請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/21854
完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 余峻瑜 | |
dc.contributor.author | Chien-Kun Ting | en |
dc.contributor.author | 丁乾坤 | zh_TW |
dc.date.accessioned | 2021-06-08T03:49:51Z | - |
dc.date.copyright | 2021-01-05 | |
dc.date.issued | 2020 | |
dc.date.submitted | 2020-12-24 | |
dc.identifier.citation | 參考文獻 一、中文部分 王延章、郭崇慧、葉鑫著(2010)。管理決策方法:問題、模型與決策.清華大學出版社。 李俊德、韓復華(2004)。以限制規劃法求解全年無休人員排班問題之研究─以護理人員排班為例。交通大學運輸與物流管理學系學位論文 林吉仁(2014)。作業研究 第二章 線性規劃。高立圖書公司出版。 侯文哲(2002)。護理人員排班資訊系統之建立與探討。成功大學工業管理科學系學位論文。 馬士華、林勇(2015)。企業生產與物流管理(第2版)。清華大學出版社。 黃光明(1972)。作業研究之七:更換問題。科學月刊 期號:0035發行日期:1972、11。 張政、謝曉嵐、耿娜(2012)。多目標優化下的手術室分派調度問題。上海交通大學學報 2012年12期。 潘定瓊(2011)。手術室護理不安全因素的調查分析及防範措施。基層醫學論壇》 2011年20期。 聶玲(2018)。不確定環境下的機器調度問題研究。財經錢線文化有限公司。 臺灣麻醉醫學會網站 臺灣麻醉護理學會網站 臺北榮民總醫院網站 臺北榮總手術室管理委員會 臺北榮總麻醉部 二、英文部分 Aickelin, U. and P. White (2004).Building better nurse scheduling algorithms. Annals of Operations Research, 128, 159–177. Bechtold, S. L. Jacobs (1996). The equivalence of general set covering and implicit integer programming formulations for shift scheduling. Naval Research Logistics, 43(2), 233–249. Bertsekas, Dimitri, P.(1999). Nonlinear Programming Second. Cambridge, MA.: Athena Scientific. Boyd, S. Vandenberghe, L.(2004). Convex Optimization.Cambridge University Press. Chen, J.-G. T. Yeung (1992). Development of a hybrid expert system for Nurse shift scheduling. Journal of Industrial Ergonomics, 9(4), 315–328. Cheng, B., J. Lee J. Wu. (1997). A nurse rostering system using constraint programming and redundant modeling. IEEE Transactions on Information Technology in Biomedicine, 1(1), 44–54. Cortes, C. Vapnik, V.(1995). Support-vector networks. Machine Learning. 20 (3): 273–297. Dowsland, K. A. J. M. Thompson (2000).Solving a nurse scheduling problem with knapsacks, networks and tabu search. Journal of the Operational Research Society, 51, 825–833. Eastaway, R.,Wyndham, J. Rice, T.(2000). Why Do Buses Come in Threes?: The Hidden Mathematics of Everyday Life. Wiley Ernst, A. T., H. Jiang, M. Krishnamoorthy, D. Sier (2004).Staff scheduling and rostering: A review of applications, methods and models. European Journal of Operational Research, 153(1), 3–27. Ferone, Gruler, Festa, Juan (2016). COMBINING SIMULATION WITH A GRASP METAHEURISTIC FOR SOLVING THE PERMUTATION FLOW-SHOP PROBLEM WITH STOCHASTIC PROCESSING TIMES.Proceedings of the 2016 Winter Simulation Conference. Frank, Budnick, Dennis,M. Richard, M.(2003).Principles of Operations Research for Management 300–353. Gong, CS., Yu, L., Ting, CK., Tsou, MY., Chang, KY., Shen, CL. Lin, SP. Predicting postoperative vomiting for orthopedic patients receiving patient-controlled epidural analgesia with the application of an artificial neural network.Biomed Res Int. 2014;2014:786418. Hentrich, M. (2015).Methodology and Coronary Artery Disease Cure. Ignatov, D.,Yu. Filippov, A.N.,Ignatov, A.D. Zhang, X.