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研究生:龍安靖
研究生(外文):An-Jim Long
論文名稱:電腦醫令全面性用藥安全警示系統之忽略行為分析
論文名稱(外文):Analyzing physicians' overriding behavior on a total medication safety reminder systems on CPOE
指導教授:張博論張博論引用關係
指導教授(外文):Polun Chang
學位類別:博士
校院名稱:國立陽明大學
系所名稱:公共衛生研究所
學門:醫藥衛生學門
學類:公共衛生學類
論文種類:學術論文
論文出版年:2009
畢業學年度:97
語文別:英文
論文頁數:80
中文關鍵詞:電腦醫令系統用藥安全用藥警示
外文關鍵詞:CPOEMedication Safetyreminder system
相關次數:
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There is evidence that patients are being prescribed a significant number of potentially harmful prescriptions despite the use of computerized safety reminder systems. Nonetheless, the physicians’ behavior with respect to the computer reminders has not been well studied yet. This problem is important because adverse drug event can result in unpredictable or undesirable effects; furthermore, it is sometime a waste of significant healthcare resources.
A systematic analysis of four different implemented reminder systems on the Computerized Physician Order Entry (CPOE) was conducted at a 737-bed teaching medical center in northern Taiwan. The log file, combined with the physicians’ profiles, was statistically examined using the Mantel-Haenszel technique.
Over the duration of this research, a total of 188,182 order sets involving 896,131 orders were entered. 0.37% of patients received potential overdose prescriptions and dosing guidance reminders were triggered, 3% of patients received potential duplicated prescriptions, 1.2% of patients received potential DDI prescriptions, and 25% of pregnant patients received potential unsafe prescriptions.
Dosing guidance and drug duplication reminder has average good acceptance rate. In dosing guidance reminder system physicians has high relative coefficient in responding two kinds of overdose reminders. Pediatric (22.2% and 37.8%) and some physicians were expected and found with high rate of acceptance. The physicians related variables (workload, department, educational background, years in practice at the target hospital and age) were found to be critically relevant to drug duplication alert system.
DDI and pregnancy safety drug reminder has worse acceptance rate and polarized results. Original designers (pharmacists) for rules (and alert database) of DDI were aiming for Neurosurgeons, Neuron-internists, Cardiac surgeons and Cardiologists and pregnancy safety for obstetrics and gynecologists. However, these physicians responded very badly to the reminders than other physicians. And according to the polarized results it is possible the reminder system has misled some physicians by implying that some prescriptions are dangerous which resulted in unintended consequences.
A total analysis between four reminder systems was made during the study. It found error-producing conditions including alerts without clinical relevant and importance, alerts are not bridging temporal spatial gap, alerts don’t help to insurance claim. These may result in active failures of the physician, like ignoring alerts and misinterpretation alert. The newly generated reason’s model states how and why physicians overrode the reminders and future implementation of reminder systems can be further improved.
There is evidence that patients are being prescribed a significant number of potentially harmful prescriptions despite the use of computerized safety reminder systems. Nonetheless, the physicians’ behavior with respect to the computer reminders has not been well studied yet. This problem is important because adverse drug event can result in unpredictable or undesirable effects; furthermore, it is sometime a waste of significant healthcare resources.
A systematic analysis of four different implemented reminder systems on the Computerized Physician Order Entry (CPOE) was conducted at a 737-bed teaching medical center in northern Taiwan. The log file, combined with the physicians’ profiles, was statistically examined using the Mantel-Haenszel technique.
Over the duration of this research, a total of 188,182 order sets involving 896,131 orders were entered. 0.37% of patients received potential overdose prescriptions and dosing guidance reminders were triggered, 3% of patients received potential duplicated prescriptions, 1.2% of patients received potential DDI prescriptions, and 25% of pregnant patients received potential unsafe prescriptions.
Dosing guidance and drug duplication reminder has average good acceptance rate. In dosing guidance reminder system physicians has high relative coefficient in responding two kinds of overdose reminders. Pediatric (22.2% and 37.8%) and some physicians were expected and found with high rate of acceptance. The physicians related variables (workload, department, educational background, years in practice at the target hospital and age) were found to be critically relevant to drug duplication alert system.
DDI and pregnancy safety drug reminder has worse acceptance rate and polarized results. Original designers (pharmacists) for rules (and alert database) of DDI were aiming for Neurosurgeons, Neuron-internists, Cardiac surgeons and Cardiologists and pregnancy safety for obstetrics and gynecologists. However, these physicians responded very badly to the reminders than other physicians. And according to the polarized results it is possible the reminder system has misled some physicians by implying that some prescriptions are dangerous which resulted in unintended consequences.
