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the claim

Excessive clinical decision support alerts in electronic health records can lead to alert fatigue, causing users to override them without review.

the verdict
SUPPORTED
the evidence backs this
Recorded sources
6 sources for · 0 against

Counts group repeated records of the same source within each side. They do not measure evidence strength or source independence.

Is it true that excessive clinical decision support alerts in electronic health records can lead to alert fatigue, causing users to override them without review?

Yes. Excessive clinical decision support alerts in electronic health records frequently lead to alert fatigue, causing high override rates among clinicians.

Verdict: SUPPORTED · 6 sources for, 0 against · Last checked

The analysis

The retrieved papers consistently support the premise that excessive and non-contextual EHR clinical decision support alerts cause alert fatigue and high rates of unreviewed overrides among clinicians.

Evidence for · 6
Temporal Change in Alert Override Rate with a Minimally Interruptive Clinical Decision Support on a Next-Generation Electronic Medical Record
2020
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Cha, W. C., Jung, W., Yu, J., Yoo, J., & Choi, J. (2020). Temporal Change in Alert Override Rate with a Minimally Interruptive Clinical Decision Support on a Next-Generation Electronic Medical Record. doi.org. https://doi.org/10.3390/medicina56120662

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More for · 5
The Real "Catch" in Clinical Automation: Rethinking Artificial Intelligence for Healthcare Workflows.
2026
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BR, S., A, L., P, N., I, V. I., & R, S. (2026). The Real "Catch" in Clinical Automation: Rethinking Artificial Intelligence for Healthcare Workflows.. doi.org. https://doi.org/10.7759/cureus.111390

Systemic Challenges in EHR Alert Design: A Thematic Analysis of Physician Discourse on X (Formerly Twitter).
2026
Get citation
G, V. & JN, A. (2026). Systemic Challenges in EHR Alert Design: A Thematic Analysis of Physician Discourse on X (Formerly Twitter).. doi.org. https://doi.org/10.1055/a-2945-3280

Integrating clinical decision support systems, nursing vigilance, and physician prescribing patterns to reduce preventable adverse drug events: a structured evidence-based narrative review on human-AI interface in medication safety.
2026
Get citation
MF, A., UO, P., & UC, N. (2026). Integrating clinical decision support systems, nursing vigilance, and physician prescribing patterns to reduce preventable adverse drug events: a structured evidence-based narrative review on human-AI interface in medication safety.. doi.org. https://doi.org/10.3389/fdgth.2026.1831150

Bridging the gap between model performance and clinical practice: A scoping review of artificial intelligence models for drug-drug interaction prediction.
2026
Get citation
DY, R., M, M., & N, M. (2026). Bridging the gap between model performance and clinical practice: A scoping review of artificial intelligence models for drug-drug interaction prediction.. doi.org. https://doi.org/10.1016/j.sapharm.2026.08.002

A Hybrid Rule-Based and Machine Learning-Based Clinical Decision Support System to Support Prescription Review: Development and External Validation Study.
2026
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J, J., KN, H., AJ, K., JH, B., YH, J., S, K., M, J., YM, A., JM, H., SW, C., J, S., S, M., & JY, L. (2026). A Hybrid Rule-Based and Machine Learning-Based Clinical Decision Support System to Support Prescription Review: Development and External Validation Study.. doi.org. https://doi.org/10.2196/101202

What does the evidence say?

The retrieved papers consistently support the premise that excessive and non-contextual EHR clinical decision support alerts cause alert fatigue and high rates of unreviewed overrides among clinicians.

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