Combatting Alert Fatigue in Nursing Practice
Chinetta Maze, RN
This project highlights how alert fatigue and clinical workflows affect medication safety and shares evidence‑based strategies to reduce alert‑related errors.
Reducing Alert‑Related Medication Errors
Frequent non-actionable EHR alerts, heavy documentation demands, and complex medication administration steps disrupt clinical focus and intensify alert fatigue.
Evidence-Based Recommendations
• Optimizing alert relevance by refining notification thresholds and streamlining medication workflows to eliminate redundant data.
• Collaboratively redesigning clinical decision support with frontline nurses to ensure alerts are actionable and reduce safety risks.
• Providing structured training on appropriately using AI in clinical workflows, emphasizing critical thinking, clinical judgment, and safe medication practices.
Medication errors are preventable situations requiring quality improvement approaches to prevent negative safety trends (Hill and Jones, 2025).
A systematic review provides evidence-based data that supports the clinical value of AI technologies in enhancing medication safety and reducing error rates. (Muhammad, et al., 2025)
Yassoub et al. reports electronic medical record (EMR) performance improvement projects that consider and address staff input, patient safety, and performance metrics can raise an organization's clinical performance (2024).
References
Hill, L., & Jones, C. T. (2025). Development of a standard operating procedure for
investigational product rights of administration in clinical trials. Journal of Clinical and Translational Science, 9(1), 7. https://doi.org/10.1017/cts.2025.10181
Muhammad Waleed Ahmad, Exploring the impact of artificial intelligence integration on medication error reduction: A nursing perspective, Nurse Education in Practice, Volume 86, 2025, 104438, ISSN 1471-5953, https://doi.org/10.1016/j.nepr.2025.104438. (https://www.sciencedirect.com/science/article/pii/S1471595325001945)
Yassoub, R., Elshehabi, N., & Alyafei, K. (2024). Electronic medical record redesign to improve patient safety and use of non-medication orders by clinicians. Eastern Mediterranean Health Journal, 30(3), 229+. https://link-gale-com.lib-proxy.jsu.edu/apps/doc/A792046810/AONE?u=jack26672&sid=ebsco&xid=4bc74405Alqaraleh, M., Almagharbeh, W. T., & Ahmad, M. W. (2025). Exploring the impact of artificial intelligence integration on medication error reduction: A nursing perspective. Nurse Education in Practice, 86, 104438. https://doi.org/10.1016/j.nepr.2025.104438
Errors often stem from system stressors like alert fatigue and cognitive over-load, requiring critical focus on clinical protocol integrity.
Each medication interaction must be reviewed with the provider. When multiple medications have alerts, nurses may fail to address each alert.
THE IMPACT
Analyzing Workflow
This project examines how frequent, non-actionable EHR alerts and documentation demands cause alert fatigue and medication errors. By analyzing the intersection of informatics and clinical workflows, it provides evidence-informed strategies to optimize decision support systems.
Technology, People, and Processes: The Key to Medication Safety
[ 01 ]
Clinical Decisions Support Systems enhance medication safety and reduce errors
Clinical decision support systems (CDSS) such as smart infusion pumps, barcode medication administration (BCMA), and predictive analytics are reshaping medication safety.
[ 02 ]
Real-world feed-back from real nurses
Qualitative data collected during this study reveled challenges from the nursing perspective: alert fatigue, usability concerns, and varying levels of digital confidence.
[ 03 ]
Real-world solutions. Education is the key.
AI has the potential to transform medication safety in nursing. Yet, its true impact will depend on how well nurses are prepared to integrate these tools into their clinical reasoning and workflows. Nurses should be prepared educationally, ethically, and practically.
Future research and policy should prioritize interdisciplinary efforts that advance not only the technology itself but also the educational frameworks that empower nurses to use it confidently, critically, and competently. Adequate training includes user engagement and professional development.