Abstract Introduction Harboring sensitive strains may prevent acquisition of resistant pathogens by competing for colonization of ecological niches. Competition may be relevant to decolonization strategies that eliminate sensitive strains and may predispose to acquiring resistant strains in high-endemic settings. We evaluated the impact of colonization with methicillin-sensitive Staphylococcus aureus (MSSA) and vancomycin-sensitive enterococci (VSE) on acquisition of methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci (VRE), respectively, when controlling for other risk factors. Methods We conducted a nested case-control study of patients admitted to eight ICUs performing admission and weekly bilateral nares and rectal screening for MRSA and VRE, respectively. Analyses were identical for both pathogens. For MRSA, patients were identified who had a negative nares screen and no prior history of MRSA. We evaluated predictors of MRSA acquisition, defined as a subsequent MRSA-positive clinical or screening culture, compared to those with a subsequent MRSA-negative nares screen within the same hospitalization. Medical records were reviewed for the presence of MSSA on the initial MRSA-negative nares screen, demographic and comorbidity information, medical devices, procedures, antibiotic utilization, and daily exposure to MRSA-positive patients in the same ward. Generalized linear mixed models were used to assess predictors of acquisition. Results In multivariate models, MSSA carriage protected against subsequent MRSA acquisition (OR = 0.52, CI: 0.29, 0.95), even when controlling for other risk factors. MRSA predictors included intubation (OR = 4.65, CI: 1.77, 12.26), fluoroquinolone exposure (OR = 1.91, CI: 1.20, 3.04), and increased time from ICU admission to initial negative swab (OR = 15.59, CI: 8.40, 28.94). In contrast, VSE carriage did not protect against VRE acquisition (OR = 1.37, CI: 0.54, 3.48), whereas hemodialysis (OR = 2.60, CI: 1.19, 5.70), low albumin (OR = 2.07, CI: 1.12, 3.83), fluoroquinolones (OR = 1.90, CI: 1.14, 3.17), third-generation cephalosporins (OR = 1.89, CI: 1.15, 3.10), and increased time from ICU admission to initial negative swab (OR = 15.13, CI: 7.86, 29.14) were predictive. Conclusions MSSA carriage reduced the odds of MRSA acquisition by 50% in ICUs. In contrast, VSE colonization was not protective against VRE acquisition. Studies are needed to evaluate whether decolonization of MSSA ICU carriers increases the risk of acquiring MRSA when discharging patients to high-endemic MRSA healthcare settings. This may be particularly important for populations in whom MRSA infection may be more frequent and severe than MSSA infections, such as ICU patients.

Background

Observational studies rarely account for confounding by indication, whereby empiric antibiotics initiated for signs and symptoms of infection prior to the diagnosis of infection are then viewed as risk factors for infection. We evaluated whether confounding by indication impacts antimicrobial risk factors for methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci (VRE) acquisition.

Findings

We previously reported several predictors of MRSA and VRE acquisition in 967 intensive care unit (ICU) patients with no prior history of MRSA or VRE who had an initial negative screening culture followed by either a subsequent negative screening culture (controls) or positive screening or clinical culture (cases). Within and prior to this acquisition interval, we collected demographic, comorbidity, daily device and antibiotic utilization data. We now re-evaluate all antibiotics by medical record review for evidence of treatment for signs and symptoms ultimately attributable to MRSA or VRE. Generalized linear mixed models are used to assess variables associated with MRSA or VRE acquisition, accounting for clustering by ward. We find that exclusion of empiric antibiotics given for suspected infection affects 17% (113/661) of antibiotic prescriptions in 25% (60/244) of MRSA-positive patients but only 1% (5/491) of antibiotic prescriptions in 1% (3/227) of VRE-positive patients. In multivariate testing, fluoroquinolones are no longer associated with MRSA acquisition, and aminoglycosides are significantly protective (OR = 0.3, CI:0.1-0.7).

Conclusions

Neglecting treatment indication may cause common empiric antibiotics to appear spuriously associated with MRSA acquisition. This effect is absent for VRE, likely because empiric therapy is infrequent given the low prevalence of VRE.

