High-priority drug-drug interaction clinical decision support overrides in a newly implemented commercial computerized provider order-entry system: Override appropriateness and adverse drug events
Open accessAbstract
Objective: The study sought to determine frequency and appropriateness of overrides of high-priority drug-drug interaction (DDI) alerts and whether adverse drug events (ADEs) were associated with overrides in a newly implemented electronic health record. Materials and Methods: We conducted a retrospective study of overridden high-priority DDI alerts occurring from April 1, 2016, to March 31, 2017, from inpatient and outpatient settings at an academic health center. We studied highest-severity DDIs that were previously designated as “hard stops” and additional high-priority DDIs identified from clinical experience and literature review. All highest-severity alert overrides (n = 193) plus a stratified random sample of additional overrides (n = 371) were evaluated for override appropriateness, using predetermined criteria. Charts were reviewed to identify ADEs for overrides that resulted in medication administration. A chi-square test was used to compare ADE rate by override appropriateness. Results: Of 16 011 alerts presented to providers, 15 318 (95.7%) were overridden, including 193 (87.3%) of the highest-severity DDIs and 15 125 (95.8%) of additional DDIs. Override appropriateness was 45.4% overall, 0.5% for highest-severity DDIs and 68.7% for additional DDIs. For alerts that resulted in medication administration (n = 423, 75.0%), 29 ADEs were identified (6.9%, 5.1 per 100 overrides). The rate of ADEs was higher with inappropriate vs appropriate overrides (9.4% vs 4.3%; P = .038). Conclusions: The override rate was nearly 90% for even the highest-severity DDI alerts, indicating that stronger suggestions should be made for these alerts, while other alerts should be evaluated for potential suppression.
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High override rates of 56.3%-95.7% have already been described for DDI alerts.
“High override rates of 56.3%-95.7% have already been described for DDI alerts [13, 21, 27–32].”
From Overall performance of a drug–drug interaction clinical decision support system: quantitative evaluation and end-user survey (2022) · cites this paper as [27]
The Results report that 95.7% of DDI alerts presented to providers were overridden, supporting the high end of the cited range. This paper does not report the 56.3% lower end; its rates across DDI pairs ranged from 83.3% to 96.6%. (LLM, conf=0.86)
Experimental — accuracy not yet measuredInterruptive alerts are one of the dominant forms of CDS and have the potential to distract from patient care and increase clinician's cognitive load.
“Interruptive alerts, or pop ups that require end-user action or acknowledgment, are one of the dominant forms of CDS and have the potential to distract from patient care and increase clinician’s cognitive load.”
From Qualitative Study of Inpatient Hospital Medicine Interruptive Alerts and Clinical Decision Support (2026) · cites this paper as [5]
The Introduction (page unavailable) says that too many CDS alerts can cause alert fatigue, leading providers to ignore or override them; the Discussion likewise calls for reducing alert burden. These passages support a potential burden on clinicians, but do not establish that interruptive pop-ups are a dominant form of CDS or specifically that they distract from patient care and increase cognitive load. (LLM, conf=0.79)
Experimental — accuracy not yet measuredThe inherent design of our site's EHR makes interruptive alerts one of the easiest and least expensive forms of CDS to implement, even though they are known to be disruptive and often ineffective.
“The inherent design of our site’s EHR makes interruptive alerts one of the easiest and least expensive forms of CDS to implement, even though they are known to be disruptive and often ineffective. 5 15 16”
From Qualitative Study of Inpatient Hospital Medicine Interruptive Alerts and Clinical Decision Support (2026) · cites this paper as [5]
The Introduction describes alert fatigue, and the Discussion reports that providers overrode nearly all high-priority drug–drug interaction alerts; these passages support the concern that alerts can be disruptive and ineffective. The paper does not say that interruptive alerts are among the easiest or least expensive forms of CDS to implement, or establish that claim about the citing authors’ EHR. (LLM, conf=0.86)
Experimental — accuracy not yet measuredOur study results are in agreement with previous reports.
“Our study results are in agreement with previous reports.”
From Overall performance of a drug–drug interaction clinical decision support system: quantitative evaluation and end-user survey (2022) · cites this paper as [27]
Edrees et al. conducted a retrospective study of overridden high-priority DDI alerts and found an override rate of 87.3% for the highest severity DDI alerts.
“Edrees et al. conducted a retrospective study of overridden high-priority DDI alerts and found an override rate of 87.3% for the highest severity DDI alerts [27].”
From Overall performance of a drug–drug interaction clinical decision support system: quantitative evaluation and end-user survey (2022) · cites this paper as [27]
Edrees et al., Nanji et al. and Wong et al. found override appropriateness rates of 45.4%, 62% and 82%, respectively.
“Edrees et al. [27], Nanji et al. [29] and Wong et al. [31] found override appropriateness rates of 45.4%, 62% and 82%, respectively.”
From Overall performance of a drug–drug interaction clinical decision support system: quantitative evaluation and end-user survey (2022) · cites this paper as [27]
More than half of the generated DDI alerts concerned the interaction between ondansetron and QTc prolonging agents and these were overridden in 96.5% of cases.
“More than half of the generated DDI alerts concerned the interaction between ondansetron and QTc prolonging agents and these were overridden in 96.5% of cases.”
From Overall performance of a drug–drug interaction clinical decision support system: quantitative evaluation and end-user survey (2022) · cites this paper as [27]
Alerts fire so frequently that most are ignored, with prior research demonstrating rates of ignoring as high as 96%.
“Optimal alert volume is unknown, but alerts fire so frequently that most are ignored, with prior research demonstrating rates of ignoring as high as 96%, almost entirely defeating their purpose.”
From Qualitative Study of Inpatient Hospital Medicine Interruptive Alerts and Clinical Decision Support (2026) · cites this paper as [5]
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Qualitative Study of Inpatient Hospital Medicine Interruptive Alerts and Clinical Decision Support
Khan, A., & Schnipper, J. (2026) · Applied Clinical Informatics · doi:10.1055/a-2955-9555
- Authors
- Edrees, H., Amato, M. G., Wong, A., Seger, D. L., & Bates, D. W.
- Affiliations
- Massachusetts College of Pharmacy and Health Sciences (US)
- Brigham and Women's Hospital (US)
- Corresponding author
- Amato, Mary G
- Venue
- Journal of the American Medical Informatics Association
- Publisher
- Oxford University Press (OUP)
- Published
- 2020-04-26
- Volume
- 27
- Issue
- 6
- Pages
- 893-900
- ISSN
- 1067-5027 (ISSN-L)
- 1527-974X
- PMC
- PMC7647273
- OpenAlex
- W3019268698
- Cited by
- 64
- References
- 33
- Citations by year
- 2026: 7 · 2025: 12 · 2024: 7 · 2023: 7 · 2022: 17 · 2021: 9 · 2020: 5
- FWCI
- 8.32
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)
- Locations
- Journal of the American Medical Informatics Association (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- IBM Watson Health
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Medicine › Geriatrics and Gerontology › Pharmaceutical Practices and Patient Outcomes
- Health Sciences › Health Professions › Emergency Medical Services › Patient Safety and Medication Errors
- Keywords
- drug-drug interaction alerts, clinical decision support, alert override, electronic health records, adverse drug reactions, drug safety, computerized physician order entry
- MeSH terms
- Academic Medical Centers, Drug Interactions, Drug Therapy, Computer-Assisted, Female, Humans, Male, Medication Errors, Retrospective Studies, Chi-Square Distribution, Decision Support Systems, Clinical, Medical Order Entry Systems, Electronic Health Records, Drug-Related Side Effects and Adverse Reactions
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