BACKGROUND: Catheter-Associated Urinary Tract Infections (CAUTIs) frequently occur in the intensive care unit (ICU) and are correlated with a significant burden.
METHODS: We implemented a strategy involving a 9-element bundle, education, surveillance of CAUTI rates and clinical outcomes, monitoring compliance with bundle components, feedback of CAUTI rates and performance feedback. This was executed in 299 ICUs across 32 low- and middle-income countries. The dependent variable was CAUTI per 1,000 UC days, assessed at baseline and throughout the intervention, in the second month, third month, 4 to 15 months, 16 to 27 months, and 28 to 39 months. Comparisons were made using a 2-sample t test, and the exposure-outcome relationship was explored using a generalized linear mixed model with a Poisson distribution.
RESULTS: Over the course of 978,364 patient days, 150,258 patients utilized 652,053 UC-days. The rates of CAUTI per 1,000 UC days were measured. The rates decreased from 14.89 during the baseline period to 5.51 in the second month (risk ratio [RR] = 0.37; 95% confidence interval [CI] = 0.34-0.39; P < .001), 3.79 in the third month (RR = 0.25; 95% CI = 0.23-0.28; P < .001), 2.98 in the 4 to 15 months (RR = 0.21; 95% CI = 0.18-0.22; P < .001), 1.86 in the 16 to 27 months (RR = 0.12; 95% CI = 0.11-0.14; P < .001), and 1.71 in the 28 to 39 months (RR = 0.11; 95% CI = 0.09-0.13; P < .001).
CONCLUSIONS: Our intervention, without substantial costs or additional staffing, achieved an 89% reduction in CAUTI incidence in ICUs across 32 countries, demonstrating feasibility in ICUs of low- and middle-income countries.

BACKGROUND: Central line (CL)-associated bloodstream infections (CLABSIs) occurring in the intensive care unit (ICU) are common and associated with a high burden.
METHODS: We implemented a multidimensional approach, incorporating an 11-element bundle, education, surveillance of CLABSI rates and clinical outcomes, monitoring compliance with bundle components, feedback of CLABSI rates and clinical outcomes, and performance feedback in 316 ICUs across 30 low- and middle-income countries. Our dependent variables were CLABSI per 1,000-CL-days and in-ICU all-cause mortality rates. These variables were measured at baseline and during the intervention, specifically during the second month, third month, 4 to 16 months, and 17 to 29 months. Comparisons were conducted using a two-sample t test. To explore the exposure-outcome relationship, we used a generalized linear mixed model with a Poisson distribution to model the number of CLABSIs.
RESULTS: During 1,837,750 patient-days, 283,087 patients, used 1,218,882 CL-days. CLABSI per 1,000 CL-days rates decreased from 15.34 at the baseline period to 7.97 in the 2nd month (relative risk (RR) = 0.52; 95% confidence interval [CI] = 0.48-0.56; P < .001), 5.34 in the 3rd month (RR = 0.35; 95% CI = 0.32-0.38; P < .001), and 2.23 in the 17 to 29 months (RR = 0.15; 95% CI = 0.13-0.17; P < .001). In-ICU all-cause mortality rate decreased from 16.17% at baseline to 13.68% (RR = 0.84; P = .0013) at 17 to 29 months.
CONCLUSIONS: The implemented approach was effective, and a similar intervention could be applied in other ICUs of low- and middle-income countries to reduce CLABSI and in-ICU all-cause mortality rates.

