Prevention's National Healthcare Safety Research Articles

Challenges in Adherence with National Healthcare Safety Network Definitions: A Central Line-Associated Bloodstream Infection Conundrum

The Centers for Disease Control and Prevention's National Healthcare Safety Network (NHSN) has standardized definitions for healthcare-associated infections including central line associated-bloodstream infections (CLABSI) and pneumonia (PNU). In conjunction with the Center for Medicare and Medicaid Services (CMS), the State of Illinois requires hospitals to report CLABSIs using NHSN. Last year, Illinois began conducting audits of CLABSI data to validate adherence with NHSN definitions. Adherence with these definitions may not always concur with clinical diagnoses.

Device-associated nosocomial infection rates in intensive care units at Cairo University hospitals: First step toward initiating surveillance programs in a resource-limited country

Device associated infections (DAIs) have major impact on patient morbidity and mortality. This study involved active prospective surveillance to measure the incidence of DAIs, evaluate microbiological profiles, and investigate excessive mortality in intensive care units (ICUs) in 3 hospitals of Cairo University applying the US Centers for Disease Control and Prevention's National Healthcare Safety Network case definitions for ventilator-associated pneumonia (VAP), catheter-associated urinary tract infection (CAUTI), and central-line associated bloodstream infection (CLABSI). Data were collected between March 2009 and May2010. A total of 1,101 patients were hospitalized for a total of 10,869 days, had 4,734 device-days, and acquired 97 DAIs, with an overall rate of 20.5/1,000 ICU days. VAP was the most commonly identified infection (88.7%); followed by CLABSI (8.2%) and CAUTI (3.1%). Excess mortality was 48% (relative risk, 1.9; P < .001) for CAUTI, 12.9% (relative risk, 1.2; 95% confidence interval, 1.1-1.4; P < .05) for VAP, and 45.7% for CLABSI. Acinetobacter baumannii was the most frequently isolated pathogen (36.1%), followed by Klebsiella pneumoniae (29.2%) and Pseudomonas aeruginosa (22.2%). High antimicrobial resistance was identified, with 85% of A baumannii isolates resistant to ciprofloxacin and imipenem, 76% of K pneumoniae isolates were extended-spectrum β-lactamase producers, and 56.3% P aeruginosa isolates resistant to imipenem (56.3%). High rates of DAI and antimicrobial resistance require strengthening infection control, instituting surveillance systems, and implementing evidence-based preventive strategies.

Device-associated infections rates in adult, pediatric, and neonatal intensive care units of hospitals in the Philippines: International Nosocomial Infection Control Consortium (INICC) findings

This study investigated the rate of device-associated health care-associated infection (DA-HAI), microbiological profiles, bacterial resistance, length of stay (LOS), and mortality rate in 9 intensive care units (ICUs) of 3 hospital members of the International Nosocomial Infection Control Consortium (INICC) in the Philippines. This was an open-label, prospective cohort, active DA-HAI surveillance study of adult, pediatric, and newborn patients admitted to 9 tertiary care ICUs in the Philippines between January 2005 and December 2009, implementing methodology developed by the INICC. Data collection was performed in the participating ICUs, and data were uploaded and analyzed at the INICC headquarters using proprietary software. DA-HAI rates were registered based on definitions promulgated by the Centers for Disease Control and Prevention's National Healthcare Safety Network. Over a 5-year period, 4952 patients hospitalized in ICUs for a total of 40,733 days acquired 199 DA-HAIs, for an overall rate of 4.9 infections per 1,000 ICU-days. Ventilator-associated pneumonia posed the greatest risk (16.7 per 1,000 ventilator-days in the adult ICUs, 12.8 per 1,000 ventilator-days in the pediatric ICU, and 0.44 per 1,000 ventilator-days in the neonatal ICUs), followed by central line-associated bloodstream infections (4.6 per 1,000 catheter-days in the adult ICUs, 8.23 per 1,000 ventilator-days in the pediatric ICU, and 9.6 per 1,000 ventilator-days in the neonatal ICUs) and catheter-associated urinary tract infections (4.2 per 1,000 catheter-days in the adult ICUs and 0.0 in the pediatric ICU). DA-HAIs pose far greater threats to patient safety in Philippine ICUs than in US ICUs. The establishment of active infection control programs that involve infection surveillance and implement guidelines for prevention can improve patient safety and should become a priority.

Health care-associated infection reporting: The need for ongoing reliability and validity assessment

Government-mandated reporting of health care-associated infections (HAIs) and new reimbursement regulations place a premium on accurate and reliable detection of HAIs. This commentary addresses the challenges and opportunities of having consistent, well-defined, and continuous methods in place to ensure the reliability and validity of HAI detection and reporting. In addition, such procedures could support the development and expertise of infection preventionists. A Web-based clinical vignette model is suggested for improving HAI reporting for hospitals participating in the Centers for Disease Control and Prevention's National Healthcare Safety Network.

Administrative coding data, compared with CDC/NHSN criteria, are poor indicators of health care–associated infections

ICD-9-CM coding alone has been proposed as a method of surveillance for health care-associated infections (HAIs). The accuracy of this method, however, relative to accepted infection control criteria is not known. Retrospective analysis of patients at an academic medical center in 2005 who underwent surgical procedures or who were at risk for catheter-associated bloodstream infections or ventilator-associated pneumonia was performed. Patients previously identified with HAIs by Centers for Disease Control and Prevention's National Healthcare Safety Network surveillance methods were compared with those of the same risk group identified by secondary infection ICD-9-CM codes. Discordant cases identified by only coding were all rereviewed and adjusted prior to final analysis. When coding and surveillance were both negative, a sample of patients was used to estimate the proportion of false negatives in this group. The positive predictive values (PPVs) ranged from 0.14 to 0.51 with an aggregate of 0.23, even after adjustment for additional cases detected on subsequent medical record review. The negative predictive values (NPVs) ranged from 0.91 to 1.00, with an aggregate of 0.96. The estimates of the true variance of PPVs and NPVs across surgical procedures were small (0.0129, standard error, 0.009; 0.000145, standard error, 0.00019, respectively) and could be mostly explained by variation in prevalence of surgical site infections. Administrative coding alone appears to be a poor tool to be used as an infection control surveillance method. Its proposed use for routine HAI surveillance, public reporting of HAIs, interfacility comparisons, and nonpayment for performance should be seriously questioned.