Artificial Intelligence in Preventing Nursing Errors in Psychiatric Units: A Review Study

Background and Aims: Nursing errors in psychiatric units can significantly impact patient safety, leading to mismanagement of medications, delayed interventions, and improper assessments. The integration of Artificial Intelligence (AI) in healthcare has introduced innovative solutions to minimize these errors and enhance nursing care quality. This systematic review examines the role of AI in preventing nursing errors in psychiatric settings. Methods: A literature review was conducted using databases such as PubMed, Science Direct, Scopus, Web of Science, and Google Scholar. Articles published between ۲۰۱۵ and ۲۰۲۵ were analyzed based on AI applications in psychiatric nursing. A total of ۵۰ studies were selected for review, emphasizing AI-driven interventions, predictive analytics, and automated decision support systems. Results: The findings indicate that AI technologies, including machine learning algorithms, natural language processing (NLP), and predictive analytics, significantly reduce nursing errors. AI-assisted medication management systems were shown to decrease prescription errors by ۵۵%, while chatbots and virtual assistants improved response time to patient needs by ۴۰%. Furthermore, AI models for behavioral risk assessment demonstrated high accuracy in predicting aggressive behaviors in psychiatric patients, allowing for timely interventions. Conclusion: AI has proven to be an effective tool in enhancing patient safety and reducing nursing errors in psychiatric care. However, challenges such as ethical concerns, data privacy issues, and the need for AI training among nurses must be addressed to optimize implementation. Future research should focus on integrating AI-driven tools into clinical decision support systems (CDSS) to ensure comprehensive psychiatric care with minimal errors.

کلیدواژه ها:

Artificial Intelligence ، Psychiatric Nursing ، Nursing