A total analysis between four reminder systems was made during the study. It found error-producing conditions including alerts without clinical relevant and importance, alerts are not bridging temporal spatial gap, alerts don’t help to insurance claim. These may result in active failures of the physician, like ignoring alerts and misinterpretation alert. The newly generated reason’s model states how and why physicians overrode the reminders and future implementation of reminder systems can be further improved.
Chapter I General Introduction 3
1.1 Introduction 3
1.2 Literature review 4
1.3 Motivation 10
1.4 Total medication safety reminder systems 11
1.5 Materials and research design 12
1.6 Outline of this research 14
Chapter II Dosing Guidance 16
2.1 Introduction 16
2.2 Methods 16
2.3 Results 18
2.4 Conclusions 21
Chapter III Duplicate Drug Checking 22
3.1 Introduction 22
3.2 Methods 23
3.3 Results 24
3.4 Conclusions 31
Chapter IV Drug-Drug Interaction 37
4.1 Introduction 37
4.2 Methods 37
4.3 Results 38
4.4 Conclusions 41
Chapter V Drug–Pregnancy Alerting 42
5.1 Introduction 42
5.2 Methods 45
5.3 Results 49
5.4 Conclusions 53
Chapter VI Total Analysis Between Systems 55
6.1 Introduction 55
6.2 Methods 55
6.3 Results 56
Chapter VII Conclusions and Perspectives 62
7.1 Comparison of this research and other researches 62
7.2 Discussions 63
7.3 Summary 65
7.4 Future research 66
[1] 蘇俊忠, 醫師費與醫師醫療行為之研究-以某公立醫院醫師為例, 1998
[2] Jeannie LH, Robert JR, George KF, et al. Continuity of care: a multidisciplinary review. Br Med J 2003;327:1219-1221
[3] Richard IC, Marta R, David DW, Gaps in the continuity of care and progress on patient safety, Br Med J. 2000;320:791-794.
[4] Kohn LT, et al. To err is human: building a safer health system. Washington, D.C.: National Academy Press, 2000.
[5] Committee On Quality Of Health Care in America, Crossing the Quality Chasm. Washington, D.C.: National Academy Press, 2000.
[6] American Hospital Association. Hospital Statistics. Chicago, Il. 1999
[7] Bates, David W.; Cullen, David J.; Laird, Nan M.; et al. Incidence of Adverse Drug Events and Potential Adverse Drug Events: Implications for Prevention. The Journal of the American Medical Association.274:29–34, 1995.
[8] Bates, David W.; Spell, Nathan; Cullen David J.; et al. The Costs of AdverseDrug Events in Hospitalized Patients. The Journal of the American Medical Association. 277:307–311, 1997.
[9] Title 11-C Medicaid Drug Utilization Review, New York State Consolidated Laws. Available at http://caselaw.lp.findlaw.com/nycodes/c108/a37.html Accessed January 31, 2007.
[10] M Tozawa, K Iseki, C Iseki, et al. Analysis of drug prescription in chronic haemodialysis patients. Nephrol Dial Transplant. 2002 Oct; 17(10):1819-24.
[11] R.J. Anderson, D.M. Melikian, J.G. Gambertoglio, et al. Prescribing medication in long-term dialysis units. Arch Intern Med. 1982 Jul; 142(7):1305-8.
[12] J.R. Spina, P.A. Glassman, P Belperio, et al. Clinical Relevance of Automated Drug Alerts From the Perspective of Medical Providers. Am J Med Qual. 2005 Jan-Feb; 20(1):7-14.
[13] P.G. Nightingale, D Adu, N.T. Richards, et al. Implementation of rules based computerised bedside prescribing and administration: intervention study. BMJ. 2000 Mar 18; 320(7237):750-3.
[14] D Magnus, S Rodgers, A.J. Avery. GPs’ views on computerized drug interaction alerts: questionnaire survey. J Clin Pharm Ther. 2002 Oct; 27(5):377-82.
[15] H. van der Sijs, J Aarts, A Vulto, et al. Overriding of Drug Safety Alerts in Computerized Physician Order Entry. J Am Med Inform Assoc. 2006 Mar-Apr; 13(2):138-47.
[16] L Taylor, R Tamblyn. Reasons for physician non-adherence to electronic drug alerts. Medinfo. 2004; 11(Pt 2):1101-5.
