Intelligent Workflow Automation Systems to Enhance Nursing Efficiency and Patient Safety
Abstract
The use of intelligent workflow automation has been attracting growing interest, as nursing practice is under sustained pressure from increased workload, documentation requirements, and ongoing patient safety risks. Based on findings from nursing informatics and clinical workflow studies, it is evident that fragmented task coordination and manual procedures contribute to delays, increased cognitive load, and avoidable errors in routine care. Automation models that combine event-driven task coordination, timely clinical notifications, and close integration with electronic health records have been linked to shorter task execution time, fewer workflow discontinuities, and fewer medication-related incidents when supported by real nursing practice. The systems facilitate earlier identification of patient deterioration and enhance uniformity in safety-related interventions, while reducing non-clinical workload requirements. This research study draws on diverse literature, which warns that the concept of automation deployed without consideration of usability, governance, and professional context may cause alert overload, undermine clinical trust, and lead to misjudgment. The evidence suggests that intelligent workflow automation reinforces nursing efficiency and patient safety only when incorporated as a social-technical solution that does not disrupt nursing autonomy, transparency, and represents real clinical practice.
Keywords: Nursing Informatics, Clinical Workflow Automation, Patient Safety Technologies, Human-Centered Computing, Healthcare Process Optimization, Real-Time Clinical Alerts, Decision Support Systems, Cognitive Load Reduction, Health Information Systems, Digital Transformation in Nursing, EHR, Electronic Health Record, AI Decision Support
Keywords:
Nursing Informatics, Clinical Workflow Automation, Patient Safety Technologies, Human-Centered Computing, Healthcare Process Optimization, Real-Time Clinical Alerts, Decision Support Systems, Cognitive Load Reduction, Health Information Systems, Digital Transformation in Nursing, EHR, Electronic Health Record, AI Decision SupportDOI
https://doi.org/10.22270/jddt.v16i2.7554References
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