( 您好!臺灣時間:2021/03/09 16:51
字體大小: 字級放大   字級縮小   預設字形  


研究生(外文):Tsai, Pei-Hsuan
指導教授(外文):Jane W.S. Liu
外文關鍵詞:medication scheduling managersmart medication dispenser
  • 被引用被引用:0
  • 點閱點閱:378
  • 評分評分:系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
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。

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
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

[AaBC] P. Aspden, J. Wolcott, J.L. Bootman, L.R. Cronenwett (Eds.), Preventing Medication Errors: Quality Chasm Series, Washington, DC: The National Academies Press, 2006.
[AsBl] Darren M. Ashcroft, P.Q., Alison Blenkinsopp, “Prospective study of the incidence, nature and causes of dispensing errors in community pharmacies,” in Pharmacoepidemiology and Drug Safety, vol. 14, no.5, pp. 327-332, May 2005.
[BaAR] N D Barber, D P Alldred, D K Raynor, etal, “Care homes’ use of medicine study: prevalence, causes and potential hram of medication errors in care homes for older people,” in Quality and Safety in Health Care, vol.18, pp. 341-346, July 2009.
[Bark] Barker, E.A.a.K., “Fundamentals of medication error research,” in American Journal of Hospital Pharmacy, vol. 47, no.3, pp. 555-571 , 1990.
[BCLP] Bates DW, L.L., Cullen DJ, Laird N, Petersen LA, Teich JM, et al. , “Effect of computerized physician order entry and a team intervention on prevention of serious medication errors,” in JAMA, vol. 280, no.15, pp. 1311-1316, October, 1998.
[BFPB] Barker KN, Flynn EA, Pepper GA, PhD, Bates DW, Mikeal RL. “Medication errors observed in 36 health care facilities,” in Archives of International Medicine, vol. 162, no.16, pp.1897-1903, September, 2002;
[BLSK] David W Bates, J.M.T., Joshua Lee, Diane Seger, Gilad J KBPArman, Nell Ma'Luf, et.al, “Using information technology to reduce rates of medication errors in hospitals,” in BMJ, vol. 320, no. 7237, March 2000.
[BrLa] Brennan TA, L.L., Laird NM, et al., “Incidence of adverse events and negligence in hospitalized patients – Results of the Harvard medical practice sudy 1,” in The New England Journal of medicine, vol. 324, pp. 370-376, February 1991.
[Buko] B. Bukovics, Pro WF: Windows Workflow Foundation in .Net 4.0, Apress, 2009.
[Card] S. K. Card, et al. The Psychology of Human-Computer Interaction, Hillsdale, N.J.: Lawrence Erlbaum Associates, 1983.
[Cart] Jerome H. Carter, American College of Physicians Observer: How EMR software can help prevent medical mistakes, 2004.
[CCSL] T. Y. Chen, C. H. Chen, C. S. Shih, J. W. S. Liu, “A Simulation Environment for the Development of Smart Devices for the Elderly,” in Proceedings of IEEE International Conference on Systems, Man and Cybernetics, 2008.
[Cent] Center, C.f.D.C.a.P.N. and f.H. Statistics. “Deaths: final data for 2006,” in National Vital Stat Rep, 2006.
[CTCS] T.Y. Chen, P. H. Tsai, T. S. Chou, C. S. Shih, T. W. Kuo, and J. W. S. Liu, “Component Model and Architecture of Smart Devices for the Elderly,” in Proceedings of the 7th Working IEEE/IFIP Conference on Software Architecture, 2008.
[Cohe] Michael R. Cohen, Medication Errors, American Pharmaceutical Association, 1999.
[Cohe08] Cohen, M.R., Medication Use: A Systems Approach to Reducing Errors, Joint Commission on Accreditation of Healthcare Organization, 2008.
[CuFH] Cutler, D.M., N.E. Feldman, and J.R. Horwitz, “U. S. Adoption of Computerized Physician Order Entry Systems,” in Health Affairs, vol.24, no.6, 2005.
[Davi] Davis, R.L., “Computerized physician order entry systems: the coming of age for outpatient medicine,” in PLoS Medicine, 2005.
[DSA09] Drug Safety and Availability: Medication Errors, June 2009, Available from: http://www.fda.gov/Drugs/DrugSafety/MedicationErrors/default.htm.
