Incidence of healthcare-associated infections in a tertiary hospital in Beijing, China: results from a real-time surveillance system

Yuzheng Zhang,Rui Huo,Yunxi Liu,Mingmei Du,Ellie Bostwick Andres,Janice Mary Johnston,Qiang Fu,Jijiang Suo,Hongwu Yao

doi:10.1186/s13756-019-0582-7

Abstract

BackgroundTo quantify the five year incidence trend of all healthcare-associated infections (HAI) using a real-time HAI electronic surveillance system in a tertiary hospital in Beijing, China.MethodsThe real-time surveillance system scans the hospital’s electronic databases related to HAI (e.g. microbiological reports and antibiotics administration) to identify HAI cases. We conducted retrospective secondary analyses of the data exported from the surveillance system for inpatients with all types of HAIs from January 1st 2013 to December 31st 2017. Incidence of HAI is defined as the number of HAIs per 1000 patient-days. We modeled the incidence data using negative binomial regression.ResultsIn total, 23361 HAI cases were identified from 633990 patients, spanning 6242375 patient-days during the 5-year period. Overall, the adjusted five-year HAI incidence rate had a marginal reduction from 2013 (4.10 per 1000 patient days) to 2017 (3.62 per 1000 patient days). The incidence of respiratory tract infection decreased significantly. However, the incidence rate of bloodstream infections and surgical site infection increased significantly. Respiratory tract infection (43.80%) accounted for the most substantial proportion of HAIs, followed by bloodstream infections (15.74%), and urinary tract infection (12.69%). A summer peak in HAIs was detected among adult and elderly patients.ConclusionsThis study shows how continuous electronic incidence surveillance based on existing hospital electronic databases can provide a practical means of measuring hospital-wide HAI incidence. The estimated incidence trends demonstrate the necessity for improved infection control measures related to bloodstream infections, ventilator-associated pneumonia, non-intensive care patients, and non-device-associated HAIs, especially during summer months.

Highlights

To quantify the five year incidence trend of all healthcare-associated infections (HAI) using a real-time HAI electronic surveillance system in a tertiary hospital in Beijing, China
The Study on the Efficiency of Nosocomial Infection Control (SENIC) project demonstrated the importance of surveillance to reduce HAI rates, with data indicating 32% of HAIs could be prevented if all hospitals conducted effective infection surveillance and control programs [2]
We modeled the incidence of HAIs using negative-binomial regression, with log number of patient days as offset, and estimated the relative increase in incidence per year in 2017 as the incidence rate ratios (IRR)

Summary

Introduction

To quantify the five year incidence trend of all healthcare-associated infections (HAI) using a real-time HAI electronic surveillance system in a tertiary hospital in Beijing, China. The US National Healthcare Safety Network (NHSN), German national nosocomial infections surveillance system (KISS), and the International Nosocomial Infection Control Consortium (INICC) reported targeted HAI data, such as: device-associated infections rates [7,8,9]. Unlike these two surveillance methods, continuous incidence surveillance can provide real-time information [10]. A Finland three-year (2011–2013) electronic HAI surveillance study based mainly on antibiotic treatment, indicated HAI incidence, which was 15.8 per 1000 patientdays and 4.9% of all discharged patients [12]

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Discussion

Conclusion