Intelligent Recommendation System for Assessing Hand Hygiene of Healthcare Workers

Nosocomial infections pose a significant threat to patient safety in healthcare settings globally, with hand hygiene being a crucial preventive measure. This study aims to develop an intelligent recommendation system encapsulated in a mobile application to assess and enhance healthcare workers' hand hygiene practices, thereby reducing nosocomial infections. The system was developed using the MVVM architecture, ensuring a robust, scalable, and maintainable solution. The application was designed in compliance with iOS Human Interface Guidelines to ensure user-friendliness. It includes departmental, workplace, and individual assessment checklists, with a scoring system ranging from 1 to 25 for each item. Technologies such as Firebase for authentication and data storage, Swift Package Manager for dependency management, and various libraries for enhanced functionality were integrated. The application successfully facilitates comprehensive tracking and analysis of hand hygiene practices. The checklist-based approach allows detailed data collection, providing quantifiable insights into compliance levels. Including dark mode and user-friendly interfaces tailored for different user types (new, non-authorized, and authorized users) enhances the user experience. The application's innovative approach combines data analytics with practical utility, making it a valuable tool in nosocomial infection control. The use of modern technologies and adherence to established design principles ensure its relevance and ease of use in healthcare environments. This intelligent recommendation system represents a significant advancement in the application of technology to healthcare challenges, particularly in infection control.