Prediction of nosocomial infection incidence in the Department of Critical Care Medicine of Guizhou Province with a time series model.

ABSTRACT:

Background

The Department of Critical Care Medicine has the highest risk of nosocomial infection. This study used an autoregressive integrated moving average (ARIMA) model to simulate the prevalence of nosocomial infections in the Department of Critical Care Medicine of Guizhou Province. We also provided a policy basis for the prevention and control of hospital infection in the Department of Critical Care Medicine of Guizhou Province.

Methods

The data of ventilator-associated pneumonia, vascular catheter-related bloodstream infections, and urinary tract intubation-related urinary tract infections in nine tertiary A comprehensive treatment hospitals in Guizhou province from January 2014 to December 2019 were collected. The ARIMA time series model was used to evaluate the mode

SUBMITTER: Cheng Y 

PROVIDER: S-EPMC7333123 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature