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First published April 25, 2007 as JAMIA PrePrint; doi:10.1197/jamia.M2369
Journal of the American Medical Informatics Association 2007;14(4):451-458
© 2007 American Medical Informatics Association

A more recent version of this article appeared on July 1, 2007
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Submitted on January 6, 2007
Accepted on April 10, 2007

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

Steven M. Handler MD, MS1*, Richard L. Altman MD2, Subashan Perera PhD3, Joseph T. Hanlon PharmD, MS4, Stephanie A. Studenski MD, MPH5, James E. Bost MS, PhD6, Melissa I. Saul MS7, and Douglas B. Fridsma MD, PhD7

Affiliation of the authors: 1 Division of Geriatric Medicine, Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA; Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA ; 2 School of Medicine, University of Pittsburgh, Pittsburgh, PA; 3 Division of Geriatric Medicine, Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA; Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA ; 4 Division of Geriatric Medicine, Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA; Department of Pharmacy and Therapeutics, School of Pharmacy, University Pittsburgh, Pittsburgh, PA; Center for Health Equity Research, Veterans Affairs Pittsburgh Healthcare System (VAPHS), Pittsburgh, PA; Geriatric Research Education and Clinical Center, VAPHS, Pittsburgh, PA ; 5 Division of Geriatric Medicine, Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA; Geriatric Research Education and Clinical Center, VAPHS, Pittsburgh, PA ; 6 Center for Research on Health Care, Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA ; 7 Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA

* To whom correspondence should be addressed.

Objective Despite demonstrated benefits, few healthcare organizations have implemented clinical event monitors to detect adverse drug events (ADEs). The objective of this study was to conduct a systematic review of pharmacy and laboratory signals used by clinical event monitors to detect ADEs in hospitalized adults.

Design We performed a comprehensive search of MEDLINE, CINHAL and EMBASE to identify studies published between 1985 through 2006. Studies were included if they: described a clinical event monitor to detect ADEs in an adult hospital setting; described laboratory or pharmacy ADE signals; and, provided positive predictive values (PPVs) or information to allow the calculation of PPVs for individual ADE signals.

Measurements We calculated overall estimates of PPVs and 95% confidence intervals (CIs) for signals reported in 2 or more studies and contained no evidence heterogeneity. Results were examined by signal category: medication levels, laboratory tests, or antidotes.

Results We identified 12 observational studies describing 36 unique ADE signals. Fifteen signals (3 antidotes, 4 medication levels, and 8 laboratory values) contained no evidence of heterogeneity. The pooled PPVs for these individual signals ranged from 0.03 [CI=0.03-0.03] for hypokalemia, to 0.50 [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 (0.03-0.27), and medication levels (0.03-0.50).

Conclusion Results from this study should help clinical information system and computerized decision support producers develop or improve existing clinical event monitors to detect ADEs in their own hospitals by prioritizing those signals with the highest PPVs.




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