(2016) Automatic Analysis, Decomposition and Parallel Optimization of Large Homogeneous Networks. Proc.ISP RAS., 28 (6): 141–152. Isken, M. (2004). An implicit tour scheduling model with applications in healthcare. Annals of Operations Research, 128, 91–109. Isken, M. W. W. Hancock (1991). A heuristic approach to Nurse scheduling in hospital units with non-stationary, urgent demand, and a fixed staff size. Journal of the Society for Health Systems, 2(2), 24–41. Jaumard, B., F. Semet T. Vovor (1998). A generalized linear programming model for nurse scheduling. European Journal of Operational Research, 107(1), 1–18. Juan, A. A., Barrios, B. B., Vallada, E., Riera, D., Jorba, J. (2014). A simheuristic algorithm for solving the permutation flow shop problem with stochastic processing times. Simulation Modelling Practice and Theory, 46, 101–117. Kostreva, M. K. Jennings (1991). Nurse scheduling on a microcomputer. Computers and Operations Research, 18, 731–739. Lewis, C.(2012). Chapter 1: Demand forecasting and inventory control. Routledge p. 3–20. Liou, JY., Ting, CK., Hou, MC. Tsou, MY.(2016). A Response Surface Model Exploration of Dosing Strategies in Gastrointestinal Endoscopies Using Midazolam and Opioids.Medicine (Baltimore). 95(23):e3520. Millar H. and M. Kiragu (1998). Cyclic and non-cyclic scheduling of 12 h shift nurses by network programming.European Journal of Operational Research, 104(3), 582–592. Rosenbloom, E. S. and N. F. Goertzen (1987).Cyclic Nurse scheduling. European Journal of Operational Research, 31, 19–23. Sanada A.(2017). Network partition for optimization Schlechter, Kira.(2009) Hershey Medical Center to open redesigned emergency room. The Patriot-News. March 2, 2009. Sokolowski, J.A. Banks, C.M. (2009). Principles of Modeling and Simulation. Hoboken, NJ: Wiley. p. 6. Ting, CK.(2019).Drug interaction is the cornerstone of modern anesthesia practice. Minerva Anestesiol. 85(3):223-225. Ting, CK., Johnson, KB., Teng, WN., Synoid, ND., Lapierre, C., Yu, L. Westenskow, DR.(2014).Response surface model predictions of wake-up time during scoliosis surgery.Anesth Analg. 118(3):546-53. Winston, Wayne Goldberg, Jeffrey. (2004). Operations research: applications and algorithms. Wu, HY., Gong, CA., Lin, SP., Chang, KY., Tsou, MY. Ting, CK.(2016). Predicting postoperative vomiting among orthopedic patients receiving patient-controlled epidural analgesia using SVM and LR. Sci Rep. 2016 Jun 1;6:27041. What is O.R.? INFORMS.org Retrieved 7 January 2020 Operations research (industrial engineering) : History – Britannica Online Encyclopedia. Britannica.com. Retrieved 13 November 2019. Definition of ALGORITHM. Merriam-Webster Online Dictionary. Archived from the original on February 14, 2020. Al-Khwarizmi - Islamic Mathematics. The Story of Mathematics. Archived from the original on July 25, 2019. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/21854 | - |
