;30(2):153-173 26. Ministry of Health, Labour and Welfare. Health insurance coverage of infertility treatments (in Japanese), 2022. 27. Children and Families Agency. https://www.cfa.go.jp/policies/boshihoken/funin/tokutei 28. Chambers GM, Baltussen R, Crawford S, et al. Does in vitro fertilization treatment provide good value for money? Front Public Health. 2023;11:1161797. PMID:36937042. 29. Seoul Metropolitan Governement. https://tchinese.seoul.go.kr 30. Thomson Medical. (2024, October). Financial Assistance Programmes for Fertility Treatments in Singapore. https://www.thomsonmedical.com/blog/financial-assistance-programs-for-fertility-treatments 31. Nicole Knight (2021, November). A Global View of IVF Treatment and Access. 32. Bahar Morshed-Behbahani et al. Infertility policy analysis: a comparative study of selected lower middle- middle- and high-income countries. Globalization and Health. 16, Article number: 104(2020) 33. Connolly MP, Hoorens S, Chambers GM, et al. The costs and consequences of assisted reproductive technology: an economic perspective. Hum Reprod Update. 2010;16(6):603-613. 34. Katz P, Showstack J, Smith JF, et al. Costs of infertility treatment: results from an 18-month prospective cohort study. Fertil Steril. 2011;95(3):915-921. 35. Crawford S, Boulet SL, Mneimneh AS, et al. Costs of achieving live birth from assisted reproductive technology: a comparison of sequential single and double embryo transfer approaches. Fertil Steril. 2016;105(2):444-450. 36. Domar AD, Gordon K, et al. Barriers and factors associated with significant delays to initial consultation and treatment for infertile patients. Fertil Steril Rep. 2021;2(4):266-274. 37. Sarah Bögl et al. The Economics of Infertility: Evidence from Reproductive Medicine. National Bureau of Economic Research. DOI: 10.3386/w32445 38. Keller, E., & Chambers, G. M. (2022). Valuing infertility treatment: Why QALYs are inadequate, and an alternative approach to cost-effectiveness thresholds. Frontiers in Medical Technology, 4, Article 1053719. https://doi.org/10.3389/fmedt.2022.1053719 39. Taimur Bhatti et al. A Comparison of the Cost-Effectiveness of In Vitro Fertilization Strategies and Stimulated Intrauterine Insemination in a Canadian Health Economic Model. Journal of Obstetrics and Gynecology Canada. Volume 30, Issue 5, P411-420, May 2008 40. Chris Skegel et al. How Do People with Experience of Infertility Value Different Aspects of Assistive Reproductive Therapy? Results from a Multi-Country Discrete Choice Experiment. The Patient. Volume 15, pages 459-472(2022) 41. Sonnenberg FA, Beck JR. Markov models in medical decision making: a practical guide. Med Decis Making. 1993;13(4):322-338. 42. Templeton A, Morris JK, Parslow W. Factors that affect outcome of in-vitro fertilisation treatment. Lancet. 1996;348(9039):1402-1406. 43. Garceau L, Henderson J, Davis LJ, et al. Economic implications of assisted reproductive techniques: a systematic review. Hum Reprod. 2002;17(12):3090-3109. 44. Van Heesch et al. Cost-effectiveness of embryo transfer strategies: a decision analytic model using long-term costs and consequences of singletons and multiples born as a consequence of IVF. Human Reproduction 2016 Nov;31(11):2527-2540 45. Neumann P J, & Johannesson M. (1994). The willingness to pay for in vitro fertilization: a pilot study using contingent valuation. Medical Care, 32(7), 686-699. 46. 