Diagnostic Accuracy of Pressure Injury Staging Among Nurses: A Multisite Study Using Knowledge Assessment and Image-Based Evaluation.

This study aims to evaluate nursing staff knowledge of the pressure injury (PI) staging system, assess their accuracy in classifying PIs using a photo-based assessment and explore factors associated with performance outcomes in tertiary hospitals in Saudi Arabia. A cross-sectional design was used. The target population was registered nurses (RNs) who had direct contact with admitted patients with PIs during the previous 2 years in three tertiary hospitals in Saudi Arabia. A total of 330 RNs participated in this study. Data were collected through an online survey using the Pressure Ulcer Prevention Knowledge Test related to PI stages, which included 21 items, and a photo-based PI staging test that included 18 photographs. The survey took approximately 10-15 min to complete. The data were statistically analysed using descriptive and correlational statistics. Among 572 eligible RNs, 330 completed the online survey and were included in the analysis. The findings indicated that the average RN knowledge score was 62.54%, suggesting insufficient knowledge of the PI staging system. This finding was consistent with the average accuracy of 62.04% in classifying the PI photographs according to the staging system. Moreover, no significant associations were observed between RNs' knowledge of the PI staging system or their ability to accurately stage PIs and their sex, age, work experience or education level. Significant gaps were identified in nurses' knowledge and accuracy in staging PIs despite relatively high educational attainment and workshop attendance. Given the importance of accurate PI staging in standardized assessment, communication, documentation, monitoring and healthcare resource allocation, these findings highlight the need for strategies to support and improve the delivery of quality patient care. Targeted competency-based training and emerging technologies, including artificial intelligence-driven image analysis, may help improve staging accuracy. Further research is needed to evaluate the clinical feasibility and impact of these approaches.