dc.description.abstract | 在過去的幾十年中,醫院的成本壓力急劇增加。這強調成本控制迫使醫院管理階層不得不以更業務導向的方式來營運。為了要達到以降低的成本來提供高質量的服務。作業研究被廣泛的應用在醫療照護產業,藉此來消除資源的低效利用。手術室被認為是帶動醫院發展的主要引擎,一個普遍問題是醫護人員每天(甚至每小時)的工作量壓力變化很大,高峰時工作人員難以應付負荷,低潮時工作量太低有巨大的成本浪費。在臺北榮總麻醉部工作的麻醉護理師們常常因為手術麻醉的時間不確定而工作到很晚的時間,造成護理質量下降,病患安全有疑慮而院方也必須付出更多人力成本。 本研究的目的是為了探索在這個過程中院方管理上所面對的挑戰與策略作為,如何透過護理師輪班班別的改變及作業研究技術來協助實現這一目標,達到多贏的目標。由於護理服務在整個醫院療服務中佔有十分重要的地位,透過合理的排班系統可以保證護理品質、並改善護理師的身心健康與生活品質、本研究透過作業研究的最佳化模型來評估如何減少麻醉護理師的工作時間和減少超出計劃的加班時間,並採取積極措施來減少資源浪費,包括最適有效的員工分配和適當班別安排,通過大量的計算實驗,我們提供了節省成本的機會和所需解決時間的想法。利用這種模型的擴展來獲得最佳化的護理排班,可以提供解決護士調度問題的方法。 本研究應用了臺北榮民總醫院麻醉部的實際個案,根據實際個案可以真實呈現所面對的巨大挑戰,結合相關的排班策略、最佳化模式、資料數據分析、因應差異性與特殊性,同時面對院方、外科、開刀房以及麻醉課題,由於環境的不同潛蕆著很大的風險,透過研究資料蒐集歸納分析,進一步探討相關議題,找到最佳的致勝方針,提供實際的策略思維及變革行動,在研究過程中也產生了許多實用的研究結論,同時也驗證了作業研究的實用性,期望這些研究成果可以提供給臺灣以及全世界的麻醉及手術室做為護理師排班的參考。 | zh_TW |
dc.description.abstract | Over the past decades, cost pressures on hospitals have increased dramatically. This emphasis on cost control forces hospital management to operate in a more business-oriented manner. In order to achieve high quality services with a reduced cost, operations research is widely applied in the healthcare industry to eliminate inefficient use of resources. The operating room is considered to be the main engine driving the development of the hospital. A common problem is that the workload of medical staff varies greatly every day (or even every hour). It is difficult for staff to cope with the load at peak times, and the workload is too low at low tide, which has huge costs. waste. Nurse Anesthetist who work at the Taipei Rong General Hospital often work late due to the uncertain timing of surgical anesthesia, resulting in a decline in the quality of care, patient safety concerns and the hospital's need to pay more labor costs. The purpose of this research is to explore the challenges and strategies faced by hospital management in this process, and how to help achieve this goal by changing the shifts of nurses' shifts and homework research techniques to achieve a win-win goal. Because nursing services occupy a very important position in the entire hospital treatment service, a reasonable scheduling system can ensure the quality of care, and improve the physical and mental health and quality of life of the nurses. This study uses an optimization model of operational research to evaluate how Reduce the working hours of anesthesia nurses and overtime beyond the plan, and take proactive measures to reduce waste of resources, including the most effective and efficient staff assignment and appropriate shift arrangements. Through a large number of calculation experiments, we provide opportunities for cost savings and Idea of the time required for resolution. Utilizing the extension of this model to obtain optimized nursing scheduling can provide a solution to the problem of nurse scheduling. This study uses the actual cases of the Department of Anesthesia, Taipei Rongmin General Hospital. According to the actual cases, it can truly present the huge challenges faced, combined with relevant scheduling strategies, optimization models, analysis of data, and response to differences and specificities. At the same time, in the face of hospitals, surgery, surgery rooms, and anesthesia issues, due to