Background: Detection of outbreaks of hospital-acquired infections is often based on simple rules, such as the occurrence of three new cases of a single pathogen in two weeks on the same ward. These rules typically focus on only a few pathogens, and they do not account for the pathogens' underlying prevalence, the normal random variation in rates, and clusters that may occur beyond a single ward, such as those associated with specialty services. Ideally, outbreak detection programs should evaluate many pathogens, using a wide array of data sources. Methods and Findings: We applied a space-time permutation scan statistic to microbiology data from patients admitted to a 750-bed academic medical center in 2002-2006, using WHONET-SaTScan laboratory information software from the World Health Organization (WHO) Collaborating Centre for Surveillance of Antimicrobial Resistance. We evaluated patients' first isolates for each potential pathogenic species. In order to evaluate hospital-associated infections, only pathogens first isolated >2d after admission were included. Clusters were sought daily across the entire hospital, as well as in hospital wards, specialty services, and using similar antimicrobial susceptibility profiles. We assessed clusters that had a likelihood of occurring by chance less than once per year. For methicillin-resistant Staphylococcus aureus (MRSA) or vancomycin-resistant enterococci (VRE), WHONET-SaTScan-generated clusters were compared to those previously identified by the Infection Control program, which were based on a rule-based criterion of three occurrences in two weeks in the same ward. Two hospital epidemiologists independently classified each cluster's importance. From 2002 to 2006, WHONET-SaTScan found 59 clusters involving 2-27 patients (median 4). Clusters were identified by antimicrobial resistance profile (41%), wards (29%), service (13%), and hospital-wide assessments (17%). WHONET-SaTScan rapidly detected the two previously known gram-negative pathogen clusters. Compared to rule-based thresholds, WHONET-SaTScan considered only one of 73 previously designated MRSA clusters and 0 of 87 VRE clusters as episodes statistically unlikely to have occurred by chance. WHONET-SaTScan identified six MRSA and four VRE clusters that were previously unknown. Epidemiologists considered more than 95% of the 59 detected clusters to merit consideration, with 27% warranting active investigation or intervention. Conclusions: Automated statistical software identified hospital clusters that had escaped routine detection. It also classified many previously identified clusters as events likely to occur because of normal random fluctuations. This automated method has the potential to provide valuable real-time guidance both by identifying otherwise unrecognized outbreaks and by preventing the unnecessary implementation of resource-intensive infection control measures that interfere with regular patient care.

Objective

To evaluate whether longitudinal insurer claims data allow reliable identification of elevated hospital surgical site infection (SSI) rates.

Design

We conducted a retrospective cohort study of Medicare beneficiaries who underwent coronary artery bypass grafting (CABG) in US hospitals performing at least 80 procedures in 2005. Hospitals were assigned to deciles by using case mix-adjusted probabilities of having an SSI-related inpatient or outpatient claim code within 60 days of surgery. We then reviewed medical records of randomly selected patients to assess whether chart-confirmed SSI risk was higher in hospitals in the worst deciles compared with the best deciles.

Participants

Fee-for-service Medicare beneficiaries who underwent CABG in these hospitals in 2005.

Results

We evaluated 114,673 patients who underwent CABG in 671 hospitals. In the best decile, 7.8% (958/12,307) of patients had an SSI-related code, compared with 24.8% (2,747/11,068) in the worst decile ([Formula: see text]). Medical record review confirmed SSI in 40% (388/980) of those with SSI-related codes. In the best decile, the chart-confirmed annual SSI rate was 3.2%, compared with 9.4% in the worst decile, with an adjusted odds ratio of SSI of 2.7 (confidence interval, 2.2-3.3; [Formula: see text]) for CABG performed in a worst-decile hospital compared with a best-decile hospital.

Conclusions

Claims data can identify groups of hospitals with unusually high or low post-CABG SSI rates. Assessment of claims is more reproducible and efficient than current surveillance methods. This example of secondary use of routinely recorded electronic health information to assess quality of care can identify hospitals that may benefit from prevention programs.