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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 唐嘉君(Chia-Chun Tang) | |
dc.contributor.advisor | 唐嘉君(Chia-Chun Tang | chiatang@ntu.edu.tw | ), | |
dc.contributor.author | Chieh-Han Su | en |
dc.contributor.author | 蘇婕涵 | zh_TW |
dc.date.accessioned | 2023-03-19T22:07:21Z | - |
dc.date.copyright | 2022-10-17 | |
dc.date.issued | 2022 | |
dc.date.submitted | 2022-09-26 | |
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J., Gupta, A., Khera, R., Ahmad, T., Desai, N. R., ... & Krumholz, H. M. (2020). Machine learning prediction of mortality and hospitalization in heart failure with preserved ejection fraction. JACC: Heart Failure, 8(1), 12-21. http://doi.org/10.1016/j.jchf.2019.06.013 Aslakson, R. A., Reinke, L. F., Cox, C., Kross, E. K., Benzo, R. P., & Curtis, J. R. (2017).Developing a research agenda for integrating palliative care into critical care and pulmonary practice to improve patient and family outcomes. Journal of palliative medicine, 20(4),329-343. https://doi.org/10.1089/jpm.2016.0567 Carson, S. S., Kahn, J. M., Hough, C. L., Seeley, E. J., White, D. B., Douglas, I. S., ... & Rubenfeld, G. D. (2012). A multicenter mortality prediction model for patients receiving prolonged mechanical ventilation. Critical care medicine, 40(4), 1171. http://doi.org/10.1097/ CCM.0b013e3182387d43 Evans, L., Rhodes, A., Alhazzani, W., Antonelli, M., Coopersmith, C. M., French, C., ... & Levy, M. (2021). 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Journal of Critical Care, 35, 7-11. https://doi.org/10.1016/j.jcrc.2016.04.010 Hapca, S., Guthrie, B., Cvoro, V., Bu, F., Rutherford, A. C., Reynish, E., & Donnan, P. T. (2018). Mortality in people with dementia, delirium, and unspecified cognitive impairment in the general hospital: prospective cohort study of 6,724 patients with 2 years follow-up. Clinical epidemiology, 10, 1743. http://doi.org/ 10.2147/CLEP.S174807 Heidenreich, P. A., Bozkurt, B., Aguilar, D., Allen, L. A., Byun, J. J., Colvin, M. M., ... & Yancy, C. W. (2022). 2022 AHA/ACC/HFSA guideline for the management of heart failure: A report of the American college of cardiology/American heart association joint committee on clinical practice guidelines. Journal of the American College of Cardiology, 79(17), e263-e421. https://doi.org/10.1016/j.cardfail.2022.02.009 Huynh, T. N., Kleerup, E. C., Wiley, J. F., Savitsky, T. D., Guse, D., Garber, B. J., & Wenger, N. S. (2013). 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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/84264 | - |
dc.description.abstract | 安寧緩和醫療近年來獲得國內外眾多關注,從管理階層、醫護專業人員至一般民眾,均自不同角度,認知到安寧緩和醫療之功能與需求。世界衛生組織等更呼籲:提供生命末期病人安寧緩和醫療,是種人權展現;此觀點亦回應我國20餘年來持續推動安寧之核心理念。然而,安寧緩和醫療雖獲得廣泛注意,如何精準預測急重症加護病房族群之安寧需求,並及時提供協助,仍是極大的挑戰。加護病房族群因為病況複雜、時間緊迫、病況進展多變、以及傳統戰勝死亡的信念,限縮了安寧緩和醫療在加護病房的角色。直至今日,許多在加護病房之末期病人仍被迫接受不合適的侵入性治療,最終卻無法延長壽命,亦無法提升末期生活品質;家屬煎熬,醫護人員也因此承受莫大壓力及決策困境。了解國內加護單位安寧緩和醫療現況及發展安寧緩和醫療需求預測指標或工具可解決上述難題,促進醫護團隊間或與病人及家屬共識,進而提升末期生活品質。目的:本研究之目的在於藉由分析大型醫學中心成人加護病房病人去識別化資料庫,了解影響重症末期加護病房病人安寧緩和醫療需求之因素。細究研究目的包括:了解影響加護病房生命末期病人使用安寧緩和醫療之因素、識別加護病房病人之安寧緩和醫療需求預測因子並建立預測模型、及驗證目標二所建立之安寧緩和醫療需求預測模型。研究方式:本研究為觀察性預測式研究(prediction research),著重預測模型之建立與外部驗證(model development with external validation)。研究進行分為兩階段,第一階段探查現況,第二階段建立預測模型及驗證。兩階段於2020後半年,自臺大醫院成人加護病房病人去識別化資料庫選取六到十月之個案進行分析。運用描述性統計、獨立樣本t檢定及羅吉斯迴歸以回答三個研究目的。結果:本研究共分析1914筆資料,現況顯示,加護病房30天後死亡率為10.5%,此群體中77.4%有使用安寧緩和醫療資源,剩下約五分之一亟需安寧緩和醫療者並未接受相關資源;影響安寧緩和醫療使用之因子,包含臨床生理指標與病人背景狀態。預測模型顯示,APACHE III分數、感染狀態、癌症病史、加護病房住院期間是否發生譫妄,以及入加護病房前是否經歷免疫抑制治療共同解釋是否使用安寧緩和醫療資源37.7%之變異性,並可成功分類88.9%的個案。另一方面,APACHE III分數、加護病房住院期是否發生譫妄、入加護病房前是否經歷免疫抑制治療,心血管病史以及入加護病房前臨床虛弱程度共同可解釋是否具安寧緩和醫療資源需求35.4%變異性,並可成功分類94.6%的個案。討論與結論:本研究為少數國內加護病房安寧緩和醫療資料庫分析,識別實際成人加護病房病人使用安寧緩和醫療資源之預測因子,也歸納出影響同一群病人安寧緩和醫療需求之預測因子。上述安寧緩和醫療資源使用與具安寧緩和醫療需求之病人應為高度重疊之族群,但卻發現有急迫安寧緩和醫療資源需求之病人,不見得即時接收到相關資源;對安寧緩和醫療資源使用與安寧緩和醫療需求兩群人之預測因子也不盡相同。上述結果反映,國內加護病房急需討論並調整安寧資源啟動與分配之判斷,以期更準確地回應重症病人安寧緩和醫療之需求。 | zh_TW |