[DSS09] Decision support systems, 26 July 2005. 17 Feb. 2009, Available form: http://www.openclinical.org/dss.html
[EHR03] EHR Definition, Attributes and Essential Requirements. Healthcare Information and Management Systems Society, 2003, Available from: http://www.himss.org/content/files/EHRAttributes.pdf. Retrieved 2006-07-28.
[EMAR09] Electronic Medication Administration Record (eMAR), 2009. Available from: http://www.dh.org/body.cfm?id=434&oTopID=434.
[EPIL] Available from: http://www.epill.com/
[EvNP] Evans DC, Nichol WP, Perlin JB, April, 2006, "Effect of the implementation of an enterprise-wide Electronic Health Record on productivity in the Veterans Health Administration," in Health Econ Policy Law, vol. 1, pp. 163–9.
[FCC] Adapted from the IEEE definition of interoperability, and legal definitions used by the FCC (47 CFR 51.3), in statutes regarding copyright protection (17 USC 1201), and e-government services (44 USC 3601)
[GaDa] Dave Garets and Mike Davis, Electronic Patient Records, Healthcare Informatics Online. Available from: http://www.providersedge.com/ehdocs/ehr_articles/Electronic_Patient_Records-EMRs_and_EHRs.pdf
[GRFN] M.Governo, V. Riva, P. Fiorini, and C. Nugent “MEDICATE Teleassistance System” in The 11th International Conference on Advance Robotics, June 2003.
[HaLL] C.C. han, K.J. Lin and J.W.S. Liu, “Scheduling jobs with temporal distance constraints,” in SIAM Journals on Computing, vol. 21, no. 5, 1995
[IMNA] A Project on Identifying and Preventing Medication Errors. Institute of Medicine of National Academies.
[IOM01] Committee on Quality of Health Care in America, Crossing the Quality Chasm: A New Health System for the 21st Century, Washington, D.C.: National Academy Press, 2001.
[JDGS] Jha, A. K., Doolan, D., Grandt, D., Scott, T. & Bates, D. W. “The use of health information technology in seven nations,” in International Journal of Medical Informatics, vol. 77, pp.848-854, March 2008.
[KBPA] Gilad J. KBPArman, Anne Bobb, Thomas H. Payne, Anthony J. Avery and et al., “Medication related clinical decision support in computerized provider order entry systems: A Review,” in JAMIA, vol. 14, no. 1, pp. 29-40, February 2007.
[KOCD] Linda T. Kohn, Janet M. Corrigan, and Molla S. Donaldson, To Err Is Human: Building a Safer Health System, Washington, D.C.: National Academy Press, 2000.
[Kopp] Koppel, B., et al., “Role of computerized physician order entry systems in facilitating medication errors,” in Journal of AMA, vol.293, no.10, pp.1197-1203, 2005.
[KSLR] M. Klien, L. Sha, J. Lohoxzky, R. Rajkumar, et al. Rate-Monotonic Analysis: Software Technology Roadmap. Available from: http://www.sei.cmu.edu/str/descriptions/rma_body.html
[KN95] KN., B., “Ensuring safety in the use of automated medication dispensing systems,” Am J Health Syst Pharm 52: p. 3, 1995.
[LeLa] Leape LL, B.T., Laird N, et al., “The nature of adverse events in hospitalized patients. Results of the Harvard Medical Practice Study II,” in N Engl J Med, vol. 324, no. 6, pp.377-384,February 1991.
[LiLa] C. L. Liu and J. Layland, “Scheduling Algorithms for Multiprogramming in a Hard Real-Time Environment,” in Journal of ACM, vol. 20, no.1, 1973.
[Lisb] Lisby, et al., “Errors in the medication process: Frequency, type, and potential clinical consequences,” in International Journal for Quality in Health Care, vol. 18, no. 4, May 2006.
[Liu00] J. W. S. Liu, Real-Time Systems, Chapters 2 and 3, Prentice Hall, 2000.
[Liu05] J. W. S. Liu, et al., “Reference Architecture of Intelligent Appliances for the Elderly,” in Proceedings of the 18th International Conference on System Engineering, August 2005.
