Research on Risk Early Warning Mechanism of Medical Equipment Performance Visualization in Big Data Environment

As the core role of medical equipment in healthcare services becomes increasingly prominent, its performance management has become a key aspect of hospital operations. This paper addresses issues such as the lack of standards, difficulties in data integration, and insufficient dynamic monitoring in traditional medical equipment performance audits, proposing a visual early warning mechanism based on big data technology. By establishing a multi-source data collection platform, a visual interaction system, and a risk warning mechanism, real-time monitoring and dynamic warnings of equipment performance are achieved. The effectiveness of the visual early warning mechanism in improving audit efficiency, optimizing resource allocation, and strengthening risk prevention is verified, providing theoretical support and practical pathways for the digital transformation of internal auditing in hospitals.