Currently accepted at: JMIR Medical Informatics
Date Submitted: Jan 27, 2026
Date Accepted: Oct 27, 2026
This paper has been accepted and is currently in production.
It will appear shortly on 10.2196/92237
The final accepted version (not copyedited yet) is in this tab.
Association Between CDSS Utilisation and Evidence-Based Nursing Practice: Cross-Sectional Multicentre Survey Study among Nurses
ABSTRACT
Background:
Evidence-based nursing (EBN) is considered the gold standard in nursing care, yet the application of evidence-based guidelines remains inconsistent, despite demonstrated benefits for quality and patient safety. Barriers include limited methodological skills, time constraints, restricted access to evidence, and insufficient organisational support. Clinical decision support systems (CDSS) are widely debated for potentially fostering the full spectrum of EBN practice, but evidence in nursing remains heterogeneous and often focuses on isolated process indicators rather than EBN as a comprehensive construct.
Objective:
This study aims to investigate whether the degree of CDSS utilisation is positively associated with putting EBN into practice and what further factors facilitate the path from CDSS utilisation to care following EBN.
Methods:
To this end, a survey was addressed to nurses in three hospitals in Germany and Switzerland that had implemented the same commercial nursing CDSS. The survey captured items related to the dimensions of EBM, the Unified Theory of Acceptance and Use of Technology (UTAUT), cognitive and academic competencies and sociodemographic covariates. To test the hypotheses on the relation between the CDSS, EBN practice and facilitating factors, a structural equation model (SEM) was estimated (n=258 participants).
Results:
The SEM revealed that the degree of utilising a CDSS was a key predictor of EBN practice, having a significant positive effect (β=0.543, p<.001). Conversely, the technology acceptance factors were a key driver of CDSS utilisation (β=0.679, p<.001). Among the competencies of nursing staff, only methodological and scientific competencies exerted a significant positive influence on EBN (β=0.444, p=.007), similar to the age of the CDSS users (β=0.365, p=.037). Overall, the model explained a high proportion of the variance in EBN (R²=.801).
Conclusions:
The findings show that digital decision support in nursing cannot only improve process adherence but also strengthen the entire spectrum of EBN practice, comprising the interaction between science and practice (knowledge), attitude and practice (trust) and science and daily work (daily practice). The findings also provide insights into what should be considered when planning to increase the acceptability of a CDSS as a vehicle to foster EBN practice. Based on the facilitating factors identified, educational measures can be tailored to build an EBN-friendly environment.
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