國家發展委員會. 人口推估查詢系統 47. 衛生福利部國民健康署. 民國111年人工生殖施行結果報告 48. 茂盛醫院生殖醫學中心. https://www.ivftaiwan.com/share-detail/202/49 49. 台大醫院婦產部 https://www.ntuh.gov.tw/obgy/Fpage.action?fid=8019 50. C.M. Verhaak et al. A longitudinal, prospective study on emotional adjustment before, during and after consecutive fertility treatment cycles. Human Reproduction. Vol.20, No.8 pp-2253-2260, 2005. 51. Brauer M; Balancing ART Costs Group. Economic evaluations of assisted reproductive technologies in high‑income countries: a systematic review. Hum Reprod Update. 2024;30(2):123‑140. PMID:38438132. 52. Sonnenberg FA, Beck JR. (1993). Markov models in medical decision making: a practical guide. Med Decis Making;13(4):322–38. 53. Lin S, McCulloh D, Bhatt S, et al. Cost‑effectiveness of preimplantation genetic testing for aneuploidy in fresh donor oocyte IVF cycles. Fertil Steril. 2021;116(3):681‑689. 54. Sloan HR, Kaser DJ, Ginsburg ES, et al. Cost‑effectiveness of IVF with PGT‑M/A to prevent spinal muscular atrophy. Genet Med. 2023;25(4):1006‑1014. 55. Franasiak JM, Forman EJ, Hong KH, et al. The nature of aneuploidy with increasing age of the female partner: a review of 15 169 consecutive trophectoderm biopsies evaluated with comprehensive chromosomal screening. Fertil Steril. 2014;101(3):656-663.e1 56. Smith ADAC, Tilling KM, Nelson SM, Lawlor DA. Live-birth rate associated with repeat in vitro fertilisation treatment cycles. JAMA. 2015;314(24):2654-2662. doi:10.1001/jama.2015.17296 57. Seifer DB, Wang SF, Frankfurter D. Cumulative live birth rates with autologous oocytes plateau with fewer number of cycles for each year of age > 42. Reprod Biol Endocrinol. 2023;21(1):94. 58. Vernimmen V, Paulussen ADC, Dreesen JCFM, et al. Preimplantation genetic testing for Neurofibromatosis type 1: more than 20 years of clinical experience. Eur J Hum Genet. 2023;31(8):918-924. doi:10.1038/s41431-023-01404-x. 59. Elena Keller, Georgina M Chambers et al. What Features of Fertility Treatment do Patients Value? Price Elasticity and Willingness-to-Pay Values from a Discrete Choice Experiment. Appl Health Econ Health Policy. 2023 Jan;21(1):91-107 60. M Connolly et al. Assessing long-run economic benefits attributed to an IVF-conceived singleton based on projected lifetime net tax contributions in the UK. Human Reproduction. 2009 Mar;24(3):626-32. | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/99573 | - |
| dc.description.abstract | 中文摘要
研究背景與動機： 隨著生殖醫學技術的快速發展，從冷凍技術的革新、縮時攝影胚胎培養到植入前基因診斷等新技術，使得不孕症患者的試管嬰兒成功率得以顯著改善。面對台灣持續下滑的生育率，政府自2021年7月開始實施全面性試管嬰兒生育補助政策，僅針對符合不孕症診斷者即可接受3-6次、每次依序別上限6-10萬元不等的補助。自政策施行至今已逾三年，根據國健署統計，共補助55,044個療程週期，獲得11,636個活產寶寶，總支出達38.6億元，平均每位活產寶寶政府支出約331,918元。 然而，文獻中普遍缺乏針對試管嬰兒療程不同決策的成本效益分析，特別是從政府補助角度出發的本土化研究。隨著擴大補助範圍與上限的討論興起，急需基於國內實際數據進行深入的成本效益分析，以提供政策制定的科學依據。 研究目的： 本研究旨在運用馬可夫模型評估台灣現行試管嬰兒補助政策的成本效益，並探討兩項政策擴大方案的經濟效益： 1. 分析不同年齡層在不同補助次數（1-8次）下的成本效益表現 2. 評估將胚胎植入前基因診斷（PGT）技術納入補助範圍的經濟效益 研究方法： 研究設計：採用離散時間馬可夫模型（Discrete-Time Markov Model）進行成本效益分析，設計四種狀態：「進行取卵與胚胎植入療程」、「單純胚胎植入療程」、「活產」、「補助結束仍未懷孕」。 年齡分層：1. <35歲：每次取卵可得3個囊胚，活產率45.2%。2. 35-37歲：每次取卵可得2個囊胚，活產率41%。3. 38-40歲：每次取卵可得2個囊胚，活產率33.2%。4. 40-42歲：每次取卵可得1個囊胚，活產率15.7%。 成本參數：首次取卵加胚胎植入補助10萬元，後續取卵加胚胎植入6萬元，單純胚胎植入2萬元。單顆胚胎切片費用2萬元。 分析軟體：使用TreeAge Pro Healthcare 2024進行模型建構與敏感性分析。 研究結果： 補助次數成本效益分析 年輕族群（<35歲）： • ICER從第1週期的222,222元降至8週期的132,882元 • 自第3週期起均低於政府支付上限，具備成本效益 中年族群（35-40歲）： • 35-37歲組：ICER由243,902元降至150,022元，第2週期後展現成本效益 • 38-40歲組：ICER由303,030元降至174,188元，改善幅度顯著 高齡族群（>40歲）： • ICER由636,943元降至438,777元，改善幅度最大（31.1%） 反映高齡族群治療成功率較低的現實。 