Advancing Nursing Documentation Through Electronic Health Records, Standardized Terminologies, and Artificial Intelligence: A Systematic Review

Abstract

Objective: This systematic review synthesized evidence on the implementation of electronic health records (EHRs), use of standardized nursing terminologies (e.g., ICNP and Omaha System), and emerging roles of artificial intelligence (AI) in nursing documentation. Methods: Following PRISMA 2020, PubMed, Scopus, Web of Science, and CINAHL were searched on 11 September 2025. The 2021–2025 range was selected to capture post-COVID-19 acceleration in digital transformation and AI adoption in nursing documentation. English-language studies (2021–2025) were screened by two reviewers and appraised using the Joanna Briggs Institute (JBI) and Mixed Methods Appraisal Tool (MMAT). Owing to methodological heterogeneity, data were synthesized narratively. Results: Of 215 records, eight studies met the inclusion criteria: two cross-sectional, two quasiexperimental, one mixed-methods, two qualitative, and one participatory action research. Facilitators of EHR use included staff training, organizational support, and system usability; barriers involved limited infrastructure, technostress, and poor patient engagement. AI-assisted documentation systems showed potential to improve documentation efficiency and accuracy; however, empirical evidence within the included studies was limited and remains preliminary. Conclusions: Integrating EHRs with standardized nursing terminologies can enhance documentation quality, interoperability, and workflow efficiency. Sustainable adoption requires professional education, institutional support, and ethical oversight of AI. Future longitudinal studies should assess long-term outcomes and scalability across settings. These findings provide evidence-based guidance for nursing practice and policy across diverse healthcare settings.