A systematic review of the performance characteristics of clinical event monitor signals used to detect adverse drug events in the hospital setting

被引:61
|
作者
Handler, Steven M.
Altman, Richard L.
Perera, Subashan
Hanlon, Joseph T.
Studenski, Stephanie A.
Bost, James E.
Saul, Melissa I.
Fridsma, Douglas B.
机构
[1] VAPHS, Div Clin Geriatr, Dept Med, Sch Med, Pittsburgh, PA USA
[2] VAPHS, Dept Biomed Informat, Sch Med, Pittsburgh, PA USA
[3] VAPHS, Grad Sch Publ Hlth, Dept Biostat, Pittsburgh, PA USA
[4] VAPHS, Sch Pharm, Dept Pharm & Therapeut, Pittsburgh, PA USA
[5] VAPHS, Ctr Res Hlth Care, Dept Med, Pittsburgh, PA USA
[6] VAPHS, Geriatr Res Educ & Clin Ctr, Pittsburgh, PA USA
[7] Vet Affairs Pittsburgh Healthcare Syst, Ctr Hlth Equ Res, Pittsburgh, PA USA
基金
美国国家卫生研究院;
关键词
D O I
10.1197/jamia.M2369
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: We conducted a systematic review of pharmacy and laboratory signals used by clinical event monitor systems to detect adverse drug events (ADEs) in adult hospitals. Design and Measurements: We searched the MEDLINE, CINHAL, and EMBASE databases for the years 19852006, and found 12 studies describing 36 unique ADE signals (10 medication levels, 19 laboratory values, and 7 antidotes). We were able to calculate positive predictive values (PPVs) and 95% confidence intervals (CIs) for 15 signals. Results: We found that PPVs ranged from 0.03 (95% Cl, 0.03-0.03) for hypokalemia, to 0.50 (95% CI, 0.39-0.61) for supratherapeutic quinidine level. In general, antidotes (range = 0.09-0.11) had the lowest PPVs, followed by laboratory values (range = 0.03-0.27) and medication levels (range = 0.03-0.50). Conclusion: Data from this study should help clinical information system and computerized decision support producers develop or improve existing clinical event monitor systems to detect ADEs in their own hospitals by prioritizing those signals with the highest PPVs.
引用
收藏
页码:451 / 458
页数:8
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