Purpose:Patients with in-hospital stroke (IHS) often present with atypical symptoms, leading to delayed workfows and poorer outcomes compared with those experiencing strokes in community settings. This study established a nurse-led stroke assessment system integrated with the PDCA (Plan-Do-Check-Act) cycle to facilitated early-detection of IHS and improve treatment efciency and quality. Method:A total of 479 patients with IHS from 2019 to 2025 were included (baseline group: 51; post-intervention group: 428). During the Plan and Do phases, a dual-track support system led by level N4 nurses was established, incorporating high-fdelity simulations and visual assessment tools adapted from focused assessment with sonography for trauma (FAST). During the Check and Act phases, Microsoft Power BI was used to monitor process bottlenecks and support iterative refnement of the system. Statistical analyses included t tests and chi-square tests and standard deviation (SD) to assess process stability. Patients with stroke mimics were strictly excluded. Result: Following implementation, the mean onset to computed tomography (CT) time was reduced from 222 minutes to 85 minutes (p < .001), reaching 66 minutes in 2025. The SD decreased from 72 to 25, indicating enhanced process stability, and the immediate notifcation rate reached 100%. Reperfusion therapy rates increased from 2.4% to 11.4% (p < .05), and the 3-month favorable functional recovery rate (modifed Rankin scale score 0–2) increased from 22.2% to 35.7% (p < .05). Baseline characteristics, including admission National Institutes of Health Stroke Scale (NIHSS) score, age, and comorbidities, showed no signifcant diferences between groups (p > .05). Conclusion: The nurse-led stroke assessment system integrated with the PDCA cycle efectively addressed a critical gap in IHS care. Through standardized training and real time monitoring, this system enhanced nursing responsiveness and ensured the stability and replicability of stroke care across departments.