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Effective communication in healthcare is a cornerstone for ensuring patient safety and optimal clinical outcomes. This narrative review explores the impact of poor communication between nurses and internal medicine physicians on patient safety. The review highlights how communication breakdowns contribute to medication errors, diagnostic delays, and suboptimal care coordination. Drawing on case studies and evidence, this paper also examines the psychological and workplace challenges that arise from inadequate communication, including stress, reduced morale, and strained interprofessional collaboration. Proposed solutions such as standardized communication tools (e.g., SBAR), interdisciplinary team meetings, and enhanced training programs are discussed to mitigate these barriers and foster a culture of effective collaboration. By addressing these issues, healthcare institutions can significantly enhance patient safety and care quality.Aim of work: The aim of this review is to examine the critical impact of poor communication between nurses and internal medicine physicians on patient safety. It seeks to identify the common barriers that hinder effective communication in healthcare settings, such as hierarchical structures, workload pressures, and differences in professional training. Additionally, the review explores the adverse consequences of communication breakdowns, including medication errors, diagnostic delays, and compromised care transitions. By analyzing case studies and existing evidence, this work highlights the significance of addressing these challenges and proposes evidence-based strategies, such as standardized communication tools, interdisciplinary meetings, and targeted training programs, to foster better collaboration and improve patient outcomes. Ultimately, the review emphasizes the importance of creating a culture that prioritizes clear, respectful, and efficient communication within healthcare teams to enhance patient safety and care quality.

The integration of artificial intelligence in restorative dentistry represents a transformative evolution in diagnostic accuracy and treatment efficacy. This article investigates the multifaceted impact of AI technologies on restorative dental practices, emphasizing several core objectives. Firstly, it evaluates how AI enhances diagnostic precision and optimizes treatment planning by employing machine learning, image recognition, and natural language processing. These advanced techniques reduce human error and improve efficiency, ensuring successful treatment outcomes. Secondly, the review explores AI's effectiveness in developing innovative dental materials and techniques. By analyzing vast datasets, AI enables a deeper understanding of the interplay between dental materials and biological factors, leading to the creation of improved biomaterials that enhance both longevity and aesthetic quality. Thirdly, the study assesses the personalized approach facilitated by AI, which tailors treatment recommendations based on comprehensive patient data, ultimately improving patient satisfaction and outcomes. Moreover, the seamless integration of advanced imaging technologies with AI streamlines procedural efficiency, significantly reducing chair time and enhancing accuracy in restorative procedures. Despite these advancements, several barriers hinder the widespread adoption of AI in dentistry, including skepticism regarding algorithm reliability and a lack of standardized implementation protocols. By addressing these challenges through robust clinical validation and creating cohesive integration strategies, dental professionals can harness AI technologies to revolutionize patient care. This article aims to inspire ongoing research and dialogue, paving the way for future innovations that bolster the efficacy of restorative interventions and redefine patient experiences in dental health.