敏感性分析 龍捲風圖分析顯示影響ICER的關鍵因素依序為： 1. 年齡參數（影響最顯著） 2. 完整補助費用 3. 政策週期數 4. 單純胚胎植入費用（影響最小） 胚胎切片技術成本效益分析 年輕族群（29歲及32歲）： • 29歲組4週期後均高於支付意願(Willingness to pay) • 29歲組3週期ICER為113,137元，32歲組為339,748元 • 年輕婦女因本身胚胎品質佳，PGT技術效益有限 高齡族群（≥38歲）： • 38歲組在3週期補助下ICER為11,608元，遠低於WTP • 4-6週期時呈現負值ICER，達到優勢地位（dominant strategy） • 42歲組自3週期起即呈現優勢地位 研究意義與貢獻 本研究首次建立台灣試管嬰兒補助政策的完整成本效益評估框架，提供以下重要貢獻： 1. 政策制定依據：為政府制定生育補助政策提供科學化的經濟評估工具 2. 資源配置優化：協助政府在有限資源下達到最大社會效益 3. 技術評估模式：建立新興生殖技術納入補助範圍的評估標準 4. 本土化研究：填補台灣生殖醫學經濟評估研究的空白 研究限制 1. 模型假設限制：基於現有數據建構，未考量個體差異及技術進步 2. 成本範圍有限：主要從政府補助角度分析，未納入患者間接成本 結論 本研究透過嚴謹的馬可夫模型分析，證實台灣現行試管嬰兒補助政策在大部分年齡層均具備成本效益。因此可進一步考慮更多補助策略，例如將PGT補助聚焦於38歲以上婦女等族群。這些發現為台灣生育政策的後續擴大提供重要參考，有助於在有限資源下達到最大的社會效益，持續服務有生育需求的民眾。 隨著生殖醫學技術持續進步，建議定期檢視並更新成本效益評估，以確保政策與時俱進，為台灣面臨的低生育率挑戰提供更有效的解決方案。 | zh_TW |
| dc.description.abstract | Abstract
Background and Motivation Since July 2017, Taiwan government initiated the expansion of subsidy for in vitro fertilization (IVF) to help couples with infertility to fulfill their hope to have a child. Patients under 45-year-old are eligible to receive reimbursement after a complete cycle of treatment including oocyte retrieval and embryo transfer. Studies have focused on the economic efficacy of different strategies from the patient’s perspective but very few from the government. Due to the variation not only from the success rate, but also from the costs of the medical treatments between countries, it is imperative that we conduct our own research depending on our own numbers to provide better evidence for the stakeholders to make future decisions. Research Objectives This study aims to evaluate the cost-effectiveness of Taiwan's current IVF subsidy policy using Markov models and explore the economic benefits of two policy expansion scenarios: 1. Analyze the cost-effectiveness performance of different age groups under various subsidy cycles (1-8 cycles) 2. Evaluate the economic benefits of including preimplantation genetic testing (PGT) technology in the subsidy coverage Research Methods Study Design: A discrete-time Markov model was employed for cost-effectiveness analysis. Analysis Software: TreeAge Pro Healthcare 2024. Research Results Cost-Effectiveness Analysis of Subsidy Cycles Young Population (<35 years): Cost-effective from the 3rd cycle with all ICERs below the willingness-to-pay(WTP) threshold. Middle-aged Population (35-40 years): 35-40 years group: ICER demonstrating cost-effectiveness after the 3rd cycle Elderly Population (>40 years): ICER with all simulations showed higher value than WTP. Sensitivity Analysis Tornado plot analysis revealed the key factors influencing ICER in order of significance: 1. Age parameters (most significant impact) 2. Complete subsidy costs 3. Policy cycle numbers 4. Frozen embryo transfer costs (least impact). Cost-Effectiveness Analysis of Preimplantation Genetic Testing Young Population (29 and 32 years): All ICER were significantly lower than the willingness-to-pay threshold except 29-year-old group with 3 subsidy cycles. Elderly Population (≥38 years): Both 38-year and 42-year group showed ICER lower than WTP from 3 to 6 cycles. Research Limitations 1. Model Assumption Limitations: Based on existing data construction, without consideration of individual differences and technological advances 2. Limited Cost Scope: Primarily analyzed from government