different environmental risks, there is a great risk. Through research data collection and analysis, we will further explore related issues, find the best winning strategy, and provide practical strategies Thinking and change actions have also produced many practical research conclusions during the research process. At the same time, they have also verified the practicality of operational research. It is hoped that these research results can be provided to Taiwan and the world's anesthesia and operating rooms as nurses' scheduling Reference. | en |
dc.description.provenance | Made available in DSpace on 2021-06-08T03:49:51Z (GMT). No. of bitstreams: 1 U0001-2312202012571000.pdf: 5872290 bytes, checksum: 6694420cd4ed6ddba82b18ba75628b9b (MD5) Previous issue date: 2020 | en |
dc.description.tableofcontents | 目錄 誌謝 II 摘要 III THESIS ABSTRACT IV 目錄 VI 圖目錄 VII 表目錄 VIII 第一章 緒論 1 第一節 研究動機與背景 1 第二節 研究問題與目的 3 第三節 研究方法與限制 4 第二章 文獻探討 6 第一節 作業研究Operational research (OR) 6 第二節 最佳化模型 13 第三節 排班系統 23 第三章 臺北榮民總醫院麻醉護理師排班現況分析 25 第一節 臺北榮民總醫院麻醉部 25 第二節 麻醉護理師 27 第三節 臺北榮總麻醉護理師排班現況 31 第四節 問題與挑戰 40 第四章 排班系統最佳化模型 42 第一節 策略分析 42 第二節 整數規劃模型 46 第三節 模型建構結果 48 第四節 模型 53 第五節 模型應用分析與交叉驗證 59 第五章 結論與建議 60 第一節 研究結論 60 第二節 研究建議與未來研究方向 62 參考文獻 63 圖目錄 圖1 研究流程圖 4 圖2 帕特里克·布萊克特(Patrick Blackett) 7 圖3 線性規劃示意圖 8 圖4 庫存控制示意圖 9 圖5 機器調度問題研究法 10 圖6 網絡分析示意圖 11 圖7 排序問題示意圖 12 圖8 作業研究步驟: 從問題到演算法 13 圖9 從問題到演算法之詳細步驟關聯圖 15 圖10 演算法範例圖 16 圖11 ANN研究論文封面 18 圖12 SVM研究論文封面 19 圖13 非線性規劃RSM研究論文封面 20 圖14 用藥策略模擬研究封面 21 圖15 用藥策略模擬研究之甦醒時間路徑圖 22 圖16 用藥策略模擬研究之反應消失路徑圖 22 圖17 臺北榮總麻醉部簡介暨歷史沿革圖 26 圖18 王學仕醫師玉照 29 圖19 臺灣之第一期麻醉護士訓練班結業合影 29 圖20 2018 年臺北榮總麻醉護理師加班時數 37 圖21 2018 年臺北榮總麻醉護理師人力與平均每人每月加班圖 37 圖22 2019下半年至2020年初臺北榮總麻醉護理師加班總時數 39 圖23 2019年9月平日各時段平均人力圖 49 表目錄 表1 麻醉專科護理師涉及侵入性人體之醫療業務範圍及項目 27 表2 麻醉專科護理師未涉及侵入性人體之醫療業務範圍及項目 28 表3 臺北榮總基礎麻醉護理人力需求及各項參數估計值 31 表4 103-108年度開刀房內接受麻醉總例數 32 表5 103-108年度開刀房內接受麻醉詳細分科例數 33 表6 103-108年度開刀外接受麻醉或鎮靜之詳細分科例數 35 表7臺北榮總麻醉護理師加班時數表 36 表8 2018-2019 年臺北榮總麻醉護理師人力各月加班一覽 38 表9 麻醉部人力擴充計畫時程表 41 表10模型範例一之每周各班別人力需求 48 表11 模型範例一之班型組合 49 表12模型範例二之每周各班別人力需求 50 表13 模型範例二之班型組合 51 表14模型範例三之每周各班別人力需求 52 表15 模型範例三之班型組合 52 表16 模型中的班型列表 53 | |
dc.language.iso | zh-TW | |
dc.title | 健康照護產業作業研究最佳化: 以臺北榮總麻醉護理師排班個案為例 | zh_TW |
dc.title | Optimization Model for Operations Research in Healthcare: A Case Study of Scheduling System of Nurse Anesthetist in Taipei Veterans General Hospital | en |
dc.type | Thesis | |
dc.date.schoolyear | 109-1 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 郭佳瑋,孔令傑 | |
dc.subject.keyword | 作業研究,最佳化模型,麻醉護理師,排班系統,手術室, | zh_TW |
dc.subject.keyword | operation research,optimization model,Nurse anesthetist,scheduling system,operating room, | en |
dc.relation.page | 66 | |
dc.identifier.doi | 10.6342/NTU202004451 | |
dc.rights.note | 未授權 | |
dc.date.accepted | 2020-12-24 | |
dc.contributor.author-college | 管理學院 | zh_TW |
dc.contributor.author-dept | 商學組 | zh_TW |
顯示於系所單位: | 商學組 |
文件中的檔案:
檔案 | 大小 | 格式 | |
---|---|---|---|
U0001-2312202012571000.pdf 目前未授權公開取用 | 5.73 MB | Adobe PDF |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。