首页|基于灰色GM(1,1)模型的我国医院感染患病率变化趋势及预测

基于灰色GM(1,1)模型的我国医院感染患病率变化趋势及预测

Trend change and prediction of nosocomial infection prevalence in China based on grey GM(1,1)model

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目的 了解我国医院感染患病率变化趋势,并采用灰色GM(1,1)模型对我国不同规模医院的医院感染患病率进行预测,为医院感染防控提供数据支持和新思路.方法 采用描述性流行病学方法分析我国医院感染患病率变化趋势,2008-2016年我国医院感染患病率数据进行灰色GM(1,1)模型构建,2018-2020年数据进行模型验证.采用构建的灰色GM(1,1)模型对2022-2024年我国医院感染患病率进行预测.结果 我国医院感染患病率呈下降趋势,随着医院规模的增加医院感染患病率升高.医院感染患病率灰色GM(1,1)模型的精度良好、拟合效果较高.2024年全国、<300张床位医院、300~599张床位医院、600~899张床位医院和≥900张床位医院的医院感染患病率可降为1.00%、0.49%、0.90%、1.13%和2.05%.结论 我国医院感染防控效果明显,灰色GM(1,1)模型对我国医院感染患病率有较好的预测效果.
Objective To understand the trend of nosocomial infection prevalence in China,and to predict the nosoco-mial infection prevalence in hospitals of different scales in China with the gray GM(1,1)model,so as to provide data support and new ideas for prevention and control of nosocomial infection.Methods Descriptive epidemiological method was used to ana-lyze the trend of nosocomial infection prevalence in China.The grey GM(1,1)model was constructed with data on nosocomial infection prevalence in China from 2008 to 2016,and the model was validated with data from 2018 to 2020.The constructed grey GM(1,1)model was used to predict the prevalence of nosocomial infection in China from 2022 to 2024.Results The preva-lence of nosocomial infection in China showed a downward trend.The prevalence of nosocomial infection increased with the in-crease of hospital scales.The grey GM(1,1)model for the prevalence of nosocomial infection has good accuracy and high fitting effect.In 2024,the prevalence of nosocomial infection in China,in hospitals with<300 beds,in hospitals with 300-599 beds,in hospitals with 600-899 beds,and in hospitals with≥ 900 beds can be reduced to 1.00%,0.49%,0.90%,1.13%,and 2.05%,respectively.Conclusion The prevention and control effect of nosocomial infection in China is obvious,and the grey GM(1,1)model has a good prediction effect on the prevalence of nosocomial infection in China.

grey GM(1,1)modelnosocomial infectionprevalenceforecast

姜雪锦、李阳、丁红红、吕敏、孙吉花

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滨州医学院附属医院,256603山东滨州

滨州市疾病预防控制中心,256603山东滨州

滨州市妇幼保健院,256603山东滨州

灰色GM(1,1)模型 医院感染 患病率 预测

2024

中国医院统计
卫生部统计信息中心,滨州医学院

中国医院统计

影响因子:0.564
ISSN:1006-5253
年,卷(期):2024.31(2)
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