Computerized detection of adverse drug reactions in the medical intensive care unit

被引:28
|
作者
Kane-Gill, Sandra L. [1 ,2 ,3 ]
Visweswaran, Shyam [3 ,4 ,5 ]
Saul, Melissa I. [4 ]
Wong, An-Kwok Ian [4 ,5 ]
Penrod, Louis E. [6 ]
Handler, Steven M. [4 ,7 ,8 ,9 ]
机构
[1] Univ Pittsburgh, Sch Pharm, Dept Pharm & Therapeut, Ctr Pharmacoinformat & Outcomes Res, Pittsburgh, PA 15261 USA
[2] Univ Pittsburgh, Dept Pharm, Med Ctr, Pittsburgh, PA 15261 USA
[3] Univ Pittsburgh, Clin & Translat Sci Inst, Pittsburgh, PA 15261 USA
[4] Univ Pittsburgh, Dept Biomed Informat, Sch Med, Pittsburgh, PA 15261 USA
[5] Univ Pittsburgh, Intelligent Syst Program, Pittsburgh, PA 15261 USA
[6] Univ Pittsburgh, Dept Phys Med & Rehabil, Pittsburgh, PA 15261 USA
[7] Univ Pittsburgh, Div Geriatr Med, Dept Med, Pittsburgh, PA 15261 USA
[8] Vet Affairs Pittsburgh Healthcare Syst VAPHS, Geriatr Res Educ & Clin Ctr GRECC, Pittsburgh, PA USA
[9] VAPHS, Ctr Hlth Equity Res & Promot CHERP, Pittsburgh, PA USA
基金
美国国家卫生研究院;
关键词
Information systems; Decision support systems; Clinical; Adverse drug reaction reporting systems; Intensive care units; Critical care; Safety; Adverse drug event; Drug toxicity; CLINICAL EVENT MONITOR; HOSPITALIZED-PATIENTS; INFORMATION-TECHNOLOGY; PATIENT SAFETY; VANCOMYCIN; ERRORS; NEPHROTOXICITY; SURVEILLANCE; AMINOGLYCOSIDE; THERAPY;
D O I
10.1016/j.ijmedinf.2011.04.005
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Objective: Clinical event monitors are a type of active medication monitoring system that can use signals to alert clinicians to possible adverse drug reactions. The primary goal was to evaluate the positive predictive values of select signals used to automate the detection of ADRs in the medical intensive care unit. Method: This is a prospective, case series of adult patients in the medical intensive care unit during a six-week period who had one of five signals presents: an elevated blood urea nitrogen, vancomycin, or quinidine concentration, or a low sodium or glucose concentration. Alerts were assessed using 3 objective published adverse drug reaction determination instruments. An event was considered an adverse drug reaction when 2 out of 3 instruments had agreement of possible, probable or definite. Positive predictive values were calculated as the proportion of alerts that occurred, divided by the number of times that alerts occurred and adverse drug reactions were confirmed. Results: 145 patients were eligible for evaluation. For the 48 patients (50% male) having an alert, the mean +/- SD age was 62 +/- 19 years. A total of 253 alerts were generated. Positive predictive values were 1.0, 0.55, 0.38 and 0.33 for vancomycin, glucose, sodium, and blood urea nitrogen, respectively. A quinidine alert was not generated during the evaluation. Conclusions: Computerized clinical event monitoring systems should be considered when developing methods to detect adverse drug reactions as part of intensive care unit patient safety surveillance systems, since they can automate the detection of these events using signals that have good performance characteristics by processing commonly available laboratory and medication information. (C) 2011 Elsevier Ireland Ltd. All rights reserved.
引用
收藏
页码:570 / 578
页数:9
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