[Technology-Enabled Nursing Practice: Clinical Decision Support, Early Warning Analytics, and Human-Centered Care]

This article was written to investigate technology-enabled nursing practice, with particular attention given to the integrated use of clinical decision support systems, artificial intelligence (AI)-driven early warning analytics, and human-centered care. As digital health technologies, electronic health records, remote monitoring, and AI continue to evolve rapidly, nursing practice has progressively shifted away from its former singular reliance on experiential judgment toward care models that incorporate data analytics, risk prediction, and real-time decision support. Evidence indicates that clinical decision support systems can enhance consistency in care processes, improve nurse recognition of patient deterioration, and support prioritization and interprofessional communication. Likewise, AI-driven early warning systems can leverage high-dimensional clinical data to detect patient deterioration earlier, thereby improving patient safety and quality of care. However, the integration of these technologies may also introduce challenges such as alert fatigue, workflow misalignment, reduced professional autonomy, and the erosion of the relational dimensions of care. Therefore, technology should be regarded not merely as an auxiliary tool but as a foundational element of contemporary nursing practice. Its design and implementation must align with nursing workflows, reinforce clinical reasoning, address ethical governance, and preserve patient dignity and human-centered values. Future efforts should prioritize nurse-led technology evaluations, education and training, and organizational governance to optimize patient outcomes and support professional development in increasingly technology-integrated nursing environments.