臺灣博碩士論文加值系統

智慧型藥物管理工具主要是為了長期服藥的使用者，協助他們從事居家照顧，在沒有仰賴專業人士輔助的情況下，也可以正確的使用藥物。藉由此套系統的輔助，可以幫助使用者正確的遵守用藥指示，避免因人為的疏忽或認知不同誤解藥物使用方式而導致錯誤。智慧型藥物管理工具是一套由藥物排程軟體和輔助給藥控制硬體所組成的系統工具。藥劑師可以利用iMAT藥物資料庫，將使用者的所有藥物處方箋正確的轉換成我們制定的machine readable的MSS格式，再經由prescription authoring tool檢查藥物之間的衝突性，最後交由藥物排程軟體去產生適當而正確的服藥時程表。藥物排程軟體可以單獨運作在電腦或者智慧型手機硬體上，再搭配一般藥盒，適時的提醒使用者服藥。也可以和全自動的藥物控制硬體也就是自動化智慧型藥盒結合，在藥盒上執行藥物排程及提醒跟紀錄等工作。藥物排程軟體跟藥物控制硬體兩者之間的操作跟行為過程是以action-oriented的模式。採用這種介面的好處是讓軟體跟硬體兩者都具備了擴展性。當有新的功能需要被加入或者已存在的功能需要被移除或修改時，只需要稍加修改甚至完全不需要變動給藥控制硬體的架構。
在藥物排程與管理上,要算出有效且適合的排程表，考慮的限制包括藥物本身的服用方式跟屬性，藥物彼此之間的交互作用所造成的可排程時間限制，使用者的行為模式以及喜好。前兩者被視為不可違背的限制，列出的所有規則必定要完全遵守，其他限制在和前兩者相抵觸時，以遵從前兩者為主。不同的排程演算法適用在不同的情境中，同時也給予不同的便利性，在此論文中我們提出兩大直覺性排程演算法系統。最後我們利用許多不同的效能參數去評比並列出比較結果。

iMAT is a system of automatic medication dispensers and software tools. It is for people who take medications on long term basis at home to stay well and independent. The system helps its users to improve rigor in compliance by preventing misunderstanding of medication directions and making medication schedules more tolerant to tardiness and negligence. A user of iMAT medication dispenser and schedule manager has no need to understand the directions of her/his medications. iMAT enables the pharmacist of each user to extract a machine readable medication schedule specification (MSS) from the user’s prescriptions and OTC directions. Once loaded into an iMAT dispenser or schedule manager, the tool automatically generates a medication schedule that meets all the constraints specified by the user’s MSS. Based on the schedule, the tool reminds the user at the times when some doses should be taken and provides instructions on how the doses should be taken (e.g., with 8 oz of water, no food within 30 minutes, etc.) In this way, iMAT helps to make complex regimens easy to follow.
We also present two families of heuristic algorithms for scheduling medications that interact with each other. All algorithms accept as input machine readable medication directions that specify the dose size and timing constraints to be met by all schedules. Simulation results on their performance in terms of success rate and schedule quality can help builders of smart medication dispensers and scheduling tools choose among algorithms and tradeoff merits along different dimensions.

中文摘要……. i
Abstract……… ii
Acknowledgement iii
Contents…….. v
List of Figures viii
List of Tables xi
Chapter 1 Introduction 1
1.1 Motivation 1
1.2 Overview 2
1.3 Contributions 5
1.4 Organization 6
Chapter 2 Related Works 9
2.1 Stages of Medication Use Process and Common Errors 9
2.2 Causes of Errors 12
2.2.1 Information of Patients and Drugs 12
2.2.2 Drug settings 13
2.2.3 Educations of Staff Competency and Patients 14
2.2.4 Environments and Medication Delivery Device 15
2.2.5 Communication 15
2.2.6 Quality Process and Risk Management 16
2.3 Existing Technologies 16
2.3.1 Electronic Medical Record 17
2.3.2 Clinical Decision Support System 18
2.3.3 Computerized Physician Order Entry 19
2.3.4 Bar-coding at Medication Dispensing and Medication Administration 20
2.3.5 Remote Dispensing System 20
2.3.6 Pillboxes and Intelligent Medication Advisory Tools 21
2.4 Related Research Projects 22
2.4.1 iMAT Medication Database and Authoring Tools 22
2.4.2 Wedjat: Smart Phone Based Medication Reminder and Monitor 25
2.5 Similarity and Difference with Existing Models 26
Chapter 3 USE SCENARIOS, ASSUMPTIONS AND OPERATIONS 30
3.1 Illustrative Example 30
3.2 Key Assumptions 32
3.3 Prescription Authoring Tool 34
3.4 Automated Medication Dispensers 36
3.4.1 Operation of A Personal Dispenser 38
3.4.2 Operation of Medication Scheduler Manager 39
Chapter 4 Scheduling model and medication schedule specification 42
4.1 Direction Parameters 42
4.1.1 Granularity and Duration 44
4.1.2 Dose Size and Separation 45
4.1.3 Maximum Total Intake Constraint 47
4.1.4 Minimum Total Intake Constraint 49
4.1.5 Time Varying Direction 50
4.1.6 Some Non-Compliant Event Type 51
4.2 Dependencies of Multiple Medications 52
4.2.1 Some Non-Compliant Event Type 54
4.2.2 Interaction (Non-Compliance) Event 59
4.3 User Preference 60
4.3.1 Calendar Interface 60
4.3.2 Feasible and Forbidden Interval 62
4.4 Graph Representation Dispensers 64
4.5 Resource Model 67
4.5.1 Processor Time Requirement 68
4.5.2 Resource Requirements 70
Chapter 5 Architecture of Dispenser 72
5.1 Major Software Components 72
5.2 Hardware Components and Driver Interface 74
5.3 Action-Oriented Collaboration 76
5.3.1 Decision Maker Interface 77
5.3.2 Communication Flow 79
5.4 Controller and Scheduler Design 80
5.4.1 Operational Specification 81
5.4.2 Controller Software Architecture 83
5.4.3 Illustrative Example 85
5.5 Evaluation 89
Chapter 6 Scheduling Algorithms 93
6.1 Parameters Consistency and Feasibility 94
6.1.1 Feasibility Test Based on Minimum Demand Schedule 96
6.1.2 Feasibility Test Based on Maximum Supply Schedule 106
6.2 Heuristic Dose Selection 109
6.2.1 Definitions 109
6.2.2 Relative Performance 111
6.3 Algorithms for Scheduling Interacting Medications 114
6.3.1 Priorities 115
6.3.2 Feasibility Test Based on Maximum Supply Schedule 116
6.4 Operations of OMAT and ODAT Algorithms 119
6.5 Relative Performance of OMAT and ODAT Algorithms 124
6.5.1 Simulation Experiments 124
6.5.2 Data on Success Rate 126
6.5.3 Data on Schedule Quality 132
Chapter 7 Summary and Future Works 141
7.1 Summary of Results 141
7.2 Future Works 143
References….. 146

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