dc.description.abstract | Background: Palliative care has continuously received a lot of attention from different groups, including policy maker, medical professions, and the general public. The World Health Organization has stressed that palliative care is essential to human dignity and is a human right. However, it remains challenging to accurately predict the palliative needs in the intensive care units (ICU) and offer timely palliative care. The application of palliative care was limited in ICUs because of complex factors, such as time constraints, unpredictable disease progression and end of life, and traditional treatment goal of cure. Evidence has shown that many patients in ICU received inappropriate invasive treatments, which negatively affected quality of end of life rather than prolonged life. Fail to introduce palliative care in ICU thus contribute to patients’ poor outcomes, families’ suffering, and medical staffs’ enormous pressure. To remedy aforementioned gaps, investigating palliative care needs and their predictors may be a good strategy. Objective: The purpose of this study was to identify the needs and predictors of palliative care in ICU by analyzing a database of adult ICU patients in Taiwan. Method: This research is an observational prediction research, with into two stages. The first stage was to investigate the utilization of palliative care resources by using the data recorded between June and July, 2020. The second stage was to establish the prediction model of palliative care needs by analyzing data recorded between June to October. Descriptive statistics, independent t-test and logistic regression were used to analyze the data. Results: A total of 1,914 data were analyzed. The mortality rate after 30 days of ICU admission was 10.5%, of which 77.4% accessed to the resources of palliative care. That is, 22.6% of the patients who had urgent need of palliative care did not receive appropriate resources. Clinical physiological indicators and patient background status significantly affect the use of palliative care resources. Predictive model showed that APACHE III score, infection status, cancer history, delirium status during ICU stay, and immunosuppressive treatment prior to ICU admission together explained 37.7% of the variability in palliative care use and could be successfully classified 88.9% of cases. On the other hand, APACHE III score, delirium status during ICU stay, immunosuppressive treatment prior to ICU admission, heart failure history, and clinical frailty scale together explained 35.4% of the variability in the urgent needs of palliative care, and can successfully classify 94.6% of the cases. Conclusions: This study identified predictors of palliative care utilization of adult ICU patients and also identified predictors of palliative care needs in. While the predictors of palliative resource use and the predictors of palliative needs should be highly overlapped, the results suggested gaps. ICU patients with urgent needs of palliative care may not receive relevant information timely. It is important for future studies to design and test strategies that can facilitate the identification of palliative care needs and proper allocation of palliative care resources in ICUs. | en |
dc.description.provenance | Made available in DSpace on 2023-03-19T22:07:21Z (GMT). No. of bitstreams: 1 U0001-2509202213383000.pdf: 1852942 bytes, checksum: bd05d5774e2e9c86180c600379eea184 (MD5) Previous issue date: 2022 | en |
dc.description.tableofcontents | 口試委員審定書 i 致謝 ii 中文摘要 iii 英文摘要 v 目錄 viii 圖目錄 x 表目錄 xi 第一章 緒論 1 第一節 研究背景與動機 1 第二節 研究目的 2 第二章 文獻查證 3 第一節 名詞定義 3 第二節 安寧緩和醫療之概念及推動 4 第三節 台灣安寧緩和醫療現況 6 第三章 研究設計與方法 9 第一節 研究架構 9 第二節 研究設計 10 第三節 研究對象 11 第四節 研究假說 11 第五節 研究倫理 11 第六節 資料處理與分析 12 第四章 研究結果 14 第一節 收案流程 14 第二節 加護病房病人屬性 15 第三節 加護病人使用安寧緩和醫療資源差異 33 第四節 全體加護病人屬性 34 第五節 全體加護病人使用安寧緩和醫療資源差異 53 第六節 加護病房病人安寧緩和醫療資源使用因素分析 54 第七節 建立亟具安寧緩和醫療資源需求模型 55 第五章 討論 57 第六章 結論與建議 61 第七章 參考文獻 62 | |
dc.language.iso | zh-TW | |
dc.title | 成人加護病房安寧緩和醫療使用現況及需求因素預測分析 | zh_TW |
dc.title | An Analysis of Current Palliative State and Predict factors in Adult Intensive Care Unit | en |
dc.type | Thesis | |
dc.date.schoolyear | 110-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 葉育彰(Yu-Chang Yeh),蔡兆勳(Jaw-Shiun Tsai) | |
dc.subject.keyword | 加護病房安寧緩和醫療,安寧緩和醫療需求,預測模型, | zh_TW |
dc.subject.keyword | palliative care in ICU,palliative needs,prediction model, | en |
dc.relation.page | 67 | |
dc.identifier.doi | 10.6342/NTU202204001 | |
dc.rights.note | 同意授權(限校園內公開) | |
dc.date.accepted | 2022-09-27 | |
dc.contributor.author-college | 醫學院 | zh_TW |
dc.contributor.author-dept | 護理學研究所 | zh_TW |
dc.date.embargo-lift | 2022-10-17 | - |
顯示於系所單位: | 護理學系所 |
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