Associate Professor International University of Health and Welfare, Japan Tokyo, Tokyo, Japan
Disclosure(s):
Retsu Fujita, Ph.D: No financial relationships to disclose
Background: The Japanese Society for Infection Prevention and Control launched the device-associated infection surveillance project in 2008. The objective of this study was to explain summary of result of this surveillance in 15 years, and to evaluate the quantitative effects of long-term surveillance and feedback reports on healthcare associated infections (HAIs).
Methods: Four types of device-associated infections were selected to be surveyed: central line-associated bloodstream infection (CLABSI), catheter-associated urinary tract infection (CAUTI), ventilator-associated pneumonia (VAP), and ventilator-associated event (VAE) in intensive care units (ICUs) and acute care wards (ACWs). In this surveillance, definitions and methods used are in line with those specified in the National Healthcare Safety Network (NHSN) manual. The time-course effects of feedback reports of HAIs surveillance were assessed by the general linear mixed regression models adjusted by observation year(fixed-effect) and institution(random-effect).
Results: As of December 2022, a total of 214 institutions participated including 193 ICUs and 425 ACWs. In ICUs, the median value of CLABSI rate per 1,000 device-days was 0.8, CAUTI rate was 1.1, VAP rate was 0.7. The median value of PVAP rate was 0(pooled mean was 0.6). In ACWs, the median value of CLABSI rate per 1,000 device-days was 0.8, CAUTI rate was 1.2. Annually, the median value of VAP rate in ICUs declined over time, but other than that the values were generally stable. The results of the general linear mixed regression model analysis confirmed that CAUTI rate (regression coefficient: -0.1956, p-value:0.0136) and VAP rate (regression coefficient: -0.1987, p-value:0.0302) were associated with duration(year) of surveillance significantly. Analysis of CLABSI showed the same trend (regression coefficient: -0.06436, p-value:0.1740) but no statistical significance.
Conclusions: The time-course effectiveness of feedback reports of HAIs surveillance were quantitatively evaluated.
Learning Objectives:
Describe time-course effectiveness of feedback reports of healthcare associated infections surveillance.
Debate the value of HAIs surveillance.
Update actual situation of healthcare associated infections in Japan.
