Nursing Documentation Transformation through AI-Enhanced Electronic Health Records and Standardized Terminologies: A Systematic Review

Abstract Background: Nursing documentation plays a pivotal role in ensuring continuity, quality, and safety of care. The integration of electronic health records (EHRs) has facilitated more accurate and accessible records; however, challenges remain regarding documentation burden, workflow interruptions, and limited patient participation. Objective: This systematic review aimed to identify, evaluate, and synthesize recent evidence on facilitators, barriers, and innovations in electronic nursing documentation, with a particular focus on standardized terminologies and emerging artificial intelligence (AI) applications. Methods: Following PRISMA 2020 guidelines, a comprehensive search of PubMed, Scopus, Web of Science, and CINAHL retrieved 215 records. After duplicate removal and screening, 8 empirical studies published between 2021 and 2025 met the inclusion criteria. Data were extracted and synthesized narratively due to methodological heterogeneity. Results: Findings highlight that system usability, organizational support, and adequate training are key enablers of EHR adoption, while infrastructural gaps and technostress pose barriers. Standardized terminologies, including ICNP and the Omaha System, improved documentation consistency and interoperability. Patient participation remained limited, though digital literacy and trust were important factors. Emerging evidence indicates that AI-assisted tools can reduce documentation time, improve accuracy, and alleviate workload. Conclusion: EHRs hold transformative potential for nursing documentation, yet their success depends on workflow- aligned system design, validated intelligent technologies, and inclusive approaches that enhance both professional practice and patient engagement.