Development and validation of a workload prediction tool for nurses in pediatric intensive care units - The QuantI2S tool

Introduction Nursing workload in pediatric intensive care units is complex and increasingly demanding. Effective staffing is essential for positive patient outcomes, as inadequate coverage correlates with higher mortality and readmission rates. Current staffing tools have limitations and fail to account for the unique challenges of pediatric care. Objective To develop and validate a workload prediction tool for pediatric intensive care nurses to enhance decision-making and resource allocation. Methods The QuantI 2 S tool was developed through literature review and expert consensus, then implemented in a 24-bed Pediatric Intensive Care Unit. Validation involved: 1) correlation with the current gold standard, 2) inter-rater reproducibility, and 3) predictive accuracy. The bedside nurse and clinical nurse specialist completed the QuantI 2 S two hours before shift end (prospective score), while an independent reviewer calculated a retrospective score from chart reviews. Agreement was assessed using Bland-Altman plots and Intra-Class Correlation (ICC). Results A total of 172 patient-observations involving 45 patients were analyzed (July–August 2016). Compared with the gold standard, QuantI 2 S showed excellent reliability ( r s = 0.738, 95% CI [0.624–0.822], p = 0.001). ICC for prospective scores was strong (0.990, 95% CI [0.985–0.993]). Bland-Altman analysis revealed near-perfect agreement (mean difference −0.03). Prospective and retrospective scores also showed excellent concordance (ICC = 0.916, 95% CI [0.872–0.946]). Discussion and conclusion QuantI 2 S accurately predicts pediatric intensive care nursing workload, demonstrating excellent reliability and ease of use. By integrating nursing activities and child-specific factors, it provides a robust framework for optimizing staffing and improving patient care.