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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 余峻瑜 | zh_TW |
| dc.contributor.advisor | Jiun-Yu Yu | en |
| dc.contributor.author | 卓俐伶 | zh_TW |
| dc.contributor.author | Li-Ling Cho | en |
| dc.date.accessioned | 2025-09-17T16:23:02Z | - |
| dc.date.available | 2025-09-18 | - |
| dc.date.copyright | 2025-09-17 | - |
| dc.date.issued | 2025 | - |
| dc.date.submitted | 2025-08-06 | - |
| dc.identifier.citation | 參考文獻
英文文獻 Alvin Rajkomar 1, Eyal Oren1, Kai Chen1, Andrew M. Dai1, Nissan Hajaj1, Michaela Hardt1, Peter J. Liu1, Xiaobing Liu1, Jake Marcus1,, Mimi Sun1, P. S., Hector Yee1, Kun Zhang1, Yi Zhang1, Gerardo Flores1, Gavin E. Duggan1, Jamie Irvine1, Quoc Le1,, Kurt Litsch1, A. M., Justin Tansuwan1, De Wang1, James Wexler1, Jimbo Wilson1, Dana Ludwig2, Samuel L. Volchenboum3,, Katherine Chou1, M. P., Srinivasan Madabushi1, Nigam H. Shah4, Atul J. Butte2, Michael D. Howell1, Claire Cui1,, & Dean1, G. S. C. a. J. (2018). Scalable and accurate deep learning with electronic health records. Digital Medicine. https://doi.org/10.1038/s41746-018-0029-1 American Well Corporation. (2024). Investor Presentation Q4 2023. https://investors.amwell.com/ Australian Digital Health Agency. (2020). National Digital Health Strategy (2020–2025). Retrieved 5/31 from https://www.digitalhealth.gov.au Campbell, D. (2024, 2024/01/09). NHS cannot embrace AI until its basic IT systems are up to scratch. The Guardian. https://www.theguardian.com/society/2024/sep/15/nhs-cannot-embrace-ai-until-its-basic-it-systems-are-up-to-scratch Care, I. (2025). IC Care 官方網站與服務說明. Retrieved 2025 from https://www.iccare.tw/ Christine Ritchie, B. L., Naomi Gallopyn, Charles Pu,Orla Sheehan, . (2021). Medical Care at Home Comes of Age. eRx Script Exchange. (2025). eRx Script Exchange Retrieved 5/31 from EUCARE. (2024). 描述其與診所系統整合、用戶端介面與遠距處方功能強調「診所數位化協作平台」定位 . Retrieved 5/31 from https://www.eucare.tw/news_20240612.html Marie Wosny, L. M. S., Janna Hastings. (2023). Experience of health care professionals using digital tools in hospitals: A qualitative systematic review. Journal of Medical Internet Research, 25, e48519. https://doi.org/10.2196/50357 Michael E. Porter. (2019). Value-Based Health Care Delivery: Core Concepts. In. My Health Record. (2025). My Health Record For everyone. Retrieved 5/31 from https://www.myhealthrecord.gov.au Nicola Rieke 1, Jonny Hancox3, Wenqi Li 4, Fausto Milletarì1, Holger R. Roth 5, Shadi Albarqouni 2,6, Spyridon Bakas7,, & Mathieu N. Galtier8, B. A. L., Klaus Maier-Hein 10,11, Sébastien Ourselin12, Micah Sheller13, Ronald M. Summers Andrew Trask15,16,17, Daguang Xu5, Maximilian Baust1 and M. Jorge Cardoso. (2020). The future of digital health with federated learning. Digital Medicine Nurses, I. C. o. (2025). INTERNATIONAL NURSES DAY 2025 Caring for nurses strengthens economies. Sascha Kraus, F. S., Anna Pluzhnikova & Anna Chiara Invernizzi. (2021). Digital transformation in healthcare: Analyzing the current state-of-research. Journal of Business Research, 123, 557–567. https://doi.org/10.1016/j.jbusres.2020.10.030 Teladoc Health. (2025). About us. Retrieved 5/31 from https://www.teladochealth.com/about WHO世界衛生組織. (2025). Nursing workforce grows, but inequities threaten global health goals. Retrieved 5/31 from https://www.who.int/news/item/12-05-2025-nursing-workforce-grows--but-inequities-threaten-global-health-goals?utm_source=chatgpt.com 中文文獻 日本厚生労働省. (2025). 