Analysis of the surveillance results of hospital-acquired infection in a hospital of integrated traditional Chinese and Western Medicine in Chengdu from 2019 to 2023
Objective To analyze the hospital-acquired infections(HAIs)and the detection of multidrug-resistant organism(MDRO)in Chengdu Integrated Traditional Chinese and Western Medicine Hospital,to evaluate the effect of the implementation of nosocomial infection quality control of the FOCUS-PDCA model,and to provide basis for improving HAIs prevention and control strategies.Methods Through the Real-Time Monitoring Platform of Hospital Infections and Infectious Diseases,HAIs case information from 2019 to 2023 of the hospital was derived.The data were organized by Excel 2010,and the incidence rates of HAIs and MDRO were statistically described by SPSS 19.0 and x2 test was conducted.P＜0.05 was considered to be statistically significant.Results The incidence rates for HAIs from 2019 to 2023 were 1.26％,1.28％,1.11％,1.03％and 1.01％,respectively,with an average incidence rate of 1.27％from 2019 to 2020 and 1.05％from 2021 to 2023.The difference in HAIs incidence rates between the two periods was statistically significant(x2=38.52,P＜0.001).The three departments with greater decreases in HAIs incidence from 2019 to 2023 were,in order,Cardiovascular Medicine,Orthopedics and Critical Care Medicine(x2=63.02,52.13 and 29.84,respectively;P＜0.001).The top three body sites being prone to infections were,inorder,the respiratory system(63.94％),the urinary system(11.35％),and the hematologic system(7.85％).The average incidence rate of MDRO in HAIs from 2019 to 2023 was 0.08％,with a statistically significant difference in the rate among different years(x2=42.55,P＜0.001).The average case rate of MDRO of HAIs from 2019 to 2023 was 0.09％,with a statistically significant difference in the rate among different years(x2=49.00,P＜0.001).Conclusions The FOCUS-PDCA model implemented in 2021 was effective in reducing the incidence of HAIs and hospital infection management.
hospital-acquired infectionsinfection ratemanagement model
万方数据
维普
