Research on Application of Meticulous Nursing Scheduling Management Based on Data-Driven Intelligent Optimization...

Area of Science:

• Healthcare Management
• Data Science
• Artificial Intelligence

Background:

• The COVID-19 pandemic highlighted challenges in nursing scheduling within healthcare facilities.
• Advancements in big data and artificial intelligence necessitate data-driven intelligent medical services.

Purpose of the Study:

• To propose solutions for refined nursing scheduling using scientific technologies.
• To accelerate hospital informatization and establish a scientific, intelligent medical platform.
• To address nursing scheduling issues in medical service data research.

Main Methods:

• Establishment of an intelligent medical service platform.
• Data-driven analysis of medical management using optimized algorithms.
• Application of a decision classification model for emergency medical treatment scenarios.

Main Results:

• Development of a basic nursing scheduling plan meeting institutional needs.
• Identification of an optimal management scheme for modern medical treatment.
• Improved allocation of human resources through refined scheduling.

Conclusions:

• The proposed intelligent medical platform effectively addresses nursing scheduling challenges.
• Integration of big data and AI enhances hospital informatization and efficiency.
• Data-driven approaches are crucial for optimizing modern medical treatment management.