【オンライン資格確認・電子処方箋】概要をわかりやすく解説します!. Retrieved 5/31 from https://www.mhlw.go.jp/stf/denshishohousen.html#2 立法院. (2023). 衛生福利部(不含社會福利部分)、疾病管制署、中央健康保險署、國家中醫藥研究所113年度單位預算評估報告. https://www.ly.gov.tw/Pages/Detail.aspx?nodeid=46463&pid=232818&utm_source 國家發展委員會. (2025). 台灣人口推估查詢系統. Retrieved 5/21 from https://pop-proj.ndc.gov.tw/Custom_Detail_Statistics_Search.aspx?n=39&_Query=8c0fb2d2-fd85-4138-b4ba-2927cc815e97 瑞竣科技. (2020). 急救地圖. Retrieved 5/31 from https://map.richitech.com.tw/MedicalEmergency/?fbclid=IwQ0xDSwKnV-tleHRuA2FlbQIxMQABHjgNm6VquFD5lyxvNaPYdlnisQ_fapjr8ZxqrNrKMB4Cb9ICfGA30D2xse1p_aem_n4LNyph14zghtROB9x_tYA 衛生福利部. (2019). 108年醫院護理服務量調查結果. 衛生福利部. (2024a). 111年老人狀況調查報告. Retrieved from https://dep.mohw.gov.tw/DOS/cp-5095-77509-113.html 衛生福利部. (2024b). 113年醫院護理服務量調查結果. 衛生福利部. (2024c). 平均健康餘命與死亡率. Retrieved from https://dep.mohw.gov.tw/DOS/cp-5083-55378-113.html 衛生福利部. (2024d). 健康平均餘命指標資料表. Retrieved from https://dep.mohw.gov.tw/DOS/lp-5082-113.html 衛生福利部中央健康保險署. (2024a). 台灣遠距醫療的推動與展望. 衛生福利部中央健康保險署. (2024b). 衛福部《通訊診察治療辦法》修正條文(2024年). Retrieved 5/31 from https://www.mohw.gov.tw/cp-16-77322-1.html WHO世界衛生組織. (2000). The world health report 2000. https://www.who.int/publications/i/item/924156198X | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/99689 | - |
| dc.description.abstract | 本研究聚焦於台灣高齡化社會下,醫療資源失衡與人力短缺挑戰所引發之照護轉型需求,針對在宅急症(Hospital-at-Home)與居家醫療服務進行制度盤點與流程優化探討。透過質性研究方法,訪談十三家不同類型之醫療與照護機構,彙整服務流程與管理瓶頸,並運用服務藍圖與營運構面分析,系統性描繪現行制度下的斷點與潛在改善方向。
研究首先指出,現有政策與制度設計中,病患接觸遠距或在宅照護之服務節點過於片段,缺乏一致化的收案條件與資訊整合機制,導致流程協作困難與醫療人力負荷沉重。在照護執行階段,機構普遍面臨 IoT 設備效能不穩、照護人力調度困難、緊急應變責任歸屬不清等問題,進一步降低整體服務可近性與持續性。研究亦發現多數機構對生成式 AI 在風險預測與病況整合上的應用潛力抱持高度期待,惟實務導入仍受限於法規與系統架構。 本研究提出五項研究建議:其一,於收案初期導入智能輔助工具,提升跨單位協作與資源導向;其二,建立以病人為中心之資訊整合與授權機制,強化照護透明度與可近性;其三,推動區域型支援網絡與互助制度,減緩單一機構人力壓力;在照護過程中逐步發展風險感知與預警機制;其五,透過政策誘因鼓勵科技業者參與醫療照護數位轉型,形成制度與產業的雙向推動。期望本研究之流程分析與制度建議,能為未來遠距照護政策與在宅急症制度提供具體、可行且病患導向之改進基礎。 | zh_TW |
| dc.description.abstract | This study focuses on the urgent need for healthcare transformation in Taiwan amid an aging society, where imbalances in medical resource distribution and workforce shortages are becoming increasingly prominent. It investigates the current institutional frameworks and process optimization opportunities for Hospital-at-Home (HAH) and home-based medical services. Utilizing qualitative research methods, the study conducted interviews with thirteen diverse healthcare and care organizations, compiled service processes and operational challenges, and systematically visualized existing service gaps and potential improvements through service blueprints and operational framework analysis.