[17] A Feldstein, S.R. Simon, J Schneider, et al. How to design computerized alerts to ensure safe prescribing practices. Joint Commission Journal on Quality and Patient Safety, 2004 Nov; 30(11):602-13.
[18] Jeannie LH, Robert JR, George KF, et al. Continuity of care: a multidisciplinary review. Br Med J 2003;327:1219-1221
[19] Richard IC, Marta R, David DW, Gaps in the continuity of care and progress on patient safety, Br Med J. 2000;320:791-794.
[20] Ortiz E, Meyer G, Burstin H, Clinical Informatics and Patient Safety at the Agency for Healthcare Research and Quality, J Am Med Inform Assoc 2002;9:S2-S7
[21] Lambrinoudakis C, Gritzalis S, Managing Medical and Insurance Information Through a Smart-Card-Based Information System, J Med Syst 2000;24:213-234
[22] Lai JT, Hou TW, Yeh CL, et al, Using Healthcare IC Cards to manage the drug doses of chronic disease patients, Comput Biol Med. 2007;37:206-213
[23] W.J. Curran, The thalidomide tragedy in Germany: the end of a historic medicolegal trial, N. Engl. J. Med. 1971;284:481-482.
[24] Lenz W, A short history of thalidomide embryopathy. Teratology 1988;38:203-215.
[25] C.J. van Boxtel, Lessons still to be learned from Thalidomide, Int. J. Risk & Safety Med 2004;16:103-106.
[26] Ornoy A, Arnon J : Clinical teratology. West J Med 1993;159:382-390.
[27] Opitz JM, Associations and syndromes: Terminology in clinical genetics and birth defects epidemiology. Am J Med Genet 1994;49:14-20.
[28] Sannerstedt R, Lundborg P, Danielsson BR, et al. Drugs during pregnancy. An issue of risk classification and information to prescribers. Drug Saf 1996;14:69-77
[29] Teratology Society Public Affairs Committee. FDA Classification of drugs for teratogenic risk. Teratology 1994;49:446-7
[30] NDRADE Susan E., GURWITZ Jerry H., DAVIS Robert L. Prescription drug use in pregnancy. Am J Obstet Gynecol 2004;191:398-407.
[31] RUBIN J. D. ; FERENCZ C. ; LOFFREDO C. Use of prescription and non-prescription drugs in pregnancy. J Clin Epidemiol 1993;46:581-589
[32] I Lacroix, C Damase-Michel, M Lapeyre-Mestre, J L Montastruc. Prescription of drugs during pregnancy in France. J Lancet 2000;356:1735-6
[33] E.L. Allen, K.N. Barker, M.R. Cohen, N.M. Davis, R.E. Pearson. (1992). Draft Guidelines on Preventable Medication Errors, American Journal of Health-System Pharmacy,49:640-648.
[34] Lesar, Timothy S.; Briceland, Laurie, and Stein, Daniel S. Factors Related to Errors in Medication Prescribing. The Journal of the American Medical Association. 277(4):312–317, 1997
[35] TA Brennan, LL Leape, NM Laird, Incidence of adverse events and negligence in hospitalized patients. Results of the Harvard Medical Practice Study I; NEJM 1991; 324: 370-6
[36] Leape, et al. System Analysis of Adverse Drug Events, The Journal of the American Medical Association 1995; 274(1): 35-43.
[37] JW Cooper; Reduction of irrational drug duplication in geriatric nursing homes. Nurs Homes Sr Citiz Care 1988; 37(1): 5-8
[38] Klarin et all; The Association of Inappropriate Drug Use with Hospitalisation and Mortality: A Population-Based Study of the Very Old. Drugs Aging 2005; 22(1): 69-82.
[39] Ranie Koshy. Navigating the information technology highway: computer solutions to reduce errors and enhance patient safety. Transfusion 2005:45:189-205.
[40] Abrahamsen, Cathie. Optimal patient safety a computer chip away. Nurs Manage 2004; 35:47-48.
[41] Karen Farris; UI researchers urge awareness of drug interactions, duplication; http://www.uiowa.edu/~ournews/2002/december/1220drugstudy.html
[42] 2002 Research in NHI of Taiwan; http://www.nhi.gov.tw/14research/file/90/90plan008.htm
[43] Mei-Hua Chuang et all; Medication Errors in Health Care Institutions; Tzu Chi Med J 2003; 15: 247-58
[44] MingpaoNewspaper;http://www.mingpaohealth.com/cfm/news3.cfm?File=20041102/news/gca1.txt
[45] Jonathan et al, Effects of computerized physician order entry on prescribing practices; Arch Intern Med. 2000;160:2741-2747
[46] Payne et al; Characteristics and override rates of order checks in a practitioner order entry system. AMIA Symp. 2002;:602-6.
