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Clinical Relevance of Automated Drug Alerts From the Perspective of Medical Providers

VA Greater Los Angeles Healthcare System-West Los Angeles and David Geffen School of Medicine, University of California, Los Angeles, jeffrey.spina{at}med.va.gov

Peter A. Glassman, MBBS, MSc

VA Greater Los Angeles Healthcare System-West Los Angeles; David Geffen School of Medicine, University of California, Los Angeles; and RAND, Santa Monica, California

Pamela Belperio, PharmD, BCPS

VA Greater Los Angeles Healthcare System-West Los Angeles, California

Rumi Cader, MD, MPH

VA Greater Los Angeles Healthcare System-West Los Angeles, and David Geffen School of Medicine, University of California, Los Angeles

Steven Asch, MD, MPH

staff for Health Services Research at the VA Greater Los Angeles Healthcare System-West Los Angeles, California, and David Geffen School of Medicine, University of California, Los Angeles

Primary Care Investigative Group of the VA Los Angeles Healthcare System

The authors used a real-time survey instrument and subsequent focus group among primary care clinicians at a large healthcare system to assess usefulness of automated drug alerts. Of 108 alerts encountered, 0.9% (n = 1) represented critical alerts, and 16% (n = 17) were significant drug interaction alerts. Sixty-one percent (n = 66) involved duplication of a medication or medication class. The rest (n = 24) involved topical medications, inhalers, or vaccines. Of the 84 potentially relevant alerts, providers classified 11% (9/84), or about 1 in 9, as useful. Drug interaction alerts were more often deemed useful than drug duplication alerts (44.4% versus 1.5%, P< .001). Focus group participants generally echoed these results when ranking the relevance of 15 selected alerts, although there was wide variance in ratings for individual alerts. Hence, a "smarter" system that utilizes a set of mandatory alerts while allowing providers to tailor use of other automated warnings may improve clinical relevance of drug alert systems.

Key Words: attitude of health personnel • clinical decision support systems • drug interactions • computer-assisted drug therapy • medication errors • prevention • control

American Journal of Medical Quality, Vol. 20, No. 1, 7-14 (2005)
DOI: 10.1177/1062860604273777


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