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請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/98322
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor吳舜文zh_TW
dc.contributor.advisorShun-Wen Wuen
dc.contributor.author周義發zh_TW
dc.contributor.authorYi Fa Zhouen
dc.date.accessioned2025-08-01T16:12:58Z-
dc.date.available2025-08-02-
dc.date.copyright2025-08-01-
dc.date.issued2025-
dc.date.submitted2025-07-29-
dc.identifier.citation參 考 文 獻
壹、中文部分
王曉琴、楊震、包城、郭松柏、許傳青,2025,〈基於SARIMA-LSTM模型的中國肺結核傳染病預測研究〉,《統計學與應用》,14(2), 8-21。
朱玉、夏結來、王靜,2009,〈單純ARIMA模型和ARIMA-GRNN組合模型在猩紅熱發病率中的預測效果比較〉,《中華流行病學雜誌》,30(9), 964-968。
朱星月、林騰飛、米源、胡明,2018,〈間斷時間序列模型及其在衛生政策干預效果評價中的應用〉,《中國藥事》,32(11), 1531-1540。https://doi.org/10.16153/j.1002-7777.2018.11.013
易力、余新華,2019,〈美國醫療器械唯一標識(UDI)系統實施進展〉,《中國醫藥導刊》,21(9), 511-515。
岳惠麗,2009,〈我國居民消費價格指數時間序列預測——基於ARIMA模型與平滑ARIMA模型的比較分析〉,《北方經貿》,8, 9-10。
馬愛霞、謝靜、唐文熙,2018,〈ARIMA模型、BP神經網路及其組合模型在衛生政策評估中的實證比較:以公立醫院價格改革為例〉,《中國衛生政策研究》,11(1), 76-83。
郭靜利、董渤,2019,〈基於SARIMA模型的國際稻米價格預測〉,《價格理論與實踐》,2019(1), 79-82。
張喜紅、李慧、曹文君、崔永梅,2018,〈SARIMA模型在長治市肺結核預測中的應用〉,《中國醫科大學學》,47(7), 585-588。
國家藥品監督管理局,2019,《醫療器械唯一標識系統規則》。取自:https://www.gov.cn/gongbao/content/2019/content_5462534.htm(最後流覽日期:2025年3月20日)
國家藥品監督管理局、國家衛生健康委、國家醫保局,2021,《國家藥監局 國家衛生健康委 國家醫保局關於做好第二批實施醫療器械唯一標識工作的公告(2021年第114號)》。取自:https://udi.nmpa.gov.cn/toDetail.html?infoId=63&CatalogId=2(最後流覽日期:2025年7月1日)
國家藥品監督管理局、國家衛生健康委、國家醫保局,2023,《国家药监局 国家卫生健康委 国家医保局关于做好第三批实施医疗器械唯一标识工作的公告(2023年第22号)》。取自:https://www.nmpa.gov.cn/ylqx/ylqxggtg/20230217152350198.html?type=pc&m=(最後流覽日期:2025年7月1日)
黃國寶、黎衍雲、吳菲、沈鑫、徐望紅,2020,〈ARIMA模型和ARIMA-SVM模型對上海市2型糖尿病患者肺結核發病的預測效果〉,《復旦大學學報(醫學版)》,47(6), 899-905。https://doi.org/10.3969/j.issn.1672-8467.2020.06.016
楊仁東、胡世雄、鄧志紅、羅塏煒、彭揚琴、孫振球、曾小敏,2016,〈湖南省手足口病發病趨勢SARIMA模型預測〉,《中國公共衛生》,32(1), 48-52。
賈志濤,2020,〈醫療器械唯一標識(UDI)系統實施探討——基於GS1標準的應用實踐〉,《中國醫藥導刊》,22(3), 201–210。
趙梅、劉維忠,2015,〈ARIMA和平滑ARIMA模型的中國棉花價格短期預測比較〉,《貴州農業科學》,43(11), 206-208。
鄭佳、易力、李靜莉,2018,〈美國醫療器械認可共識標準管理體系研究〉,《中國醫療器械雜誌》,42(2), 119-121, 132。
劉靚、郭媛媛、張文思、陳聰,2022,〈我國醫療器械唯一標識 (UDI) 應用分析與展望〉,《中國醫藥導刊》,24(9), 903–908。
盧鵬飛、須成傑、張敬誼、韓侶、李靜,2019,〈基於SARIMA-LSTM的門診量預測研究〉,《大數據》,5(6), 101-110。

貳、英文部分
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/98322-
dc.description.abstract為加強醫療器械的識別追蹤和上市後監管,美國食品和藥物管理局實施了唯一設備標識(Unique Device Identification,UDI)制度,以提升器械可追溯性和不良事件監測。然而,針對高風險植入式醫療器械的UDI政策效果尚缺乏實證評估。本研究以Mentor公司生產的MemoryGel乳房植入體(III類高風險醫療器械)為例,評估UDI實施對其不良事件報告趨勢的影響。我們提取了FDA不良事件資料庫(MAUDE)2010–2020年的報告資料,聚焦“受傷”類事件,採用中斷時間序列分析框架並結合SARIMA模型進行分析,將2014年10月設為干預時點。結果顯示,UDI實施後不良事件報告數出現顯著的立即增加:自2014年10月起,MemoryGel植入體相關“受傷”事件的月報告數躍升約116例(p<0.001)。此外,不良事件報告的長期趨勢由實施前的逐月緩升(約+0.95例/月)轉為實施後的逐月下降(約-0.85例/月),斜率淨變化約-1.80(p<0.001)。這些發現表明,UDI制度通過強化器械層級可追溯性,提高了不良事件報告的完整性和準確性。更重要的是,追溯能力的提升使監管者和製造商及時發現並糾正器械缺陷(如定向召回或技術改進),從源頭減少不良事件發生並提高患者安全。綜上,UDI政策顯著強化了高風險植入式醫療器械的可追溯性和上市後安全監測,為這一監管舉措的有效性提供了有力實證支援。zh_TW
dc.description.abstractMedical device-associated adverse events have raised serious patient safety concerns, prompting regulatory initiatives to improve device identification and tracking. The U.S. Food and Drug Administration (FDA) implemented the Unique Device Identification (UDI) system, which assigns a unique code to each medical device to enhance traceability and post-market surveillance. However, empirical evidence on UDI’s impact on safety outcomes for high-risk implantable devices remains limited.
