(untitled) (The Review of Diabetic Studies, 2024)
Introduction: Healthcare-associated infections (HAIs) remain a major challenge in hospitals, affecting patient safety, outcomes, and healthcare costs. Traditional infection control often faces limitations due to fragmented communication, inconsistent protocol adherence, and delayed pathogen detection. Multidisciplinary collaboration, combined with AI-assisted tools and digital technologies, offers a promising approach to enhance infection prevention and management (Adams et al., 2020; Birgand et al., 2022). Aim of Work: This study aims to evaluate the impact of coordinated efforts among dentistry, nursing, radiology, laboratory diagnostics, and health informatics on improving infection control outcomes and reducing HAIs. Methods: A mixed-methods design was employed, integrating quantitative audits of clinical documentation with qualitative interviews and focus groups of healthcare professionals. Data from multiple departments were analyzed to assess compliance, efficiency, and effectiveness of infection control practices (Karajizadeh et al., 2021; Maleki Varnosfaderani & Forouzanfar, 2024). Results: Findings indicate that multidisciplinary collaboration and technological integration improve documentation quality, enhance early detection of infections, streamline interventions, and reduce HAIs. Nurses, dentists, radiology staff, and laboratory personnel played crucial roles, supported by health informatics systems enabling real-time monitoring and predictive analytics. Challenges included protocol adherence, staff training, and ethical considerations in AI use. Conclusion: Effective hospital infection control is achieved through the synergy of human expertise, interprofessional collaboration, and AI-supported technologies. Addressing operational and ethical challenges ensures sustainable improvements in patient safety and healthcare quality.