BACKGROUND: The cluster detection of health care-associated infections (HAIs) is crucial for identifying HAI outbreaks in the early stages.
OBJECTIVE: We aimed to verify whether multisource surveillance based on the process data in an area network can be effective in detecting HAI clusters.
METHODS: We retrospectively analyzed the incidence of HAIs and 3 indicators of process data relative to infection, namely, antibiotic utilization rate in combination, inspection rate of bacterial specimens, and positive rate of bacterial specimens, from 4 independent high-risk units in a tertiary hospital in China. We utilized the Shewhart warning model to detect the peaks of the time-series data. Subsequently, we designed 5 surveillance strategies based on the process data for the HAI cluster detection: (1) antibiotic utilization rate in combination only, (2) inspection rate of bacterial specimens only, (3) positive rate of bacterial specimens only, (4) antibiotic utilization rate in combination + inspection rate of bacterial specimens + positive rate of bacterial specimens in parallel, and (5) antibiotic utilization rate in combination + inspection rate of bacterial specimens + positive rate of bacterial specimens in series. We used the receiver operating characteristic (ROC) curve and Youden index to evaluate the warning performance of these surveillance strategies for the detection of HAI clusters.
RESULTS: The ROC curves of the 5 surveillance strategies were located above the standard line, and the area under the curve of the ROC was larger in the parallel strategy than in the series strategy and the single-indicator strategies. The optimal Youden indexes were 0.48 (95% CI 0.29-0.67) at a threshold of 1.5 in the antibiotic utilization rate in combination-only strategy, 0.49 (95% CI 0.45-0.53) at a threshold of 0.5 in the inspection rate of bacterial specimens-only strategy, 0.50 (95% CI 0.28-0.71) at a threshold of 1.1 in the positive rate of bacterial specimens-only strategy, 0.63 (95% CI 0.49-0.77) at a threshold of 2.6 in the parallel strategy, and 0.32 (95% CI 0.00-0.65) at a threshold of 0.0 in the series strategy. The warning performance of the parallel strategy was greater than that of the single-indicator strategies when the threshold exceeded 1.5.
CONCLUSIONS: The multisource surveillance of process data in the area network is an effective method for the early detection of HAI clusters. The combination of multisource data and the threshold of the warning model are 2 important factors that influence the performance of the model.

We report the results of International Nosocomial Infection Control Consortium (INICC) surveillance study from January 2012 to December 2017 in 523 intensive care units (ICUs) in 45 countries from Latin America, Europe, Eastern Mediterranean, Southeast Asia, and Western Pacific.
During the 6-year study period, prospective data from 532,483 ICU patients hospitalized in 242 hospitals, for an aggregate of 2,197,304 patient days, were collected through the INICC Surveillance Online System (ISOS). The Centers for Disease Control and Prevention-National Healthcare Safety Network (CDC-NHSN) definitions for device-associated health care-associated infection (DA-HAI) were applied.
Although device use in INICC ICUs was similar to that reported from CDC-NHSN ICUs, DA-HAI rates were higher in the INICC ICUs: in the medical-surgical ICUs, the pooled central line-associated bloodstream infection rate was higher (5.05 vs 0.8 per 1,000 central line-days); the ventilator-associated pneumonia rate was also higher (14.1 vs 0.9 per 1,000 ventilator-days,), as well as the rate of catheter-associated urinary tract infection (5.1 vs 1.7 per 1,000 catheter-days). From blood cultures samples, frequencies of resistance, such as of Pseudomonas aeruginosa to piperacillin-tazobactam (33.0% vs 18.3%), were also higher.
Despite a significant trend toward the reduction in INICC ICUs, DA-HAI rates are still much higher compared with CDC-NHSN\'s ICUs representing the developed world. It is INICC\'s main goal to provide basic and cost-effective resources, through the INICC Surveillance Online System to tackle the burden of DA-HAIs effectively.

This study estimated the attributable direct medical economic burden of health care-associated infections (HAIs) in China. Data were extracted from hospitals\' information systems. Inpatient cases with HAIs and non-HAIs were grouped by the propensity score matching (PSM) method. Attributable hospitalization expenditures and length of hospital stay were measured to estimate the direct medical economic burden of HAIs. STATA 12.0 was used to conduct descriptive analysis, bivariate χ2 test, paired Z test, PSM ( r = 0.25σ, nearest neighbor 1:1 matching), and logistic regress analysis. The statistically significant level was set at .05. The HAIs group had statistically significant higher expenditures and longer hospitalization stay than the non-HAIs group during 2013 to 2015 ( P < .001). The annual average HAI attributable total expenditure, medicines expenditure, out-of-pocket expenditure, and number of hospitalization days per inpatient were (2015 US$) 6173.02, 2257.98, and 1958.25 and 25 days during 2013 to 2015. The direct medical cost savings was estimated at more than 2015 US$12 billion per year in Chinese tertiary hospitals across the country. The significant attributable direct medical economic burden of HAIs calls for more effective HAI surveillance and better control with appropriate incentives.