The findings reveal that under the current policy and institutional design, patient access points to remote and home-based care are fragmented, lacking standardized intake criteria and integrated information systems. These issues result in collaboration inefficiencies and increased burdens on medical personnel. During the care delivery phase, organizations commonly face challenges such as unstable performance of IoT devices, staffing difficulties, and unclear responsibilities in emergency responses, all of which hinder service accessibility and continuity. Furthermore, many institutions express high expectations for the potential of generative AI in risk prediction and clinical data integration, although practical implementation remains constrained by regulatory and system limitations. The study offers five key recommendations: (1) introduce intelligent support tools at the intake stage to enhance cross-institutional coordination and resource alignment; (2) establish patient-centered information integration and authorization mechanisms to improve care transparency and accessibility; (3) promote the development of regional support networks and collaborative assistance systems to alleviate the manpower burden on individual institutions; (4) gradually develop risk-sensing and early warning mechanisms throughout the care process; and (5) implement policy incentives to encourage participation from the tech industry in the digital transformation of healthcare services. This study aims to provide concrete, feasible, and patient-oriented strategies for improving future remote care policies and HAH systems. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2025-09-17T16:23:02Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2025-09-17T16:23:02Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | 目 次
口試委員會審定書……………………………………………………………………i 誌謝………………………………………………………………………………… ii 中文摘要…………………………………………………………………………… iii 英文摘要…………………………………………………………………………… iv 目次………………………………………………………………………………… v 圖次………………………………………………………………………………… vii 表次………………………………………………………………………………… viii 第一章 緒論 1 1.1研究背景 1 1.1.1台灣人口老化加速推升高齡者照護需求 1 1.1.2國人不健康平均餘命為7.41年 4 1.1.3台灣醫療資源配置不均及醫護短缺問題 5 1.1.4後疫情時期政策與社會氛圍階對遠距醫療接受度上升 7 1.2研究動機 8 1.2.1台灣醫療與照護體系有迫切轉型需求 8 1.2.2現有政策之服務尚有價值延伸可能性 8 1.2.3台灣居家醫療/照護服務缺乏使用者中心之盤點 8 1.3研究問題與目的 8 第二章 文獻探討 10 2.1價值導向照護與整合照護模型演進 10 2.2在宅/居家照護與遠距照護的定義與分類 11 2.2.1數位健康(Digital Health)的範疇與定義 11 2.2.2在宅/居家照護定義與分類 12 2.3台灣遠距與在宅/居家照護現況 13 2.3.2通訊診療與健保政策演進 