[47] Saul et al; Physicians' Decisions to Override Computerized Drug Alerts in Primary Care. Arch Inter Med; Nov 24, 2003; 163, 21; 2625
[48] Anderson RJ, Melikian DM, Gambertoglio JG et al. Prescribing medication in long-term dialysis units. Arch Intern Med1982; 142: 1305–1308
[49] AM J Med Qual 2005; 20(1): 7-14.
[50] Taylor L, Tamblyn R. Reasons for physician non-adherence to electronic drug alerts. Medinfo. 2004;11:1101–5.
[51] Magnus D, Rodgers S, Avery AJ. GPs’ views on computerized drug interaction alerts: questionnaire survey. J Clin Pharm
[52] McConnell TS, Cushing AH, Bankhurst AD, et al: Physician behavior modification using claims data: Tetracycline for upper respiratory infection. West J Med 1982 Nov; 137:448-450
[53] Buck CR Jr, White KL: Peer review: Impact of a system based on billing claims. N Engl J Med 1974 Oct 24; 291:877-883
[54] Brook RH, Williams KN, Rolph JE: Controlling the use and cost of medical services: The New Mexico Experimental Medical Care Review Organization: A Four-Year Case Study, R-2241- 1978
[55] H. van der Sijs, J Aarts, A Vulto, et al. Overriding of Drug Safety Alerts in Computerized Physician Order Entry. J Am Med Inform Assoc. 2006 Mar-Apr; 13(2):138-47.
[56] World Bank statistics. Available http://www.worldbank.org Accessed July 1, 2007.
[57] T.J Chen, L.F. Chou, S.J. Hwang. Patterns of ambulatory care utilization in Taiwan. BMC Health Serv Res. 2006; 6:54
[58] Annette Queiner-Luft, Inez Eggers, Gabriela Stolz, et al. Serial Examination of 20,248 Newborn Fetuses and Infants: Correlations Between Drug Exposure and Major Malformations. Am J Med Genet 1996;63:268-276
[59] M.F. Mayo-Smitha, A Agrawalb. Factors associated with improved completion of computerized clinical reminders across a large healthcare system. Int J Med Info. 2007; 76:710-716
[60] C.M. Ruland; Improving patient safety through informatics tools for shared decision making and risk communication. Int J Med Info. 2004; 73:551-557
[61] A Laxmisan, F Hakimzada, O.R. Sayan. The multitasking clinician: Decision-making and cognitive demand during and after team handoffs in emergency care. Int J Med Info, In Press, Corrected Proof, Available online 23 October 2006,
[62] D.J. France, S Levin, R Hemphill. Emergency physicians - behaviors and workload in the presence of an electronic whiteboard. Int J Med Info. 2005; 74(10):827-837
[63] J.G. Anderson, C.E. Aydin, S.J. Jay. Evaluating health care information systems: methods and applications. Thousand Oaks, CA: Sage; 1994, p 55.
[64] B.K. Kaplan, D Duchon. Combining qualitative and quantitative methods in information systems research: a case study. MIS Q. 1988; 12:570-86.
[65] D.E. Forsythe. Using ethnography to build a working system: rethinking basic design assumptions. Proc AMIA Annu Fall Proc. 1992; 505-9.
[66] V.L. Patel, L.M. Currie. Clinical cognition and biomedical informatics: Issues of patient safety. Int J Med Info. 2005; 74(11-12):869-885
[67] RUBIN J. D. ; FERENCZ C. ; LOFFREDO C. Use of prescription and non-prescription drugs in pregnancy. J Clin Epidemiol 1993;46:581-589
[68] I Lacroix, C Damase-Michel, M Lapeyre-Mestre, J L Montastruc. Prescription of drugs during pregnancy in France. J Lancet 2000;356:1735-6
[69] J J. KUPERMAN, A BOBB, T H. PAYNE, etc. Medication-related Clinical Decision Support in Computerized Provider Order Entry Systems: A Review. J Am Med Inform Assoc. 2007;14:29–40
[70] MI. HARRISON, R KOPPEL, S BAR-LEV, Unintended Consequences of Information Technologies in Health Care—An Interactive Sociotechnical Analysis. J Am Med Inform Assoc. 2007;14:542–549
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