This study provides an empirical evaluation of the UDI policy’s effect on adverse event reporting trends for a high-risk implantable medical device: the Mentor MemoryGel breast implant. Adverse event records from January 2010 through December 2020 were extracted from the FDA’s Manufacturer and User Facility Device Experience (MAUDE) database. We focused on reported patient injuries associated with this device and employed an interrupted time series design using a seasonal autoregressive integrated moving average (SARIMA) model. The analysis considered October 2014—when UDI compliance became mandatory for Class III devices—as the intervention time point.
Results indicate that UDI implementation was associated with a statistically significant immediate increase in adverse event reports. In particular, the monthly count of injury-related reports for MemoryGel breast implants jumped by approximately 116 cases immediately after UDI enforcement began (p < 0.001). Moreover, the long-term trend of adverse events reversed direction following UDI: prior to late 2014, monthly injury reports were gradually increasing (by about +0.95 per month), whereas after UDI implementation they showed a gradual decline (by about –0.85 per month). This change in slope (approximately –1.80 reports per month) was statistically significant (p < 0.001).
These findings suggest that the UDI system improved the completeness and accuracy of adverse event reporting by greatly enhancing device traceability, thereby strengthening post-market monitoring and early risk detection. More importantly, improved traceability enabled manufacturers and regulators to more rapidly identify and correct device defects (e.g., through targeted recalls or technical modifications), which likely contributed to a reduced incidence of adverse events over time and improved patient safety. In conclusion, the UDI policy has had a markedly positive impact on the traceability and safety monitoring of high-risk implantable medical devices, providing strong empirical support for this regulatory initiative and its important role in protecting public health.
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dc.description.tableofcontents口試委員會審定書 I
誌謝 II
摘要 III
ABSTRACT IV
目次 VI
圖次 VII
表次 VIII
第一章 前言 1
第一節 研究背景和研究動機 1
第二節 研究目的與研究問題 9
第二章 美國醫療器械標記法的歷史沿革及文獻綜述 11
第一節 美國醫療器械標記法案的歷史沿革 12
第二節 病人安全與醫療器械風險 26
第三節 MAUDE資料庫及醫療器械不良事件報告制度簡介 29
第四節 基於MAUDE資料庫的現有研究 36
第五節 UDI政策相關研究現狀 39
第六節 Mentor MemoryGel乳房植入體之臨床研究綜述與方法斷裂問題 43
第七節 小結 45
第三章 研究設計 47
第一節 研究假設 48
第二節 資料來源、時間範圍、研究目標選擇 49
第三節 中斷時間序列(ITS)方法與SARIMA建模 56
第四節 資料處理 73
第五節 SARIMA模型的構建 78
第四章 統計結果分析 87
第一節 描述性統計分析 87
第二節 ITS-SARIMA模型估計結果 90
第三節 模型診斷 94
第四節 內部效度分析 100
第五章 結論與建議 105
第一節 研究發現與政策意涵 105
第二節 研究限制與未來研究建議 112
參 考 文 獻 123
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dc.language.isozh_TW-
dc.subject可追溯性zh_TW
dc.subject中斷時間序列分析zh_TW
dc.subjectSARIMA模型zh_TW
dc.subject唯一設備標識zh_TW
dc.subject高風險植入式醫療器械zh_TW
dc.subjectMentor MemoryGel乳房植入體zh_TW
dc.subjectMAUDE資料庫zh_TW
dc.subjectMentor MemoryGel breast implanten
dc.subjectMAUDE databaseen
dc.subjectSeasonal autoregressive integrated moving average (SARIMA) modelen
dc.subjectInterrupted time series analysisen
dc.subjectTraceabilityen
dc.subjectHigh-risk implantable medical deviceen
dc.subjectUnique Device Identificationen
dc.titleUDI政策對高風險植入式醫療器械不良事件趨勢的影響zh_TW
dc.titleImpact of UDI Policy on the Trend of Adverse Events in High-Risk Implantable Devicesen
dc.typeThesis-
dc.date.schoolyear113-2-
dc.description.degree碩士-
dc.contributor.oralexamcommittee林澤民;李達宇zh_TW
dc.contributor.oralexamcommitteeTse-min Lin ;JOHN TAYU LEEen
dc.subject.keyword唯一設備標識,高風險植入式醫療器械,可追溯性,中斷時間序列分析,SARIMA模型,MAUDE資料庫,Mentor MemoryGel乳房植入體,zh_TW
dc.subject.keywordUnique Device Identification,High-risk implantable medical device,Traceability,Interrupted time series analysis,Seasonal autoregressive integrated moving average (SARIMA) model,MAUDE database,Mentor MemoryGel breast implant,en
dc.relation.page141-
dc.identifier.doi10.6342/NTU202502575-
dc.rights.note同意授權(全球公開)-
dc.date.accepted2025-07-30-
dc.contributor.author-college社會科學院-
dc.contributor.author-dept公共事務研究所-
dc.date.embargo-lift2025-08-02-
顯示於系所單位:公共事務研究所

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