Nurses' Knowledge of Insensible Water Loss and the Evolution of a Digital Decision-Support Tool for Personalized...

Background/Objectives: Fluid balance management is a core nursing competency, particularly in high-acuity settings. However, the assessment of insensible water loss remains challenging due to the lack of standardized methods, which may increase variability in clinical reasoning. In this context, digital tools may support a more structured and personalized approach. This study aimed to assess nurses' knowledge of fluid balance and insensible water loss [perspiratio insensibilis (PI)] and to evaluate the usability and perceived quality of a pilot digital clinical decision-support tool (CareBalance-N). Secondary analyses explored differences across clinical settings and the association between knowledge level and app evaluation. Methods: A cross-sectional observational study was conducted among 50 nurses working in three clinical settings: hemodialysis (n = 20; 40%), internal medicine (n = 15; 30%), and intensive care (n = 15; 30%). Knowledge was assessed using a structured questionnaire (score range: 0-100), while the usability and perceived quality of the digital application for fluid balance were evaluated using the User Version of the Mobile App Rating Scale (uMARS). Differences between settings were analyzed using ANOVA, and correlations were assessed using Pearson's correlation coefficient. Results: The mean knowledge score was 67.6 ± 7.7, with significant differences across clinical settings [F(2, 47) = 28.4; p < 0.001]: hemodialysis 73.6 ± 6.0, intensive care 66.9 ± 4.7, and internal medicine 60.3 ± 5.1. The mean uMARS score was 3.91 ± 0.17, with particularly high ratings for functionality (4.19 ± 0.17) and perceived impact (4.17 ± 0.16). A strong positive correlation was found between knowledge scores and app evaluation (r = 0.943; p < 0.001). Conclusions: These findings highlight variability in nursing knowledge across clinical settings and suggest that digital tools such as CareBalance-N may represent a promising approach to facilitate more structured clinical reasoning and fluid balance assessment. However, these potential benefits require validation in real-world clinical settings. Further studies are needed to evaluate their impact on decision-making processes, the accuracy of fluid balance assessment, patient safety, and clinical outcomes.