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A Study On The Status Of Infection In A Comprehensive Tertiary Hospital In Jilin Province

Posted on:2024-02-17Degree:MasterType:Thesis
Country:ChinaCandidate:H T ZhangFull Text:PDF
GTID:2544307112483484Subject:Public health
Abstract/Summary:PDF Full Text Request
Objective:To investigate the hospital infection presenting rate of a comprehensive tertiary hospital in Jilin Province from 2017-2021,analyze the hospital infection situation and identify risk factors,construct a hospital infection column line graph model,and predict the probability of hospital infection in patients.To compare the hospital infection presenting rate in Jilin Province,determine the infection control level of the hospital within the province,improve hospital infection prevention and control measures,and make recommendations and suggestions.Methods:Two statistical software,SPSS 22.0 and R3.6.1,were utilized for this survey.Firstly,the data of hospital infection present rate(age,gender,etc.)from 2017-2021 were analyzed with SPSS 22.0 to understand the basic information of infection in this hospital;subsequently,the statistically significant factors were analyzed by single factor analysis and multi-factor binary logistic regression analysis to construct a column line graph model;finally,the hospital was compared with the hospital infection present rate in Jilin province to get a comprehensive understanding of the hospital’s the level of the province.Results:A total of 8954 hospital-acquired infections were investigated in 2017-2021,and a total of 187 hospital-acquired infections were reported.(1)The hospital infection presenting rate during the five-year period was 2.08%,and the comparison of infection presenting rate in different years was not statistically significant(X~2=4.415,P>0.05).(2)Infection prevalence rate by age:the highest infection prevalence rate was 2.40%for patients≥65 years old;1.88%for patients 15-64 years old and 0%for patients≤14 years old.There was no statistically significant difference in the prevalence of infection among patients of different age groups(X~2=4.606,P>0.05).(3)Hospital infection prevalence rate by gender:2.46%for male patients and 1.60%for female patients.There was a statistically significant difference in infection presenting rates between males and females(X~2=8.005,P<0.05).(4)The hospital-acquired infection presenting rate was 2.06%in a five-year tertiary care hospital with≥1500 beds.(5)Risk factors associated with hospital-acquired infections:urinary tract intubation,tracheotomy,immunosuppression,hemodialysis and antineoplastic therapy,were all independent risk factors for infection,with statistically significant differences(P<0.05).(6)A line graph model for predicting the occurrence of hospital-acquired infections was drawn by R3.6.1 software,and the predictive efficacy of the model was tested byROC curve,and the model fit was good.Conclusion:1.the trend of infection presenting rate in a comprehensive tertiary care hospital in Jilin Province was relatively stable from 2017 to 2021.The highest hospital-acquired infection presenting rate was among patients≥65.The hospital infection presenting rate of male patients was higher than that of female patients.The present rate of infection in the intensive care medicine department was the first.2.The top three composition ratios of different infection sites were lower respiratory tract,upper respiratory tract and urinary tract infections.3.The risk factors in a comprehensive tertiary care hospital in Jilin province were:tracheotomy,urinary tract intubation,hemodialysis,immunosuppressive and antineoplastic therapy.4.In terms of hospital size,the highest 2.06%of hospitals with≥1500 beds,most of the hospitals with≥1500 beds in Jilin Province belong to tertiary hospitals,and the infection present rate of tertiary hospitals in this survey is 2.08%,which is similar,indicating that the level of infection in this hospital is relatively well controlled.5.The hospital infection column line graph model allows for an individualized hospital risk assessment of patients visually by quantifying each risk factor,and patients can add up the scores corresponding to the risk factors to arrive at a total score,and the risk of hospital infection occurrence is derived from the total score.
Keywords/Search Tags:general tertiary care hospital, hospital-acquired infection, presenting rate, risk factors, hospital-acquired infection prediction model
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