subsidy perspective, not including patients' indirect costs Conclusions Through rigorous Markov model analysis, this study confirmed that Taiwan's current IVF subsidy policy demonstrates cost-effectiveness across most age groups. We recommend further study to expand the current subsidy cycle limits and adopting an age-threshold strategy to focus PGT subsidies on women aged 38 and above. These findings provide important references for Taiwan's future fertility policy expansion, helping to achieve maximum social benefits with limited resources while continuing to serve citizens with reproductive needs. As reproductive medicine technology continues to advance, we recommend regular review and updates of cost-effectiveness evaluations to ensure policies remain current and provide more effective solutions to Taiwan's low fertility rate challenges. | en |
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| dc.description.tableofcontents | 目 次
口試委員會審定書………………………………………………………………….…….. i 致謝……………………………………………………………………………….. ii 中文摘要………………………………………………………………………….. iii 英文摘要………………………………………………………………………….. vi 第一章 緒論……………………………………………………………………. 1 1.1研究背景與動機……………………………………………………………………….... .1 1.2研究目的……………………………………………………………………….……….. ..2 第二章 文獻探討………………………………………………………………….3 2.1 IVF的演進與技術發展……………………………………..……………..…3 2.2 全球少子化趨勢與各國IVF補助政策………………………………………………6 2.3 IVF成本結構與經濟評估指標………………….……………………………….9 2.4 馬卡夫模型於生殖醫學成本效益之應用………..……………………………………..11 2.5 台灣IVF成本與補助政策研究現況………….………………………………………15 第三章 研究方法………………………………………………………………..18 3.1 研究設計與架構…………………………………………………………..18 3.2 參數收集與資料來源……………………………………………………….19 3.3 成本效益的衡量指標…………………………………………………….20 第四章 研究結果………………………………………………………………22 4.1 補助週期次數影響……………………………………………………….…22 4.2 胚胎切片影響………………………………………………………….…23 第五章 討論………………………………………………………………… 24 5.1 補助週期次數分析討論………………………………………………… 24 5.2 胚胎切片技術分析討論………………………………………………24 5.3 研究限制與未來展望……………………………………………………25 第六章 結論………………………………………………………………………26 圖表………………………………………………………………………………27 參考文獻………………………………………………………………………… 40 | - |
| dc.language.iso | zh_TW | - |
| dc.subject | 生育率 | zh_TW |
| dc.subject | 補助政策 | zh_TW |
| dc.subject | 試管嬰兒 | zh_TW |
| dc.subject | 馬可夫模型 | zh_TW |
| dc.subject | 胚胎植入前基因診斷 | zh_TW |
| dc.subject | 成本效益分析 | zh_TW |
| dc.subject | cost-effectiveness analysis | en |
| dc.subject | Markov model | en |
| dc.subject | preimplantation genetic testing | en |
| dc.subject | fertility rate | en |
| dc.subject | subsidy policy | en |
| dc.subject | In vitro fertilization | en |
| dc.title | 利用馬卡夫模型分析台灣試管嬰兒補助政策的決策成本效益 | zh_TW |
| dc.title | Cost-Effectiveness Analysis of Taiwan’s IVF Subsidy Policy : A Markov Model Approach | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 113-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 陳祈玲;嚴明芳 | zh_TW |
| dc.contributor.oralexamcommittee | Chi-Ling Chen;Ming-Fang Yen | en |
| dc.subject.keyword | 試管嬰兒,補助政策,成本效益分析,馬可夫模型,胚胎植入前基因診斷,生育率, | zh_TW |
| dc.subject.keyword | In vitro fertilization,subsidy policy,cost-effectiveness analysis,Markov model,preimplantation genetic testing,fertility rate, | en |
| dc.relation.page | 44 | - |
| dc.identifier.doi | 10.6342/NTU202504315 | - |
| dc.rights.note | 同意授權(限校園內公開) | - |
| dc.date.accepted | 2025-08-08 | - |
| dc.contributor.author-college | 醫學院 | - |
| dc.contributor.author-dept | 臨床醫學研究所 | - |
| dc.date.embargo-lift | 2030-08-08 | - |
| 顯示於系所單位： | 臨床醫學研究所 | |
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