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研究生:連耕鋒
研究生(外文):Geng-Feng Lian
論文名稱:利用系統模擬方法改善骨科門診-運動醫學組之門診服務品質
論文名稱(外文):Improving Outpatient Service Quality in Sports Team of Department of Orthopaedic Surgery by Using Simulation Approach
指導教授:盧大平盧大平引用關係
口試委員:史瑞田梁曉帆
口試日期:2012-07-24
學位類別:碩士
校院名稱:國立臺北科技大學
系所名稱:工業工程與管理系碩士班
學門:工程學門
學類:工業工程學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
語文別:英文
論文頁數:103
中文關鍵詞:系統模擬門診等候時間病患滿意度服務品質指標
外文關鍵詞:SimulationOutpatient waiting timePatient satisfactionService quality index
相關次數:
  • 被引用被引用:3
  • 點閱點閱:355
  • 評分評分:
  • 下載下載:80
  • 收藏至我的研究室書目清單書目收藏:0
本研究以桃園國軍總醫院之骨科運動醫學組為研究背景,有別於大部份西方國家只接受提前預約的病患,台灣的醫療門診病患可選擇現場掛號或提前預約,在此制度下,門診流程將更為複雜且難以預測,並造成病患常花費很長的時間在等待看診。根據醫院內部之滿意度問卷調查,等待時間過長是病患最不滿意評比項目,而病患的滿意度也將會影響醫院從健保局所申請的預算經額。綜合上述兩個理由,此研究將以改善門診病患等候時間為主要目標,首先,本研究在骨科部運動醫學組門診現場實際收集了兩個月的資料,並從醫院內部管理系統取得一整年的醫生看診資料。以統計方法進行分析,找出幾個關鍵參數,例如:病患到達分配、遲到、檢查與未看診比例、及醫生服務時間分配等,並使用系統模擬軟體ARENA_13.0建構出與現實醫療流程相符的模擬模型。再來,設計七個改善方案進行模擬與敏感度分析,找出其中有較佳改善績效的方案,其中調整病患人數比例至現場掛號10%,預約掛號90%,在我們研究中對現場掛號病患等候時間能有34.47%的改善,對預約掛號病患能有50.4%的改善。

Nowadays, patient satisfaction is an important service quality index(SQI)for many hospitals. In Taiwan, healthcare system has a mixed-type registration which accepts for both walk-in patients and scheduled patients. It is different from western countries which accept only scheduled patients. A long waiting time (WT) of outpatient clinics is caused by a complex registration system. A survey questionnaire of patient satisfaction showed that the long waiting time is the most dissatisfied service quality for healthcare providers. This study focused on improving clinical services by proposing feasible solutions for the healthcare providers to reduce outpatient waiting time. We collected and observed data for two months from real world situation and used data from hospital database for building and validating simulation models. Seven scenarios are performed: scenarios I adjusted proportion between walk-in patients and scheduled patients, scenario II-VI adjusted patient sequencing, and scenario VII adjusted late rate and applied a late policy for late patients. The study ran the simulation models and did a sensitivity analysis for testing the scenarios and finding out which parameters are the key drivers of patient waiting time. The scenario I (adjusting the proportion: 10% for walk-in patients and 90% for scheduled patients) has the highest percentage of waiting time improvement (average: 34.47 % for walk-in patients and 50.4 % for scheduled patients) compared with the other scenarios. The overall results are shown that adjusting proportion of patient scenario and patient sequencing scenario can improve patient waiting time in the mixed-type registration and are possible to apply to any outpatient clinics.

摘要 i
ABSTRACT ii
誌 謝 iv
CONTENTS v
LIST OF TABLES viii
LIST OF FIGURES xii
Chapter 1 INTRODUCTION 1
1.1 Research motivations 1
1.2 Research Background 3
1.3 Research Objectives 5
1.4 Research Scope and limitation 5
1.5 Research Processes 6
Chapter 2 LITERATURE REVIEW 8
2.1 Service satisfaction 8
2.2 Outpatient waiting time 9
2.3 Simulation 10
Chapter 3 RESEARCH METHODOLOGY 12
3.1 Research Processes 12
3.2 Collect and analyze data 13
3.3 Build a simulation model 14
3.4 Validate a simulation model 15
3.5 Run simulation and do a sensitivity analysis 17
3.6 Analyze results 17
Chapter 4 SIMULATION EXECUTION 18
4.1 Building a model for each consultation section 18
4.1.1 Comparison between two doctors in the sports team of department of orthopaedic surgery 18
4.1.2 Model building 19
4.2 Model validation 23
4.2.1 Dr. A’s morning consultation section 24
4.2.2 Dr. A’s afternoon consultation section 27
4.2.3 Dr. A’s evening consultation section 30
4.2.4 Dr. B’s morning consultation section 33
4.2.5 Dr. B’s afternoon consultation section 36
4.3 Definitions of scenarios 38
4.3.1 Scenario I: Adjusting the proportion of walk-in patients and scheduled patients 39
4.3.2 Scenario II: Adjusting sequence of walk-in patients and scheduled patients. 39
4.3.3 Scenario III: Assigning front numbers to walk-in patients and later numbers to scheduled patients. 41
4.3.4 Scenario IV: Assigning front numbers to scheduled patients and later numbers to walk-in patients. 42
4.3.5 Scenario V: Assigning some front numbers to walk-in patients and later numbers to walk-in and scheduled patients. 43
4.3.6 Scenario VI: Assigning some front numbers to walk-in patients and assigning later numbers to walk-in and scheduled patients with different patient sequencing. 44
4.3.7 Scenario VII: Adjusting the late rate and applying a late policy for late patients. 45
Chapter 5 SIMULATION RESULTS 46
5.1 Analyze results 46
5.1.1 Scenario I: Adjusting the rate between walk-in patients and scheduled patients. 46
5.1.2 Scenario II: Adjusting sequence of walk-in patients and scheduled patients. 52
5.1.3. Scenario III: Assigning front numbers to walk-in patients and later numbers to scheduled patients. 63
5.1.4. Scenario IV: Assigning front numbers to scheduled patients and later numbers to walk-in patients. 69
5.1.5. Scenario V: Assigning some front numbers to walk-in patients and assigning later numbers for walk-in and scheduled patients. 74
5.1.6. Scenario VI: Assigning some front numbers to walk-in patients and assigning later numbers to walk-in and scheduled patients with different patient sequencing. 86
5.1.7. Scenario VII: Adjusting the late rate and applying a late policy for late patients. 92
5.1.8. Proposed scenarios 93
Chapter 6 CONCLUSIONS 95
6.1 Conclusions & Discussions 95
6.2 Future directions 96
LIST OF REFERENCES 98
APPENDIX 101


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