Intrahospital infection risk analysis method and system based on association rule and complex network

Abstract

The invention discloses a hospital infection risk analysis method and system based on association rules and a complex network. The method comprises the following steps: performing keyword retrieval through a web crawler to obtain hospital infection related data; formulating a hospital infection event risk factor summary table based on the hospital infection related data; based on the hospital infection event risk factor summary sheet, performing data mining by using an Apriori algorithm to obtain a frequent item set and an association rule; constructing a complex network based on the frequent item set and the association rule; determining key risk nodes according to the node degree and the intermediary centrality in the complex network, and marking the key risk nodes as key risk factors of hospital infection accidents; and performing prevention and control according to the key risk factors. According to the method, based on real hospital infection data, mutual influence among multiple risk factors is considered, association rule mining and a complex network are combined to determine key risk factors, and therefore effective prevention and management and control are carried out.

Description

technical field [0001] The invention relates to the technical field of public health, in particular to a nosocomial infection risk analysis method and system based on association rules and complex networks. Background technique [0002] In December 2019, the new crown pneumonia began to spread in China and quickly swept the world. As the front line of the fight against the new crown pneumonia epidemic, medical staff are always facing a huge risk of nosocomial infection in addition to treating patients. Nosocomial infection, also known as hospital-acquired infection, refers to the non-primary infection acquired by the population during the stay and treatment in the hospital. It not only poses a threat to the health of patients and medical staff, but also affects the efficiency of treatment, leading to the further spread of the epidemic. Surveys have shown that management of nosocomial infections often requires prolonged hospital stays, additional investigations, surgical in...

AI Technical Summary

Problems solved by technology

It not only poses a threat to the health of patients and medical staff, but also affects the efficiency of treatment, leading to the further spread of the epidemic

Surveys show that management of nosocomial infections often requires prolonged hospital stays, additional investigations, surgical interventions, and antimicrobial therapy, all of which significantly increase healthcare costs

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