A Systematic Review of the Performance Characteristics of Clinical Event Monitor Signals Used to Detect Adverse Drug Events in the Hospital Setting

Abstract

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 1985–2006, 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% CI, 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.