Intelligent Medical Resource Allocation Strategy for Overloaded Hospitals in Emergency Situations, Considering Reliability and Cost  
Author Jiafeng Wang

 
Co-Author(s) Tianmeng Zhu; Yu Wang; Yunkai Zhai; Hongyan Dui

 
Abstract Edge-cloud collaboration in healthcare is increasingly applied to enhance real-time monitoring and diagnosis of patients. However, in emergencies, overloaded hospitals often face a shortage of intelligent devices, leading to insufficient medical resources and delays in patient treatment. While numerous studies have explored various medical resource allocation strategies, they often overlook strategies for allocating intelligent medical devices within an edge-cloud collaborative context. This paper addresses this gap by optimizing an intelligent medical resource allocation strategy based on a Healthcare Edge-Cloud Collaborative System (H-ECCS). The study models the reliability of H-ECCS from the perspective of communication data transmission and conducts a comprehensive cost analysis, including energy consumption and network indicators. It categorizes hospital wards based on the severity of patients' conditions according to the Enhanced Early Warning Score (EEWS) standards. In a case simulation using data from the First Affiliated Hospital of Zhengzhou University, an improved NSGA-II algorithm is employed for multi-objective optimization, and resource allocation is conducted based on the Pareto optimal set and ward risk. The specific strategy prioritizes high-reliability and high-cost equipment for wards with more severe conditions and allocates lower-reliability and lower-cost equipment to wards with less severe conditions. The results demonstrate that this strategy effectively balances reliability and cost, enhancing the overall efficiency of medical services and emergency response capabilities.

 
Keywords Allocation strategy, Reliability, Cost, Edge-cloud collaborative architecture, Multi-objective optimization
   
    Article #:  RQD2024-192
 

Proceedings of 29th ISSAT International Conference on Reliability & Quality in Design
August 8-10, 2024