Related Experiment Video
Updated: Mar 16, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
Development and validation of a workload prediction tool for nurses in pediatric intensive care units - The QuantI2S
Camille Jutras1, Julien Gardner2, Jean Théroux3
1Faculty of Medecine, Université de Montréal, 2900 Edouard Montpetit Blvd, Montreal, Quebec H3T 1J4, Canada; Pediatric Intensive Care Unit, CHU Sainte-Justine, 3175 Chemin de la Côte-Sainte-Catherine, Montreal, Quebec H3T 1C5, Canada.
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 QuantI2S 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 QuantI2S 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, QuantI2S showed excellent reliability (rs = 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:
QuantI2S 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.
Related Concept Videos
Current Trends in Nursing I
Current Trends in Nursing II
Nursing Interventions II: Selecting and Classifying the Nursing Interventions
Nursing Implementation
The five steps to implementing effective nursing care include reassessing the patient, reviewing and revising the existing nursing care plan, organizing the resources and care delivery, anticipating and preventing complications, and implementing nursing interventions.
Planning Nursing Care I
Nursing Clinical Information System
A Nursing Clinical Information System (NCIS) is a specialized type of healthcare information system tailored to meet the unique needs of nursing practice. It incorporates the principles of nursing informatics to streamline information management and improve the quality of care delivery.
Critical attributes of NCIS include: