Nosocomial infection poses a significant threat to patient safety and increase their disease burden. Outbreaks of nosocomial infection are the main harmfulness associated with nosocomial infection, which making them socially sensitive issues. Nosocomial infection surveillance and warning are core contents of nosocomial infection management. Accurate early warning technology for nosocomial infection outbreaks can reflect the management capability of infection prevention and control. This study designed an early warning system based on a multi-dimensional and multi-scale comprehensive information surveillance mode for nosocomial infection outbreaks which was launched in March 2023. This system extracted the process-related indicators of nosocomial infection from various hospital information systems into the nosocomial infection database center. Under the multi-dimensional and multi-scale surveillance mode, the process-related data were stratified according to the predefined dimensions and scales, then generating time-series datasets of numerous subgroups. The system conducted weekly for all time-series datasets of subgroups based on warning rules, and subsequently sent out warning signals to managers. These warning signals could be verified by managers through data check, case verification and epidemiological investigation. Once a nosocomial infection outbreak was confirmed, intervention measures could be implemented promptly. In practical application, the system generated warning signals for nosocomial infection clusters in 12 departments on August 7th, 2023. The traditional nosocomial infection case report system ultimately reported 54 nosocomial infection cases, which distributed across 13 departments, with clusters(more than 3 cases) observed in 6 departments. All these 6 departments received warning signals generated from our system. It has been demonstrated that our system could predicted the nosocomial infection clusters 5.3 days earlier than the traditional nosocomial infection case report system on average, with warning sensitivity of 100.0% and positive predictive value of 50.0%. Early warning under the multi-dimensional and multi-scale comprehensive information surveillance mode was able to transform the work pattern of nosocomial infection outbreaks control and management from passive to active. Particularly it has advantages in early detection for occult outbreaks, providing a valuable support for improving nosocomial infection management capability.

Coronavirus disease 2019 (COVID-19) is an acute respiratory infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. It is highly contagious and can cause death in severe cases. As reported by the World Health Organization (WHO), as of 6:36 pm Central European Summer Time (CEST), 12 August 2022, there had been 585 950 285 confirmed cases of COVID-19, including 6 425 422 deaths (WHO, 2022).
Humans ; COVID-19 ; SARS-CoV-2 ; Mental Health ; Cohort Studies ; Quality of Life ; China/epidemiology* ; Health Personnel ; Hospitals ; Lung