طراحی و پیادهسازی سامانه هوشمند شیفتبندی پرسنل پرستاری مبتنی بر هوش مصنوعی
کد: G-1453
نویسندگان: Hossein Moein Jahromi * ℗, Maryam Jafari, Hamide Mirzaie, Zahra Jamshidi
زمان بندی: زمان بندی نشده!
برچسب: دستیار مجازی هوشمند
دانلود: دانلود پوستر
خلاصه مقاله:
خلاصه مقاله
Background and Aims: Nurse scheduling in hospitals is a complex and time-consuming task, often performed manually, leading to human errors and inefficiencies. This study aims to design an AI-based intelligent scheduling system to automate nurse shift planning, optimizing fairness and operational efficiency while enhancing staff satisfaction. Method: The proposed system utilizes optimization algorithms and machine learning to generate shift schedules. It incorporates factors such as unit requirements, legal regulations, staff preferences, and workload balance. The system analyzes historical data to identify optimal scheduling patterns and adapts to sudden changes through predictive modeling. A prototype will be developed and tested in a simulated hospital environment, involving a sample of nursing staff and administrative personnel to evaluate usability and performance. Results: The system is expected to reduce scheduling time by at least 50%, minimize errors in shift assignments, and improve compliance with labor regulations. Preliminary simulations indicate a 30% increase in schedule fairness, as measured by equitable shift distribution and adherence to staff preferences. Additionally, the system’s predictive capabilities enhance preparedness for staffing shortages, ensuring uninterrupted hospital operations. Conclusion: By automating nurse scheduling, this AI-based system significantly enhances operational efficiency and reduces the administrative burden on nursing managers. It promotes a better work-life balance for nurses, potentially increasing job satisfaction and retention rates. The findings underscore the need to transition from traditional scheduling methods to intelligent solutions in healthcare management. This system could serve as a foundation for similar applications in other service-oriented sectors, with future work focusing on real-world implementation and scalability to diverse healthcare settings.
کلمات کلیدی
Artificial Intelligence, Nurse Scheduling, Healthcare Management
