Nursing Workload Assessment in a Stroke Unit at a Portuguese Hospital: A Prospective Observational Study

ABSTRACT Background The Nursing Activities Score is a promising tool to calculate nursing workload in Intensive and Intermediate Care Units of different typologies. Aim To assess nursing workload in a Stroke Unit using the Portuguese version of the Nursing Activities Score. Study Design Prospective observational study conducted with patients admitted to a Stroke Unit from November 2024 to February 2025. The study was approved by the Ethics Committee and was reported in accordance with the STROBE guidelines. Results The study included 69 patients admitted to the Stroke Unit for more than 24 h. Each participant generated an average nursing workload of 45.30 ± 7.39 points/day. The Stroke Unit recorded a median nursing workload of 159.40 (IQR: 126.60–211.90) points/day and an average occupancy rate of 82.0%. The days of admission and discharge are periods that tend to generate greatest nursing workload. There were statistically significant differences between the first and the last nursing workload assessments. Altered state of consciousness and fibrinolysis in the Stroke Unit are associated with greater nursing workload on the admission day. Conclusions This study revealed the potential of the Nursing Activities Score as a tool to assess nursing workload in Intermediate Care Units, such as Stroke Units. The Nursing Activities Score showed an imbalance between nursing resources and reported care needs. The nursing workload was higher in the first assessment than in the last, reflecting the trend towards recovery of autonomy and improvement of the participants' clinical condition throughout the length of stay. There are demographic and clinical characteristics present at the time of admission that may be associated with a higher nursing workload. Relevance to Clinical Practice Nursing workload assessment using the Nursing Activities Score enables identification of patients and periods with the greatest care needs, thereby supporting decision‐making in complex environments such as Stroke Units.