Customizing clinical decision support to prevent excessive drug–drug interaction alerts
Abstract
The estimated rate of drug–drug interactions (DDIs) varies widely based on the populations studied and the interactions selected for inclusion.1,2 DDIs are a significant cause of patient morbidity and mortality and increased hospitalization costs but are quite predictable and, therefore, preventable.3 This predictability, combined with knowledge of DDI mechanisms, should make DDIs ideal candidates for clinical decision support (CDS), yet DDI CDS systems have not lived up to their potential to improve patient safety. Commercial software programs designed to assist pharmacists during prescription processing have included DDI alert software for many years. With the implementation of computerized prescriber order entry (CPOE), DDI software produces prodigious numbers of alerts for both pharmacists and physicians. The commercial DDI software used by the department of pharmacy services at the University of Washington (UW) Medicine Health System produces nearly 25,000 alerts in a typical 24-hour period from approximately 900 inpatient beds. Exposing practitioners to this number of alerts causes user desensitization and alert fatigue.4,5 Alert fatigue is a major problem with DDI CDS systems and is often the result of DDI software that has poor specificity, with alerts that are considered irrelevant overridden about 90% of the time.6–10 Computerized DDI CDS does not achieve its intended function when its recommendations are almost universally ignored and “work arounds” are actively pursued.
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All interactions were reviewed before CDS implementation, causing 65% of all major interactions to be reclassified to lower levels.
“All interactions were reviewed before the implementation of CDS, causing 65% of all major interactions to be reclassified to lower levels [15].”
From Drug interaction alert override rates in the Meaningful Use era: No evidence of progress (2014) · cites this paper as [15]
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Drug interaction alert override rates in the Meaningful Use era: No evidence of progress
Bryant, A. D., Fletcher, G. S., & Payne, T. H. (2014) · Applied Clinical Informatics · doi:10.4338/aci-2013-12-ra-0103 · Cited by 172 · see citing works
Horn, J., & Ueng, S. (2019) · Annals of Pharmacotherapy · doi:10.1177/1060028019863419 · Cited by 26 · see citing works
Self-citation
- Authors
- Horn, J. R., Hansten, P. D., Osborn, J. D., Wareham, P., & Somani, S.
- Affiliations
- University of Washington (US)
- University of Wisconsin–Madison (US)
- University of Wisconsin Health (US)
- Corresponding author
- Horn, John R.
- Venue
- American Journal of Health-System Pharmacy
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-04-15
- Volume
- 68
- Issue
- 8
- Pages
- 662-664
- ISSN
- 1079-2082 (ISSN-L)
- 1535-2900
- OpenAlex
- W1982086950
- Cited by
- 26
- References
- 15
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 1 · 2023: 2 · 2021: 3 · 2019: 2 · 2017: 2 · 2016: 4 · 2015: 2 · 2014: 3 · 2013: 1 · 2012: 2
- FWCI
- 4.10
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- American Journal of Health-System Pharmacy (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Medicine › Geriatrics and Gerontology › Pharmaceutical Practices and Patient Outcomes
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Toxicology › Pharmacovigilance and Adverse Drug Reactions
- Keywords
- drug-drug interactions, clinical decision support, alarm fatigue, computerized physician order entry, patient safety, medication errors, inpatient prescribing
- MeSH terms
- Drug Interactions, Humans, Medication Errors, Pharmacists, Decision Support Systems, Clinical, Medical Order Entry Systems
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