14 2.3.3健保支付制度從論量計酬走向價值導向的轉型趨勢 15 2.3.4數位導入的商業模式隨政策逐漸多元 16 2.4國際相關政策 17 2.4.1美國、英國、德國與日本在保險給付與政策開放度上相對領先 17 2.4.2政府主導數位化平台服務 20 2.4.3新型態遠距醫療商業模式 21 2.5醫療與健康產業數位發展與限制 21 2.5.1醫療產業數位化落後 21 2.5.2多元利害關係人影響系統運作 22 2.5.3資料治理與人工智慧技術提升評估模型效率 23 2.6 服務藍圖與營務構面 24 2.6.1服務藍圖與流程分析 24 2.6.2服務營運管理四構面 24 第三章 研究方法 25 3.1研究設計 25 3.2資料來源與對象 25 3.3半結構式訪談大綱 26 3.4分析方法 28 3.4.1次級資料分析 28 3.4.2開放式編碼 28 3.4.3服務藍圖繪製與主題整合 29 第四章 研究結果與分析 30 4.1遠距/居家/在宅醫療服務現況 30 4.1.1各照護計畫執行現況與角色與參與現況 30 4.1.2醫療歷程與病患型態 31 4.1.2遠距醫療、居家醫療與在宅急症的相似性 32 4.2 服務營運構面與管理議題 33 4.2.1提供的服務:服務推動與照護連續性 33 4.2.2顧客管理制度:病例資訊可近性與民眾認知落差 34 4.2.3員工管理制度:制度推行方式與人力負荷的雙重挑戰 35 4.2.4資金供應機制:給付制度與資源投入的不對稱 36 4.2.5 初級編碼分析小結與整體回饋 38 4.3服務藍圖與服務斷點 39 4.3.1 照護啟動階段:前期佈局與民眾認知推動 42 4.3.2 評估與收案規劃階段:標準分歧與系統斷裂 42 4.3.3 照護執行與緊急應變:人力與設備資源雙重壓力 42 4.3.4結案轉銜:制度斷層與追蹤中斷 42 4.4技術導入與人機協作現況與展望 45 4.4.1 IoT設備與檢測技術導入 45 4.4.2 資訊同步與跨單位協作需求 45 4.4.3生成式 AI 與人機協作潛力 46 4.4.4技術應用情境 47 4.5 小結 48 第五章 結論與建議 50 5.1研究建議 50 5.2研究限制 52 5.3未來研究方向 52 附錄 54 附錄一:各機構服務藍圖 54 參考文獻 59 | - |
| dc.language.iso | zh_TW | - |
| dc.subject | 遠距照護 | zh_TW |
| dc.subject | 在宅急症 | zh_TW |
| dc.subject | 居家醫療 | zh_TW |
| dc.subject | 服務流程優化 | zh_TW |
| dc.subject | 科技導入 | zh_TW |
| dc.subject | Technology Adoption | en |
| dc.subject | Telecare | en |
| dc.subject | Acute Care at Home | en |
| dc.subject | Home-based Medical Services | en |
| dc.subject | Service Process Optimization | en |
| dc.title | 在宅急症與居家醫療之服務流程改善與科技導入探討 | zh_TW |
| dc.title | Exploring Service Process Improvement and Technological Integration in Hospital-at-Home and Home-Based Medical Care | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 113-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.coadvisor | 胡凱焜 | zh_TW |
| dc.contributor.coadvisor | Kae-Kuen Hu | en |
| dc.contributor.oralexamcommittee | 曾智揚;潘令妍 | zh_TW |
| dc.contributor.oralexamcommittee | Chih-Yang Tseng;Ling-Yen Pan | en |
| dc.subject.keyword | 遠距照護,在宅急症,居家醫療,服務流程優化,科技導入, | zh_TW |
| dc.subject.keyword | Telecare,Acute Care at Home,Home-based Medical Services,Service Process Optimization,Technology Adoption, | en |
| dc.relation.page | 61 | - |
| dc.identifier.doi | 10.6342/NTU202502640 | - |
| dc.rights.note | 同意授權(限校園內公開) | - |
| dc.date.accepted | 2025-08-10 | - |
| dc.contributor.author-college | 進修推廣學院 | - |
| dc.contributor.author-dept | 生物科技管理碩士在職學位學程 | - |
| dc.date.embargo-lift | 2027-12-27 | - |
| 顯示於系所單位: | 生物科技管理碩士在職學位學程 | |
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