[LLSB] J. W. S. Liu, K. J. Lin, W. K. Shih, R. Bettati and J. Y. Chung, “Imprecise Computations,” in IEEE Proceedings, vol. 82, pp. 1-12, January 1994.
[MIMP] Mobile Intelligent Medication Management Platform Project plan, National Yang Ming University, Taiwan, 2009,
[Morg] Morgan, S., Medication Error Statistics, Prescription, July, 2005.
[Murr] Murray, M. D., “Automated medication dispensing devices,” Chapter 11 in Making health care safer: a critical analysis of patient safety, 01-E58, Agent for Healthcare Research and Quality, 2001.
[MyMS] Available from: https://secure.medactionplan.commymedscheduleindex.htm
[Paic] J., K.W., N. Paice, and e. al, “The effect of computerized physician order entry on medication errors and adverse drug events in pediatric inpatients,” in Pediatrics, vol.112, no.3, pp. 506-509, September 2003.
[PDR] PDRHealth, Drug Information, Available from: http://www.pdrhealth.com/drug_info/.
[Robe] Robert Dicks, “Study shows for first time decrease in mortality associated with physician order entry system,” May 2010, Stanford University Medical Center. Available from: http://www.eurekalert.org/pub_releases/2010-05/sumc-ssf042710.php
[SCIE05] “Helping older people to take prescribed medication in their own home: what works?” SCIE, 2005. Available from: http://www.scie.org.uk/publications/briefings/briefing15/index.asp
[Scot] Scott, G.R.K.a.J.E., “Medication Compliance and Health Education among Outpatients with Chronic Mental Disorders,” in Medical Care, vol. 28, no.12 p. 1187-1197, December 1990.
[ScZG ] Doris Schwartz, M.W., Leonard Zeitz, Mary E. W. Goss, “Medication errors made by elderly chronically ill patients,” in A.J.P.H, vol. 52, no. 12, pp.2018-2029, December 1962.
[ShLi] C. S. Shih and J. W. S. Liu, “Scheduling State-Dependent Jobs,” in Proceedings of 2002 IEEE Symposium on Real-Time Systems, pp. 3-14, December 2002.
[ShLC] C. S. Shih, J. W. S. Liu and I. Cheong, “Scheduling Jobs with Multiple Feasible Intervals,” in Proceedings of 2003 RTCSA, pp. 213-231, February 2003.
[SpSL] B. Spruri, L. Sha, J. P. Lehoczky, “Aperiodic task Scheduling for Hard Real-Time Systems,” in Real-Time Systems Journal, vol. 1, no. 1, 1989.
[Veac] Veacez, P.J., "An individual based framework for a study on medical error," in International Journal for Quality in Health Care, vol. 18, no. 4, May 2006.
[Vist06] "VistA:Winner of the 2006 Innovations in American Government Award" The Ash Institute for Democratic Governance and Innovation at Harvard University's John F. Kennedy School of Government. Available from”:http://www.innovations.va.gov/innovations/docs/InnovationsVistAInfoPackage.pdf.
[Wan99] Wan, D., “Magic Medicaine Cabinet: A situated portal for consumer healthcare,” in Proceedings of First International Symposium on Handheld and Ubiquitous Computing, September 1999.
[Wan01] F. Wang., “RED: Model-Checker for Timed Automata with Clock-Restriction Diagram,” in Workshop on Real-Time Tools, August 20, 2001.
[WIKICD]Available from:
[WIKICP]Available from:
[WZTL] Mei-Ying Wang, John K. Zao, P. H. Tsai, J. W. S. Liu, “Wedjat: A Mobile Phone Based medication Reminder and Monitor,” in IEEE International Conf. on BioInformatics and BioEngineering, pp. 423-430, June 2009.
[YHST] H. C. Yeh, P. C. Hsiu, C. S. Shih, P. H. Tsai and J. W. S. Liu, “APAMAT: A Prescription Algebra for Medication Authoring Tool,” in Proceedings of IEEE International Conference on Systems, Man and Cybernetics, vol. 5, pp. 4284-4291, October 2006.

註: 此連結為研究生畢業學校所提供,不一定有電子全文可供下載,若連結有誤,請點選上方之〝勘誤回報〞功能,我們會盡快修正,謝謝!
第一頁 上一頁 下一頁 最後一頁 top
系統版面圖檔 系統版面圖檔