BACKGROUND: We reviewed Burkholderia cepacia infections in a hospital from 2013-2016 to report a suspicious outbreak that occurred in a surgical intensive care unit in 2015, and to outline the infection control measures adopted thereafter.
METHODS: Review of the health care-associated infection data regarding B cepacia via the surveillance system, hospital information system, electronic medical records, and laboratory information system together with the outbreak investigation was managed by the health care-associated infection control team.
RESULTS: During June 1-14, 2015, 4 cases of ventilator-associated pneumonia (VAP) were identified; B cepacia was isolated from endotracheal aspirate samples. On June 16, 120 environmental samples were collected and analyzed for microbiologic differentiation. Thirteen strains of B cepacia were prominently found in the expiratory blocks of ventilators, revealing the biocontamination source. After chemical disinfection without damaging ventilator components, repeat microbiologic testing of random ventilator samples yielded negative results until July 30, 2015. Retrospective data showed that isolation rates of B cepacia strains had increased since 2014. Although the resistance phenotype of these strains varied slightly, they exhibited similar patterns of antibiotic susceptibility.
CONCLUSIONS: Routine cleaning and disinfection of ventilators, in addition to an intervention bundle, should form part of an integrated VAP prevention and management approach.

We report the results of an International Nosocomial Infection Control Consortium (INICC) surveillance study from January 2007-December 2012 in 503 intensive care units (ICUs) in Latin America, Asia, Africa, and Europe. During the 6-year study using the Centers for Disease Control and Prevention\'s (CDC) U.S. National Healthcare Safety Network (NHSN) definitions for device-associated health care-associated infection (DA-HAI), we collected prospective data from 605,310 patients hospitalized in the INICC\'s ICUs for an aggregate of 3,338,396 days. Although device utilization in the INICC\'s ICUs was similar to that reported from ICUs in the U.S. in the CDC\'s NHSN, rates of device-associated nosocomial infection were higher in the ICUs of the INICC hospitals: the pooled rate of central line-associated bloodstream infection in the INICC\'s ICUs, 4.9 per 1,000 central line days, is nearly 5-fold higher than the 0.9 per 1,000 central line days reported from comparable U.S. ICUs. The overall rate of ventilator-associated pneumonia was also higher (16.8 vs 1.1 per 1,000 ventilator days) as was the rate of catheter-associated urinary tract infection (5.5 vs 1.3 per 1,000 catheter days). Frequencies of resistance of Pseudomonas isolates to amikacin (42.8% vs 10%) and imipenem (42.4% vs 26.1%) and Klebsiella pneumoniae isolates to ceftazidime (71.2% vs 28.8%) and imipenem (19.6% vs 12.8%) were also higher in the INICC\'s ICUs compared with the ICUs of the CDC\'s NHSN.

BACKGROUND: To explore the characteristics and distribution of hospital length of stay (LOS) and direct hospitalization costs of children with cerebral palsy (CP) affected by health care-associated infection (HAI).
METHODS: A prospective observational study was performed from March 2010 to February 2012 on HAI cases among hospitalized children with CP. Demographic, clinical, and HAI data were recorded. Mann-Whitney test, chi-square test, and multiple linear regressions were used for data analysis.
RESULTS: Of 528 patients with CP, 151 (28.6%) suffered HAI in the form of respiratory tract infection. Male to female ratio was 2.87. About 50 patients had recurrent HAI. Upper respiratory infection and pneumonia were common infections. HAI occurring more than once contributed mainly to total LOS, and the length of HAI was >10 days in >50% of patients. Frequency of HAI was an independent predictor of LOS, and frequency of HAI and LOS were independent predictors of hospitalization costs.
CONCLUSIONS: Health care-associated respiratory infection significantly impacted LOS and total cost of children with CP admitted for rehabilitation. These data should assist in establishing preventive and control measures for HAI to help improve the quality of rehabilitation and survival in the long run.