Adequate nurse staffing is crucial for optimal patient outcomes, especially in critical care settings. Evidence-based tools that guide staffing decisions are essential for enhancing clinical care. Patient acuity tools represent one such evidence-based method. This article explores the effectiveness of a neonatal acuity tool within an Australian tertiary neonatal healthcare environment, specifically examining its role in classifying patient acuity and determining nurse-to-patient staffing ratios in comparison to current practices.
A study was conducted over a 10-week period in 2023 within a Neonatal Intensive Care Unit (NICU) and a Special Care Baby Unit (SCBU). Data was collected using a neonatal acuity tool, assessing patient conditions across 16 domains at two points daily – before morning and evening nursing shift changes. This comprehensive data collection encompassed all newborns admitted to these units.
The study revealed significant insights into acuity levels and staffing needs. Among ventilated newborns cared for with a 1:1 nurse-to-patient ratio, a substantial 78% registered scores within the L4-high acuity band (score ≥ 26). The remaining 22% of scores fell into the L3-high acuity band (18-25). For newborns receiving non-invasive respiratory support in the NICU at a 1:1 staffing ratio, a notable difference emerged. The proportion of patients scoring within the L4 acuity band was significantly higher in the nasal high-flow group compared to the nasal continuous positive airway pressure group (P = 0.032). This effect was not observed in NICU settings with a 1:2 staffing ratio, nor in SCBU settings with 1:2 or 1:3 ratios for newborns on nasal high-flow.
The findings of this study, evaluating a neonatal acuity classification system against current nurse-to-patient staffing allocations in an Australian tertiary NICU, suggest that refining staffing ratios for specific patient groups receiving respiratory support is feasible and potentially beneficial. Critical care acuity tools offer a data-driven approach to optimize nurse staffing, ensuring that resources are allocated effectively based on patient needs.
